global atmosphere research programme

Annual report 2002 to 2003

Research results

Global Atmosphere Research Programme

Department for the Environment, Food and Rural AffairsNobel HouseSmith SquareLondon SW1E 5DUTelephone 020 7238 6000Internet service http://www.defra.gov.uk/

Crown Copyright 2004

Copyright in the typographical arrangement and design vests in the Crown.

Extracts made from this publication may be made for non-commercial in-house use, subject to the source being acknowledged.

Applications for reproduction should be made in writing to The Copyright Unit, Her Majesty’s Stationery Office, St Clements House, 1-16 Colegate,Norwich NR3 1BQ.

Please go to Defra’s climate change web pages – www.defra.gov.uk/environment/climatechange

Published by the Department for the Environment, Food and Rural Affairs on the Defra website.

PB8442b

Cover photograph acknowledgement: © National History Photographic Agency (NHPA)

To Note: Evidence is growing that Arctic Sea is thinning and decreasing in extent. The Met Office Hadley Centre predicts that summer sea ice maywell disappear by the end of the century.

For further details of GA’s activities, please visit our pages on the Defra website:www.defra.gov.uk/environment/climatechange/index.htm

Chapter 1

Introduction 5

Chapter 2

Contract summary and GA research programme charts 11

Chapter 3

Ozone layer – prediction and detection 17Analysis of ozone levels over the UK: phase III 18

Chapter 4

Ozone layer – impacts 21Ultraviolet measurements and their analysis 22

Chapter 5

Climate change – prediction and detection 25Climate Prediction Programme 26UK ARGO Project 81

Chapter 6

Climate change – earth observation 83AATSR – prime industrial contract and management information system contract 84AATSR – post launch flight operations support 86AATSR – principal investigator and validation activities 88

Chapter 7

Climate change – trace gases and radiative forcing 93Atmospheric measurements of trace gases at Mace Head,

Republic of Ireland 94Interpretation of long-term measurements of radiatively active trace

gases and ozone depleting substances phase III 102

Chapter 8

Climate change – impacts 109The Climate Impacts LINK Project 110UK Climate Impacts Programme 2002 113Global impacts of climate change on human health 120Global impacts of climate change on water resources 122Global impacts of sea-level rise as a result of climate change 125Global impacts of climate change on food security 130Global impacts of climate change on natural vegetation 135INDO-UK programme on impacts of climate change in India 139IPCC Working Group II: Technical Support Unit 143The impacts of climate change on chinese agriculture 145

3

Contents

CHAPTER 9

Climate change – response strategies 149CO2 and energy use in buildings 150Industrial sector CO2 emissions 156UK emissions by sources and removals by sinks due to land use,

land use change and forestry activities 158UK greenhouse gas inventory and regional inventories for England,

Northern Ireland, Scotland and Wales 163Emissions and projections of fluorinated gases 167Estimation of methane emissions from abandoned coal mines 172Methane emissions from UK landfill sites and impact of EU Landfill

Directive and national strategies on UK greenhouse gas emissions 176

CHAPTER 10

Further information 183

4

Annual report 2002 to 2003 Research results

Chapter 1

Introduction

Global Atmosphere (GA) Division takes the lead within Government on developingpolicy responses to climate change (also referred to as global warming) and depletionof the stratospheric ozone layer.

GA’s objectives are to:

• negotiate the implementation and strengthening of international agreementsto reduce greenhouse gas emissions;

• ensure effective implementation of the UK domestic programme of measuresto control greenhouse gas emissions and to work with other governmentdepartments to set the UK on a long term path to a low carbon economy;

• negotiate effective international and EU controls on ozone depletingsubstances;

• ensure effective UK input to the international scientific assessments of ozonedepletion and climate change; and

• assess the impacts of climate change and the need for adaptation responses.

The issues of human-induced stratospheric ozone depletion and climate change areglobal in extent, long-term in scope and inherently complex in nature. They requireconsiderable further investigation in order to understand the basic processes involvedand develop solutions. Trends in long-term data need to be observed; impacts need tobe monitored and projected into the future; and effective ways to respond to theseconsiderable challenges need to be devised. To this end, GA commissions a programmeof scientific research, supporting the development of policy responses to these issues.

The key aims of the GA research programme are to:

• reduce uncertainty in climate predictions;

• improve climate impact assessments and adaptation strategies;

• meet the UK’s national and international commitments for assessing trends ingreenhouse gas emissions and future projections;

• improve assessment of mitigation options and costs;

• help to build internationally acceptable approaches to responding to climatechange in the long term;

• continue long term measurement of changes occurring in the ocean and theatmosphere; and

• continue to measure levels of ozone and UVB over the UK.

This report covers output from the Global Atmosphere Division’s research programmefor contracts operating in the financial year 2002/2003.

6

Chapter 1 Introduction

Overview of research programmeClimate change

The research funded by GA Division has a broad remit, reflecting the areas covered bythe three Working Groups of the Intergovernmental Panel on Climate Change, namely:

• The Scientific Basis of Climate Change;

• Impacts, Adaptation and Vulnerability; and

• Mitigation (i.e. the reduction of greenhouse gas emissions)

Science

The scientific basis of climate change is still a pivotal area of research, with a particularemphasis on improving climate predictions, particularly at a regional scale, reducinguncertainties and increasing understanding of often complex climate processes. Thisarea of work has a direct political impact, both nationally and internationally, andguides policy decisions. In future, it will help to define the level of cuts in emissionsneeded on a global scale to stabilise greenhouse gases in the atmosphere at a levelthat avoids dangerous climate change. The Climate Prediction Programme at theHadley Centre continues to underpin policy needs for basic climate understanding andprediction, at a cost of approximately £8 million per annum.

Impacts and adaptation

The assessment of climate change impacts and adaptation responses has steadily grownin importance during recent years, particularly as the public has become aware of thepotential impacts of climate change, for example, in the wake of the flooding eventsexperienced in the UK in 2000 and 2002, and the extremely high temperatures insummer 2003. The UK Climate Impacts Programme (UKCIP) – funded by GA at anannual cost of £0.5 million – is a stakeholder-led programme which helps localauthorities and organisations to assess the impacts of climate change on their activities.UKCIP coordinates climate impacts assessment activities and provides common toolsand data sets for use within such assessments. In addition, projects aimed at the globalassessment of climate change impacts, especially in particularly vulnerable parts of theworld, will help to identify the level of greenhouse gas mitigation required to avoid theworst effects.

Mitigation

GA’s research programme enables the UK to continue to meet its internationalreporting commitments to the United Nations Framework Convention on ClimateChange (UNFCCC – see Box 4). The UK reports an annual inventory of greenhouse gasemissions by sources and removals by sinks, and approximately every three to four yearsa national communication. The latter sets out the policies and measures in place andplanned to meet its Kyoto target (12.5% reduction below 1990 levels by 2008-12) anddomestic goal for carbon dioxide (20% below 1990 levels by 2010). Research isundertaken to underpin development of the UK Climate Change Programme andidentify cost-effective measures to reduce emissions across many sectors of the UK

7

Introduction

economy. The mitigation research programme also assesses policies on climate changein other countries, particularly in developing countries, and this work will help to informfuture negotiations on the shape of commitments beyond Kyoto.

Stratospheric ozone depletion

Policy on stratospheric ozone is relatively mature and actions under the MontrealProtocol have already arrested the rise in ozone depleting substances in theatmosphere. There is less controversy over the science than for climate change soresearch in the UK has focused more on evaluating the effectiveness of internationalcontrols and maintaining observations of ozone and UVB levels over the UK to meetdomestic and international commitments. The problem is not yet resolved, however,and the ozone layer is only anticipated to recover to a pre -1980s state by 2050. Thisprogress will depend on continued international compliance with the terms of theMontreal Protocol and future legislation on any new substances that are found to haveozone depleting potential. Research is also needed into the interactions betweenclimate change and stratospheric ozone, in particular to identify whether this coulddelay recovery of the ozone layer.

Future researchLooking ahead to the next few years, the GA research programme aims to reduceuncertainty in climate predictions, improve impact assessments and adaptationstrategies, improve assessment of mitigation options and costs, and assist in buildinginternationally acceptable approaches to the negotiation of a long-term internationalresponse to climate change. Further details are provided in chapter 7.

Under the SR2002 spending review, GA was successful in securing additional fundingto cover enhanced supercomputing requirements to improve high resolution regionalclimate predictions and to improve the assessment of changes to extreme weatherevents. This was prompted by the floods of 2000 and work in this area will be reportedon in GA’s research report for 2003/2004.

Links with other research programmesGA Division aims to encourage participation of research contractors in wider nationaland international programmes, and to contribute to such programmes to ensurebenefits to the UK are optimised. To this aim, we make the best efforts to integrate theresults of projects funded within GA’s research programme with climate change andatmospheric research outputs from research programmes of the research councils andother government departments.

Coordination between key funding agencies is undertaken in the UK within the GlobalEnvironmental Change Committee (GECC) chaired by Defra’s Chief Scientific Adviser.The committee seeks to ensure that there are no significant gaps or unnecessaryoverlap in the UK’s overall research effort on climate change. Coordination and

8


collaboration occurs at the sub-programme level, for example between UKCIP and theTyndall Centre, and between the Hadley Centre and the atmospheric scienceprogrammes of the NERC.

Key elements of GA’s research programme, such as the UK climate change scenariosand the Hadley Centre’s climate modeling, have provided valuable information tosupport the work of other Defra policy divisions dealing with flood management, waterresources, agriculture and the marine and terrestrial environments.

Internationally, we continue to press for greater coordination of policy relevant climatechange research within the EU and will work to influence and make best use of theEU’s 6th Framework Programme of Research. The UK was instrumental in setting up asub-group for science under the EU’s Working Party on Climate Change (WPCC) whichcoordinates EU policy on climate change. The sub group supports input to negotiationson scientific issues under the UNFCCC. The UK will continue to press for more focusedconcerted action on specific areas such as meeting the ultimate aim of the Convention,impacts and adaptation and proposals for greater coordination of European research onclimate change. Additionally, through various research activities, we collaborate withresearch organizations further afield (for example, through the climate impacts projectsin India and China).

9

Introduction

Chapter 2

Contract summary and GAresearch programme charts

Contract summary

In 2002/2003, Global Atmosphere Division supported 35 research contracts in 21different establishments at a total of £12 million (ex VAT)

Title Contractor Contract Value2002/03

1. Ozone Layer – Prediction and Detection

Measurement and Analysis of Ozone Levels Over the U.K. ** Meteorological Office 82,861

Analysis of Ozone Levels over the UK: Phase III AEAT/Hayman 60,731

Sub-total 143,592

2. Ozone layer – Impacts

Ultraviolet Measurements and their Analysis University of Manchester Institute 25,182 of Science and Technolgy (UMIST)

Sub-total 25,182

3. Climate Change – Prediction and Detection

Climate Prediction Programme Meteorological Office 8,441,000

IPCC Working Group 1: Technical Support Unit Meteorological Office 67,600

Climate Observations (ARGO) Meteorological Office 448,710

Sub-total 8,957,310

4. Climate Change – Earth Observation

AATSR – Management Information System Vega Group Plc 35,711

AATSR – Prime Industrial Astrium 376,236

AATSR – Post Launch Flight Operations Support Rutherford Appleton Laboratory 294,242

AATSR – Validation Activities University of Leicester 111,053

AATSR – Principal Investigator University of Leicester 5,608

Sub-total 822,850

5. Climate Change – Trace Gases and Radiative Forcing

Long-term Monitoring of Trace Gases at Mace Head International Science Consultants 124,953

Interpretation of Long-term Measurements of Ozone-Depleting Substances Phase III Meteorological Office 60,820

Sub-total 185,773

6. Climate Change – Impacts

Climate Impacts LINK Project University of East Anglia 92,263

Review of UK Impacts Indicators ** Centre for Ecology and Hydrology 7,500

UKCIP 2002 Programme University of Oxford 517,942

Global Impacts of Climate Change on Human Health London School of Hygiene and 10,190Tropical Medicine

Global Impacts of Climate Change on Water Resources University of Southampton 5,850

Global Impacts of Sea-level Rise as a Result of Climate Change Middlesex University 9,400

Global Impacts of Climate Change on Food Security Parry Associates 64,020

Global Impacts of Climate Change on Natural Vegetation Centre for Ecology and Hydrology 14,043

INDO-UK Programme on Impacts of Climate Change in India Environmental Resources 260,316Management

Agricultural Impacts in China AEA Technology 154,530

IPCC II Technical Support Unit Meteorological Office 96,906

2001 Climate Change Scenarios for UKCIP ** University of East Anglia 64,771

Climate Impacts LINK Project University of East Anglia 3,578

Sub-total 1,301,309

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Chapter 2 Contract summary and GA research programme charts

7. Climate Change – Response strategies

CO2 and Energy Use in UK Buildings British Research Establishment Ltd 61,353

Industrial Sector CO2 Emissions Entec 57,892

UK Emissions by Sources and Removals by Sinks due to Land Use, Land Use Change and Forestry Centre for Ecology and Hydrology 168,215Activities (LULUCF)

UK GHG Inventory and Regional Inventories for England, NI, Scotland and Wales AEA Technology 164,093

Emissions and Projections of Fluorinated Gases for the UK AEA Technology 25,000

Baseline for CDM projects (LULUCF) ** ECM 2,537

Baseline for CDM projects (non-LULUCF) ** ECOS 12,176

Estimation of Methane Emissions from Abandoned Coal Mines IMC Group Consulting LTD 75,000

Methane Emissions from UK Landfill Sites and Impact on LQM and ERM 0EU Landfill Directive and National Strategies onUK Greenhouse Gas Emissions

Sub-total 566,266

Research Programe Total 12,002,282

** Report not included in this publication

13

Contract summary and GA research programme charts

Climate change - response strategies

Climate change - impacts

Climate change - trace gases and radiative forcing

Climate change - earth observation

Climate change - prediction and detection

Ozone layer - impacts

Ozone layer - prediction and detection

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2

5

3

12

9

8.957

0.823

0.186

1.301

0.5660.144

0.0252002/2003 contract value (£m) by topic.

Number of contracts by topic 2002/2003.

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Universities

Private Sector

Other Research Institutes

Hadley Centre

NERC

8.441

0.190

2.170

0.366

0.836

9

1

3

19

3

Contract value (£m) by research body2002/2003 (total=£12m).

Number of contracts by research 2002/2003 (total=35 contracts).

15

Contract summary and GA research programme charts

Chapter 3

Ozone layer – predictionand detection

Contract No: EPG 1/1/116Title: Analysis of ozone levels over the UK: Phase IIIContractor: AEA Technology PI: J Lampert

Aims and objectives

1. The main purpose of this work is the maintenance and daily operation of the UKstratospheric ozone monitoring programme.

Introduction

2. The maintenance and data collection are undertaken by the Met Office at two oftheir monitoring stations network (two sites: Camborne in Cornwall and Lerwickin the Shetland Islands). The data is then transferred to “Netcen” for screening,processing and final dissemination. Processing and dissemination occur daily.Dissemination involves uploading a ‘best daily average’ to a dedicated web pageon the internet and issuing the results to the World Ozone and Ultra Violet DataCentre (WOUDC) Real-time Mapping Centre. A weekly email is also issued to alist of interested individuals. Monthly data are submitted to the WOUDC forinclusion on their archive.

3. “Netcen” have developed a dedicated web site for Defra with the specificpurpose of disseminating stratospheric ozone data to the public. An example ofthis web page is illustrated by Figure 3.1. This is updated daily with the processeddata, provides archive access to historical data and ozone maps, contains a list ofrelated links, provides further contact details and answers the most frequentlyasked questions.

Fig 3.1: The UK stratospheric ozone web page.

18

Chapter 3 Ozone layer – prediction and detection

4. Days where the processed total ozone is below 2 standard deviations less thanthe long term average mean for that month are designated as ‘low ozone’ eventsand are reported to Defra immediately along with additional analysis. An exampleof such an event is shown in Figure 3.2, a map output from the WOUDC Real-time Mapping Centre (to which the UK daily data is submitted) illustrating a lowozone event on January 13th 2003.

Fig 3.2: Example of WOUDC Real-time Mapping Centre output showinglow ozone event on January 2003.

Results over the year

5. The results of the programme between 1st April 2002 and 31st March 2003 arepresented below in Figures 3.3 and 3.4, which are time series charts of totalozone values recorded at both stations.

6. Low ozone events reported over the year were:

i. 296 Dobson units measured at Lerwick on 17th June 2002;

ii. 230 Dobson units measured at Lerwick on 16th September 2002;

iii. 226 Dobson units measured at Lerwick on 27th September 2002;

iv. Low total ozone over UK on 20th December – no data available from eitherstation on this day; and

v. 238 Dobson units measured at Camborne on 13th January – 238 atCamborne.

19

Ozone layer – prediction and detection

Figure 3.3: Time series showing daily total ozone at Camborne andlongterm monthly averages with +/-2 SD.

Figure 3.4: Time series showing daily total ozone at Lerwick and longtermmonthly averages with +/-2 SD.

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Chapter 4

Ozone layer – impacts

Contract No: EPG 1/1/151Title: Ultraviolet measurements and their analysisContractor: UMIST PI: Dr A.R.Webb

Aims

1. To make spectral measurements of solar shortwave ultraviolet (UV) radiation atthe Earth’s surface in order to:

i. produce an ultraviolet climatology;

ii. enable detection of long-term trends that may arise as a result ofstratospheric ozone depletion or other atmospheric changes; and

iii. contribute to the understanding of radiative interactions with the atmosphere.

Introduction

2. An increase in ultraviolet B (UVB) radiation in the biosphere could cause many,predominantly detrimental, biological and chemical effects. UVB is likely toincrease when stratospheric ozone decreases, but the effect of local ozonedepletion will be modified by the local weather in the short-term and any otherclimate changes in the long-term. Measuring the UV radiation enables it’s dailyand seasonal ranges at a site to be established under the prevailing weatherconditions of the location. In the UK there is great variability on all time scalessince cloud, a major attenuator in the troposphere, is so changeable from day-to-day and year-to-year. If there are long-term changes in the UV climatology theseshould be identifiable with a data record of sufficient length, and spectralmeasurements allow exploration of the cause of the change.

Measurement facilities

3. The solar UV monitoring site at Reading University (51.50N) has been in routineoperation since December 1992, providing one spectrum per hour between sunriseand sunset in the range 280-500nm at 1nm wavelength step and 2s per nm. Thedata-set has, up until 2002, been measured with an Optronic 742 spectroradiometer.A Bentham DM150 spectroradiometer with improved slit function, cosine responseand a faster scan speed was run in parallel and synchronised with the Optronic 742for more than a year to establish continuity in the data. The Bentham, with itsimproved performance, has been the main monitoring instrument in 2003, andrecords spectra every half hour at 0.5nm intervals.

4. The University of Manchester Institute of Science and Technology (UMIST) is a citycentre site 2 degrees further north than Reading. Here a Biospherical InstrumentsGUV-541 radiometer has been employed to measure UV radiation in 5 narrowwavebands since 1997. The bands are centred at 305, 313, 320, 340 and 380nmand sampled at 2-3Hz. Five minute averages of the radiation in each band arerecorded throughout the day. Site and calibration details for both sites remain thesame as in previous reports.

22

Chapter 4 Ozone layer – impacts

5. In previous years ozone measurements have been supplied by the UKMeteorological Office (UKMO) from their sites at Camborne and Lerwick. In June2000 a Brewer Mark III spectrometer was installed at UMIST under a differentprogramme, but the data can be used to support the UMIST UV measurements.An ex-UKMO Brewer Mark IV instrument was repaired and recalibrated in June2002 and has been making ozone measurements at Reading.

Results

6. Consistent spectral UV measurements are now available from the Reading sitefor the years 1993-2003 inclusive, with only one prolonged break in the data setduring the winter of 1996-1997 when a malfunction proved difficult to identifyand remedy. The operation of a higher specification instrument would result in anapparent change in the UV data as a result of the improved instrumentcharacteristics. Careful characterisation of the two instruments and a number ofquality control techniques however, plus analysis of the data gathered by bothinstruments operating synchronously, will enable the two data sets to behomogenised and avoid step changes in the data due to instrument artifacts.This does require the additional inspection and processing of all data gatheredsince 1993. Since this work was only partially funded in the current reportingperiod, the UV data-set was not ready for trend analysis within the financial year2002/2003. The Reading time series, based on the Optronic 742 data alone, canbe seen in previous GA Annual reports.

7. The time series of data from UMIST is too short to enable any meaningful analysisin terms of climatology or long term trends in UV, but it can be used to illustratethe way in which atmospheric variables other than ozone affect UV. Figure 4.1shows the column ozone and erythemal UV radiation measured each day at noonfor the years 1997 to 2003. There are clear annual cycles in both data sets, withyear to year variations. Regression analyses of both data sets (which should notbe extrapolated to infer long term trends) show a slight decrease in both columnozone (-1.9%) and erythemal UV over the measurement period. One wouldexpect that a decrease in ozone would give a corresponding increase in UVradiation. UV radiation is also attenuated by cloud and aerosol in the atmospherehowever. Inspection of sunshine hour climatology shows that the years 1998,2001 and 2002 were particularly devoid of sunshine in the summer months(when UV is usually at its maximum) while 1997 was the best summer in thisrespect in the monitoring period. Thus the absolute UV in these years isgoverned more by the year-to-year variation in cloud than by the slight declinein column ozone.

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Ozone layer – impacts

Figure 4.1: UV Index at noon (bottom left) and column ozone (bottomright) as measured at Manchester. The top panels are the annual solarzenith angle cycle, a major determinant of radiation at the surface.

The UV data is submitted to both the World Ultraviolet Data Centre in Toronto, and theEuropean UV database, that is part of the EC EDUCE project.

Related publications

Webb, A.R., Bais, A.F, Blumthaler, M., Gobbi, G-P., Kylling,A., Scmitt,R., Thiel, S., etal.(2002) Measuring Spectral Actinic Flux and Irradiance: Experimental Results from theADMIRA (Actinic Flux Determination from Measurements of Irradiance) Project. J.Atmospheric and Oceanic Technology 19(7), 1049-1062.

Webb, A.R., Kift, R., Thiel,S., Blumthaler,M., Kylling,A., Schmitt,R., Gobbi,G-P. (2002)Empirical Approach to Converting Spectral UV Measurements to Actinic Flux Data. In:Ultraviolet Ground and Space based measurements, models and Effects. SPIE volume4482 Slusser, Herman and Gao (Eds) pp104 – 114.

Grobner, J., D. Rembges, A. F. Bais, M. Blumthaler, T. Cabot, W. Josefsson, T. Koskela, T.M. Thorseth, A.R. Webb, U. Wester, (2002) Quality Assurance of Reference Standardsfrom nine European ultraviolet monitoring laboratories. Applied Optics 41(21) 4278-4282.

Webb A.R., Kift, R., Thiel,S. and Blumthaler M. (2002) An Empirical Method for theConversion of Spectral UV Irradiance Measurements to Actinic Flux Data. AtmosphericEnvironment 36, 4397 – 4404.

Webb, A.R. (2003) UV Instrumentation for Field and Forest Research. J. Ag. and ForestMeteor. (In Press – invited review)

Kylling, A., Webb, AR.,Bais, A., Blumthaler, M., Schmitt,R., Thiel, S.,Kazantzidis, A., Kift,R., Misslbeck,M., Schallhart, B., Schreder, J., and Topalogou,C. Actinic Flux frommeasurements of Irradiance. J. Geophys. Res. (in press)

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Chapter 5

Climate change – prediction and detection

Contract No: PECD 7/12/37Title: Climate Prediction ProgrammeContractor: Met Office, Hadley Centre PI: G J Jenkins

Aims

1. The aims of the Climate Prediction Programme (CPP) are:

i. To maintain the Hadley Centre as a world-leading institution in order toprovide the UK government with the most up-to-date advice on all aspectsof natural and man-made climate change;

ii. To provide the scientific basis for UK policy on climate change under the UNFramework Convention on Climate Change (UNFCCC);

iii. To provide specific scientific guidance to the UK negotiators in preparationfor the Conferences of the Parties (CoP); Subsidiary Body on Scientific andTechnical Administration (SBSTA);

iv. To act as a national focus for climate change research in the UK;

v. To provide advice and scenarios to optimise policies on adaptation to climatechange, eg., through UKCIP; and

vi. To provide timely, authoritative contributions to international scientificassessments, including those of the Intergovernmental Panel on ClimateChange.

Principal scientific objectives

2. i. To predict to the year 2100 and beyond the global and regional change inclimate expected from increasing concentrations of radiatively and chemicallyactive trace gases and aerosols;

ii. To assess changes in climate and major climate sub-systems in the context ofArticle 2 of the Convention;

iii. To characterise and quantify the influence of human activities on global and,where possible, regional climate change (including the UK) using modelsimulations and appropriate in situ and remotely sensed observationaldatasets of climate variables;

iv. To maintain a state-of-the-art atmosphere general circulation model, coupledatmosphere-ocean GCM model and regional model suite and appropriatecomputing facilities; and

v. To manage the Programme, disseminate the results to Defra and othergovernment departments, the media and the general public.

26

Chapter 5: Climate change – prediction and detection

Background

3. Increasing atmospheric concentrations of greenhouse gases originating fromhuman activity are expected to change the Earth’s climate significantly. Followingthe scientific debate initiated in the mid-1980s, which led to the creation of theIPCC, the first policy commitment by the UK government minister was given in astatement by the Environment Minister, Lord Caithness, to the TorontoConference on Climate Change and Sustainable Development in 1988.

4. In response, the Department decided to expand its climate change researchprogramme and in 1989/1990, asked the Meteorological Office to carry out theClimate Prediction Programme, building on the existing Climate ResearchProgramme (CRP), funded by the Ministry of Defence. The Hadley Centre wasestablished to house the CPP operating alongside and interdependently withthe CRP.

5. The complexity of the science means that the CPP depends upon collaborationwith researchers in other parts of the Met Office, and other centres in the UKand internationally, with the Hadley Centre acting as a focus. There is substantialinvolvement with the UK research base principally funded by the NaturalEnvironment Research Council, and international programmes such as WCRP andIGBP and the work of other climate research centres.

6. In addition to its direct influence on UK policy, the Hadley Centre contributes itsresearch results to the assessments undertaken by the Intergovernmental Panelon Climate Change. 7 Lead Authors and 3 Convening Lead authors of the ThirdAssessment Report (published in 2001) came from the Hadley Centre, and theprocess of planning input into the Fourth Assessment (due in 2007) has alreadybegun.

7. In collaboration with UEA, Hadley Centre global predictions were used to createthe first UK Climate Change Scenarios for the UK Climate Impacts Programme in1998. Improved scenarios, from the regional model, were completed andlaunched by Mrs Beckett in April 2002. Hadley Centre staff have givenpresentations to many of the UKCIP regional and sectoral meetings. Work onclimate scenarios for small islands of the British-Irish Council, using the 25kmRegional Model is well advanced, and a report is due for publication in summer2003. The Hadley Centre regional climate model (PRECIS) was installed in theIndian Institute of Tropical Meteorology as part of Defra’s Indo-UK ImpactsProgramme, and at the Chinese Academy of Agricultural Science under the DefraChina-UK project.

8. Following the late-2000 flooding in many parts of the UK, a new area of thework plan of the CPP was set up in 2002, aimed at making better predictions ofthe effect of climate change on flooding. The work will be based on the regionalclimate model and carried out in collaboration with Natural Environment ResearchCouncil (NERC), Centre of Ecology and Hydrology (CEH) Wallingford.

27


Work programme

9. The main tasks are:

Climate model development

i. To maintain a state-of-the-art atmosphere general circulation model, coupledatmosphere-ocean GCM model suite and regional climate model; and

ii. To develop models which represent to carbon cycle, the sulphur cycle,atmospheric chemistry and other physical, chemical or biological effects ofclimate change, and progressively integrate these into climate models.

Climate change prediction

i. To predict to the year 2100 (and beyond) the global and regional change inclimate expected from increasing concentrations of radiatively and chemicallyactive trace gases and aerosols, under a number of scenarios of futureemissions, particularly those from IPCC Task Group on Climate ImpactAssessments (TGCIA);

ii. To assess changes in climate and major climate sub-systems in the context ofArticle 2 of the Convention; and

iii. To quantify the uncertainty in predictions, using physics ensembles.

Monitor global and UK climate

i. To monitor (using in-situ and remote sensing) changes in a number ofclimate variables, including surface temperatures, temperatures through thedepth of the atmosphere, precipitation, sea-level pressure and humidity, andanalyse trends in these.

Detection and attribution of climate change

i. To characterise and quantify the influence of human activity on global and,regional climate change (including the UK) using model simulations andappropriate in situ and remotely sensed observational data sets of climatevariables.

Programme management and computing

i. To manage and promote the Programme, disseminate the results to Defraand other governmental departments, the media and the general public;

ii. To provide a national focus for relevant UK and international research; and

iii. To procure, maintain, operate and update as necessary computing facilities.

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Management of subcontracts

10. During 2002/2003, the following sub-contracts were managed on behalf ofDefra, each contributing in a direct sense to the Climate Prediction Programmework:

Institute Topic

Centre for Ecology and Hydrology Coupling CEH models to Hadley CentreRCMs

Centre for Ecology and Hydrology Development of the IH-HC analoguemodel

Imperial College Development of spectral techniques

Southampton Oceanography Centre Further development of the oceancarbon cycle model

Southampton Oceanography Centre Comparison of marine temperatures

University of East Anglia Development and use of a RCM forSouthern Africa

University of Leeds Multi-component aerosolparameterisation development

University of Reading GCOS Support

University of Manchester Institute of Ice particle spectra investigationScience and Technology (UMIST)

Information

11. Routine scientific enquiries concerning climate change have been dealt with bythe Hadley Centre, including those from the press and other media. TheDepartment has been kept informed of enquiries related to policy or controversialaspect of the subject. Copies of relevant newly published papers and articles andunpublished results, have been sent to the Department on a regular basis. TheCentre has provided ad-hoc and timely expert scientific advice on climate changeissues for use in responding to parliamentary questions, for Ministerial briefingsor as a result of other official enquiries.

12. A report “Climate Change Science; some recent results from the Hadley Centre”was distributed in large numbers, particularly at the UNFCCC CoP 8 meeting inDelhi, where Hadley Centre staff manned a stand. An update of the bookletdescribing the PRECIS regional climate modelling system was produced anddistributed, and a Hadley Centre presentation describing its availability to, anduse in, developing countries was chaired by Mr Meacher.

13. As the planning community increasingly realises that they will need to takeclimate change into account, demand for presentations have increased. In2002/2003 some 45 presentations were given to central and local government,regulators, Environment Agency, industry groups, etc.

29


Results from programmes of work

14. In many cases, the work reported below has been undertaken in co-operationwith the MoD Government Meteorological Research Programme, but wherepossible the results given are limited to those under the Defra Programme.

15. The Hadley Centre’s work is divided into a number of sections which are reportedon in the following annexes:

1. Global Predictions of Climate Change and Sea Level Rise

2. Prediction of Regional Climate Change

3. Monitoring and Analysis of Climate Change

4a. Sea Surface Temperature Observations from (A)ATSR

4b. Cloud Properties from (A)ATSR

5. Detection and Attribution of Climate Change

6. Medium Term Climate Predictions

7. Clouds and Radiation

8. The Global Carbon Cycle and Ecosystems

9. Ocean Modelling

10a. Aerosol Modelling and their effects

10b. Modelling of Atmospheric Chemistry

11. Programme Management, Co-ordination and Dissemination – NOT USED

12. Provision of Computing Support – NOT USED

13. Physical, Chemical, Biological Effects of Climate Change

14. Probability, Uncertainty and Risk

30


Annex 1: Global predictions of climate change Aim

1. To simulate and predict change in global climate using state-of-the-art coupledocean atmosphere general circulation models.

Background

2. The purpose of this annex is to provide the fundamental predictions of globalclimate change for use either directly, to drive higher resolution regional models,or for use by impacts modellers. Both policy relevant scenarios (non-mitigationand stabilisation) and idealised scenarios are used. A significant fraction of theoutput now involves making assessments of the mechanisms of change, which isimportant because it allows us to better appreciate the realism of the predictionsand often highlights where model improvements are needed.

3. Annex 1 has strong links with several other annexes. This year the links to Annex9 (ocean modelling) have been particularly strong.

Activities for 2002/2003

i. Projections of storm surge heights around the United Kingdom for the SRESfuture emissions scenarios were completed and the results reported;

ii A multi-century evolution of the Greenland ice sheet was begun and thefirst 180 years of results assessed and the results reported;

iii. Analysis of a set of idealised sea level experiments has been carried out tolook at different factors influencing the regional pattern of time mean sealevel rise;

iv. A comparison and evaluation of the thermohaline circulation’s sensitivity togreenhouse gas forcing in HadCM2 and HadCM3 was made and reported;

v. Recent and future changes in Arctic sea ice in HadCM3 were assessed andthe results submitted to a journal;

vi. The climate variability related to ENSO was examined in a HadCM3 warmingexperiment and the results reported;

vii. A model prediction of climate change due to the SRES A1B emissionsscenario was set up and begun. It is due to complete during summer 2003;and

viii. An observationally based estimate of the climate sensitivity was made usingocean heat content and surface temperature measurements. The resultshave now been published.

31


Results

Sea level

5. Variations in sea level have been investigated on a range of scales, from a fewhours (storm surges), through decadal time scales (regional patterns of time meanchange), to century scale changes (Greenland ice sheet). Increases in mean sealevel are predicted to reduce the return period of a given height of storm surgearound the entire UK coastline. The size of the reduction depends on location.Changes in storminess will reduce it further at many locations and vertical landmovements will modify the pattern of changes also. The pattern of time mean sealevel rise is also known to be spatially inhomogeneous. Our recent work highlightsthe importance of salinity changes to the pattern of change and that some of thethermal change results from a redistribution of heat within the ocean, rather thanadditional heat. Surface wind, heat and moisture all effect the spatial pattern ofchange. Shown below in Figure 5.1 is the regional pattern of relative sea-levelchange after 70 years of a 2% per year increasing CO2 simulation (left panel).When the wind anomalies from this simulation are applied to a control simulation(right panel) sizeable sea level changes occur in some regions.

Figure 5.1: Regional pattern of relative sea-level change after 70 yearsof a 2% per year increaseing CO2 simulation (left panel). When the windanomalies from this simulation are applied to a control simulation(right panel) sizeable sea level changes occurred in some regions.

6. The Greenland ice sheet is expected to contribute to sea-level rise in a warmingclimate, and there is a possibility that changes in the ice sheet (such as therelease of fresh water from the ice sheet into the north Atlantic Ocean) maymodify the climate further. To include these feedbacks, a Greenland ice sheetmodel has been coupled to HadCM3. The first 180 years of a 4xCO2 simulationshow a reduction in ice sheet volume of around 0.73% per decade (around 5.1mm of sea level rise per year).

32


Thermohaline circulation

7. Confidence in the prediction of future changes in the strength of thethermohaline circulation (THC) is limited by disagreements between differentmodels. To better understand the predictions in the Hadley Centre models themechanisms associated with THC changes have been compared in HadCM2 andHadCM3. Both models initially show a weakening, but there is a gradual recoveryin the former whilst the THC strength stabilises at a reduced value in the later.The difference appears to be primarily due to the pattern of heat flux forcing inthe two models. Additionally, salinity advection, which is an important stabilisingmechanism, is not well represented in the low-resolution (more diffusive)HadCM2 ocean. HadCM2 THC changes also depend on local conditions in aregion of large flux correction (the physically more realistic HadCM3 is not fluxcorrected). The analysis methods developed during this work will allowcomparison of HadCM3 with other climate models in the future, leading toreduced uncertainty in THC predictions.

Arctic sea ice

8. The Arctic region response of a four member HadCM3 ensemble simulation wasexamined for the period 1860 and 1999. The decreasing trend in ice extent (of-2.5% per decade) for the period 1970 to 1999 is similar to the observations(Figure 5.2). Further, in HadCM3 it appears that natural forcing (solar and/orvolcanic) are very unlikely to be responsible for a trend of this magnitude. Thesimulated decrease in volume appears to be somewhat less than some recentobservations. In the future, HadCM3 predicts that the ice extent will continue todecline, with a reduction of around 13% per oC of global mean warming. Forthe A1FI emissions scenario this corresponds to around a 55% reduction of the1990 extent.

Figure 5.2: Comparison of simulated and observed Northern Hemispheresea ice extent. The solid line shows the observations and the dotted linethe model.

33


Response of ENSO in a HadCM3 warming experiment

9. The results showed that the lack of ocean resolution at the thermocline and theoverly strong relationship between atmospheric convection and SSTs both affectthe model’s ability to simulate ENSO. This is exacerbated in a warmer climatebecause of the deeper thermocline (the ocean model’s vertical resolution becomecoarser at depth) and greater SSTs. As the warming continues, the maximum SSTanomaly during ENSO events is seen to shift westward from the Eastern pacific,and the amplitude of the anomalies increases. Future work will look at thewhether the energetics of the ENSO will alter in a warmer climate.

Climate sensitivity

10. A probability distribution of values for effective climate sensitivity were estimatedfrom observations of ocean heat content (insitu temperature) changes, surfacetemperature changes and radiative forcing using a heat balance equation. Theuncertainty in each parameter leads to a probability distribution for the climatesensitivity with a lower bound (5th percentile) of 1.6 oC. The dominantuncertainty is in the radiative forcing, especially the aerosol forcing. Reducing theuncertainty in the parameters in future should provide a model-independentmeans of constraining climate sensitivity further. Figure 5.3 below illustrates theprobability distribution of effective climate sensitivity deduced from observations.The dashed line shows the mode and the dotted line the median.

Figure 5.3: Probability distribution of effective climate sensitivity.

0.020

0.015

0.010

0.005

0.000

Prob

abili

ty p

er 0

.1 K

inte

rval

0Climate sensitivity (K)

2 4 6 8 10

34


Annex 2: Predictions of regional climate changeAim

1. To simulate and predict changes in climate at a regional scale.

Background

2. Impacts of climate change on socio-economic sectors will be felt at a local orregional scale, and hence impacts assessments will require predictions at aresolution down to tens of kilometres or less. These assessments are central toUK and other governments’ ability to adapt to climate change and to provideinformation on vulnerability as required by the UN Framework Convention onClimate Change. To address this need we have developed regional climatemodels (RCMs) and a high resolution atmospheric global model. These are beingused at the Hadley Centre to provide high quality regional simulations globally(at a resolution of 150km), for Europe (at 50 and 25km) and for southern Africa(at 50km). Also, the functionality for using RCMs on PCs has been provided inthe PRECIS regional climate modelling system which is now in use in India andChina and has been made available to eight African countries with countriesfrom all regions expressing keen interest.

Activities for 2002-2003

i. Analysis of an RCM prediction of extreme precipitation changes over UKgridboxes matched with regions affected by the autumn 2000 floods wascompleted and written up for a journal paper;

ii. Data from the 25km resolution RCM simulations of European climatechange was analysed and provided for a report on climate change scenariosfor the British Irish Council;

iii. In depth analysis of predictions of southern African climate change fromHadley Centre global and regional models have resulted in several reportsand draft publications, with four journal papers either accepted or submittedfor publication or permission to publish;

iv. The Defra/ DfiD/UNDP sponsored PC regional model climate modellingsystem PRECIS (version 1) was released with an initial training course in CapeTown given to participants from eight African countries. The model was alsodisplayed at CoP8 with an accompanying brochure; and

v. A visiting scientist from the Chinese Academy of Agricultural Sciences(CAAS) was hosted for a year to gain experience in Hadley Centre climatemodelling over China and specifically training in the use of PRECIS as a toolfor providing climate change scenarios for use in impacts models.

35


Results

4. Analysis of RCM predicted changes in UK extreme precipitation for the end of thecentury has demonstrated significant reductions in return periods with thefrequency of 20 year events reducing by a factor of seven or more. The analysiswas extended to provide an estimate for the change in extreme precipitationpredicted by this experiment as a result of climate change to date. This used ascaling approach and indicated a likely reduction in return periods should bebeing experienced currently. Analysis of climate extremes over southern Africa hasalso demonstrated large changes with the implications for these on waterresources in particular being explored where the importance of including changesin variability in particular was demonstrated.

5. Analysis of the 25km RCM prediction of European climate change hasdemonstrated the expected higher information content but also the expectedconsistency with predictions at 50km. Given that there is only one predictionavailable at this resolution, the latter is important in the context of the UKCIP50km scenarios released last year; where the use of initial condition ensemblesand different emissions scenarios provides a better estimate of some aspectsuncertainty in future predictions.

6. PRECIS, the PC-based regional model, has successfully been tested and appliedover various regions. Results from the prototype PRECIS system, its RCM anddriving GCM indicated many technical issues and identified deficiencies in someaspects of simulated climate. The former have been addressed resulting in a veryrobust and user-friendly system. The latter motivated a reformulation of the GCMto improve further the global quality of boundary conditions. The PRECIS RCMwas also updated to retain scientific consistency. These activities, along withproducing the training materials funded under the UNDP contract, definedversion 1 of PRECIS. This was initially released to our collaborators at CAAS andalso IITM in India and then subsequently, after a very successful training course inCape Town, to eight African countries.

36


Figure 5.4: Estimates of the return periods of the annual maximum 30 dayprecipitation extreme for pre-industrial climate (1860), the climate of thepresent day (2000) and the climate of the end of the century (2090).

Huntingford, C., R. G. Jones, C. Prudhomme, R. Lamb, and J. H. C. Gash, 2003:Regional climate model predictions of extreme rainfall for a changing climate.Q. J. R. Met. Soc. 129, 1607-1621.

10

8

6

4

2

Lewes Shrewsbury

Ann

ual M

axim

um (m

m/d

ay)

2 5 10 20 50 100Return Period (yr)

10

8

6

4

2A

nnua

l Max

imum

(mm

/day

)


10

8

6

4

2

York

Ann

ual M

axim

um (m

m/d

ay)


Prediction for 1860 climatePrediction for 2000 climatePredication for 2090 climate

37


Annex 3: Monitoring and analysis of climate changeAim

1. To monitor climate change by establishing, maintaining, improving and analysinghigh quality data sets of climate variables for use in studies of detection andattribution.

Background

2. Changes in temperature and humidity in the free atmosphere are of considerableinterest. The former because observations suggest the tropical troposphere is notwarming as fast as models predict and the second because humidity changes area strong climate feedback. Society is most sensitive to changes in extreme eventssuch as storms or other extreme weather events. Therefore analysis of observationsis needed to see if any changes have taken place and to evaluate simulations.

Activities

3. Quality control and analysis of sub-daily pressure data from 1950 has been donein order to assemble a data set of extreme storms over the UK and Iceland.

4. A new gridded daily maximum-temperature data set based upon global dailystation observations was created. Initial evaluation showed that the gridded datarepresent the large-scale spatial patterns and the seasonal cycle of the sourcedata well.

5. We have produced the first release of a new atmospheric temperature data set(HadAT1). This data set is based on records from 477 radiosonde stations. Eachrecord was corrected for “jumps” by comparison with near-neighbours and,unlike earlier data sets, is independent of temperatures measured from satellite.This new data set was compared with an earlier radiosonde temperature data setand large-scale patterns were found to be grossly similar. A qualitativecomparison of zonal-mean trends with satellite temperatures, over the period ofoverlap, shows that these adjustments bring the radiosonde and satellite seriesinto closer agreement. This procedure, as expected, smoothes fields of anomaliesand trends. However, the coverage is sparse in many regions, and we plan toimprove this by incorporating additional stations.

6. In-situ measurements of upper air humidity from radiosondes are beset withproblems. Major sources of possible systematic bias related to different reportingpractices and instrument limitations have been identified. Daily data are beingused to develop a global gridded radiosonde atmospheric humidity data set(HadAH) for research and model comparison.

7. The Hadley Centre contribution to the Global Upper-Air Network (GUAN) projectcontinues with the provision of a web site and routine network monitoringstatistics. Routine receipt by the Hadley Centre of CLIMAT TEMP reports from the152 GUAN stations has improved to 75% in 2002/2003 from a 65% receipt in1998/1999 and 70% in 2001/2002.

38


Results

8. Over the UK, extreme storms have shown an increase since 1950 the mostsignificant being over the southern UK as illustrated in Figure 5.5. The “y-axis”represents the number of ‘storms’ occurring over each region during January –March of each year divided by the number of stations that were reporting in thatyear. The smoothed line represents the decadally averaged values calculated usinga 21-term binomial filter. The dashed line is a least-squares fit to the data and redsignifies the trend is significant at the 5% level. Changes in the distribution ofsevere storm events over both the UK and Iceland may imply a southerly shift ofthe North Atlantic storm track. Current ‘gale’ indicators, which have dailyresolutions, are mostly unable to resolve these extreme storm events.

Figure 5.5: Time series of October – December extreme storms for(a) UK and Iceland (b) Iceland (c) UK (d) northern UK (e) western UKand (f) southern UK.

39


9. Comparison between a gridded data set of observed daily maximum with thosesimulated by the model HadAM3 is on the whole encouraging. There aresignificant differences (Figure 5.6) however. The main cause of these is thedifferent mean climatology between the two data sets. Even when this isaccounted for, the extreme high and low ends of the temperature distributionscan differ substantially with the model showing greater range at both ends of thedistribution for most areas. It is not yet known whether this is a problem with thenew observed data, with the model or a combination of both.

Figure 5.6: January, (a) and (c), and July, (b) and (d), maximumtemperature standard deviations for the gridded observations andHadAM3 driven by observed SST and sea-ice.

10. Radiosonde and satellite based tropospheric temperature records show that mostof the recent difference in trends between the surface and the free tropospherearises in the tropics. As shown in Figure 5.7 below the radiosonde dataset wasHadRT2.1s, in which stratospheric temperatures were adjusted to be consistentwith MSU-TLS7 where known instrument changes occurred and the biases werefound to be significant using a student’s t-test. The thick black contour indicatestrends significant at the 5% level (two-sided t-test). Regions of significant relativetropospheric cooling are concentrated in those areas where deep convection isimportant. These regions are where current climate models predict maximumtropospheric warming. We have shown that observed tropical tropospherictemperatures are statistically related to stratospheric temperature changes as wellas to surface temperature changes. An ensemble of climate models simulationsforced with the major anthropogenic and natural forcings, and observed seasurface temperatures (SST) however, fail to replicate the observational link withthe stratosphere. We concluded that stratospheric cooling is likely to have

40


contributed to the cooling of the troposphere relative to the surface in regions oftropical convection, and that the mechanisms underlying this link are notcaptured in the current generation of climate models.

Figure 5.7: Trends in zonal-mean temperature anomalies for 1979-2001(K/decade), based on radiosonde9 and surface19 data. Top: annual; lowerleft: December to February; lower right: June to August.

11. In order to understand whether trends are related to internal variability of theclimate system or recent climate change, the role of the El Nino/SouthernOscillation (ENSO) in UTRH variability has been assessed. ENSO is the onlyidentifiable mode of UTRH variability contributing about 25% of the total tropicalvariance. Humidity follows the general pattern of shifted convection during anENSO event. As a result of ENSO forcing, large changes in UTRH over theequatorial Indian and Atlantic oceans occurs many months following an ENSOevent. Changes in local tropospheric temperatures also contribute to the netchange in UTRH during ENSO.

12. Observed trends in Upper Tropospheric Relative Humidity (UTRH) have beenstudied using satellite data for the period 1979 -1998. While there is nosignificant global trend, this is a result of cancellation of significant regional andzonal trends of opposite sign (see Figure 5.8). Relative humidity has increasednear the equator, and decreased in the subtropics. We find that long-term trendsin UTRH are little affected by the removal of ENSO. Analysis of zonal mean timeseries also shows that a simple intensification of the hydrological cycle does notexplain the observed changes. Preliminary comparison of these observations with

41


HadAM3 simulations suggests the model does not reproduce them. A number ofpossible explanations are under investigation relating to inter-satellite calibrationissues, tropospheric temperature trends, or modes of decadal climate variability.

Figure 5.8(a): Regional (>90% confidence) and (b) zonal trends of UpperTropospheric Relative Humidity (UTRH) for March 1979 to August 1997 in%/yr. As observed by the HIRS instrument flown on NOAA series satellites.

Global UTRH Trends 03/79 08/97

0 90oE 180 90oW 060oS

30oS

0

30oN

60oN

%yr 1

0.3 0.2 0.1 0 0.1 0.2 0.3

Zonal UTRH trends 03/79 08/98

0.15 0.10 0.05 0.00 0.05 0.10 0.15Trend (%yr 1)

60oS

40oS

20oS

0

20oN

40oN

60oN

Latit

ude

(a)

(b)

42


Annex 4a: SST observations from (A)ATSRAim

1. To develop optimum sea-surface temperature measurements from the (A)ATSRseries of satellite radiometers for use in global climate monitoring.

Background

2. Sea-surface temperature (SST) measurements to <0.3 K accuracy (with less than0.1°C drift per decade) are required for climate change detection. Satellite-derived SSTs can be used to augment existing climatological databases, whichhave previously been dependent on in situ observations. The Along-TrackScanning Radiometers (ATSR-1 and -2), and their successor, the Advanced ATSR(AATSR) have been designed to provide such accuracy. AATSR has beensubstantially funded by Defra and was launched on board ESA’s Envisat platformon 1st March 2002. The main scientific objective of the AATSR is continuity of theATSR-1 and -2 data sets, in order to extend a 10-year near-continuous record forclimate research out to at least 15 years.

Activities

3. The satellite-derived SST retrieved from (A)ATSR relates to the top few microns ofthe ocean (the skin). For consistency with the historical record, therefore, thesatellite skin SST must be converted to an equivalent bulk temperature, usingphysical models for the skin effect and the diurnal thermocline. The AATSRprocessor has been developed to receive the AATSR data in real time from ESAand convert it into a bulk SST with error estimates suitable for assimilation intothe HadISST climate quality analysis and other NWP analyses at the Met Office.

4. Highlights of activities this year have been:

i. Commenced ATSR-2 processing for 1998 consistent with AATSR processingand compared with microwave TMI SSTs;

ii. AATSR data started to be received from ESA in near real time from 19August 2002 and the in-house processing to bulk SST commenced shortlyafter. An AATSR data monitoring web site has been set up for the AATSRvalidation team at:www.metoffice.com/research/nwp/satellite/infrared/aatsr/index.html ;

iii. A report/presentation was made to ESA at the ENVISAT validation workshopon the first 3 months of AATSR data received (September – November 2002)showing the AATSR SSTs were at least as good as those from ATSR-2; and

iv. Scientific studies have continued on the (A)ATSR error analysis and model toflag observations affected by diurnal thermoclines.

43


Results

5. Validation of the AATSR SSTs on a global scale provides firm evidence that theinstrument and SST products are close to or within specifications. A time seriesof the daily global mean difference between AATSR skin and bulk SSTs and buoySST (Figure 5.9) shows, apart from one exception, the mean daily AATSR-buoySST difference is consistent throughout the period. AATSR skin SST is within±0.3 K of the buoy SST, while the bulk SST can stray to the warm side of thesebounds. Mean differences for all match-ups in August – November (excluding 4obvious anomalies) are summarised in Table 5.1. There is little difference betweenthe skin SST and the buoy SST at night when we should expect a bias o between-0.1 and -0.2 K from the skin effect. This may indicate that the night-timeretrieval algorithm is too warm by this amount. There is a mean bias of (0.15Kbetween the 2 channel and 3 channel dual-view algorithms at present, with thecooler dual-view 2-channel algorithm providing SSTs closer to the true skintemperature than the dual-view 3-channel SST. The origin of this bias isunderstood and the methodology to correct for it is being implemented tobring 2-channel and 3-channel SST retrievals into agreement.

Figure 5.9. Time series of (a) daily global mean difference between AATSRSST (skin in blue, bulk in orange) and buoy SST, (b) standard deviation ofthe difference, and (c) number of buoy match-ups per day.

August September October November19 19 2 9 16 23 30 7 14 21 28 4 11 18 25 2


1.0

0.5

0.0

–0.5

–1.0

2

0

AA

TSR

– bu

oy S

ST /

KS.

D. o

f A

ATS

R –

buoy

SST

/ K

(a)

(b)

44


Table 5.1. AATSR SST minus buoy SST (August-November 2002).

Skin – buoy Bulk – buoy

mean SD n Mean SD n

All 0.04 0.52 1804 0.19 0.52 1804

Night 0.04 0.39 751 0.18 0.38 751

Day 0.05 0.59 1053 0.20 0.59 1053

6. Figure 5.10 shows a comparison of the monthly mean AATSR bulk SST forFebruary 2003 with the in-situ SST dataset HadISST1, that demonstrates acrossthe globe differences are generally well below 1 K. Differences between HadISST1and the AATSR data are often in areas of strong SST gradients where the analysishas slightly misplaced the region of strong gradient. Other areas where there aredifferences are along the equatorial Pacific and over the southern Oceans.

Figure 5.10. AATSR bulk SSTs minus HadISST1 SSTs for February 2003.

AATSR bulk_D2dD3n SST minus HadISST1 (1 dg), February 2003

180 90W 0 90E 18090S

45S

0

45N

90N

SST difference / degrees Celsius

+5 +4 +3 +2 +1 +0.3 0.3 1 2 3 4 5


60

40

20

0

Num

ber

of m

atch

ups (c)

45


7. To enable the AATSR SST product to be assimilated into an SST analysis anestimate of the error (bias and variance) has to be made taking into account alluncertainties entering the product generation. Values for the AATSR bulk SSTshave been computed for various situations and will be provided along with theSST product.

8. For the future it is planned to continue the processing, in real time of the AATSRdata set and in parallel to continue to process the old ATSR-1/2 datasets in orderto build up a complete 15 year climate quality SST record from the ATSR sensors.

46


Annex 4b: Cloud properties from AATSRAim and Background

1. Cirrus (ice crystal) clouds have an important effect on current climate, and anychanges to their characteristics will have a substantial feedback on climatechange. Hence it is vital that cirrus clouds and their optical properties are wellrepresented in climate models.

Activities

2. During this year a database of the single-scattering properties for randomlyoriented ice aggregates has been completed for both solar and thermalwavelengths. The database consists of the following scattering properties: theextinction cross-section, single-scattering albedo, asymmetry parameter andscattering phase function. The single-scattering properties have been producedat wavelengths between 0.2µm and 30µm at a resolution in wavelength spaceof about 0.20µm. The database therefore covers the entire wavelength rangethat is important to cloudy radiative transfer within the Unified Model.

3. The major advantage of the new database is that it also incorporates a scatteringphase function, which will allow the simulation of satellite radiances and thus allowa direct comparison between the climate model and remotely sensed radiometricmeasurements (at both solar and thermal wavelengths). A further advantage of thenew optical properties is that they have been rigorously tested using ATSR-2 andaircraft radiometric measurements of cirrus cloud covering both solar and thermalwavelengths, between the scattering angles of 10°-170°. Moreover, unlike thepresent optical properties the new optical properties are based on the first principlesof electromagnetic theory. The new database of optical properties has beentransferred to the Hadley Centre for incorporation into the climate model.

Results

4. Given that the new optical properties generally well represent the radiative propertiesof cirrus cloud, retrievals from ATSR-2 based on these optical properties can now bestudied with greater confidence. As an example of this the potential relationshipbetween retrieved crystal effective dimension (De) and cloud temperature (Tc) is furtherstudied. In the climate model it is assumed that there exists a simple deterministicrelationship between De and Tc (i.e., smaller and larger ice crystals are alwaysassociated with colder and warmer temperatures, respectively). The basic assumptionin the model is that this relationship holds throughout, even for convective cloud.The example figures given below illustrate that the relationship between De and Tcis rather more complex than that given by a simple deterministic model.

5. Figures 5.11 and 5.12 show the behaviour of De as a function of Tc for two cases(for reasons of brevity only two distinct cases are shown here). Most of the casesindicate only a weak or very weak relationship between De and Tc. Figure 5.11shows a strong relationship between De and Tc, which is atypical. The reason forthis is because the case shown in Figure 5.11 is based on retrievals fromstratiform ice cloud where the ice crystals have gravitationally settled; for such

47


quiescent cases such a relationship is to be expected. Figure 5.12 shows a casewhere the retrievals are taken from tropical convection and in this case theinverse of Figure 5.11 is found. That is the larger ice crystals are more associatedwith the colder temperatures. For such cloud the vertical velocities can be asgreat as 20 ms-1 enabling much larger ice crystals to be transported to the cloudtop, i.e., lower temperatures.

6. In general the results do not support a simple deterministic model of De as afunction of Tc alone. As illustrated from Figure 5.12 it is also important to includelarge-scale dynamics and microphysical processes. If within the UM the large-scaledynamics and microphysical processes are correctly represented then the patternsof behaviour found in the figures should be followed by the UM output, i.e., theyshould evolve naturally, without the need for an assumed statistical relationship.

Figure 5.11: De plotted against cloud temperature (Tc), over mid-latitudestratiform ice cloud on the 23rd July 1996.

Figure 5.12: De plotted against cloud temperature (Tc), over a tropicalconvective ice cloud on the 22nd July 1996.

80

60

40

20200 220 240 260

Cloud Temp (K)

De

(mirc

rons

)

100

80

60

40

20

0200 220 240 260

Cloud Temp (K)

De

(mirc

rons

)

48


Annex 5: Detection and attribution of climate change Aim

1. To seek attribution of recent climate changes to human and natural influences, atthe global and regional scale, through comparison of model and observational data.

Background

2. There remain many uncertainties that limit our confidence in answering the keyquestion of how much of recent warming is caused by increasing greenhousegases. Knowledge of the past contribution of greenhouse gases in turn constrainspredictions of future warming. Whereas most work to date has concentrated onvery large-scale changes in temperature, attribution studies are now beingapplied to regional scales and other variables, in order to consider changes thatare likely to have a significant impact on society.

Activities

3. Highlights of activities this year have been:

i. An investigation into the sensitivity of global-scale attribution results toerrors in the modelled pattern of response to aerosols;

ii. A calculation of the likely contribution of anthropogenic and natural factorsto 20th century temperature change in six continental-scale regions,including North America and Europe;

iii. An estimation of the uncertainty in future UK climate based on amulti-model analysis constrained to observed climate change.

Results

4. The Third Assessment Report of the IPCC concluded that most of the warmingover the last 50 years is likely to have been due to the increase in greenhouse gasconcentrations. The forcing due to aerosols, especially due to the indirect effectson clouds however, is still very uncertain. So far attribution analyses have not fullytaken account of uncertainty in the pattern of climate response to sulphateaerosols. We have investigated the sensitivity of attribution results by perturbingmodelled patterns of response to aerosols, varying in turn the relativecontributions from the Northern and Southern hemispheres, high and lowlatitudes, land and ocean and from North America and Eurasia. We find thatattribution results are most sensitive to changing the hemispheric temperaturedifference, but overall, the conclusion of the IPCC report is found to be robustto a wide range of uncertainty in the climatic response to sulphate aerosols.

5. A paper has recently been submitted to Geophysical Research Letters showingthat the warming effects of increasing greenhouse gas concentrations have nowbeen detected on continental scales. Figure 5.13a and 5.13b shows estimates(with their uncertainties) of scaling factors by which the modelled response from

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greenhouse gases (G), aerosols (SO) and natural forcings (NAT) needs to bemultiplied in order to agree with the observed temperature response in Europeand N America. Where the uncertainty bar is entirely above the zero, this meansthat the relevant signal has been detected (at the 5% level) and, where theuncertainty bar includes 1, this indicates that the model simulation of the climaticresponse to this forcing is consistent with the estimated observed response tothis forcing.

6. Warming from greenhouse gases is clearly detected in North America (Figure5.13a) and is just detected in Europe (Figure 5.13b), according to this analysis.The uncertainty bars on the scaling factors for aerosols (SO) and natural factors(NAT) are larger reflecting the greater uncertainty in the contributions from theseforcings. The best estimates of the contributions from these forcings over the20th century are shown in Figure 5.13c and Figure 5.13d. Greenhouse gasesprovide an accelerating warming in both regions, with aerosols producing ageneral net cooling, with cooling starting earlier in Europe than in N America.Our analysis indicates that HadCM3 appears to overestimate aerosol cooling inEurasia, which could possibly be related to missing warming from black carbon.

Figure 5.13: (a) Estimates with their uncertainties of scaling factors bywhich model response from greenhouse gases (G), sulphate aerosols andozone (SO) and natural factors (NAT) need to be multiplied in order toagree with the observed temperature response in N America. (b) as (a)but for Europe. (c) Best estimates of the contributions from G, SO andNAT to observed decadal-mean 20th century temperature changes inNorth America (d) as (c) but for Europe.

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7. Past work has shown that attribution analyses can be used to provideobservationally based constraints on predictions of 21st century globaltemperature rise. We have extended this work to provide initial estimates of“Probability Density Functions”( PDFs) of England and Wales precipitation usingknowledge of the likely future PDFs of global-mean temperatures. Since regionalpatterns of climate change differ between models, the approach that has beentaken is to include simulations from four different coupled climate models so asto roughly sample the possible range of regional uncertainty. Each model’sprediction of regional climate changes is scaled in line with the scaling appliedto their global temperature predictions. These PDFs are then combined into anoverall PDF, assuming each model’s prediction is equally valid.

8. Figure 5.14 shows the PDFs of changes in winter and summer UK precipitationunder the SRES A2 scenario. The red solid lines are the PDFs of future climaticmean values which are multi-peaked, reflecting the different contributions fromthe four GCMs considered (better sampling of possible future regional predictionswould produce smoother PDFs). The red dashed lines in Figure 5.14 include thepotential fluctuations of the actual future world around their climatic meanvalues and are consequently smoother. Winters are expected to become wetterand summers drier but there is a large spread in the PDFs. These result from awide spread of relationships in the different models between global meantemperature and UK precipitation. Improvements to the analysis, such asincluding more models and investigating observational constraints on climatevariables other than global temperature, could help to reduce the uncertainty infuture UK climate changes.

Figure 5.14: Probability density functions (PDFs) of England and Waleswinter and summer precipitation changes under SRES A2 scenario in 2020s.

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Annex 6: Medium-term climate predictionsAims

1. To investigate the skill of predictions of climate for 5-15 years ahead. Prospectsfor achieving skill beyond the seasonal time scale depend on the ability to predictthe evolution of sea surface temperatures (SSTs) from observed initial conditionsand the ability to predict the secular response to changes in anthropogenicforcing. The level of skill in a given region will also depend on the extent towhich SST forces a characteristic regional response in the atmosphere.

Background

2. Defra policy is to encourage potentially vulnerable sectors of UK industry andcommerce to take account of climate change in future planning. Whilst theyrealise the importance of this, they also need predictions over the medium term,which will be dominated by natural variability. In addition, predictions of globalchange over the next 5 years could be used to pre-empt criticism of UKgreenhouse gas emissions policy in the event of a run of cold years, for example.

Activities

3. Predictions are initialised by assimilating observed ocean and atmosphereanomalies into the coupled model, currently HadCM3. During 2002/2003 weassessed the skill of HadCM3 using a new set of 60 decadal hindcasts containingimprovements relative to a corresponding set made during 2001/2002. Initialconditions were generated by assimilating (6 hourly) ECMWF reanalysis fields ofobserved atmospheric winds, temperatures and surface pressure and (monthly)analyses of observed ocean temperature and salinity from 1st January 1979 to 1stDecember 1993. Hindcasts were started from 1st March, June, September andDecember in each year. The effects of anthropogenic, solar and volcanic forcingswere included in both the assimilation and hindcast experiments.

4. The ocean analyses were improved relative to those used to initialise previoushindcasts as follows:

i. Analyses of temperature and salinity anomalies are obtained by optimalinterpolation from observation sites using spatial covariances from HadCM3(there being insufficient data to calculate observed covariances below thesurface). Recognising that model covariances will contain errors we nowrestrict their use to local regions in which they are sufficiently accurate toreduce the expected error in the resulting analysis. Model fields are nowspatially smoothed prior to the calculation of covariances as this is found togive better agreement with observed covariances of SST and reducesundesirable small scale noise in the analyses;

ii. The full four dimensional analysis of temperature and salinity, consisting ofhorizontal fields at each model level for a time series of consecutive months,is now performed in a single step, whereas previously the spatial analysis foreach month was done prior to the temporal analysis. This removes a

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potential source of inaccuracy arising from the need to estimate correlationsbetween analysis errors from the spatial and temporal stages; and

iii. The optimal interpolation procedure requires values for a number ofparameters (e.g. assumed observation errors and the number of consecutivemonths used in temporal analysis). These were previously estimatedsubjectively but are now determined objectively by identifying valueswhich give the best scores in verification of analyses against independentobservations.

5. The forecast model was improved by increasing the background coefficient ofvertical mixing of momentum in the ocean. This led to a beneficial reduction insimulated interannual variability of tropical Pacific SST and improved the skill offorecasts of El Nino-Southern Oscillation (ENSO) events. This suggests that asystematic investigation of the effects of uncertainties in model physics couldlead to further improvements in forecast skill, however this will not be practicableuntil a strategy is developed to control drift in the model climate in response tochanges in formulation.

6. Decadal prediction involves identifying a skilful signal in a time series of climateanomalies which may be relatively small in magnitude compared to “noise”arising from unpredictable components of natural variability. Ensemble averaginga number of forecasts is therefore an obvious method of increasing the signal tonoise ratio in the forecasts. We have begun to investigate ensemble techniquesby converting each of our 60 hindcasts from a single model integration into anensemble of four, initialised from consecutive days immediately preceding thehindcast period. This work will continue next year.

7. The main priorities for 2003-2006 are:

i. Assess the potential of ensemble techniques to improve forecast skill,focusing initially on ensembles which sample uncertainty in the initialconditions (see above);

ii. Produce a first forecast of 2005-2015 using HadCM3; and

iii. Commence development of a new ensemble prediction system based onHadGEM and sampling uncertainties arising from model physics and initialconditions.

Results

8. The net effect of the improvements in our analysis of ocean observations isdemonstrated in Figure 5.15, which compares temperature anomalies at ~200mproduced by the new analyses with those produced previously. Although theanomaly patterns are broadly similar, the new analyses are much smoother andcontain far less small scale structure which would not be expected to bepredictable beyond the seasonal time scale.

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Figure 5.15: An example of potential temperature anomalies at 204mproduced by improved ocean analyses used to produce hindcasts runduring 2002-2003 (a), compared with analyses used to produce previoushindcasts run during 2001-2002 (b).

9. A necessary condition for forecast skill on the decadal time scale is to achieve skillon the seasonal time scale. In Figure 5.16 we compare the skill of our decadalprediction system (DePreSys) against that obtained by coupled ocean-atmosphereGCMs from European modelling centres participating in the EU FP 5 project“DEMETER”.

Figure 5.16: Correlation between forecast and observed SST anomalypatterns in the northern hemisphere for hindcasts initialised from 1stFebruary (ECMWF, CNRM, GloSea) or 1st March (DePreSys) in various years.

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10. On average the skill of DePreSys in predictions of SST slightly exceeds that ofother models in the extratropics (e.g. Figure 5.16) and is comparable to othermodels in the tropics (not shown). This confirms that DePreSys is a state of theart forecasting system on the seasonal time scale and therefore a plausible toolfor the investigation of predictability at longer lead times. Recent tests suggestthat the poor performance of DePreSys in 1979 and (to a lesser extent) 1980(Figure 5.16) could be improved by starting the assimilation integration used toinitialise the hindcasts from an earlier date than January 1979, probably becausethe ocean circulation in the model requires 1-2 years to reach equilibrium withthe analyses of temperature and salinity being assimilated.

11. Skill on the interannual to decadal time scale is most likely to be found byensemble, spatial and temporal averaging of individual model forecasts in orderto remove unpredictable components of variability. Production of a set of 60 fourmember ensemble hindcasts with initialisation dates lagged by one day willprovide a suitable dataset to assess skill on these time scales (see Activities sectionabove). Pending completion of the required model integrations we can obtain apreliminary indication of extended range predictability from the set of 60individual hindcasts already produced, by averaging individual model integrationsinitialised 0,1,2,3,... seasons before the start of the forecast period. Figure 5.16shows predictions of annually and globally averaged near-surface landtemperature produced by averaging sets of six seasonally lagged hindcasts.An encouraging level of skill is apparent for predictions with a lead time of twoyears. Since forecast skill typically decreases with increasing forecast lead time,Figure 5.17 should represent a lower bound on the skill available from ensemblesof hindcasts initialised from consecutive days rather than seasons.

Figure 5.17: A time series of predictions and verifying observations ofglobal and annual average land surface air temperature anomaly for twoyears ahead. Each prediction was obtained by averaging six individualmodel integrations initialised 0,1,2...,5 seasons prior to the start of theforecast period.

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Annex 7: Clouds and radiationAims

1. To improve climate models by evaluating the representation of clouds, watervapour and their radiative effects, in order to identify and prioritise areas forimprovement.

2. To estimate the magnitude of water vapour and, where possible, cloud feedbackson climate change, by identifying and quantifying those feedbacks operating inthe present day climate.

Background

3. The most important feedback mechanisms in the prediction of climate change arethose related to water in its gaseous, liquid or solid phases. The feedbacks due toclouds remain the largest single source of uncertainty in the estimation of theclimate sensitivity to changes in greenhouse gases. This project aims to evaluate andimprove the representation of clouds and water vapour in climate models throughdetailed comparison with earth observations and their variability. It also aims toestimate the magnitude of cloud and water vapour feedbacks by looking at thoseacting in present day climate and by understanding the relevant processes.

Activities

4. Both cloud and water vapour feedback processes are highly dependent on therobust simulation of relative humidity (RH). A strongly positive water vapourfeedback in models arises due to the near-constancy of RH. While moisturechanges near to the surface are well understood, it has yet to be adequatelydemonstrated that decadal changes in upper tropospheric RH in models isrealistic. To explore this issue, we perform explicit simulations of High ResolutionInfrared Sounder (HIRS) satellite water vapour radiances (the methods for whichwere developed and reported on in the last annual report), which are sensitive toupper tropospheric RH, within the Hadley Centre atmosphere-only climate model(version HadAM3). Evaluation of HadAM3 over the 20 year HIRS period isenhanced by accounting for satellite sampling issues and by utilizing additionalsatellite and reanalysis data.

5. Recent work at the Hadley Centre and elsewhere indicates that combiningsatellite data with dynamical information from meteorological reanalyses providesa powerful tool for assessing climate model simulations of clouds and cloudproperties. We have utilised this approach to study clouds and their interannualvariability over the tropical oceans in two versions of the Hadley Centre model,HadAM3 and HadAM4.

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Results

6. As briefly described last year, climatological averages of HadAM3 (e.g. HIRS-12(6.7 micron) water vapour channel) compare well with observations, althoughdifferences relating to circulation errors can be identified. Figure 5.18 showscomparisons of the HIRS observations and additional satellite data of column-integrated water vapour and normalised clear-sky greenhouse effect (the fractionof surface emission that does not escape as clear-sky OLR). This indicates thatHadAM3 can adequately simulate the interannual variability of moisture andclear-sky radiation in response to the prescribed sea surface temperature forcing.An analysis of the spatial signature of the interannual variability of T6.7 in themodel and satellite data shows that the model can also accurately reproduce thespatial characteristics of interannual variation in UTH. The consistent variability ofT6.7, the brightness temperature at 6.7 microns (e.g. in Figure 5.18) suggeststhat the model can accurately simulate decadal fluctuations in upper tropospherehumidity (UTH) providing the apparently robust variability in upper tropospherictemperature is confirmed. Future work is required to further demonstrate therobust nature of the HIRS satellite data however.

7. As can be seen in Figure 5.18, observations/NCEP are shown in black and the rangefrom a 3 member HadAM3 ensemble are shown for standard (dark blue) andmodified (light blue) model diagnostics. The mean monthly climatological valuesare removed and the time-series smoothed using a 5 month moving average.

Figure 5.18: Interannual anomalies over the tropical oceans (30oS-30oN)for (a) surface temperature (K), (b) column water vapour (kg m-2 ), (c)normalized greenhouse trapping (fraction of surface emission that doesnot escape as clear-sky OLR) and (d) HIRS 6.7 _m brightness temperature (K).

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8. Figure 5.19 shows satellite observations of medium thickness high cloud combinedwith sea surface temperature (SST) data and reanalysis fields of mid-troposphericvertical motion to show the distribution of this cloud type in terms of ‘dynamicalregimes’. Also shown are two versions of the atmosphere-only Hadley Centremodel (HadAM3 and HadAM4) forced with the observed SST and sea-icedistributions. It can be seen that the representation of this type of cloud issignificantly improved in the more recent version of the model, HadAM4, comparedto the previous version, HadAM3. This particular improvement is primarily the resultof including a parametrization for anvil cloud associated with deep convection,which is generally associated with warm SSTs and large-scale ascending motion.

Figure 5.19: The distribution of medium thickness high cloud with respect todynamical regimes defined in terms of SST and vertical motion at 500 hPa.Data is for the tropical oceans for the period 1985-1989. Top – ISCCP datacombined with ECMWF reanalyses; Centre – HadAM3; Bottom – HadAM4.High cloud is defined as having cloud top pressure less 440 hPa; mediumthickness cloud is defined as having a visible optical between 3.6 and 23.

9. More detailed analysis of the many different cloud types occurring over the fullrange of dynamical regimes shows how particular model improvements (e.g. theinclusion of a new boundary layer scheme or the increase in vertical resolution)contribute to the generally improved representation of tropical cloud in HadAM4compared to HadAM3. One of the most important perturbations to tropical cloudoccurring on interannual timescales is associated with ENSO events. While therelevance to cloud feedbacks that might occur on longer timescales is not clear,the cloud changes that take place provide an opportunity both to increase our

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understanding of the physical processes operating within the climate system andto improve the representation of these processes in climate models.

10. Figure 5.20 shows the evolution of the anomalies in high, medium thickness cloudamount across the equatorial Pacific for the period 1985-89. The interannual variabilityduring this period is dominated by the El Niño warm event of 1986-1987 and thesubsequent cold La Niña event of 1988. The two models’ contrasting ability to simulatethe observed cloud variations follows directly from the analysis in terms of dynamicalregimes. HadAM3 is unable to generate sufficient amounts of this cloud type over areasof warm SST and strong ascent and consequently fails to represent the cloud variationsassociated with perturbations to the SST and large-scale circulation associated withENSO variability. HadAM4, on the other hand, produces a much more realisticsimulation of the interannual variability compared to the satellite data, consistent withits improved representation of this cloud type deduced from Figure 5.19.

Figure 5.20: The evolution of anomalies in medium thickness high cloudover the equatorial Pacific for the period 1985-89. Top – ISCCP data Centre –HadAM3; Bottom – HadAM4. Values are averaged over 5ºN-5ºS. Theanomalies are calculated by removing the mean annual cycle and thenapplying a 5-month running mean to emphasise the interannual variations.

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11. A more thorough examination of the variability in the two models indicates that thesuccess or failure to represent different cloud types has important consequences:the improved simulation of clouds in HadAM4 leads to an improvement in thesimulation of the top-of-atmosphere radiation budget anomalies and greaterconsistency between the variations in cloud types and those in the radiationbudget.

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Annex 8: The global carbon cycle and ecosystemsAim

1. This annex aims to predict climate change taking into account interactions withland surface, vegetation and the carbon cycle, and to provide general advice onthe carbon cycle and sinks.

Background

2. Our first experiment with the first coupled climate-carbon cycle model (publishedin “Nature” in 2000) showed a strong, positive feedback, which significantlyaccelerated global warming compared with non-interactive carbon cycleexperiments. This was primarily due to the impact of climate change on the soilcarbon storage, but there were also contributions from the ocean carbon cycle,and a marked loss of vegetation in the Amazon basin. This year has focussed onthe mechanisms behind these climate-carbon cycle feedbacks and on theirimplications for CO2 stabilisation.

Results

Amazon dieback

3. Under increased carbon dioxide the Hadley Centre GCMs tend to produce adrying of the Amazon river basin, which leads to forest “dieback” in climate-carbon cycle projections. Such a climatic impact would be catastrophic withinthe real Earth system, so it is vital that we understand and validate the relevantprocesses within the model. During this research year a detailed study of themodelled dieback phenomenon was carried out in collaboration with partners atCEH Wallingford and Reading University. The study concluded that the primarycause was a persistent “El Nino-like” sea-surface temperature pattern whichemerges in the GCM, resulting in reduced rainfall across large parts of Amazonia.Comparison with other GCMs shows that this pattern of change is mostpronounced in the Hadley climate-carbon cycle model, but this model is alsoamongst few GCMs which is able to reproduce observed relationships betweenEl Nino and year-to-year rainfall variations in the current Amazon rainfall.Further work is planned to constrain the projections based on local carbon fluxmeasurements, and on responses of the Amazon forest to past environmentalchange (e.g. ice ages).

Dangerous climate change

4. A number of additional model experiments have been carried out to explore thecritical points in the climate-carbon cycle interaction. These experiments includeones in which the CO2 concentration is stabilised at a given level (e.g. theWRE450, WRE550 scenarios), and one ABW in which additional forcing factorssuch as aerosols and solar variability are included. Figure 5.21 summarises theoutputs of these runs in terms of two key carbon cycle parameters at the year2100, namely the total land carbon and the vegetation carbon stored in SouthAmerica. Amazon forest dieback was found to decrease continuously with the

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CO2 concentration by 2100 (see lower right panel of Figure 5.21), but the totalland carbon appears to peak at a CO2 concentration of 550ppmv, reducing forhigher values (see lower left panel of Figure 5.21). This implies that the landcarbon cycle will provide a brake on CO2 increase and climate change up to thiscritical level, but produce an acceleration of climate change thereafter. The modelclimate-carbon cycle model therefore has a threshold at about 550ppmv.

Figure 5.21: Range of CO2 scenarios explored with the Hadley Centre’sclimate-carbon cycle GCM (top right), and the impact of these scenarioson global land carbon (lower left) and South American vegetation carbon(lower right) , both as a function of the CO2 concentration at 2100.

Implications for CO2 stabilisation

5. The existence of strong carbon cycle feedbacks also has implications for theemissions cuts necessary to stabilise at a given atmospheric CO2 concentration.The GCM stabilisation scenarios shown in Figure 5.22 (WRE450 and WRE550)were used to calibrate a very simple climate-carbon cycle model. Figure 5.22compares results from this simple representation with standard emissionsscenarios for stabilisation. In the absence of climate-carbon feedbacks (blue line)the simple model allows slightly higher emissions (between 2000 and 2300) foreach stabilisation level, than the standard scenario (black line). Once climateeffects on the carbon cycle are included however, the simple model producesdrastic reductions in the allowable emissions for stabilisation (red line). Muchmore rapid reductions in CO2 emissions are therefore required to reach particularstabilisation levels once climate-carbon cycle feedbacks are included.

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Figure 5.22: Impact of climate-carbon cycle feedbacks on the allowableemissions (from 2000 to 2300) for stabilisation at each CO2 concentration.The black line is from the standard “WRE” scenarios, and the red and bluelines are fits to the Hadley GCM with and without climate-carbon cyclefeedbacks.

Sensitivity of ocean carbon uptake to model structure

6. Work continues in collaboration with our partners at SouthamptonOceanography Centre to improve the representation of ocean biologicalprocesses in the Hadley Centre Ocean Carbon Cycle Model (HadOCC). Differentversions of HadOCC including dissolved organic matter (DOM), and distinguishing(silicate-limited) diatoms as a special class of plankton, were compared to modelswhich include minimal biology, or no biology at all. This study concluded that aexplicit representation of the marine ecosystem is required to represent theeffects of climate change on ocean carbon uptake. Further development ofHadOCC is planned to include iron-limitations on the ocean carbon sink.

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Annex 9: Ocean modellingAim

1. To improve the understanding of the role of the oceans in climate and to furtherdevelop the ocean GCM for use in the coupled climate model.

Background

2. The ocean circulation plays a key role in climate by redistributing heat and freshwater around the globe. Further, the rate at which the climate will change inresponse to increasing greenhouse gases depends on the rate of heat uptake bythe oceans, and possible changes in ocean circulation could lead to rapid orirreversible climate changes in future. This annex addresses the needs tounderstand the key ocean processes for climate and to model them accurately.

Activities

3. Work under Annex 9 has focused on evaluation of the ocean component of theHadley Centre climate model against observations, on understanding theimportance of small scale ocean processes not currently resolved in climatemodels, on further understanding of the processes controlling the stability of theAtlantic thermohaline circulation and on providing input to the design of futureocean observing systems for climate.

Results

Role of small scale ocean processes

4. An idealised global warming scenario has been completed using the new coupledmodel HadCEM. HadCEM uses the same atmosphere model as HadCM3 but hasfiner ocean resolution (0.33 degrees in the horizontal and twice the number ofvertical levels). For the first time in a coupled climate model, this allows arepresentation of ocean eddies, as well as improved resolution of boundarycurrents and sill throughflows.

5. As reported last year, the model shows a number of improvements in its simulationof pre-industrial climate. Further analysis has shown the important role played by‘Tropical Instability Waves’ in the transport of heat by the tropical Pacific Ocean(Figure 5.23); this process is poorly resolved at standard resolution. The effect ofthis extra ocean heat transport on the atmosphere is fairly small in HadCEM, butthere is reason to believe that if the atmosphere model resolution were increased aswell there could be a significant impact on the tropical circulation.

6. The global warming scenario shows a slightly faster rate of warming, particularlyaround the North Atlantic, than in a parallel run with standard ocean resolution.This may be a result of the somewhat weaker response of the Atlantic THC (seebelow) in HadCEM, and the reasons behind this are under investigation. TheTropical Instability Waves either side of the equator carry significant heat

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transport in the model, but are not resolved at standard (HadCM3) oceanresolution. The importance of these small scale features for the local meteorologyhas been shown in recent observational studies, while their effect on the generalatmospheric circulation in the tropics requires further investigation using higheratmospheric resolution.

Figure 5.23: Instantaneous sea surface temperature in the tropical Pacific,from the HadCEM eddy-permitting coupled model.

Model evaluation

7. An ongoing focus of ocean model evaluation is on ‘ventilation’ processes,i.e. processes by which heat, salt and chemical tracers which enter the oceanat its surface are transmitted to the ocean interior. Ventilation is important indetermining the rate of ocean heat uptake under global warming, as well as inredistributing important biogeochemical tracers that determine the ocean carboncycle. A study has begun on the use of chemical tracer observations to giveinformation on ventilation. Preliminary results show the promise that real tracerobservations (e.g. of CFCs) can be used to give information on currents andmixing, and this will be pursued in the coming year.

8. There has been ongoing evaluation of prototypes of the ocean component ofthe new Hadley Centre climate model, HadGEM1. A joint analysis has beenperformed of a number of coupled models, including HadCM3 and HadCEM,which share the same atmospheric component. This has provided valuableinformation on the role of ocean model formulation, resolution etc. in coupledmodel errors, and some specific topics are being followed up with a view tofeeding into improved simulations in HadGEM1.

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Stability of the Atlantic Thermohaline Circulation (THC)

9. The THC plays a key role in the climate of Europe and may be vulnerable toinstability, possibly resulting in substantial and rapid climate change in thenorthern hemisphere. Further analysis of a suite of HadCM3 runs has allowed usto develop a robust picture of what processes control the stability of THC in themodel. Unfortunately not all these processes can be tested against observationsat present.

10. Strong links have been developed with a number of UK and internationalprogrammes in this field, with both observational and modelling interests, andfurther work has been done on using simulated observations to judge thebenefits of a potential long term observing system for the THC. The focus ofwork in this area over the next few years will be on developing the first semi-objective assessment of the likelihood of rapid THC changes under given climateforcing scenarios.

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Annex 10a: Aerosols and their effectsAim

1. Development of the capability to simulate aerosols in a fully-interactive mannerwithin the climate model so that climate predictions can take account of theireffects. Assessment of aerosol radiative forcings and improved understanding ofthe processes and factors influencing them.

Background

2. There are a variety of different kinds of aerosol particle, of which several arebelieved to exert significant radiative forcing, either directly (by scattering andabsorbing radiation) or indirectly (by influencing the albedo and lifetime ofclouds). As discussed in the IPCC 3rd Assessment Report, the magnitude, spatialdistribution, and the past and future evolution of these aerosol radiative forcingsare very uncertain.

Activities

3. i Considerable code development was undertaken to introduce fossil fuelblack carbon aerosol, mineral dust, and biomass smoke as independentoptions in HadGEM1. These are in addition to the sulphur cycle scheme andsea-salt aerosol parameterization installed last year, so users will in future beable to choose any combination of 5 different aerosol types;

ii. Experiments to investigate the climate sensitivity to fossil fuel black carbonaerosol were performed, using a “slab” model version of the HadAM4configuration. This was in response to a publications that highlighted theimpact of black carbon emissions and proposed that there is greater climatesensitivity to black carbon than to carbon dioxide. Experiments on theradiative forcing due to pollution of continental snow cover by black carbonwere also carried out;

iii. Work on indirect aerosol effects focused on comparing several alternativeparameterizations of the “autoconversion” process that initiates drizzle, andplays a key role in the cloud lifetime effect. The difficulty of modelling thisprocess introduces a large uncertainty factor in estimates of indirect forcing;and

iv. Advice and assistance were provided to various Hadley Centre scientistsneeding aerosol effects in their studies (using HadCM3 and similar versionsof the model), for example the predictions using global and regional modelsand the Probability Predictions project (Annex 14).

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Results

4. i The three new aerosol schemes have been installed in the Unified Model;testing continues;

ii. The results of our experiments suggest that the climate sensitivity to blackcarbon forcing is actually somewhat weaker than the sensitivity to CO2forcing, in contrast with the publication showing that sensitivity to blackcarbon forcing is much stronger. Analysis of the relevant mechanismscontinues; and

iii. Applying recent theoretical advances, and comparing model output withobservations from the ACE-2 field campaign, we have established which ofthe autoconversion schemes in the current literature performs best. Howeverit has to be said that even the “best” scheme is far from perfect.

Figure 5.24: The diagram shows the simulated annual mean surfacetemperature change, in degrees Celsius, due to 4 times the fossil fuelblack carbon emissions for 1985.

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Annex 10b: Atmospheric chemistryAim

1. To include the influence of atmospheric chemistry in predictions of climatechange and simulations of recent climate.

Background

2. The purpose of this research is to provide models and simulations of atmospherictrace gases which are important to climate change. These include greenhousegases such as methane and ozone as well as oxidants such as the hydroxyl radicalwhich are responsible for the atmospheric production of sulphate aerosol. It isclear that the oxidation of organic compounds such as terpenes also adds to theglobal aerosol burden and there is a need to model these compounds. As theinteractions between climate change, ecosystems, and atmospheric chemistry aremodelled with a global environment model, there is the opportunity to representprocesses such as natural emissions as an interactive quantity where emissions arepredicted from the ecosystem type and the climate. Recent effort has beendirected towards assembling a model capable of fulfilling an interactive role inthe HadGEM model.

Activities

3. i. The development and testing of the HadGEM/STOCHEM model wascompleted;

ii. The tropospheric chemistry model (STOCHEM) was coupled to the landcarbon cycle scheme with predictions of natural methane emissions fromwetlands and isoprene emissions from vegetation being used to driveSTOCHEM;

iii. A paper on the production of aerosol from sulphates, terpenes, and nitrateswas published;

iv. Earlier results from long-running simulations of coupled troposphericchemistry and climate models have been analysed to further ourunderstanding of the role of climate change on methane and ozone budgetsin the troposphere; and

v. We have initialised a collaborative research programme with NERC todevelop a new atmospheric chemistry model using the semi-Lagrangiantracer transport model.

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Results

HadGEM/STOCHEM model

4. The version of STOCHEM intended for use with the HadGEM1 model has beenextensively updated and tested. This model is coupled on a timestep basis with theatmosphere model and has a better horizontal and vertical resolution thanHadCM3/STOCHEM creating a model with around six times the number of gridpoints. Tests of this model have included tracer transport studies using short-livedtracers where STOCHEM was compared directly with the semi-Lagrangian scheme inthe atmosphere model. Validation against observations was also carried out, notablyagainst the ozonesonde network observations and assembled aircraft data. Thesestudies have resulted in upgrades to the model performance and we now haveconfidence that the model is performing well. Figure 5.25 shows a comparisonbetween model results and ozonesonde profiles for January at selected stations.

Fig.5.25: Ozone profiles from the HadGEM1/STOCHEM model comparedto ozonesonde observations for January.

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Tropospheric chemistry and climate change

5. The experiments made with the HadCM3/STOCHEM model are the longestcontinuous runs made with any coupled chemical transport model. Effort hasfocused on both the role of climatic variability on tropospheric oxidants, and theeffect of climatic changes on greenhouse gases. Figure 5.26 shows the changesto ozone decadal-mean concentration profiles between 2005 and 2095 analysedover sea and land portions of the atmosphere. Ozone concentrations in thecontrol model have risen dramatically over the land areas because the majorincreases to NOx concentrations occur, principally in the northern hemisphere.Comparison with the climate change model results show that reductions due toclimate change are similar over oceans and land areas.

Figure 5.26: Changes to ozone profiles between the 2000-2009 decadeand the 2090-2099 decade over land and ocean areas. Both control (CON)and climate change (CC) scenarios are shown.

Co-operation with NERC and model development

6. Planning of the development of a new atmospheric chemistry model based onthe semi-Lagrangian tracer transport scheme in the atmosphere model hasresulted in the definition of a joint NERC Centres for Atmospheric Sciences(NCAS) and Met Office project. Work will start soon on this model which will bedeveloped as a combined stratosphere and troposphere model.

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Annex 13: Physical, chemical, biological effects of climatechangeAim

1. To make predictions of specific physical, chemical and biological effects of climatechange as input to impacts studies.

Background

2. Simulations of the effects of climate change for impacts studies have generallybeen performed with models separate from the climate model. Such simulationshave therefore neglected feedbacks from these effects on each other and back tothe climate system. Furthermore, limitations on resolution and data transfer haveoften led effects simulations to neglect sub-gridscale land surface variations andshort-timescale climate variability. Such effects would be more appropriatelysimulated within the climate model itself, with the final responses then beingsupplied to impacts models. The core objective of this research is to incorporatemodels of these effects within the climate model, to provide better input toimpacts studies.

Modelling river flow

3. The proper representation of river flows in GCMs is important for a number ofreasons. Changes in river flow may be a major effect of climate change onsociety. The flow of freshwater from the land to the oceans exerts a significantinfluence on the thermohaline circulation, so a good representation of river flowis important for a realistic reproduction of the thermohaline circulation in acoupled atmosphere-ocean GCM. River flow is also a potentially useful quantityfor validating hydrological aspects of large-scale models, as rivers can indicate thestate of the surface water budget across very wide areas. To address these issues,the “TRIP” river-routing scheme has been implemented in HadCM3 andHadGEM. In HadCM3, TRIP produces improved agreement in river flowseasonality with observations for most major rivers.

Climate change in urban areas

4. Urbanisation can significantly modify the physical properties of the landscape,and this is known to exert important influences on local meteorology. However,the potential interactions between urban meteorology and greenhousegas-induced climate change have so far received little attention. Urban andnon-urban areas are likely to exhibit different sensitivities to greenhouse forcing,but this is generally not accounted for in climate change impacts studies.Increased urbanisation may itself provide an additional climate forcing.

5. A new parametrisation of urban areas has been implemented in the HadleyCentre General Circulation Model (GCM), to allow investigation of urban landsurface processes in simulations of climate change and its impacts. The scheme isembedded within the MOSES2 land surface scheme (Essery et. al. 2001), which

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calculates separate energy balances for individual land surface types within eachGCM gridsquare. It is therefore possible to diagnose the temperatures of urbanand non-urban land separately. As an initial sensitivity study, climate simulationswere performed with (i) current urban areas and (ii) with all urban areas replacedby non-urban land. In both present-day and doubled-CO2 climate simulations,the temperatures over an urban land surface are generally warmer than those innon-urban areas (Figures 5.27 and 5.28). The changes in the urban heat islandunder doubling CO2 varied in sign with location and with the backgroundmeteorology at the time. In some cases the CO2-induced warming was greaterover urban land than non-urban land, in other cases the urban land warmed less.It was concluded that the interactions between urban heat islands andradiatively-forced climate change are complex and must be represented with aparametrization within the GCM rather than a simple adjustment to resultssimulated for non-urban areas.

Figure 5.27: Daily minimum temperature frequency for urban and non-urban (grass) areas simulated for the London area.

Figure 5.28: Daily maximum temperature frequency for urban and non-urban (grass) areas simulated for the London area.

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Wetlands and methane emissions

6. The representation of sub-gridscale heterogeneity in water table depth andsurface saturation is important for the simulation of wetlands. A paper on thenew large-scale hydrology model (“LSH”), which represents wetlands, has beensubmitted and is currently under review. LSH has also been implemented inHadGEM, and in the GCM-Analogue model “IMOGEN”.

7. LSH also includes a model of methane emissions, which depend on temperatureand wetland area. In a simulation with IMOGEN and LSH, climate change ispredicted to increase natural methane emissions by a quantity similar to theanticipated increase in anthropogenic methane emissions, which contributesapproximately 6% of the total anthropogenic climate change by 2100 underthe IS92a scenario.

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Annex 14: Probability, uncertainty and riskAim

1. To quantify the uncertainty in climate change predictions, and the risk ofoccurrence of different outcomes, by estimating the probability distributionof future climate changes using large ensembles of model simulations.

Background

2. Predictions of climate change are made using climate models, mathematicalrepresentations of physical processes in the climate system. We have anincomplete understanding of many processes, and may be ignorant of others.Even processes we do understand can only ever be represented approximately,due to the finite resolution of the models. These limitations render the modelimperfect, and predictions from it uncertain. Further sources of uncertainty arisefrom the effects of natural variability and imperfect knowledge of futureanthropogenic emissions. There is a clear requirement from stakeholders forpredictions in a probabilistic form which account for uncertainty and cantherefore be used in risk analysis. This work aims to address this need.

Activities and future plans

3. The aim of the Probability Predictions project is to produce probabilisticpredictions of 21st century climate change for a range of climate variables forany region of the world. This requires large ensembles of GCM simulationsaccounting for uncertainties in emissions, natural variability and modelling ofclimate processes. The first stage of this project has been to simulate theequilibrium response to doubled CO2 using a large ensemble of 53 versions ofHadSM3, a computationally efficient climate model consisting of the atmosphericGCM HadAM3 coupled to a simple mixed layer ocean with prescribed heattransports. Each version differs from the standard version of the model througha perturbation to one of its physical parameters controlling a key atmosphericprocess. The availability of a large ensemble, the first of its kind in the world,allows the robustness of the climate response to be quantified in a much morerigorous manner than previously.

4. The next stage of the project will be to produce a second perturbed physicsensemble which can be used to provide plausible probabilistic predictions of theresponse to doubled CO2. This requires an objective “Climate Prediction Index”(CPI) of model reliability in order to weight the contributions of differentensemble members. It also requires improved sampling of modelling uncertaintiesby allowing multiple perturbations to GCM parameters. Such an ensemble hasnow been designed, using the results of the first ensemble and an early versionof the CPI to identify an ensemble of model versions which are (a) likely to givea plausible simulation of climate change (in order to avoid wasting computer timerunning unrealistic models), and (b) achieve the maximum coverage of modelparameter space subject to (a). The procedure used to design this ensemble,and results from it, will be described in future reports.

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5. Ultimately planners require probabilistic predictions of 21st century climate changeunder specified (e.g. SRES) forcing scenarios. Ideally these would be generated byrunning a large ensemble of versions of a full coupled ocean-atmosphere model(e.g. HadCM3L) from pre-industrial conditions to 2100 in order to account foroceanic thermal inertia and changes in ocean circulation. This is computationallyunfeasible at present, however we plan to estimate the results of such anensemble from the second HadSM3 perturbed physics ensemble. This will involverunning additional simulations for a small subset of HadSM3 ensemble membersin order to establish scaling factors required to infer time dependent 21st centurychanges from the HadSM3 2xCO2 equilibrium response. For each member of thissubset the required additional experiments will consist of: (a) simulations of theequilibrium response to anthropogenic changes in sulphate aerosol (and possiblytropospheric ozone); (b) simulations of pre-industrial to 2100 climate usingHadCM3L driven by observed forcing up to 1990 and SRES scenario forcing from1990-2100. Experiments (a) and (b) and the original HadSM3 equilibrium 2xCO2experiments will be used to calibrate scaling factors which will then be applied tothe remainder of the HadSM3 2xCO2 ensemble to generate the requiredprobability distributions of 21st century change.

6. During 2004/2005 this approach will deliver, for selected emissions scenarios,probabilistic predictions of 21st century climate accounting for uncertainties innatural variability and model parameters influencing physical atmosphericprocesses. In the long term it will be necessary to generalise our methodology toaccount for a wider range of modelling uncertainties. For example uncertaintiesin the parameterisation of sub-grid scale physical processes include stochastic andstructural aspects (currently unaccounted for) as well as uncertainties in thevalues of parameters.

7. The stochastic aspect arises from the fact that a given set of values of basic gridbox model variables input into the parameterisation schemes (e.g. temperature,moisture, surface pressure and winds) should imply some distribution of valuesfor the output variables (e.g. cloud cover, precipitation, turbulent eddytransports), since the latter depend on unresolved small scale structure inside themodel grid box. Currently the parameterisation schemes in HadAM3 aredeterministic, i.e. they always produce the same outputs for a given set of inputsand do not account for the stochastic element of the parameterisation problem.

8. Structural uncertainties arise from fundamental differences in the nature of theparameterisation equations between different GCMs, arising from differentinterpretations of the underlying physics. Furthermore uncertainties in futureclimate change are influenced by modelling uncertainties in Earth Systemmodules such as ocean physics, carbon cycle and atmospheric chemistry,whereas we currently account only for uncertainties in modelling of thephysical atmosphere. From 2005/2006 and beyond we will develop a“second generation” ensemble climate prediction methodology based onthe new Earth System model HadGEM, for which the widest possible rangeof uncertainties will be accounted for.

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Results 2001–2002

9. Here we present results from the first perturbed physics ensemble, in which weinvestigate uncertainties in the equilibrium response to a doubling of CO2 arisingfrom the modelling of atmospheric physical processes and natural variability. Processuncertainties were sampled by defining an ensemble of 53 versions of HadSM3.Each ensemble member differs from the others in the value of one of 28parameters (a coefficient, threshold or logical switch) controlling some aspect ofthe representation of sub-grid scale physical processes in terms of grid box modelvariables. Parameters were chosen from each major class of physical processesrepresented in the model (cloud, convection, radiation, boundary layer, landsurface, sea ice and dynamics), allowing us to sample a wide range of uncertainties.

10. Those parameters consisting of a coefficient or threshold were perturbed to themaximum and minimum of their plausible ranges according to advice receivedfrom experts. Each perturbed physics ensemble member consisted of one control(present-day) simulation and one with doubled CO2. Both were run toequilibrium, such that the global mean temperature showed a 20-year trendwhich was no greater than some pre-defined threshold. The climate responsewas estimated as the difference between these 2xCO2 and control equilibrium20 year periods.

Figure 5.29: Equilibrium response to a doubling of CO2 of 20 year meanJune to August surface air temperature simulated by 53 versions ofHadSM3 consisting of the standard version plus 52 versions containinga perturbation to one of 28 atmospheric physics parameters.

11. Figure 5.29 above shows the distribution of the surface air temperature responsesimulated by each ensemble member. Basic features of the patterns, such asenhanced warming over the continents and at high latitudes in the winterhemisphere, are common to each member of the ensemble. Significant regionalvariations between the individual simulations are also apparent however,indicating significant uncertainty in the warming.

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12. The use of a large number of model versions allows a statistically reliable estimateof ensemble spread to be calculated. This allows the robustness of the simulatedresponse to be quantified: For example Figure 5.30 (bottom panel) shows thatthe magnitude of the ensemble-mean change in December-February mean sealevel pressure exceeds twice the ensemble standard deviation over much of thetropical Pacific and Atlantic Ocean, and at high latitudes in both hemispheres,indicative of a change in circulation significant at the ~5% level or better. Inother regions the changes are less significant.

Figure 5.30: Statistics of the December to February 20 year mean responseof mean sea level pressure (MSLP) to doubled CO2. Bottom panel showsthe perturbed physics ensemble-mean response divided by the ensemblestandard deviation. Top panel shows the variance of the responses in a 30member ensemble of the standard version of HadSM3 distinguished bydifferent initial conditions divided by the variance of the responses in the53 member perturbed physics ensemble.

13. The spread in the perturbed physics ensemble contains components from bothparameter changes and from natural variability. In order to estimate the relativecontributions of each source of uncertainty we also produced a pair of 600 yearsimulations of control and 2xCO2 climate using the standard version of the model.This experiment was divided into thirty 20-year sections in order to define anensemble in which the 30 members differ only in their initial conditions and hencethe ensemble spread arises purely from the effects of natural variability. The toppanel in Figure 5.30 shows that the variance in the response of the December-February circulation is driven mainly by parameter uncertainties in some parts ofthe tropics, whereas natural variability is the dominant source of variance in manymid- and high-latitude regions. For surface temperature (not shown), parameteruncertainty is the dominant source of variance at almost all locations.

14. In order to provide credible estimates of uncertainty we need an objectivemeasure of the fitness of models to simulate climate change which can be usedto weight the predictions of ensemble members according to reliability. For thispurpose we are developing a “Climate Prediction Index (CPI)” which measuresthe ability of models to simulate a range of relevant aspects of present dayclimate. It is obtained from root mean square (r.m.s.) differences between spatialpatterns of simulated and observed long term averages normalised by thestandard deviation of simulated interannual variations. For each of 32 surface and

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atmospheric climate variables (Figure 5.31) this non-dimensional r.m.s. differenceis calculated for each season, giving 128 numbers which are averaged to providethe CPI for a given version of the model.

Figure 5.31: Field variables used in the first version of the ClimatePrediction Index and values of its components for December to February,consisting of (-1 times) the root mean square difference between longterm means of the simulated and observed fields normalised by thestandard deviation of simulated interannual variations, for two of the53 members of the perturbed physics ensemble.

15. Use of the CPI to weight ensemble members requires the assumption that areliable simulation of present climate implies a reliable simulation of futureclimate change. This depends on the extent to which feedbacks determining themagnitude of climate change are constrained by the observational criteriaemployed. Since the CPI is based solely on climatological mean patterns it is likelyto represent a necessary but not sufficient condition in this context. It is anecessary condition because, for example, GCMs containing regional biases arelikely to simulate feedbacks in the wrong place, or of the wrong strength. Thereliability of simulated feedbacks on the other hand could be quantified moreprecisely by accounting for inter-variable relationships implied by the nature ofthe driving physical processes but not yet represented in the CPI. The CPI will beexpanded in future to include such relationships.

16. Figure 5.32 shows the impact of weighting predictions of the perturbed physicsensemble members according to the CPI, using the response of June to Augustprecipitation as an example. We use exp (-CPI2) to weight the ensemblemembers, this representing the likelihood that the observed data belongs to theprobability distribution of model values, averaged over all components of the CPIand all field elements of each component.

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Figure 5.32: Frequency distributions of the 20 year mean response of Juneto August precipitation to doubled CO2 in the perturbed physics ensemblewhen all ensemble members are given equal weight (blue), or weightedaccording to exp(-CPI2) (red).

17. The results indicate an impact of the CPI weighting, which varies with region.In many regions (e.g. Amazonia) the weighting effectively removes one or moreoutlier ensemble members whose simulations of present day climate are poor.Although the red (i.e. CPI weighted) curves of Figure 5.32 may be interpretedas probability distributions of the response, these distributions are likely to beunrealistically narrow because the ensemble members only sample a limitedsubset of the parameter space of the model, each member differing from thestandard model version in only one parameter. We have therefore developed amethod of using the CPI to infer an optimal ensemble of combinations of valuesfor model parameters, thus allowing us to design a second perturbed physicsensemble which will provide unbiased probabilistic estimates of the response todoubled CO2 (see “Activities and Future Plans” section above).

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Contract No: EPG 1/1/126Title: UK Argo ProjectContractor: Met Office PI: Jon Turton

Aims and objectives

1. Argo will be a global array of 3,000 free-drifting profiling floats that will measurethe temperature and salinity of the upper 2,000 m of the ocean and provideinformation on deep ocean currents. Argo will be a key component of the GOOS(the Global Ocean Observing System) and the ocean domain of the GCOS (GlobalClimate Observing System) to which UK has central commitments.

Background

2. The UK contribution to Argo was initiated by OST in 1999 and is jointly fundedby Defra, MoD and NERC; UK Argo is being implemented by the Met Office withsupport from SOC, BODC and UKHO. Since its inception in early 1999 13 othernations (Australia, Canada, China, Denmark, France, Germany, India, Japan, NewZealand, Republic of Korea, Russia, Spain and USA), along with the EuropeanCommission, have also committed support for Argo.

Activities

3. As at early June 2003 there are over 800 operating Argo floats (see Figure 5.33 below)with coverage starting to build in the Indian and Southern Oceans. Expectations arethat the 1,000 float milestone will be passed in 2003 and that a full 3,000 float arraywill be in place by end 2005. Operating UK floats are shown in red and have beendeployed in a number of regions around the globe. Climate simulations made by theHadley Centre (Banks and Wood, 2002) suggest freshening in southern Indian Oceanand Arabian Sea intermediate waters is a signal of anthropogenic climate change.Guided by these results, UK Argo floats have been deployed in these regions tomonitor salinity. A priority for Argo over the next few years will be to deploy morefloats in the Southern Hemisphere (where 2,000 of the 3,000 floats will be required).

Figure 5.33: Showing the locations of operating Argo floats in June 2003.UK floats are shown in red, all others in blue.

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Results

4. An assessment by SOC of the salinity data from our floats in the South IndianOcean indicates that 21 out of 23 floats were accurate to better than 0.01 usingonly the factory calibration. These floats were deployed from a research vessel,and high-quality CTD data (with accuracy of order 0.002) were available toprovide a reference at each deployment location. The CTD data showed that thewater properties between about 10 and 14°C (the ‘upper thermocline’ water)were uniform over large spatial scales (many hundreds of kilometres). The resultssuggest that any sensor drift over 10 profiles (3 months) for the 2002 floats andup to 30 profiles for the 2001 floats is of the same order of magnitude as theocean variability, and so cannot be distinguished from it. Delayed mode post-processing may enable further improvements in salinity calibration to be made.

5. Figure 5.34 (on the left) shows the observed freshening at 30° S in the IndianOcean between 1987 and 1962 (from Bindoff and McDougall, 2000). The resultsfrom the Indian Ocean 30° S section, and floats deployed along this section, in2002 (right hand figure – note the vertical scales are different) suggest that watermass changes may have reversed direction between 1987 and 2002 to thatobserved between the early 1960’s and 1987. The floats deployed along thissection (and other floats deployed subsequently) will provide continuousinformation which will help to quantify the spatial and temporal variability whichis needed to interpret the section data (1962, 1987 and 2002) and climate modelresults. Detailed analysis of these data, by the Met Office and SOC, is underway.

Figure 5.34: (Left) showing the change (freshening) in salinity in theintermediate waters of the South Indian Ocean as derived fromhydrographic sections in 1987 and 1962. (Right) salinity change, since1987, based on float data in 2002.

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Chapter 6

Climate change – earthobservations

Contract No: EPG 1/1/94 Title: AATSR: Prime industrial and management information system contractContractors: EADS Astrium Ltd., Vega plc PI: M Buckley

Introduction1. This report provides a summary of the status of the AATSR Prime Contract and

the AATSR Management Information System Contractor (MISC). It presents anoverview of the aims and objectives of the contracts and summarises the principalactivities carried out and results over the reporting period.

Background2. The Advanced Along Track Scanning Radiometer (AATSR) is a remote sensing

instrument capable of making highly accurate measurements of Sea SurfaceTemperature (SST). It flies on the European Space Agency’s (ESA) ENVISAT-1 satellite,launched in March 2002. AATSR is the third in a series of similar instruments, whichstarted with ATSR-1 (funded by SERC) on the ERS-1 satellite launched in July 1991,and continued with ATSR-2 (funded by NERC) on ERS-2, launched in April 1995.

3. AATSR was developed as part of a collaborative programme between the UKDepartment for Environment, Food and Rural Affairs (Defra), NERC and the AustralianDepartment of Industry, Tourism and Resources (DITR), with Defra as Lead Agency.

4. Defra’s primary objectives for the AATSR programme are to continue theconsistent, long-term set of global SST measurements started by ATSR-1 andATSR-2 and to use this data set in research into climate change.

5. AATSR was assumed to be an operational instrument (since the first was flyingsuccessfully and the second was nearing completion), when responsibility wastransferred to Defra in 1993. As such, it represented the first attempt withinEurope to reduce the cost of space hardware by transferring the cost ofprocurement from the R&D sector to a user funding agency. The UK fundedapproximately 70% of the AATSR instrument through the AATSR Prime Contractand Australia has funded approximately 30% of the instrument through fiveseparate contracts with Australian industry. Defra have also placed additionalcontracts to provide technical and scientific support to the AATSR programme,in the form of the MISC and the AATSR Principal Investigator (PI).

6. AATSR data are being processed, archived and disseminated via the ENVISATground segment developed by ESA. Defra also funds data validation activitiesand limited AATSR-specific ground segment facilities to support the AATSRprogramme and in-orbit instrument operations.

AATSR prime contractAims and objectives

7. The objective of the AATSR Prime Contract has been to manufacture, assemble,integrate, test and deliver an operational AATSR instrument and to providePost-Delivery Support. The Prime Contractor was responsible for providing an

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Chapter 6 Climate change – earth observations

instrument that is compliant with the Instrument Performance Requirements andwhich therefore meets the scientific objectives of the mission. The Prime Contractwas placed with British Aerospace Space Systems Limited, now Astrium Limited,in December 1993 after a competitive tender process.

Activities and results

8. Astrium supported the commissioning of AATSR, which was successfullycompleted in September 2002, and since then have continued to provide expertinstrument support during routine AATSR operations.

AATSR management information system contract

Aims and objectives

9. The objective of the MISC is to provide technical and programmatic support to Defraduring procurement of the AATSR instrument and the development of the associatedground segment. Following a competitive tender, the MISC was placed with VEGAGroup PLC in April 1993. Since then the contract has been extended several times.The current contract covers AATSR activities up to the end of September 2003.

10. The work undertaken by the MISC can be summarised as follows:

i. Programme administration - including technical and programmatic co-ordination,contract monitoring and reporting activities, and the maintenance of the AATSRManagement Information System Database (MISD); and

ii. Programme development and implementation – providing support to Defra inintegrating the engineering and flight operations side of the programme withthe scientific research and data applications.

Activities and results

11. The MISC continued to monitor the progress of the Space Segment PrimeContract. This has included reviewing progress with Astrium, liaison with partnerorganisations and the evaluation of technical issues of importance arising duringAATSR commissioning and routine operations.

12. The MISC assisted Defra in monitoring the AATSR Post-Launch Flight OperationsSupport contract placed by Defra with the Rutherford Appleton Laboratory (RAL).The activities and results of this contract are described elsewhere in this report.

Conclusion

13. The key event of this reporting period has been the successful completion ofAATSR’s commissioning in September 2002. AATSR is now routinely producinghigh quality science data.

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Climate change – earth observations

Contract No: EPG 1/1/121Title: AATSR post launch flight operations supportContractor: Rutherford Appleton Laboratory PI: B Maddison

Introduction

1. The Envisat satellite has an ambitious and innovative payload that will ensure thecontinuity of the data measurements from previous satellite missions. The Envisatdata will support Earth science research and allow monitoring of the evolution ofenvironmental and climatic changes. The Advanced Along Track ScanningRadiometer (AATSR) instrument will provide continuity of stable well calibratedSea Surface Temperature data for use in a wide range of Earth Observationstudies and in particular supply the long term observations of Sea SurfaceTemperature needed urgently for the debate on climate change.

2. Defra’s AATSR Post Launch Support Activities: fund the activation of the flightsegment, verification of the instrument performance, and optimisation of theAATSR system will ensure that the scientific products are of the highest quality.This is essential for the continuation of the unique >10 year near-continuous SeaSurface Temperature data set at the levels of accuracy required (0.3 K or better)for climate research and for the community of operational as well as scientificusers who will have been developed through the ERS-1 and ERS-2 missions.

Aims and objectives

3. The AATSR instrument was launched on the European Space Agency’s ENVISATsatellite in March 2002, and will monitor sea surface temperatures (SSTs), whichcan be used to provide information about climate. Defra is responsible to ESA forthe provision of Flight Operations Support to the AATSR instrument as well asproviding continued support to the AATSR Instrument Processor by the provisionof Test Data Sets against which it will be validated. Defra are therefore required todevelop and maintain an AATSR Reference Processor to be used in the continueddevelopment and verification of the AATSR algorithms, and to generate the TestData Sets for verification of the operational software within the PDS.

4. There are two phases to this contract (AATSR Post Launch Operations Support)a commissioning phase and an operations phase. The main objectives of thecommissioning phase of the contract are activation of the flight segment,verification of the instrument performance and optimisation of the system toensure that the scientific products are of the highest quality. Then, following onfrom a successful commissioning phase, the main objectives in the AATSR PostLaunch Operations Support Contract are to assess the AATSR instrumentperformance using instrument housekeeping and science data; use the daily andlong-term trends to make predictions about the likely future performance of theinstrument and identify and report of any instrument anomalies.

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Activities/methodology

5. The main activities of this contract are:

i. Characterisation (calibration where appropriate ) of the instrument’s in-orbitperformance;

ii. Validation of Ground Segment procedures and engineering monitoring tools;

iii. Optimisation of the instrument settings to ensure the best quality data arecollected;

iv. In-orbit verification of the AATSR instrument’s capabilities to demonstrateAATSR is meeting its formal instrument and scientific performancespecifications;

v. Provision of information for the operation of the instrument in the long-termwith due regard to mechanism lifetimes and the long- and short-termscience requirements for the mission;

vi. Provision of daily visible calibration files; and

vii. Provision of Test Data Sets to support testing of the ESA OperationalProcessor.

Results

6. These are as follows:

i. Ground segment procedures and the engineering tools have been validated;

ii. The AATSR Instrument has been successfully commissioned and optimizedfor “best performance”;

iii. The AATSR Engineering data system web site is providing AATSR instrumentand calibration engineers and scientists with instrument performance/calibration data and instrument trends data;

iv. Daily visible calibration files are being provided to the ESA Operation Processor;and

v. The Reference Processor has provided Test Data Sets to support the testingof the ESA Operational Processor.

Conclusions

7. The AATSR instrument has been successfully commissioned and, in all cases, iseither meeting or exceeding all its performance requirements and is producinggood quality science data with a radiometric performance comparable to that ofATSR-2 instrument. Based on current performance AATSR should meet its lifetimeperformance requirements.

For further information visit internet addresses:www.atsr.rl.ac.uk/ and www.atsrus.ag.rl.ac.uk/atsr/

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Contract No: EPG 1/1/157 and EPG 1/1/131Title: AATSR principal investigator and validation activitiesContractor: The University of Leicester PI: Professor David T Llewellyn-Jones

Aims and objectives

1. The AATSR PI/validation contract provides support to the Principal investigator (PI)and the Validation Scientist (VS), based at the University of Leicester, for theDefra-funded Advanced Along-Track Scanning Radiometer (AATSR). The AATSR isa space sensor that was successfully launched by the European Space Agency(ESA) on-board the ENVISAT satellite, in March 2002. Its main objective is toprovide accurate measurements of global sea-surface temperature, to be used bythe Hadley Centre in their Defra-funded programme of climate prediction andresearch. Other important aspects include the measurement of land surfacetemperature, clouds, aerosol and vegetation.

2. The PI and validation programme at Leicester is augmented within the contractby the work of the AATSR Project Scientist at the Rutherford Appleton Laboratory(RAL) and by key validation data-collection activities, supported by Sub-contractsat RAL and the Southampton Oceanography Centre (SOC).

3. The role of the PI is to ensure that the AATSR sensor meets its scientificperformance requirements and that the data exploitation programme iseffectively carried out. The VS is responsible for ensuring that AATSR’sgeophysical data products are correctly validated. In order to validate thegeophysical products, the VS must devise, coordinate and manage acomprehensive validation programme involving many collaborating institutes.Scientifically, the objectives of the validation programme are to determine theoverall accuracy of the AATSR data-products, to perform global inter-comparisonsof AATSR data with other sensors, and to improve our understanding of thedetermination of land surface temperature. Most importantly, the VS mustensure, in the case of anomalies or sub-standard data-products, that appropriateremedial action is taken in a timely manner.

Progress over the reporting period

4. This reporting period covers the first full year of operation of the AATSR and hastherefore been a crucial one for this project. The main activities carried out overthe last year have been the commissioning and validation of the AATSR sensor.Commissioning of the AATSR instrument was successfully carried out by teams atRAL and EADS Astrium Ltd (UK) under separate contracts from Defra and the PIteam carried out a review of these commissioning results, which were reported toESA at the ENVISAT Commissioning Phase Review held at ESTEC in September2002. At this review it was clear that AATSR is meeting its technical performancerequirements, including radiometric performance, scan mirror running and thatthe instrument is extremely stable. Figure 6.1 shows an example of one month’sglobal SST data from AATSR. The temperatures recorded are close to theiranticipated values and the coverage is excellent despite a few inevitable datagaps, mainly due to persistent cloud-cover.

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Figure 6.1: One month of global Sea-Surface Temperature data fromAATSR is shown for October, 2002. The temperature values are indicatedon the colour scale to the right of the plot. Black areas in the oceans aredue either to persistent clouds or to missing data.

5. Following the prompt and successful commissioning of the AATSR, a programmeof data-collection for validation started in May 2002, with participation fromcollaborating scientists in Australia, the USA, France, Spain and others including,of course, the UK. This process, coordinated by the VS, will continue, withvarying priorities, throughout the mission. Analysis of the collected data and theircomparison with AATSR measurements, is now well underway.

6. So far, highlights of the validation programme include:

i. The systematic comparison of global SST fields, such as that presented inFigure 4.1, with data from in situ buoys. This work, performed by the UK MetOffice and Hadley Centre, clearly indicates that the AATSR SST values arewithin specification;

ii. The comparison of AATSR global SST fields with those obtained from othersatellite systems. This work, carried out at the University of Leicester, isparticularly revealing because it shows the power of along-track scanning (theunique feature of AATSR’s viewing geometry) in making accurate surfacetemperature measurements in the presence of atmospheric aerosol. Oneexample is presented in Figure 4.2, which shows the difference between SSTsmeasured by AATSR and the NASA-developed MODIS sensor in the Easterntropical Atlantic. The difference between the measurements corresponds to thepresence of Saharan dust outbreaks, which are known to occur at regularintervals and are of significant climatic interest and importance, but difficult tomonitor effectively;

iii. Quantitative comparisons have been carried out by RAL of the AATSR visibleand near infrared reflectance channels with data from the ESA sensor, MERIS,also on the ENVISAT satellite. These have shown excellent agreement, whichwill give high confidence in the quality of AATSR data over land; and

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iv. An autonomous radiometer system, developed by the SouthamptonOceanography Centre, has been successfully deployed on a ferry making dailytrips between the UK and Spain, therefore enabling it to collect data fromevery cloud-free overpass. Data from this system have the potential to providehighly accurate SST validation points on a regular basis. This is an importantcomplement to the global analyses carried out by the UK Met Office, which donot have the benefit of the accuracy offered by radiometric correlative data.

Figure 6.2: The difference between SST values obtained from AATSR andfrom MODIS over the Eastern Tropical Atlantic.

7. In Figure 6.2 above, the pale blue coloured pixels indicate low differences andyellow-orange coloured pixels represent higher discrepancies. The differencereveals the presence of an outbreak of Saharan Dust, which has differing effectson the SST values retrieved from the two sensors. The along-track scanningmethod of AATSR uniquely allows it to correct for the presence of atmosphericaerosol.

8. In addition to these highlighted measurements, high precision SST data has beencollected by teams in Australia, the UK and the USA. Initial analysis of the highprecision data confirms that the AATSR SST values are meeting their accuracytargets, by achieving accuracies better than 0.3 K. Also, a special series ofmeasurements over land has been coordinated in order to validate ESA’s newAATSR Land Surface Temperature product. Initial results have shown that thisproduct, devised by collaborators from CSIRO, Australia, will also achieve highlevels of accuracy.

9. Alongside the successful validation activities described above, the PI and VS havealso carried out important organisational functions. These include, for example,convening two meetings of the AATSR Science Advisory Group (SAG) on 9th May2002 and 27th February 2003. The membership of the SAG has been reviewedand modified to reflect the start of the data exploitation phase.

10. Support was also provided to two important ESA reviews, the ENVISATCommissioning Phase and calibration review in September 2002, which havealready been mentioned, and the ENVISAT Validation Review, held in December.The outcome of these reviews was successful from the point of view of AATSR,but the valuation review, although it revealed excellent results from AATSR,

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showed that there are still some open issues concerning the ENVISAT initialValidation programme and a further review is to be held by ESA later in 2003.It should also be mentioned that the AATSR PI team have participated in anumber of promotional events, ranging from conference presentations to pubiclectures and TV or radio interviews, all of which serve to increase externalawareness of the excellence of AATSR and of Defra’s role in funding it.

Conclusions

11. The AATSR validation programme has already demonstrated the high levels ofperformance and quality in the sensor and its data products during the first yearof operations. The performance of the sensor is certainly equal to and in manyrespects better than that of its two predecessors. The next year, when the initialvalidation programme is complete, should see the start of widespread andproductive exploitation of the data from AATSR.

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Chapter 7

Climate change – tracegases and radiative forcing

Contract No: EPG: 1/1/130TITLE: Measurement of radiatively important trace gases at Mace Head Contractor: International Science Consultants PI: P. Simmonds

Aims and objectives

1. To provide accurate, long-term measurement, archiving and analysis of keyradiatively and chemically active gases in the atmosphere to aid in theunderstanding of the role of these gases in global atmospheric change, andassess the effectiveness of international controls on emissions of greenhousegases and ozone depleting substances.

2. The principal objective of the research is to provide high frequency, high precisionmeasurements of the key atmospheric trace gases relevant to stratospheric ozonedepletion and climate change, using automated instrumentation at theatmospheric observatory at Mace Head, Ireland. Other objectives include:

i. To continue high-quality measurements of carbon dioxide, methane, ozone,carbon monoxide, nitrous oxide, and the six principal atmospherichalocarbons CCl3F (CFC-11), CCl2F2 (CFC-12), CCl2FCClF2 (CFC-113), CCl4,CHCl3 and CH3CCl3 at Mace Head, Ireland;

ii. To obtain routine in-situ measurements of the hydrochlorofluorocarbons(HCFCs), hydrofluorocarbons (HFCs), methyl bromide and other halogenatedgases relevant to stratospheric ozone depletion and climate change;

iii. To continue international collaboration and data exchange within the globalNASA/Advanced Global Atmospheric Gases Experiment (AGAGE) project.This will include, inter alia, the determination of global magnitude andlatitudinal distribution of the surface sources of greenhouse gases;

iv. In collaboration with the UK Meteorological Office to analyse and interpretthe atmospheric concentrations and trends of the ozone-depleting andradiatively active trace gases monitored at Mace Head. To estimate regional(European) and national (UK) emissions; and

v. To maintain an up-to-date calibrated database of all the trace gasesmeasured under contract to Defra at the Mace Head site and to maintain asecondary database of measurements made as part of the AGAGE globalnetwork.

Results

3. Continuous measurements of the radiatively active gases, CFCs, HFCs, HCFCs andother halocarbons have continued at Mace Head, Ireland, over the period April2002 to April 2003, producing an overall excellent dataset. Both the automatedGC and GC-MS instruments have operated almost flawlessly during the past12 months. However, the Siemens CO2 analyser experienced a number ofmechanical problems during the year. Since the instrument is now 12-years old itwill be replaced in the summer of 2003. Similarly the 16-year old ozone analyser

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Chapter 7 Climate change – trace gases and radiative Forcing

was retired in April 2003 and replaced with a new Thermoelectron ozoneanalyser. Most other minor problems were resolved as they occurred duringregular site visits.

4. Because Mace Head receives both clean oceanic air characteristic of thebackground troposphere as well as polluted air masses from Continental Europewe take great care to sort the data to obtain baseline monthly means. In additionto a statistical filtering process, which is routinely performed as part of the AGAGEprogramme by Georgia Institute of Technology, our colleagues at the Met. Officealso select baseline data using their “NAME” particle dispersion model. Combiningthe most recent measurements with the long-term observations recorded at MaceHead we observe a number of interesting trends. Atmospheric mixing ratios of themajor greenhouse gases CO2, CH4, N2O, and ozone are presently at their highestever-levels. In Figure 7.1, we plot the monthly mean concentrations of carbondioxide and the 12-month moving average. Based on a linear trend fitted to this12-month average CO2 has increased at a rate of 1.8 ppb/year over the 10-yearsof observations. For hydrogen also shown in Figure 7.1, there is no clearly definedtrend, although the growth anomaly in the 1998-1999 period is clearly defined bythe higher monthly means. We believe that the higher values in the 1998-1999time frame were attributable to the large-scale Russian and Indonesian fires, whichoccurred during this period.

Figure 7.1: Trends in carbon dioxide baseline concentrations 1992–2002.

5. For methane, shown in Figure 7.2, we observe an annual rate of increase overthe period 1987-March 2003 of 6.5 ppb/year, calculated from the 12-monthlyaveraging of the baseline monthly means.

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Climate change – trace gases and radiative forcing

Figure 7.2: Trend in methane and nitrous oxide baseline concentrations1987–2003.

6. This rate of increase has slowed dramatically over the last four years (1999-March2003) however, with an annual increase of only 0.37 ppb/yr. As noted in theliterature during 1998 there was a large positive anomaly in the global CH4growth rate. Dluglokencky, [2001]1 attributed this to increased emissions fromwetlands in the high-northern and southern-tropical latitudes resulting fromwetter-than-normal conditions. Our observations also confirm this 1998-1999methane growth anomaly, although we also observe anomalously high growthrates for hydrogen, carbon dioxide, carbon monoxide, methyl chloride and ozoneduring the same period. The fact that all these species can result from biomassburning, suggests that the 1998-1999 growth anomaly in these species couldalso be explained by large-scale fires and the global effects of the exceptional ElNino which also occurred during this period.

7. Nitrous oxide, also shown in Figure 7.2, is increasing at a rate of 0.79 ppb/yearover the 16-years of observations. Figure 7.3 shows the calculated trends (1987-2003) for the unpolluted ozone and carbon monoxide monthly means of 0.46ppb/year, and a downward trend of 1.5 ppb/year, respectively.

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1 Duglokenkcy, E.J., B.P. Walter, K.A. Masarie, P.M. Lang, and K.S. Kasischke, Measurements of an anomalous globalmethane increase during 1998, Geophys Res Lett., 28, 499-502, 2001.

Figure 7.3: Trends in the baseline monthly means of ozone and carbonmonoxide.

8. Two of the principal ozone-deleting CFCs, (CFC11, and CFC-113) are alsodeclining in the atmosphere at rates of 1.6 and 0.6 ppt/yr, respectively.Conversely CFC-12 and HCFC-22 continue to increase with HCFC-22 growing atabout 5.6 ppt/year. In the case of CFC-12 the average annual growth rate from1994 through 2003 was only 0.8 ppt/year, which is approximately one twentiethof its rate of increase in the late 1980’s. Moreover, this rate of increase continuesto slow year-on-year as is evident in the time series of all of the CFC-12observations plotted in Figure 7.4. In addition to the obvious slowing of thetrend, the magnitude of the pollution events (elevated red lines) have alsosubstantially decreased over time, but have not yet disappeared. This isattributable to the bank of old refrigeration units and old installations.

Figure 7.4: AGAGE time series of Mace Head CFC-12 observations.Baseline mole fractions (black), pollution events (red).

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9. Methyl chloroform (CH3CCl3) and carbon tetrachloride (CCl4) are both decreasingin the atmosphere but at dramatically different rates. Over the past 4 years CCl4has declined at an annual average rate of about 0.8 ppt/yr, while CH3CCl3 hasdecreased at an annual average rate of 7.5 ppt/yr from 1999-2003. When airmasses are transported from Continental Europe to Mace Head duringanticyclonic conditions, unlike CFC-12, it is now very difficult to discern anysignificant increase in the background atmospheric concentration of CH3CCl3 asshown in Figure 7.5. This is a powerful demonstration of the effectiveness of thephase out of these compounds under the terms of the Montreal Protocol and itsvarious amendments. European) emissions of CH3CCl3 estimated by the “NAME”model have now decreased to about 2 thousand tonnes yr-1, compared withaverage annual emissions of more than 30 thousand tonnes yr-1 in the 1996-1998 time frame.

Figure 7.5: Time series of Mace Head methyl chloroform observations(Blue = baseline mole fractions, red = pollution events).

10. We observe substantial growth rates through sustained emissions for the mainHFCs and HCFCs, which have replaced the CFCs in refrigeration and foamblowing applications. Trends have been calculated for the baseline-filteredmonthly means over the period 1994-2003. For example, HFC-134a is currentlygrowing at an annual average rate of 3.28 ppt/year, while the HCFCs 141b and142b are increasing at 1.78 ppt/year and 1.06 ppt/year, respectively. Figure 7.6,records the exponential growth rate of HFC-134a from 1994-2003. The AGAGEbaseline-filtered monthly means are recorded as blue dots, while the baselinefiltering used by the Met. Office “NAME” model are depicted by the pink dots.We also collect monthly flask samples for NOAA/CMDL as part of a collaborativeprogramme, and these samples are subsequently analysed at the CMDLlaboratories for many of the GC-MS species. Where we have NOAA/CMDL flaskmeasurements these data are also included in the figures as green dots.

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Figure 7.6: Baseline filtered monthly means for HFC-134a.

11. Of special interest are the decreasing trends in methyl chloride (CH3Cl, 12.6ppt/year), methyl bromide (CH3Br, 0.53 ppt/year), and methylene chloride(1.54 ppt/year). The fact that both CH3Cl and CH3Br are steadily decreasing in theatmosphere at both Mace Head and also at Cape Grim, Tasmania implies that achange has occurred which is affecting a common major source of both gases(possibly biomass burning) and/or their major sink process (destruction byhydroxyl radical). The decline in methyl bromide emissions appears to be in linewith its phase-out under the terms of the Montreal protocol and its amendments[Yokouchi et al, 2002]2, while a reduction in the many solvent applications ofmethylene chloride is consistent with its decreasing atmospheric abundance.More problematic is the concurrent decline in methyl chloride. The most likelyexplanation is that the major fires in 1998 caused an anomalous increase in theatmospheric abundance of CH3Cl, which has subsequently begun to decline.

12. Summaries of the trends calculated for all species currently monitored at Mace Headare summarised in Table 7.1 (decreasing trends), and Table 7.2 (increasing trends).

Table 7.1: Decreasing annual average trends in Mace Head baselinemonthly means.

Species Average annual trendCFC-11 -1.66 ppt/yr (1994-2003)CFC-113 -0.64 ppt/yr (1994-2003)CH3CCl3 -7.5 ppt/yr (1994-2003)CCl4 -0.8 ppt/yr (1994-2003)CHCl3 -0.26 ppt/yr (1994-2003)Carbon monoxide (unpolluted) -1.48 ppb/yr (1987-2003)Carbon monoxide (polluted) -5.65 ppb/yr (1987-2003)CH3Cl -12.65 ppt/yr (1994-2003)CH3Br -0.53 ppt/yr (1994-2003)CH2Cl2 -1.54 ppt/yr (1994-2003)

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2 Yokouchi, Y., Toom-Sauntry, D., Yazawa, K., Inagaki, T., and Tamaru, T., 2002b: Recent decline of methyl bromidein the troposphere. Atmos. Environ. 36, 4985-4989.

Table 7.2: Increasing annual average trends in Mace Head baselinemonthly means.

Species Average annual trend

Carbon dioxide +1.8 ppm/yr (1992-2003)

Methane +0.37 ppb/yr (1999-2003) + 6.5 ppb/yr (1987-2003)

Nitrous oxide +0.76 ppb/yr (1994-2003)

Ozone (unpolluted) +0.46 ppb/yr (1987-2003)

Ozone (polluted) +0.39 ppb/yr (1987-2003)

CFC 12 +0.8 ppt/yr (1999-2003)

HFC 134a +3.28 ppt/yr (1994-2003)

HCFC 22 +5.6 ppt/yr (1998-2003)

HCFC 141b +1.78 ppt/yr (1994-2003)

HCFC 142b +1.06 ppt/yr (1995-2003)

HCFC 152a +0.31 ppt/yr (1994-2003)

HFC 124 +0.11 ppt/yr (1998-2003)

Halon 1301 +0.07 ppt/yr (1998-2003)

Halon 1211 +0.13 ppt/yr (1994-2003)

Publications

Current publications resulting from this research are summarised below:

1) Continuous observations of carbon dioxide at Mace Head, Ireland from 1995-1999 and its net European ecosystem exchange. R.G. Derwent, D.B. Ryall, A.J.Manning, P.G. Simmonds, S’Odoherty, S. Biraud, P. Ciais, M. Ramonet, and S.G.Jennings, Atmos Environ, 36, 2799-2807, 2002.

2) Quantification of Carbon Dioxide, Methane, Nitrous oxide, and Chloroformemissions over Ireland from atmospheric observations at Mace Head. S. Biraud, P.Ciais, M. Ramonet, P Simmonds, V. Kazan, P. Monfray, S. O’Doherty, T. G. Spain,and S.G. Jennings, Tellus, 54B, 41-60, 2002.

3) Black Carbon Aerosol and Carbon Monoxide in European Regionally Polluted AirMasses at Mace Head, Ireland During 1995-1998. R.G. Derwent, D.B. Ryall, S.G.Jennings, T.G. Spain, and P. G. Simmonds. Atmos. Environ, 35, 6371-6378, 2001.

4) Evidence for significant variations of atmospheric hydroxyl radicals in the last twodecades. R.G. Prinn, J. Huang, R.F. Weiss, D.M. Cunnold, P.J. Fraser, P. G.Simmonds, C. Harth, P. Salameh, S. O’Doherty, R.H.J. Wang, L. Porter, B.R. Miller,and A. Mc Culloch, Science, 292, 1882-1888, 2001.

5) In-situ chloroform measurements at AGAGE atmospheric research stations from1994-1998. S. O’Doherty, G.A. Sturrock, D. Cunnold, D. Ryall, R.G. Derwent, R.Wang, P. Simmonds, P.J. Fraser, R.F. Weiss, P. Salameh, B.R. Miller, and R. G. Prinn,J. Geophys. Res., 106, 20,429-20,444, 2001.

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6) Estimating source regions of European emissions of trace gases from observationsat Mace Head., D.B. Ryall, R.G. Derwent, A.J. Manning, P.G. Simmonds, andS.O’Doherty, Atmos. Environ, 35, 2507-2523, 2001.

7) Transport of Boreal forest fire emissions from Canada to Europe, C Forster, U.Wandinger, G. Wotana, P. James, I. Mattis, D. Althausen, P. Simmonds, S.O’Doherty, G. G. Jennings, C. Kleefeld, J. Schneider, T. Trickl, S. Kreipl, H. Jagerand A. Stohl., J. Geophys Res, 106, 22,887-22,906, 2001.

8) AGAGE observations of Methyl Bromide and Methyl Chloride at Mace Head,Ireland, and Cape Grim, Tasmania, 1998-2001. P.G.Simmonds et., Submitted tothe Journal of Atmospheric Chemistry.

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Contract No: EPG 1/1/142Title: Interpretation of long-term measurements of radiatively activetrace gases and ozone depleting substances Phase IIIContractor: Met Office PI: A Manning

Aims and objectives

1. To analyse the long-term measurements of radiatively active trace gases andozone depleting trace gases being made at Mace Head to provide up-to-dateinformation on trends in atmospheric concentrations and global, regional andnational emissions.

Introduction

2. Since 1987, high frequency, real time measurements of the principal halocarbonsand radiatively active trace gases have been made at Mace Head, Ireland. Formuch of the time, the measurement station, which is situated on the Atlanticcoast, monitors clean westerly air that has travelled across the North AtlanticOcean. However, when the winds are easterly, Mace Head receives substantialregional scale pollution in air that has travelled from the industrial regions ofEurope. The site is therefore uniquely situated to record trace gas concentrationsassociated with both the Northern Hemisphere background levels with the morepolluted air arising from Europe.

3. Using the Mace Head data and a Lagrangian dispersion model, NAME, drivenby the output from the Met Office’s Numerical Weather Prediction model it ispossible to estimate Northern Hemisphere baseline concentrations for each tracegas and their European and UK emission distributions.

4. The atmospheric measurements and emission estimates of greenhouse gasesprovide an important independent cross-check for the emissions inventoriessubmitted to the United Nations Framework Convention on Climate Change(UNFCCC). This verification work is consistent with good practice guidance issuedby the Intergovernmental Panel on Climate Change (IPCC) and helps todetermine whether the inventories are reasonable and whether internationallyagreed reductions in emissions are being implemented.

Activities and methodology

5. The main aims of the project are as follows:

i. Analyse and update annually global baseline atmospheric concentration trendsand European emissions of the gases controlled by the Montreal Protocol;

ii. Analyse and report baseline emissions and concentrations of direct andindirect greenhouse gases measured at Mace Head and at other sites whereavailable; and

iii. Identify variations from expected trends in concentration and emissions of gases.

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6. For the eight year period 1995 to 2002 the NAME model has generated, at sixhour intervals, maps of the origin of the air (within ten days of transport) arrivingat Mace Head. The model has been re-run for the whole eight year periodmaking use of the new utility of being able to run the model backwards in time.This new feature has enabled a marked reduction in statistical noise to beachieved, from around 10% to 2%.

7. If the air has predominately come from the Atlantic ocean (excluding southernlatitudes) and the local atmospheric conditions at Mace Head are well-mixed theobservation point is considered to be baseline. By removing outlying points and byapplying a smoothing filter through these baseline points a baseline concentrationtime-series has been derived for each trace gas (Tables 7.3 and 7.4).

Table 7.3: Baseline concentrations and average seasonal perturbation in ppt ofthe major man-made halocarbons in the AGAGE observations at Mace Head forthe period 1995-2002.

Gas 1995 1996 1997 1998 1999 2000 2001 2002 Seasonalamplitude

CFC-11 269 267 266 264 263 262 260 258 2

CFC-12 533 538 540 543 544 546 546 546 3

CFC-113 84 84 83 83 82 82 81 81 1

CFC-114 17 17 17 17 17 0

CFC-115 8 8 8 8 8 0

Halon-1301 3 3 3 3 3 0

Halon-1211 4 4 4 4 4 0

HCFC-124 1 1 1 2 2 0

HCFC-141b 5 8 10 11 13 15 16 17 2

HCFC-142b 8 9 11 12 13 14 15 15 1

HCFC-22 146 152 159 162 5

HFC-125 1 1 2 2 2 0

HFC-134a 2 4 6 10 14 17 21 25 3

HFC-152a 1 1 1 2 2 2 3 3 1

Methyl bromide 11 11 10 10 9 2

Methyl chloride 558 539 524 513 526 95

Methyl chloroform 113 95 80 66 55 47 38 33 10

Carbon tetrachloride 103 101 100 99 98 97 96 95 1

Chloroform 12 13 12 12 12 11 11 11 2

Methylene dichloride 36 39 38 34 32 30 28 30 17

Trichloroethene 2 2 1 2 3

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Table 7.4: Baseline concentrations and average seasonal perturbation in ppb ofthe radiatively-active trace gases in the AGAGE observations at Mace Head forthe period 1995-2002.

Gas 1995 1996 1997 1998 1999 2000 2001 2002 Seasonalamplitude

Carbon monoxide 110 118 147 126 112 105 123 64

Methane 1802 1804 1802 1815 1820 1820 1818 1822 35

Nitrous oxide 312 313 314 315 315 316 317 318 1

Hydrogen 499 503 494 505 506 496 492 500 39

8. The by-product of the baseline derivation are time-series of the observedperturbations of each trace gas from their baseline values. These perturbationsare driven by emissions on regional scales which have yet to be fully mixed on theglobal scale. Using these perturbation time-series and the NAME model output toindicate where the air has originated from, emission distributions of each tracegas have been estimated. The iterative best-fit technique, simulated annealing, isused to derive these values based on a statistical score combining correlationcoefficient, normalised mean square error and fraction with a factor of two(Manning et al 2003). Three-year rolling averages for the UK and Europe aregiven in Tables 7.5 – 7.8.

Table 7.5: Estimates of UK source strengths in thousand tonnes yr-1 of themajor man-made halocarbons from 1995-2002 (three year averages).

Gas 1995-1997 1996-1998 1997-1999 1998-2000 1999-2001 2000-2002

CFC-11 0.89 0.74 0.87 0.76 0.93 0.68

CFC-12 1.47 1.01 1.00 0.71 0.89 0.66

CFC-113 0.36 0.18 0.18 0.11 0.15 0.11

CFC-114 0.10 0.14 0.07

CFC-115 0.04 0.03 0.03

Halon-1211 0.11 0.14 0.12

Halon-1301 0.04 0.07 0.08

HCFC-124 0.03 0.05 0.04

HCFC-141b 0.74 0.59 0.55 0.63 0.88 0.86

HCFC-142b 0.42 0.41 0.36 0.37 0.51 0.41

HCFC-22 2.34 2.18

HFC-125 0.16 0.23 0.21

HFC-134a 0.63 0.56 0.70 0.79 1.29 1.33

HFC-152a 0.02 0.02 0.03 0.03 0.07 0.07

Methyl bromide 0.26 0.28 0.25

Methyl chloride 3.13 2.82 4.17

Methyl chloroform 2.08 1.03 0.59 0.28 0.14 0.10

Carbon tetrachloride 0.23 0.21 0.18 0.14 0.15 0.15

Chloroform 1.17 0.97 0.94 0.82 1.00 1.03

Methylene dichloride 11.58 10.51 10.59 8.27 9.49 8.59

Trichloroethene 6.01 6.18

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Table 7.6: Estimates of UK source strengths in million tonnes yr-1 of radiatively-active trace gases from 1995-2002 (three year averages).

Gas 1995-1997 1996-1998 1997-1999 1998-2000 1999-2001 2000-2002

Carbon monoxide 3.01 3.06 2.52 2.80 2.30

Hydrogen 0.07 0.07 0.07 0.06 0.07 0.05

Methane 2.02 1.79 1.94 1.72 2.27 1.99

Nitrous oxide 0.09 0.08 0.08 0.08 0.10 0.09

Table 7.7: Estimates of European source strengths in thousand tonnes yr-1 ofthe major man-made halocarbons from 1995-2002 (three year averages).

Gas 1995-1997 1996-1998 1997-1999 1998-2000 1999-2001 2000-2002

CFC-11 6.5 7.4 9.3 7.3 5.7 6.7

CFC-12 12.3 12.6 15.6 11.7 8.5 7.5

CFC-113 3.6 2.5 2.2 1.0 0.7 0.7

CFC-114 1.0 2.0 0.5

CFC-115 0.9 0.7 0.7

Halon-1211 1.0 0.8 1.1

Halon-1301 0.5 0.5 0.6

HCFC-124 1.0 0.7 0.6

HCFC-141b 8.3 9.3 11.5 13.2 7.8 7.5

HCFC-142b 8.0 7.8 12.0 5.9 5.9 4.0

HCFC-22 27.3 28.2

HFC-125 1.3 1.6 3.5

HFC-134a 6.7 7.7 11.7 13.2 10.8 14.1

HFC-152a 0.7 0.7 0.9 1.0 1.7 3.3

Methyl bromide 5.2 5.1 4.4

Methyl chloride 64.5 60.6 59.7

Methyl chloroform 19.5 13.5 6.9 1.6 1.2 1.0

Carbon tetrachloride 4.6 4.7 4.9 4.3 4.3 3.2

Chloroform 11.4 13.8 18.5 10.1 8.1 5.7

Methylene dichloride 74.4 81.2 114.0 88.7 54.3 52.5

Trichloroethene 62.1 68.6

Table 7.8: Estimates of European source strengths in million tonnes yr-1

of radiatively-active trace gases from 1995-2002 (three year averages).

Gas 1995-1997 1996-1998 1997-1999 1998-2000 1999-2001 2000-2002

Carbon monoxide 48.0 54.6 47.8 57.2 68.8

Hydrogen 1.1 1.0 0.7 0.7 0.9 1.4

Methane 18.7 19.5 24.5 19.4 21.2 20.1

Nitrous oxide 1.0 1.1 1.3 1.0 0.8 1.2

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9. Figure 7.7a, nitrous oxide emissions for 1995-1997, illustrates the type ofEuropean emission map that is generated by this technique. The ‘best-fit’algorithm iterates from a randomly generated emission map to the one that mostclosely fits the observations at Mace Head. The technique has no knowledge ofland-sea boundaries, it solves purely to best fit the observations at Mace Head,any land-sea distinctions evolve from the fitting process.

10. A land-sea divide can be enforced within the fitting algorithm, i.e. by assumingfor example all emissions are land-based (Figure 7.7b, nitrous oxide emissions1995-1997 with a sea mask). The final ‘best-fit’ emission map will have a poorerfit than when no enforced assumptions are applied.

Figure 7.7: Nitrous oxide estimated emission maps for 1995-1997 (a) no assumptions (b) zero sea emission assumption.

(a) (b)

11. Naturally the maps with a sea mask applied concentrate the emissions onto theland areas, the estimated Irish and UK totals are therefore most affected by thisassumption. The estimated UK totals for nitrous oxide for each 3-year periodwith enforced zero sea emissions are given in Table 7.9, on average they are 43%higher than when no sea mask assumption is applied, the European totals areonly marginally affected.

Table 7.9: Estimates of UK and European source strengths in million tonnes yr-1

of nitrous oxide from 1995-2002 (three year averages) when a zero sea emissionassumption is applied.

Gas 1995-1997 1996-1998 1997-1999 1998-2000 1999-2001 2000-2002

UK 0.14 0.12 0.12 0.10 0.13 0.13

Europe 1.0 1.1 1.4 0.9 0.9 1.2

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12. The NAME inverse modelling emission results for UK and Europe have beencompared against other emission inventories (www.unfccc.int) where available(Table 7.10). The inverse modelling results for each species for both the UK andEurope are all well within a factor of 2 of the UNFCCC estimates. The UK NAMEtotals are systematically lower than the UK’s inventory estimates submitted to theUNFCCC. This is because the inversion technique has no knowledge of land-seaboundaries and due to errors in modelling the meteorology and transport theemissions can be marginally displaced into the sea and therefore not included.When a zero sea emission assumption is enforced (as shown in Table 7.10b) theUK NAME totals move closer to the UNFCCC estimates. The European totals arenot directly comparable. The UNFCCC total is the summation of the emissionestimates from 12 European countries (UK, Ireland, France, Germany, Denmark,Sweden, Belgium, The Netherlands, Luxembourg, Spain, Portugal and Italy) andthe NAME estimates cover the area enclosed on the map shown in Figure 5.7.

Table 7.10: Comparison of NAME and UNFCCC emission estimates in Gg yr1 for(a) Methane and (b) Nitrous oxide (zero sea assumption).

Methane 1995-1997 1996-1998 1997-1999 1998-2000 1999-2001 2000-2002

UK NAME 2020 1790 1940 1720 2270 1990

UNFCCC 2962 2837 2676 2505 2341 –

Europe NAME 18700 19500 24500 19400 21200 20100

(EU12) UNFCCC 16147 15833 15471 15121 14787 –

Nitrous oxide 1995-1997 1996-1998 1997-1999 1998-2000 1999-2001 2000-2002

UK NAME 140 120 120 100 130 130

UNFCCC 190 191 176 159 142 –

Europe NAME 1000 1100 1400 900 900 1200

(EU12) UNFCCC 1190 1170 1122 1074 1046 –

Publications

R.G. Derwent, D.B. Ryall, A.J. Manning, P.G. Simmonds, S. O’Doherty, S. Biraud, P.Ciais, M. Ramonet, S.G. Jennings.Continuous observations of carbon dioxide at Mace Head, Ireland from 1994-1999 andits net European ecosystem exchange. Atmospheric Environment, 36, pp.2799-2807, 2002

A.J. Manning, D.B. Ryall, R.G. Derwent, P.G. Simmonds, S. O’Doherty.Estimating European emissions of ozone-depleting and greenhouse gases usingobservations and a modelling back-attribution technique. In press Journal of Geophysical Research, March 2002.

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Chapter 8

Climate change – impacts

Contract No: EPG 1/1/124Title: The Climate Impacts LINK ProjectContractor: University of East Anglia PI: Dr D Viner

Introduction and background

1. In 1991 the Department of the Environment established the Climate Impacts LINKProject to act as the interface between the climate modelling activities of theHadley Centre and the wider UK climate change impacts research community.The LINK Project instigates a two-way channel of data and information flowbetween the Hadley Centre and the national impacts research community anddisseminates appropriate climate data and accompanying scientific and technicaladvice. The LINK Project is also responsible for the co-ordination of theIntergovernmental Panel on Climate Change (IPCC) Data Distribution Centre (DDC).

2. The core aims of the LINK Project that were laid down in 1991 are still validtoday. These have resulted in the LINK Project becoming an important componentof the international climate change research community. Since March 2003 theLINK Project has been run by the Climatic Research Unit in collaboration with theBritish Atmospheric Data Centre (BADC).

Activities

3. A core role of the LINK Project is to provide scientific and technical support to theinternational climate change research community; this is done through formaland informal methods, such as:

i. e-mail communication;

ii. the Climate Impacts LINK Project Web site (see below);

iii. the IPCC Data Distribution Centre (see below);

iv. publications (peer reviewed journals, contributions to reports, book reviews);and

v. attendance and presentations at conferences, workshops and invitedmeetings.

4. The Climate Impacts LINK Project facilitates the exchange of ideas regardingscenario construction and their application within impacts assessments andadaptation studies. By providing data through a personal point of contact,which is in engaged with both the climate modelling and climate changeresearch communities, the Climate Impacts LINK Project encourages theconsistent use of results from the Hadley Centre and provides a supportenvironment for researchers to make enquiries about the availability,interpretation and application of climate models and datasets.

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Chapter 8 Climate change – impacts

Data processing, quality control and the construction and maintenance of databases

5. Increases in the computing resources available for climate change experimentshave led to increases in the length and number of integrations being performed.The Climate Impacts LINK Project now hosts an on-line data archive of over oneand a half terabytes. Since March 2003 data extraction, processing and archivingactivities have been moved from the Climatic Research Unit and are now beingundertaken by the BADC. This transfer of activities will result in faster datatransfer from the Hadley Centre to the archive. Additionally, increased storagecapacity and integration of BADC’s existing system will enable users to customisetheir data requests.

6. The Climate Impacts LINK Project hosts the following four main databases, whichhouse the information and data that can be accessed to help service the climatechange research community:

i. The climate change research community database, including details of datausers, project details and publications that have used results from the HadleyCentre’s climate change experiments;

ii. The datasets for the IPCC Data Distribution Centre (see below);

iii. Observed climate database, including global and regional datasets; and

iv. The Hadley Centre’s results databases, containing results of the most recentclimate change experiments performed by the Hadley Centre and alsoprevious generations of results.

Provision of scientific and technical support

7. A major aspect of the LINK project is to provide informal scientific and technicaladvice to members of the climate change research community, this role is beingundertaken at the Climatic Research Unit. This community ranges from thosewho are already using the Hadley Centre results for climate research through toscientists who are making initial enquiries about climate change and impactsresearch.

8. The other platform for communication to the wider community is through theLINK Project’s web site (http://www.cru.uea.ac.uk/link ), which is accessed by over50,000 individuals each year. The web site acts as the focal point for climateimpacts researchers and provides information about the Hadley Centre’s climatemodels, the datasets available from their experiments through LINK, and otherbackground, supporting and guidance information.

The IPCC Data Distribution Centre and the Task Group on Scenarios for Climate ImpactsAssessment (TGCIA)

9. The IPCC DDC is jointly operated by DKRZ (Germany), the Climate Impacts LINKProject and CIESIN (USA) and has been functioning since early 1998. The DDCcontinues to play an important role in the ongoing IPCC assessment processand supports the activities of the Technical Support Units of Working Groups I, II

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and III. The DDC is accountable to the Task Group on Scenarios for ClimateImpacts Assessment (TGCIA), which in turn submits reports to the IPCC Bureau.The specific activities of the DDC include:

i. collating new climate model datasets that meet TGCIA quality controlcriteria;

ii. enhancing and extending Guidance Material;

iii. widening the range of accompanying climate, environmental and socio-economic datasets that currently exist and those that become available; and

iv. encouraging climate modelling centres to make available daily data.

The DDC is web-based and the site receives approximately 35,000 unique hitsper year. (See www.ipcc-ddc.cru.wea.ac.uk)

Conclusions

10. The Climate Impacts LINK Project and the IPCC DDC provide key focal pointsfor the international climate change research community and have enabled thewidespread and efficient use of the results from the Hadley Centre’s climatechange experiments. It is estimated that the Hadley Centre’s datasets are themost widely used results in climate change impacts assessments.

Publications

Viner D and Palutikof J. 2003 The changing interactions between climate andForestry. In Forest Research and the 6th Framework Programme, Report of theOpen Seminar 5th November 2002 Paris. Publ. European Forestry Institute

Viner D. 2003 Climate Change Impacts Assessments – A Review of the IPCCWGII TAR Global Ecology and Biogeography 12 87-88

Clark R.A., Fox., C., Viner D. and Livermore M. 2003 North Sea cod and climatechange – modelling the effects of temperature on population dynamics. ClimateChange Biology (in Press)

Parry M.L., Viner D. and others 2002 Investigation of Thresholds of Impact ofClimate Change on Agriculture in England and Wales. Jackson EnvironmentInstitute Research Report. No4. pp136

Parry M.L., Viner D. et al., 2002 Scenarios and data for future research on theimpact of climate change. Global Environmental Change.

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Contract No: EPG1/1/143Title: UK Climate Impacts Programme 2002Contractor: University of Oxford PI: Dr Chris West

Aims and objectives

1. The aim of UKCIP is to develop and maintain a framework that facilitates andsupports integrated research on the impacts of climate change, and adaptationto climate change in the UK.

2. The Programme objectives are:

i. to promote and co-ordinate stakeholder-led assessments on the impacts of,and adaptation to climate change in the UK, at a regional and national level,with an increased emphasis on exploring adaptation options within studies;

ii. to develop a framework for integration and synthesis of studies, to progresstowards a national integrated assessment of the impacts of climate changeat the end of the second phase;

iii. to provide advice and assistance to stakeholders and researchers onconducting studies, provide common tools, methodologies and datasets;provide guidance on how to use UKCIP tools and datasets;

iv. to develop capacity on climate change outside the Programme Office, byproviding training and support to regional climate change partnerships andto key UKCIP contacts in the public and private sector;

v. to provide a focal point for UK climate change impacts and adaptationinformation and disseminate information from UKCIP and UKCIP studies;and

vi. to develop appropriate links with related Programmes and organisationsboth within the UK and other countries.

3. The UK Climate Impacts Programme (UKCIP) was established by Defra (thenDETR) in 1997 with the aim of establishing a research framework for theintegrated assessment of climate change impacts in the UK.

4. At the heart of UKCIP is a Programme Office based at the Environmental ChangeInstitute, part of the University of Oxford. The Programme is advised by a SteeringCommittee comprised of representatives of key Government departments, publicagencies, the private sector and NGOs. A Science Advisory Panel oversees theintegrity of the work. A User Forum enables partner organisations to interactdirectly with the Programme. There are also a number of steering committees forstudies operating within the Programme.

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5. The Programme works in a ‘bottom-up’ mode, supporting organisations toinitiate studies that assess their vulnerability to climate change impacts andidentify adaptation responses. It has become a new link between stakeholdersand researchers and helps make connections between partners to stimulate abroad-based approach to the study of climate change impacts.

6. It is intended that the broad-based approach should lead to an integratednational assessment. Integration is being achieved principally through:

i. core data sets and common scenarios (both socio-economic and climatechange);

ii. common frameworks to handle risks and uncertainty and costing of impacts;

iii. consistent Programme Office provision of advice; facilitation of networkingof funders and researchers and the sharing of information; and

iv. development and application of Programme Office experience.

Objective 1 – stakeholder-led assessments

7. UKCIP is actively engaged with some thirty regional and sectoral studies, at allstages from nascent to detailed quantitative studies. Through active participationin steering groups or partnerships, provision of tools and specific advice, UKCIPis able to guide the process, improve the scientific quality, and ensure uptake ofthe results.

Department for Environment, Food and Rural Affairs Steering Committee

Science Advisory User ForumUKCIP Programme Office

RegionalIntegratedAssessment

(REGIS)

INTEGRATION

Regional/Sub-UK Sectoral Studies

Scotland Wales NorthernIreland

SouthEast

England

South West

England

NorthWest

England

NorthEast

England

WestMidlands

EastMidlands

LondonYorkshire

&Humberside

Gardens WaterDemand Health

Biodiversityreview (DEFRA)

Biodiversity(MONARCH)

Marine environment

Builtenvironment

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8. All the English Regions and the devolved administrations have scoping studiescomplete or underway. The status of these at March 2003 is shown:

“Region” Status of scoping study Completion date

Scotland Completed; further actions being undertaken December 1999

Northern Ireland Completed; further actions being considered March 2002

Wales Completed; further studies underway February 2000

North east Completed; further actions being undertaken November 2002

North west Completed; active partnership continuing December 1998

Yorkshire/Humberside Completed; further actions underway June 2002

West Midlands Scoping study underway (Autumn 2003)

East Midlands Completed; further actions being undertaken July 2000

East of England Scoping study underway (Autumn 2003)

London Completed; active partnership continuing October 2002

South east Completed; active partnership continuing November 1999

South west Completed; active partnership continuing January 2003

9. The SECCP now has fee-paying members supporting a full-time coordinator. TheNWCG is exploring a similar move, while Yorkshire Forward, the Greater LondonAuthority, and The North East Regional Assembly have all agreed to fund climatechange coordinators for their regional partnerships. In the regions still tocomplete scoping studies, UKCIP has actively promoted the persistence of thepartnership beyond the delivery of the scoping study report.

10. There were three studies started this year – the new East of England and WestMidlands regional scoping studies will both report in 2003, and the £2 millionUKCIP/EPSRC portfolio of projects in Building Knowledge for a Changing Climatewas initiated.

11. This portfolio is the result of collaboration between UKCIP and Engineering andPhysical Sciences Research Council to engage stakeholders in setting and runninga research agenda to study the potential long term impacts of climate change onthe built environment, transport and utilities in the UK. EPSRC have to date fundedsix consortia-based projects to a value of £2.2 million. Subjects covered in theseprojects are urban drainage, planning, energy and telecommunications, builtheritage, and risk management; additionally common work on downscaling andon an integrating framework add value to the portfolio’s delivery of knowledge.

12. A number of government departments are now assessing their vulnerability toclimate change for the ENV(G) Committee of the Cabinet, and UKCIP has helpedseveral initiatives.

13. During the year, the Garden scoping study Gardening in the Global Greenhouse –the impacts of climate change on gardens in the UK was launched at an event atthe Royal Society in November 2002. The study reviews the existing literature andprovides an overview of the best current information available. It also identifieskey information gaps in assessing the impacts on gardening, heritage gardensand commercial horticulture, and defines a future research agenda. The reportwas received with great press interest.

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Objective 2 – framework for integration

14. The Building Knowledge for a Changing Climate portfolio has an integratingframework built into it so that the six projects can deliver more together thanthey can individually to the community of research user stakeholders. Theconcept is illustrated in the figure.

15. UKCIP’s intention is to develop a framework for integration and synthesis ofstudies and to progress towards a national integrated assessment of the impactsof climate change at the end of the second phase. The process, starting with thepromotion of the importance of the cross-linkages between sectors and regions,already uses the output from regional studies to identify sectoral issues andidentifying common interest in addressing those issues. Given the number ofindividual studies being undertaken, it has been necessary to provide integrationas an “add-on” refinement. In order to facilitate this, the UKCIP is consideringthe implication of this approach.

Objective 3 – advice and assistance

16. UKCIP attends study steering group meetings whenever possible, and guides theprogress of the study. The researchers within both scoping studies and the morequantitative studies are given advice and guidance on use of the scenarios, onfundamental issues of prediction and uncertainty, on the datasets available, andon ownership and data quality issues. Additionally, UKCIP staff are able to givegood advice on the methodology being used. Researchers consistently say howmuch they value being able to consult UKCIP in this way.

17. The UKCIP02 climate scenarios published this year have been enthusiasticallytaken up and used with seventy users taking out licenses. Much of the projectmanagement skill that UKCIP deploys is aimed at passing on best practice instudy methodology from one study to another.

18. As an adjunct to the preparation of the British Irish Council’s high-resolutionisland scenarios by the Hadley Centre, UKCIP contributed, with Hadley Centreand Global Atmosphere Division, to a series of awareness raising workshops inthe Channel Islands and the Isle of Man. At these workshops, we were able topresent some of the anticipated changes, and to set the administrations on theirway to adapting to those changes.

High resolutionweather station Risk management

INTEGRATING FRAMEWORK Widerworld

StakeholderForum

Urban drainage

Urbanplanning Energy Heritage DTI

projects

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19. A great deal of effort has gone into making the guidance on handling risk anduncertainty useful to decision-makers and using risk and uncertainty as a way ofmaking climate change impacts more compatible with the way that decisionmakers work.

20. To promote integration within the portfolio, one of the Building Knowledge for aChanging Climate projects was formulated as a service to the others in providinga common methodology to provide relevant scale datasets to the portfolio.

Objective 4 – develop capacity

21. Capacity building has been the focus of UKCIP’s work in developing networks ofpartners with business and with local authorities to add to the existingnetworking with regional groupings. The networking proposal to address capacitybuilding was endorsed by the User Forum and by the UKCIP Steering Committeeand developed by the team. For a network based on local authorities, UKCIPreached agreement with the Local Government Association (LGA) and with theImprovement and Development Agency (IdeA) to work together on a guidancedocument for Local Authorities, using the IdeA’s existing group of Councils forClimate Protection (CCP) as an initial network. UKCIP has worked with theSustainability sub-group of the Advisory Committee on Business and theEnvironment to devise a methodology for addressing the business community.A strategy for this purpose was drawn up and some preparatory informationmaterial assembled. UKCIP will work through a small group of trade associations,institutions, and unions, to multiply its ability to connect to large numbers ofbusinesses. A number of regional contacts have been supplied with presentationsand with regional illustrations of UKCIP02 Climate Scenario data for use inawareness raising on a regional scale.

Objective 5 – focal point

22. UKCIP has been proactive in promoting UKCIP and the UKCIP website(www.ukcip.org.uk) to a wide range of organisations, both as a sourceof climate change impact information, but also a vehicle for more activeinvolvement. The UKCIP website is extremely popular all over the world,with over a quarter million hits during the week following the launch of theUKCIP02 Scenarios, and another peak after the launch of the Gardens study.

23. UKCIP has dispatched over 11,000 publications this year, separate from thosedispatched by other partners. These comprised 4,000 UKCIP02 scenariodocuments, 6,000 other 2002 – 2003 reports and 1,000 publications fromearlier years. The new monthly electronic newsletter E-news now has 2,700recipients and generates a lot of further enquiries.

24. UKCIP staff are regularly asked to speak at meetings and to give mediainterviews, both opportunities to advertise the information and opportunitiesavailable from UKCIP. Attendance at COP 8 in Delhi was an opportunity toshowcase UKCIP and make links to a number of kindred programmes aroundthe world.

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Objective 6 – develop appropriate links

25. UKCIP has developed its working relationships with a number of relevantorganisations:

i. Government (Defra Divisions, ODPM, DCMS, MOD, DfT, EA, HMT, devolvedadministrations);

ii. Research (e.g. Tyndall Centre, Hadley Centre, Hazards Forum, otherresearchers and consultancies);

iii. Business (ACBE, CBI, Arena, RDAs);

iv. Local Authorities (LGA, IdeA, ICLEI, Regional Assemblies, individual councils);

v. Sustainability (SD Commission, Carbon Trust, Carbon); and

vi. Disclosure Project, Environmental Law Foundation).

26. UKCIP has exchanged information with a number of overseas programmes. Thesecondment to UKCIP of Andy Reisinger of the Climate Change Office, Ministryfor the Environment, New Zealand for a month, was useful beyond his work onthe Local Authority guidance, and we intend to continue to exchange news,documents, and thoughts with New Zealand.

Conclusions

27. The first year of the second phase of the UK Climate Impacts Programme hasseen evolution on a number of fronts and, despite continuing uncertainty overthe year’s budget, significant progress on achieving the objectives of theprogramme:

i. The new UKCIP climate scenarios were published this year and havestimulated a great deal of interest;

ii. Reports of four Regional scoping studies and the Gardens study have beenpublished and launched;

iii. The sub-UK coverage by scoping studies is complete, with only the last twoEnglish regions to report in the coming year;

iv. Regional partnerships in a number of forms are now driving forward theirown climate impacts agenda;

v. The large EPSRC-funded portfolio of projects Building Knowledge for aChanging Climate has been launched with excellent stakeholderinvolvement; and

vi. A successful User Forum was held , and stimulated work on capacity-buildingnetworks of partners to operate in the business and local authority fields.

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28. During the next year, UKCIP intends to make significant progress towardsmeeting its objectives, but particularly,

i. to publish its guidance for local authorities, to populate the underpinningresource base with the help of CCP, IdeA, and LGA and to realise a localauthority climate impacts network;

ii. To realise the proposed UKCIP link to business approach with trade associations;

iii. To publish and build experience in using both the risk management andcostings methodologies as well as a guide to using the UKCIP “toolbox”;

iv. To complete the coverage of the regional scoping studies, to bring allregional partnerships up towards the activity of the best, and to encourageintegration across and within regions; and

v. To understand and promote the concept of “post-hoc” integration.

Publications

29. All available at www.ukcip.org.uk

Climate Change Scenarios for the UK – the UKCIP02 scientific report (available inboth Technical Report and Briefing Report)

Warming up the Region – Yorkshire and Humberside climate change impactsscoping study (available in both Technical Report and Briefing Report)

London’s Warming – the impacts of climate change on London (available in bothTechnical Report and Briefing Report)

Gardening in the Global Greenhouse – the impacts of climate change on gardensin the UK (available in both Technical Report and Briefing Report)

And the Weather Today is...North East summary report

Warming to the Idea – South West region climate change impacts scoping study(available in both Technical Report and Briefing Report)

Building Knowledge for a Changing Climate – the impacts of climate change onthe built environment

Ready for Impact – an introduction to UKCIP

Proceedings from the UKCIP User Forum

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Contract No: EPG/1/1/139Title: Global impacts of climate change on human healthContractor: London School of Hygiene and Tropical Medicine PI: RS Kovats

Aims

1. We assessed the effect of climate change and population growth on futurepopulations at risk of malaria, using socio-economic scenarios and climateprojections made using the HadCM3 climate model driven by SRES emissionsscenarios (IPCC Special Report on Emissions Scenarios). These scenarios arenon-interventionist scenarios and imply no explicit climate policies to reduceemissions. The aim of the scenarios is to provide a consistent input to bothclimate models and impact models in relation to the drivers of global change.The emission scenarios are presented in four “storylines” (A1FI, B1, A2 and B2)which represent mutually consistent characterisations of future states of theworld during the 21st century, including demographic and economicdevelopment and associated changes in climate and sea level.

Activities

2. The assessment used the malaria module of the MIASMA model (v2.2.),developed by Martens and colleagues at ICIS. This model links GCM (GeneralCirculation Model) climate scenarios with an impact module that applies theformula for the basic reproduction rate (Ro ) of mosquitoes, to calculate the‘transmission potential’ (TP) of the malaria mosquito population, and to estimatethe population at risk.

3. The work was carried out by a multidisciplinary team of scientists from threecollaborating institutions: The London School of Hygiene and Tropical Medicine(LSHTM) (UK); The International Centre for Integrative Studies (ICIS) (theNetherlands); and the Climatic Research Unit (UK).

Results and conclusions

4. Many more people are projected to be at risk of contracting malaria. The vastmajority of this additional population are located in developing countries, wheremalaria is currently restricted by climate factors (such as in arid and highlandregions). The ability of these countries to manage any climate-induced increasein malaria will depend on their capacity to develop and sustain malaria controlprogrammes. A net decrease in population at risk due to climate change isindicated in the least developed countries, where climate, in general, is alreadyfavourable for transmission. For those countries that currently have a limitedcapacity to control the disease, the model estimates an additional population atrisk > 1 month transmission per year) of between 90 (A1FI) to over 200 (B2b)million by the 2080s.

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5. Regions in South East Asia and central Asia are highlighted as particularlyvulnerable for changes in socio-economic conditions with respect to malaria.Climate change will cause a redistribution of the area meeting conditions suitablefor transmission of malaria. The most important regions with respect to climate-related impacts on the current distribution of malaria are likely to be Africa andAsia. This assessment shows that climate change will expand the “potential”transmission zone. Many other factors, however, will determine the time at whichindividual countries achieve the capacity to control the disease. These will need tobe addressed in future assessments of the potential impact of climate change onglobal malaria.

Investigators

R S Kovats, Centre on Global Change and Health, London School of Hygiene andTropical Medicine, UK

Dr P Martens, M van Lieshout, International Centre for Integrative Studies,Maastricht University, Maastricht, The Netherlands

M Livermore, Climatic Research Unit, University of East Anglia, UK

Publications and other output

Kovats RS, van Lieshout MC, Livermore M, McMichael AJ, Martens P. ClimateChange and Health. Final Report for Defra. LSHTM, London, January 2003.

Van Lieshout MC, Kovats RS, Livermore M, Martens P. Climate Change andMalaria: Analysis of SRES climate and socio-economic scenarios. GEC, in press.2003.

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Contract No: EPG 1/1/70Title: Global impacts of climate change on water resourcesContractor: University of Southampton PI: Prof N W Arnell

Aims and objectives

1. The broad aim of this project was to assess the global and regional impacts onwater resources stresses of the four IPCC SRES “storylines”. Each storyline hasnot only a different pattern of greenhouse gas emissions, but also differentpopulation and economic characteristics. The project is part of the “Fast Track”suite of estimates of the implications of climate change at the global scale.The specific objectives were to:

i. Simulate river runoff at a spatial scale of 0.5x0.5o under climate scenariosbased on seven transient experiments conducted using HadCM3 (one A1FIemissions scenario, three A2 emissions, one B1 and two B2) and a pre-existing macro-scale hydrological model;

ii. Estimate population by major watershed by the 2020s, 2050s and 2080s,under the SRES storylines; and

iii. Calculate indices of water resources stress by watershed, and sumpopulations living in water-stressed watersheds under different climate andpopulation scenarios.

Background

2. A previous Defra-funded assessment of the implications of climate change forglobal water resources used climate scenarios constructed from HadCM2 andHadCM3 under the IS92a emissions scenario, with one projection of futurepopulation, and calculated indices of water resources stress at the national level.The current study extends this earlier work by exploring a range of differentsocio-economic futures, and by involving calculations at a finer spatial scale.

Activities

3. A macro-scale hydrological model has been used to simulate stream-flow acrossthe world, at a spatial resolution of 0.5x0.5o; runoff is aggregated to around1300 watersheds and islands. The implications of natural multi-decadal climaticvariability have also been assessed, using climate scenarios taken from a long,unforced HadCM3 simulation: the effects of future climate change are comparedwith this multi-decadal variability.

4. Watershed population under each population projection (A1 and B1 have thesame population projection, so there are just three different population scenarios)was estimated in the following stages:

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i. Estimates of national population change under each scenario were acquiredfrom the Centre for International Earth Science Information Network(CIESIN), New York;

ii. These changes in national population were applied to the GriddedPopulation of the World version 2 data set, to produce maps of populationat a resolution of 2.5x2.5; and

iii. These gridded data were then aggregated to the watershed.

5. The approach assumes that population everywhere within a country grows atthe same rate: this is of course unlikely, but the effects of this assumption areminimised by the aggregation to the watershed scale.

6. A number of indices of water resources stress were considered, including indicesbased on per capita water availability and estimates of future water withdrawals.Projections of future withdrawals are extremely unreliable (and are verydependent on base year), so an indicator based on per capita availability wasused: a watershed is deemed to be water-stressed if there is less than1000m3/capita/year. Note that this index does not take into account access toavailable water.

7. Climate change is assumed to have an “impact” if watershed runoff changes bygreater than the standard deviation of runoff due to natural multi-decadalvariability. A watershed has an increase in stress either if it is already stressed andclimate change reduces runoff by more than the standard deviation, or if it movesinto the stressed class. A watershed has an apparent decrease in stress either if itis already stressed and climate change increases runoff, or if it moves out of thestressed class. The two directions of change are not comparable, however,because increased runoff where it occurs tends to happen during the wet season,and may not be helpful if there is no storage. The “net” effect of climate changeis therefore not calculated, as it is not an appropriate measure.

Results

8. At each time horizon – the 2020s, 2050s and 2080s – each of the scenariosproduces a similar pattern of change in average annual runoff. Runoff reducesacross much of North America, South America, Europe, the Middle East, centraland southern Africa, and eastern Australia. Runoff increases in high latitudes inNorth America and Asia, and in south east Asia. The very strong correlationbetween the seven sets of changes, at each time horizon, suggests that thepattern of change reflects a climate change signal rather than the noise ofnatural multi-decadal climatic variability, although multi-decadal variability leadsto differences in magnitude of change in individual watersheds. At each timehorizon, the correlation between the ensemble members is no greater than thecorrelation between all seven climate scenarios.

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9. By the 2020s, there is no clear systematic difference between the magnitudes ofchange in the seven sets of change in annual runoff, and there is only limitedevidence of a systematic pattern by the 2050s (the A1FI changes have the samespatial distribution as, but greater magnitudes than, the B1 changes). This impliesthat the seven scenarios can be taken as a single ensemble set. By the 2080s thesystematic differences are greater – A1FI produces the greatest change, followedby the A2 ensemble set, then the B2 set and finally B1 – although even hereit is difficult to clearly distinguish between A1F and one of the A2 ensemblemembers.

10. The numbers of people defined as living in water-stressed conditions dependson the precise indicators and thresholds used: the current study assumes waterstressed watersheds have less than 1000 m3/capita/year. Climate change increasesrunoff in some parts of the world – largely southern and eastern Asia – butdecreases it in others – including southern Africa, around the Mediterranean,large parts of Europe and much of central and south America. The numbers ofpeople affected depends more on the assumed population growth scenario thanon the emissions scenario. By 2025 between 395 and 1660 million people areadversely affected by climate change: by 2055 the numbers adversely affected arebetween 800 and 1200 million under the A1/B1 world, between 1200 and 2000million under the A2 world, and between 1100 and 1200 under the B2 world.Areas with an increase in runoff will not necessarily see a reduction in waterresources stresses because the extra water generally occurs during the high runoffseason and may not be available to sustain supplies during the dry season.

Conclusions

11. The project has firstly demonstrated where climate change may have the greatestimpact on water resources, and given an indication of the magnitude of impact,as discussed above. The project has also demonstrated that the impact of climatechange over the next few decades depends more on the assumed rate ofpopulation increase than on the effect of different emissions scenarios.

Publications

Arnell, N.W. (2003) Effects of IPCC SRES emissions scenarios on river runoff:a global perspective. Submitted to Hydrology and Earth System Sciences.

Arnell, N.W. (2003) Climate change and global water resources: SRES emissionsand socio-economic scenarios. Submitted to Global Environmental Change.

Arnell, N.W. , Livermore, M.J.L, Kovats, R.S., Levy, P., Nicholls, R., Parry, M.L.and Gaffin, S.R. (2003) Climate and socio-economic scenarios for global-scaleclimate change impacts assessments: characterising the SRES storylines.Submitted to Global Environmental Change.

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Contract No: EPG 1/1/137Title: Global impacts of sea-level rise as a result of climate changeContractor: Middlesex University PI: Prof. R.J. Nicholls

Introduction

1. The IPCC Special Report on Emissions Scenarios (SRES) has produced a range ofscenarios of future emissions of greenhouse gases, based on discrete storylineswith plausible assumptions about demographics, economics, technology andother relevant factors. This study examines the regional and global flood impactsof possible sea-level rise due to four SRES emission scenarios (A1FI, A2, B1, B2)as part of the Fast Track Assessment. The global sea-level rise scenarios arederived from the Hadley Centre HADCM3 model. The SRES population and GrossNational Product (GNP) scenarios were downscaled from the original, regionalSRES scenarios by the Centre for International Earth Science Information Network(CIESIN), with some additional work required for small countries (<150,000people), by the Fast Track team.

2. All the SRES sea-level rise scenarios are smaller than the sea-level rise scenariosreported previously by the Hadley Centre, except for those used in the IS92astabilisation analysis (see Arnell et al., 2002). The projected rise in sea level undereach of the SRES scenarios are nearly identical during the 2050s, but havebecome distinct by the 2080s, with a net global rise of 22, 25, 28 and 34 cmfor the B1, B2, A2 and A1FI worlds, respectively.

3. Global population is projected to increase from approximately 5.3 billion in 1990to 14.2 billion, 10.2 billion and 7.9 billion in the 2080s (under the A2, B2 andA1/B1 worlds, respectively). In addition, the average GDP/capita is projected toincrease from about $3,800 in 1990 to $13,000, $20,000, $36,600 and $52,600(under the A2, B2, B1 and A2 worlds, respectively), over the same time frame.Hence, the A2 world is poorest and most densely populated, while the A1 worldhas the highest living standards and lowest population density. These socio-economic differences influence both the human exposure to flooding andsea-level rise, and the quality of flood management.

Methods

4. The coastal zone is already densely populated and is a major focus for migration,particularly to urban locations. Therefore exposure to flooding and damageduring major storms is already significant and increasing. While sea-level rise is amean effect, it also raises the height of sea level during extreme events, such asstorm surges, and hence increases the flood risk to these expanding coastalpopulations. (Note that all other climate variables such as the incidence andintensity of storms are considered constant in this analysis). By considering theprotection standard of flood defences, the change in flood frequency can beestimated and the effect of sea-level rise in terms of flood impacts can beevaluated. The scenarios considered in the analysis are given in Table 8.1.

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Table 8.1. Scenarios considered in the flood analysis.

Factor Scenario name Definition

Subsidence (only in 1. Natural subsidence 15 cm/centurysubsiding areas)

2. Human-induced 45 cm/centurysubsidence (due to groundwater extraction)

Coastal population change 1. Low growth As national population change

2. High growth Increases at double the populationincrease (and decreases at half anypopulation decrease)

Protection standards 1. Constant protection Fixed (1990) protection standards usingGDP/capita

2. In Phase Evolving Protection standards improve in phaseProtection with GDP/capita, but only considering

1990 surge levels (i.e. sea-level rise isnot considered)

3. Lagged Evolving As ‘In Phase Evolving Protection’, exceptProtection protection standard improvements

occur with a 30-year time lag behindGDP/capita change.

5. Three protection scenarios are considered as defined in Table 6.1. As livingstandards rise, so evolving protection standards are upgraded, but only assumingthe flood conditions existing in 1990 i.e. there is only adaptation to the climatevariability (storm surges) in 1990 and no adaptation to global sea-level rise. Basedon experience around the world, ‘Lagged Evolving Protection’ appears to be themost realistic assumption. For each time-step various parameters, expressinghuman exposure and risk of flooding, are calculated, including (1) the populationof the coastal flood plain and (2) the number of people who actually experienceflooding by storm surge in a typical year (termed average annual people flooded).

Validation

6. Globally, the model predicts that approximately 200 million people lived in thecoastal flood plain (below the 1,000-year flood elevation) in 1990. Further, about5% of these people (about 10 million people/year) experienced flooding by astorm surge at this time. At the national level, the model is supported by theavailable estimates from independent national level vulnerability assessments(e.g., www.survas.mdx.ac.uk), giving broad confidence in the analysis.

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Results

7. Globally, the population of the coastal flood plain is projected to increase underall SRES scenarios. By the 2080s, it will have increased to between 286 million(A1 world, low coastal population growth) and 840 million people (A2 world,high coastal population growth). Sea-level rise will further increase this growthdue to an increase in the size of the flood plain, but the effect is relativelymodest, with a maximum increase of 67 million people (or 8%) in the A2 world(with high coastal population growth and natural subsidence).

8. The number of people who experience flooding will change as a result ofchanges in exposure and protection standards without sea-level rise. Assumingconstant (1990) protection, the exposed population grows (and relative sea-levelrise due to subsidence occurs), reaching 30 to 49 million/year under the A2 worldin the 2080s. Assuming in-phase evolving protection, the number of peopleflooded increases to the 2020s in all cases, but subsequent behaviour showssignificant variation. The number of people flooded diminishes from the 2020s tothe 2080s under the A1FI , B1 and B2 worlds, to levels well below those in 1990.In contrast, in the A2 world, the number of people flooded increases to 16 to 28million/year in the 2050s and then decreases to 11 to 19 million people/year inthe 2080s.

9. Global-mean sea-level rise and natural subsidence could have significant impactson coastal areas, but the additional impacts take some time to become manifest.Under constant protection impacts are apparent by the 2050s, and by the 2080sthere is a 3- to 5-fold increase in the incidence of flooding compared to thereference scenario. Under in-phase evolving protection, impacts are not apparentuntil the 2050s for the A2 world, and the 2080s in the other cases. Themagnitude of additional impacts is typically an order of magnitude lower thanunder constant protection (Figure 8.3).

Figure 8.3: Additional People Flooded (per year) due to sea-level riseunder the SRES Scenarios and (a) Constant Protection and (b) In PhaseEvolving Protection. For both low and high population growth scenariosand the low subsidence scenario (note the different scales).

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10. Table 8.2 ranks the four SRES worlds in terms of relative impacts based on allconsistent scenario combinations from Table 8.1. The A2 world emerges as thatwhich is most vulnerable to coastal flooding with or without climate change(and most vulnerable to loss of coastal wetlands, although this analysis is notpresented here). In contrast, the B1 world would appear to give the lowestimpacts in terms of coastal flooding and wetland loss, based on its lowerpopulation, higher GDP/capita and the smallest projected global sea-level rise.

Table 8.2. Ranking of the SRES worlds for the magnitude of coastalflooding (and wetland loss), with and without climate change: Synthesisfor all realistic scenario combinations.

No climate change Climate change

Highest Impacts Coastal flooding Wetland loss Coastal flooding Wetland loss

A2 A1FI/A2 A2 A1FI/A2

B2 A1FI/B2

Lowest A1FI/B1 B1/B2 B1/B2 B1

Impacts

11. This analysis shows that the impacts of climate change may depend more onsocio-economic factors than the magnitude of climate change (e.g. the poorer,more populated A2 world versus the richer less populated A1 world). This placesclimate change in the broader context of sustainable development.

12. Regionally, small island regions stand out as experiencing significant flood impactsin all SRES futures. The worst impacts are predicted for the A2 and A1FI worlds.This reinforces earlier conclusions about the vulnerability of these small islandregions and the particular need to prepare for adaptation to sea-level rise inthese regions.

Conclusions

13. These results should be seen as a broad analysis of the sensitivity of the coastalsystem to the SRES global-mean sea-level rise scenarios. The A2 world appears tobe most vulnerable to both sea-level rise, and other change factors (even thoughthe largest rise in sea level occurs in the A1FI world), while the B1 world is leastvulnerable. While not quantitatively analysed, the trend of the results suggestslarger impacts of sea-level rise on coastal flooding in the 22nd Century(particularly under the A1FI scenario), suggesting that discussions on climatepolicy should not simply focus on 21st Century impacts. More importantly, theresults indicate that socio-economic conditions fundamentally control impactsboth with and without climate change, suggesting that a greater consideration ofthe role of development pathways on impacts and adaptation to climate changecould be useful.

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Publications

Arnell, N.W., Cannell, M.G.R., Hulme, M., Kovats, R.S., Mitchell, J.F.B., NIcholls,R.J. Parry, M.L., Livermore,, M.T.J. and White, A. 2002. The consequences of CO2stabilisation for the impacts of climate change Climatic Change, 53, 413-446.

Nicholls, R.J., 2003. Coastal Flooding and Wetland Loss in the 21st Century:Changes Under The SRES Climate And Socio-Economic Scenarios. GlobalEnvironmental Change, in review.

Arnell, N.W., M.J.L. Livermore, S. Kovats, P. Levy, R. Nicholls, M.L.Parry and S.Gaffin, 2003. Climate and socio-economic scenarios for climate change impactsassessments: characterising the SRES storylines. Global Environmental Change,in review.

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Contract No: EPG 1/1/136Title: Global impacts of climate change on food securityContractor: Parry Associates PI: Martin Parry

Aims and objectives

1. The central aim of the study was to provide a global assessment of the potentialeffects of climate change on crop yields and world food security under the fourIntergovernmental Panel on Climate Change (IPCC) SRES worlds: A1, A2, B1 andB2. In order to achieve this, seven future climate scenarios (A1FI, A2a, A2b, A2c,B1, B2a and B2b) were derived from experiments conducted using the UKHadley Centre’s third generation coupled atmosphere-ocean global climatemodel (HadCM3). The analysis sought to include both biophysical processes andeconomic responses to shifts in comparative advantage. Specifically, theobjectives were to calculate quantitative estimates of climate change impactson the amount of food produced globally, and to determine the consequencesto world food prices and the number of people at risk of hunger.

Introduction

2. The Food and Agriculture Organization (FAO) reports that since the 1970s worldfood production has increased at a faster rate than the growth of the globalpopulation – a trend that is expected to continue for at least the next 30 years.This projection, however, is based on stable world markets, moderate populationprojections and favourable climatic conditions – assumptions that are far fromguaranteed. For example, while agricultural trade has grown dramatically inrecent decades, figures suggest that between the 1980s and 1990s the share ofless developed countries in world agricultural exports declined, while at the sametime their share in world agricultural imports increased. When combined with thefact that, despite recent technological advances such as improved crop varietiesand irrigation systems, weather and climate are still key factors in agriculturalproductivity, the future of the world’s hungry looks less certain.

3. Seeing climate change as an additional burden that could have far-reaching effects– not just on crop potential and resource degradation but also on patterns of tradeamong nations, economic development and food security – this study examines thepotential effects of climate change on crop yields, agricultural productivity, and thepopulations at risk of hunger in regions vulnerable to food shortages.


4. Building on previous work, this project provides the first estimates of climateinduced yield changes under the new SRES emission scenarios, as quantified byHadCM3. Statistical transfer functions were developed based on currentunderstanding of processes of crop growth and development, obtained fromexperimental field data and validated simulations conducted using site-specificcrop models. The crops modelled were wheat, rice, and maize, which account forapproximately 85% of the world cereal exports. The derived functions are

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appropriate for application in global environmental change studies because theyincorporate responses to higher temperatures, changed hydrological regimes, andhigher levels of atmospheric CO2. These functions were used to estimate theresponses of crop yields, with and without the direct effects of CO2, togreenhouse gas-induced climate change. These biophysical impacts were thenused as perturbed inputs to the Basic Linked System (BLS) world food trademodel to simulate the agro-economic consequences of anthropogenic climatechange – changes in regional productivity, fluctuations in global commodity pricesand the resulting impact on the total number of people considered at risk ofhunger worldwide.

5. Adaptation strategies consistent with the SRES storylines were considered andincorporated in the evaluations made in this study. Farm-level adaptations weretested by the crop models (which result in yield changes), and economicadjustments to the yield changes were tested by the BLS world food trade model(which result in national and regional production changes and price responses).Farm-level adaptations tested in the crop models include: planting date shifts;planting of more climatically-adapted varieties; irrigation; and fertiliserapplication. Economic adjustments represented within the BLS frameworkinclude: increased agricultural investment; reallocation of agricultural resourcesaccording to economic returns (including crop switching); and reclamation ofadditional arable land as a response to higher cereal prices. It is assumed thatthese economic adjustments do not to feed back to the yield levels predicted bythe crop modelling study.

Results

6. Comparing the biophysical impacts witnessed under each of the four SRESscenarios the A1FI scenario, as expected with its large increase in globaltemperatures, exhibits the greatest decrease in yields, especially by the 2080s(Figure 8.4). Decreases are worst in Africa and the former Soviet Union, rangingbetween -30% and -10%. A more modest down turn in potential cereal yieldsis also expected in tropical and equatorial parts of Asia and South America.In contrast, under the coolest climate change scenario (B1) cereal yield decreasesin the future never exceed 10% anywhere in the world (Figure 8.4).

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Figure 8.4: Potential changes in regional cereal yields in the SRES A1FI andB1 worlds by the 2080s, including the direct effect of increasedatmospheric CO2 concentrations.

7. Decreases in cereal yields are estimated to cascade through the agriculturalsystem – decreases in agricultural productivity are witnessed under all the SRESfutures, particularly under the A1FI and A2 worlds where shortfalls in globalcereal production could exceed 400mmt if the potentially beneficial effects ofelevated atmospheric CO2 concentrations fail to be realised (Figure 8.4). Theworst-case scenario – global cereal prices increase in response, as much asdoubling by the 2080s under the A2 scenario resulting in ~600 million additionalpeople being placed at risk of hunger due to climate change. The B1 world incontrast witnesses only a slight increase in the number of people at risk ofhunger, peaking at ~60 million in the 2050s before declining to ~35 million by

B1

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the 2080s as continued economic growth grants more people access to thenecessary funds to acquire food (Figure 8.5). In this illustration the lightlycoloured bars represent the additional number of people at risk of hunger in theabsence of the beneficial direct CO2 effect on crops. The solid bars represent theadjusted change in the number of people at risk of hunger assuming the fullrealisation of the CO2 fertilisation effect on global cultivars.

Figure 8.5: Estimated changes in the number of people at risk of hungerwith respect to 1990 levels.

Conclusions

8. Climate change due to increasing greenhouse gases is likely to affect crop yieldsdifferently from region to region across the globe. Under the HadCM3 climatechange scenarios used in this study, the effects on crop yields in mid- and high-latitude regions appear for the first time to be detrimental adding to theproblems previously witnessed at lower latitudes as the global climate changes.The use of the SRES scenarios has highlighted several non-linearities in the worldfood supply system, both in the biophysical sense, where levels of atmosphericCO2 reach new levels, and the socio-economic sense where changes inpopulation dynamics and economic and political structures complicate thetranslation of biophysical climate change impacts into social indices such as thenumber of people at risk of hunger.

9. While the world, for the most part, may be able to continue to feed itself underall of the SRES scenarios during the rest of this century, the more favourableeffects on yield in temperate regions, which in turn lead to the less impactedworld futures depend to a large extent on full realisation of the potentiallybeneficial direct effects of CO2 on crop growth – a factor that remains open todebate. What is clearly demonstrated is that that regional differences are likely togrow stronger through time, leading to a significant polarisation of effects, withbeneficial effects on yields and production occurring in the developed world andnegative effects in the less developed world (excluding China).

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10. It should be emphasised that the results reported here are not a forecast of thefuture. There are very large uncertainties that preclude this, due to:

i. the uncertainties about climate change at the regional level;

ii. the effects of future technological change on agricultural productivity;

iii. the potential realisation of any benefits from the CO2 “fertilisation” effect;

iv. uncertainties about adaptive capacity in less developed regions; and

v. trends in demand (including population growth), and the wide array ofpossible adaptations.

11. this study should therefore be considered more an exploratory assessment ofthe sensitivity of the world food system, rather than a prediction of its future.See new website at: www.cru.uea.ac.uk/~mattl/food.html


Arnell, N., M. Livermore, S. Kovats, P. Levy, R. Nicholls and M. Parry (2003)“Climate and socio-economic scenarios for climate change impacts assessments:characterising the SRES storylines” Global Environmental Change. (Submitted)

Livermore, M., M. Parry, C. Rosenzweig, A. Iglesias and G Fischer (2003) “Globalfood security and the IPCC SRES: assessing the threat from climate change inseveral equi-plausible worlds,” Global Environmental Change. (In preparation)

Parry M. (2002) “Viewpoint: Scenarios for climate impact and adaptationassessment,” Global Environmental Change, Vol.12 pp.149-153.

Parry, M. and M. Livermore (2002) “Climate Change, Global Food Supply andRisk of Hunger,” Issues in Environmental Science and Technology, No.17,pp.109-137.

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Contract No: EPG1/1/140Title: Global impacts of climate change on natural vegetationContractor: NERC/CEH PI: P.E. Levy

Aims and objectives

1. Our objective was to project the possible impact of changes in climate, CO2 andland use (as prescribed by the Intergovernmental Panel on Climate Change SRESsocio-economic scenarios) on natural vegetation, in terms of both the globaldistribution of vegetation types, and changes in biomass and soil organic matter(and thus carbon fluxes).

2. We used a process-based dynamic global vegetation model (HyLand), whichsimulates the growth and distribution of different vegetation types, incorporatingthe effects of changes in land use. Specifically, we aimed to:

i. quantify the carbon source/sink strength of the terrestrial biosphere;

ii. quantify the contribution of the various factors to the net carbon flux;

iii. predict the future global distribution of vegetation types; and

iv. identify regions under greatest threat from global change.

Results

3. Under all SRES scenarios simulated, the terrestrial biosphere is predicted to be anet sink for carbon over practically all of the 21st century. This sink peaks around2050 and then diminishes rapidly towards the end of the century, as a result ofclimate change. Figure 8.6 shows the global distribution of the change in totalecosystem carbon (plant plus soil) projected by the model for 2100 under all fourSRES scenarios. The spatial pattern is broadly similar in all scenarios, with naturalvegetation losses consistently being seen in Amazonia, the Sahel, south centralUSA and central Australia. These are the regions predicted to be at greatest riskfrom the deleterious effects of the simulated global environmental change.

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Figure 8.6 Predicted change in total carbon (plant + soil, kg C m-2) between1990 and 2100 in the four SRES scenarios.

4. Averaged over the period 1990 to 2100, the net sink (the net biome productivity,NBP) varies between scenarios, from ~2 to 6 Pg C y-1. Figure 8.7 shows thecontribution of climate change, elevated CO2 and land use change on this netsink. In all scenarios, elevated CO2 has the largest influence. This effect is greatestin the A1F and A2 scenarios (which involve the highest fossil fuel emissions andCO2 concentrations). The effect of climate change is considerably smaller, andacts to reduce NBP in all scenarios. This largely results from the decline in theAmazonian forest areas where rainfall declines markedly. The reduction in rainfallin the Amazon basin is not reproduced in all GCMs, so there is considerableuncertainty in this result.

5. The effect of land use change can also be positive or negative, depending onwhether cropland is contracting or expanding in the scenario (ie. whether naturalvegetation is regrowing or being removed). Here, cropland contracts in two outof the three land use scenarios. This may seem to be a rather optimistic view offuture world development, in that global forest area does not decline overall(despite expected continued tropical deforestation) and cropland areas do notgenerally expand (despite continued population growth). There is largeuncertainty in the future trend in cropland area as population increases. Until veryrecently, cropland area has shown a linear increase with population. However, inthe last 50 years, in which the population has doubled, the increase in croplandarea has been very small. How this trend will continue with a possible furtherdoubling of the population over the next century is clearly highly uncertain.

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Figure 8.7: Influence of the three main input factors on the predicted netbiome productivity (NBP) over the period 1990 to 2100 in the four SRESscenarios (A1F, A2C, B1 and B2B), and in two scenarios where land usechange was assumed to change in proportion with population growth inthe A2 and B2 scenarios.

6. In Figure 8.7 grey bars show the predicted value when all factors are included inthe simulation; other bars show the contribution from climate change, elevatedCO2 and land use change to this value. Note that there are interaction effects.

7. In two additional simulations in which land use change was assumed to scalewith population change in the A2 and B2 scenarios, the losses of carbon throughland use change exceeded the carbon gains through enhanced net ecosystemproductivity, resulting in a large net source in the case of A2 (Figure 8.7).

8. Without the beneficial effects of elevated CO2, the effects of climate change aremuch more severe. This is of some serious concern, as the long-term and large-scale effects of elevated CO2 are still open to question.

Conclusions

9. The terrestrial biosphere will be a net sink for carbon over the 21st century, basedon standard SRES scenarios, though sink diminishes rapidly towards 2100.

10. The effect of land use change may be a significant source or sink, depending onthe scenario. It is a major source if land use changes in proportion withpopulation growth.

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11. The largest influence is the CO2 concentration; the effect of climate change isless, and counteracts elevated CO2.


Levy, P.E., Cannell, M.G.R., Friend, A.D. and White, A. (submitted) The influenceof land use change on global-scale fluxes of carbon from terrestrial ecosystems.Climatic Change.

Levy, P.E., Cannell, M.G.R. and Friend, A.D. (submitted) Impact of future changesin climate, CO2 concentration and land use on natural ecosystems and theterrestrial carbon sink. Global Environmental Change-Human and PolicyDimensions.

Arnell, N.W., Livermore, M.T.J., Kovats, R.S., Levy, P.E., Nicholls, R.J., Parry, M.L.and Gaffin, S.R. (submitted) Climate and socio-economic scenarios for global-scale climate change impacts assessments: characterising the SRES storylines.Global Environmental Change-Human and Policy Dimensions.

Levy, P.E. (2003) Effects of changes in climate, land use, and nitrogen depositionon the terrestrial carbon sink: a process-based model analysis. Wengen GlobalChange Workshop.

Levy, P.E. (2003) Effects of changes in CO2, climate, land use, and nitrogendeposition on the terrestrial carbon sink: a process-based model analysis.Geophysical Research Abstracts, 5, 1758.

Levy, P.E., Wendler, R., van Oijen, M., Cannell, M.G.R. and Millard, P. (2003)Assessing the effect of nitrogen enrichment on the terrestrial carbon sink.Geophysical Research Abstracts, 5, 1688.

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Contract No: EPG 1/1/89Title: INDO-UK programme on impacts of climate change in IndiaContractor: Environmental Resources Management Ltd PI: Fiona Mullins

Aims and objectives

1. Under this four-year research programme, Indian scientists are carrying outscientific studies to build a comprehensive picture of the possible future impactsof climate change in India. The project builds on India’s existing expertise to:

i. assess the sectoral impacts of climate change;

ii. reduce the uncertainties in current climate change prediction models; and

iii. make a valuable contribution to international climate science.

2. Research on climate change scenarios and socio-economic scenarios provide basicassumptions on key impact variables such as temperature increase, sea-level rise,precipitation, population and economic growth for the time periods 2020, 2050and 2080. Six further studies will use the climate change and socio-economicscenarios to assess the impacts on:

i. sea level variability (for example a sea level rise of 1 metre could displace7 million people);

ii. water availability and quality (annual river run off may fall by 70% in someareas);

iii. forests (for which biomass production may drop significantly);agriculture (which currently occupies two thirds of the labour force and willbe vulnerable to changing crop yields – particularly wheat and rice – andwater availability);

iv. health (with increased incidence of malaria and other vector-borne diseasesa likely consequence of climate change); and

v. energy, industry and transport infrastructure (particularly vulnerable to sealevel rise in coastal areas).

Background

3. Climatologically, India occupies a very important position in the South-East Asianregion. The physiographic features and the geographic location, which controlthe climate of the country, bestows it with a great wealth of natural resources(e.g. surface and ground water, forestry and vegetation). The prediction andassessment of the impacts of climate change is still an emerging field and is acomplex area of research. A great deal more work is needed to understand thepossible magnitude and potential consequences of the projected climate changeand its impacts on the country.

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Activities

4. The following paragraphs summarise progress during the period April 2002 –March 2003:

Climate change impacts scenarios for India (Dr Rupa Kumar Kolli, IITM Pune)

(a) IITM (Indian Institute of Tropical Meteorology) have carried out preliminaryscenarios of the impacts of climate change on Indian precipitation, temperaturesetc., based on simulations from the Hadley Centres’ regional climate modelHadRM2. The Institute has used this to create scenarios for the three time slices2020s, 2050s and 2080s. IITM have provided preliminary data on these impactsscenarios to the sectoral researchers and are now using the Hadley Centre’sPRECIS model to develop more refined scenarios.

Socio-economic scenarios for India (Ms Ulka Kelkar, TERI Delhi)

(b) Tata Energy Research Institute (TERI) is developing a common set of socio-economicassumptions for the programme, such as demographic parameters, economicgrowth, governance and land use data. TERI has created a framework for the socio-economic scenarios, and a set of storylines. They are developing quantitativeindicators consistent with these scenario storylines. Based on different trends inpopulation growth and economic growth the scenarios correspond to differentpatterns of demographic and economic changes, social and cultural developments,and emerging trends related to energy, technology, and environment. They havedeveloped projections for population and economic demand, food-grains, water,fuelwood and electricity under 4 scenarios for 2020 and 2050. They are continuingto develop these scenarios in consultation with each of the sectoral impacts studies.

Impacts of climate change on water resources (Dr G B Pant, IITM Pune)

(c) To evaluate the precipitation patterns represented by high-resolution regionalclimate models, IITM have analysed the daily rainfall data simulated by the HadleyCentre Regional Climate Model (HadRM2). The control (CTL) simulation, whichrepresents 1990 climate, has been used to assess how representative the model-generated rainfall data are for the three river basins included in the study. For allthree basins, July and August are the months in which they receive maximumrainfall and this feature is well-represented in the model simulations. Thevariability of rainfall for different seasons has been generally overestimated by themodel for all three river basins. However, the model bias in terms of variability isrelatively small in the case of the Ganga river basin. The patterns of extremes inthe Krishna and the Godavari basins are similar to the observed patterns. Theseasonality in the rainfall of the above three basins is remarkably well-reproducedby the model. IITM have completed interim reports on:

i. “Baseline Precipitation Analysis for the Indian Region”;

ii. “Spatio-Temporal Variability of Rainfall over Major River Basins: Past Changesin Water Availability and Quality”; and

iii. “Precipitation Climatology of Selected River Basins and Validation of Climate:Model Simulations of Precipitation”.

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Extreme sea level variability along the coast of India (Dr A S Unnikrishnan,NIO Goa)

(d). A database has been prepared on extreme sea levels and storm surges occurringover the 15 year period 1974-1988 at various tide gauge stations along theIndian coast. The Indian National Institute of Oceanography (NIO) haveestablished links with the Proudman Oceanographic Institute, UK, for softwareand literature support for extreme sea level analysis and the University ofLancaster. The HadRM2 data received from IITM Pune for the mean sea levelpressure and winds at the surface were converted to a format that is compatiblewith NIO modelling software. 20 years of daily data were examined and extremeevents of cyclones were identified in the North Indian Ocean region with acontrol and a doubled greenhouse gas run. NIO has submitted the report“Extreme Sea Level Variability along the Coast of India”.

Impacts of climate change on forest (Dr N H Ravindranath, IISc Bangalore)

(e) The Indian Institute of Science (IISc) has prepared a baseline report on forests inIndia (including a digitised Western Ghat vegetation map and vegetation maps atnational level) and a baseline scenario. The Institute is collaborating with ForestSurvey of India, Wild life Institute, IITM and the University of Edinburgh fordifferent components of work including modelling. Both HYBRID 4.1 and BIOME 3models are being run using Indian data and preliminary outputs for BIOME3 areavailable. Field work, investigating the socio- economic situation in the WesternGhats, is currently underway (locations are being selected, base line data is beingassembled, preliminary analysis is in progress). A report on climate change impactson vegetation at the national level is being prepared. The preliminary outputsindicate a shift from wetter to drier forests (i.e. from evergreen to deciduous)along the Western Ghats, as temperature increases and rainfall decreases.

Impacts of climate change on industries, energy and transport (Dr P R Shukla,IIM Ahmedabad)

(f) The Indian Institute of Management (IIM) completed the identification ofsub-sectors and impacts, and began development of an impact matrix whichinvolved collection of data from secondary sources. Work on the Konkan Railwaycase-study is in progress (data collection from secondary sources completed,primary data collection in progress). IIM’s interim report on unit damage costwas submitted in March 2003.

Impacts of climate change on human health (Dr A P Mitra, NPL Delhi)

(g) The Indian National Physical Laboratory (NPL) produced a literature review andan analysis of studies on malaria, ozone and epidemiology for the Indian sub-continent. The hot-spots for Malaria incidences have been identified for the stateof Gujarat and Orisaa for the period 1995-2000 and digitised maps have beenprepared. The relationship between a set of conducive environmental parametersfor the growth and proliferation of malaria parasites and malaria incidences iscurrently being investigated.

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Impacts of climate change on agriculture (Dr N K Kalra, IARI, Delhi)

(h) The Indian Agricultural Research Institute (IARI) has evaluated the climaticvariability throughout the year over different agro-ecological regions of thecountry, on the basis of historic weather datasets. IARI are refining the cropgrowth model (INFOCROP) to account for water balance, nutrient balance, aninsect-pest component and crop-weather interactions, in order to assess theoverall impact of climate change. Inter-seasonal climatic variability and climatechange has been linked with the dynamic wheat model (WTGROWS) to evaluatethe yield response under various production environments, and to identify suitableagronomic management options (irrigation amounts, nitrogen application anddate of sowing) to sustain productivity in various growing regions of the country.The dependence of the yield of important crops on seasonal temperature has beenestablished from historic datasets. The linkage of soil microbial carbon with theorganic carbon content, soil texture and temperature has been established inorder to derive the nitrogen availability in the soil, for uptake by crops.

Results

5. Preliminary impacts scenarios modelling results available on CD ROM.

Conclusions

6. Expected June 2004 (with the agriculture study possibly concluding inSeptember 2004).

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Contract No: EPG 1/1/150Title: IPCC: Technical Support UnitContractor: Met Office PI: P. van der Linden

Working Group I-TSU

1. The Intergovernmental Panel on Climate Change (IPCC) Working Group I(investigating the scientific basis of climate change) Technical Support Unit (TSU)continued to support Working Group I (WGI) activities until the end of June2002, when responsibilities were transferred to the new WGI TSU in the USA.The work included organisation of a workshop on Changes in Extreme Weatherand Climate Events (11th -13th June, 2002, Beijing, China), which was attendedby 106 delegates from around the world. Apart from Sir John Houghton, the UKCo-chair for WGI, and members of the TSU, three UK scientists attended themeeting with support from Defra, two of whom were from the Met Office’sHadley Centre for Climate Prediction and Research.

Working Group II-TSU

2. In September 2002, the Met Office’s Hadley Centre was successful in its bid tocontinue hosting an IPCC support unit; with the retirement of Sir John Houghtonas Co-Chair and the appointment of Professor Martin Parry as a Working Group II(climate change impacts, adaptation and vulnerability) Co-chair. The HadleyCentre was selected as the host organisation for the TSU of WGII.

3. TSU activities for WG II during 2002/2003 have focussed on the design andstructure of the Fourth Assessment Report (AR4) which is scheduled forcompletion in 2007. Two expert meetings were organised in support of thisprocess, both focussing on the appropriate topics as major cross cutting themesin AR4: one concentrated on the theme ‘Water’; and a second on SustainableDevelopment. Preliminary work for later expert meetings and for the ScopingMeetings for AR4 was also undertaken.

4. The first of the expert meetings, on the theme of ‘Water’ was held at the officesof The World Meteorological Organization in Geneva on the 11th to 13thNovember 2002. It was organised by the WGII TSU but experts andrepresentatives from all three working groups were invited. Thirty-nine peopleattended, comprising 16 experts, 15 stakeholders from the water managers andusers community, (of whom three were UK experts) and 8 IPCC representatives.The meeting recommended that the topic be given special treatment in the AR4and be subsequently followed by an IPCC Technical Paper.

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Members of the IPCC WGII Bureau attended the meeting and are shown in theaccompanying figure. Left to Right: Dr. Edmundo de Alba Alcaraz (Vice-chair,Mexico), Prof. Jean-Pascal van Ypersele (Vice-chair, Belgium), Dr. John Zillman(Vice-chair, Australia), Dr. Renate Christ (Deputy Secretary IPCC), Dr. John Stone(Vice-chair, Canada), Prof. Martin Parry (Co-chair, UK), Dr. Abdelkader Allali(Vice-chair, Morocco), Dr. Osvaldo Canziani (Co-chair, Argentina) and Dr. LuckaKajfez-Bogataj (Vice-chair, Slovenia)

5. An Expert Meeting on Climate Change and Sustainable Development, held jointlyby Working Groups II and III, took place on the 5-7 March in Colombo, Sri Lanka,the management of which was led by WGII. Nineteen experts, stakeholders andrepresentatives of the IPCC, including the two Working Groups, attended. Localarrangements were made by Dr. Mohan Munasinghe, IPCC Vice Chair withoverall responsibility within the AR4 for cross cutting themes, of whichsustainable development is one.

Experts provided input into the scope of Climate Change and its links in eitherdirection with Sustainable Development that might be included within the AR4.Additionally they indicated ways in which the issues could be structured withinthe Assessment. A meeting report is available that will also be provided todelegates to the forthcoming author meetings in order that they may take theExpert Meeting outcomes into consideration.

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Contract No: EPG 1/1/127Title: The impacts of climate change on Chinese agricultureContractor: AEA Technology PLC PI: P. Harris

Aim

1. To manage and deliver on behalf of Defra, a collaborative research projectbetween China and the UK to undertake a detailed assessment of the potentialimpacts of climate change on agriculture in China.

Objectives

2. To build capacity in climate change research in China by facilitating the exchangeof expertise between UK and Chinese centres.

3. To provide climate change scenarios for China for the 2020s, 2050s and 2080s.

4. To provide socio-economic scenarios for China relevant to agriculture, for the2020s and 2050s.

5. To provide an overview of the overall effect of climate change of agriculture inChina, including economic costs of damages and/or adaptation.

6. To disseminate results of the project through annual workshops, a web site andscientific papers.

Introduction

7. Considerable work on the impacts of climate change on agriculture has beenundertaken in China. This includes forecasting any changes in crop productionpotential in 2030 and 2056, and the resulting economic implications for foodstocks (wheat and maize throughout the country, rice in some areas). An initialassessment, using a range of global-scale climate change scenarios, indicated apossible change in crop yield from -21% to +54%. However, because of theclimate change models’ relatively low geographic resolution, uncertainties in cropmodel parameters, and unclear socio-economic scenarios, an improvedassessment is needed.

Activities and methodology

8. Work programme

i. Development of national climate change scenarios for the 2020s, 2050s and2080s, using the output of the regional climate model and drawing onexpertise from the Hadley Centre.

ii. Development of agriculture-relevant national socio-economic scenarios forthe 2020s and 2050s.

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iii. Development of a land-use change scheme for China involving theapplication of remote sensing data;

iv. Assessment of the impacts of climate change on arable agriculture (wheat,rice, cotton, maize) in China;

v. Identification of regions requiring more detailed case studies, which could bedeveloped in a follow-up phase 2 of the work; and

vi. Communication of results, (in appropriate language) via a publicly-accessibleinternet site, workshops, scientific papers and reports for a non-technicalaudience.

9. The programme will also provide for 3 1-week study tours to the UK by staff atthe Institute of Agrometeorology and for training visits (2-6 months in duration)to relevant UK Institutions in the areas of:

i. Crop modelling;

ii. GIS/remote sensing;

iii. Integrated approaches; and

iv. Soil impact modelling.

10. The aims of these training visits is for the Chinese scientists are to:

i. understand and learn to use current models developed in western countries(UK and elsewhere);

ii. understand the parameters needed to adapt models to Chinese conditions;

iii. adapt the models to Chinese conditions (both during the training visits andwherever possible, in-between the two training periods, in China); and

iv. use the models to deliver the research objectives outlined above.

Results

Study visits

11. From April to June 2002, Dr. Li Yue visited Cranfield University to develop aproposal for a comprehensive framework for an integrated impact assessmentmodel for Chinese agriculture.

12. From April to August 2002, Mr. Wei Xiong also visited Cranfield University fortraining in Crop Modelling, Integrated Approaches and GIS/Remote Sensing.

13. Dr. Xu Yinlong completed a year-long training visit to the Hadley Centrewhere he had been studying and adapting the PRECIS regional climate changescenario model.

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Workshops

14. A project workshop was held in Beijing on 11th and 12th September 2002.This was attended by the Foreign Office Minister, Dennis McShane and reportedon Chinese television.

15. In order to disseminate information about the project more widely, a specialsession dedicated to the project was held as part of the International Symposiumon Climate Change held in Beijing in April 2003.

Study tour

16. In November 2002 a delegation of five Chinese experts in climate change visiteda range of organisations and research centres in the UK to discuss climate andenvironmental change and the impact of these on forestry and agriculture.

Conclusions

17. Considerable climate modelling work has been undertaken using the HadleyCentre PRECIS regional model, including a successful run to produce a predictionof climate change in China for the 2070s. Progress was also made onconstructing a crop model suitable for use in China. Modelling of the impactson rice, wheat and maize is nearly complete, whereas progress on modelling theeffects on cotton has taken more time. Work has also been carried out onadapting the ROTH-C model for predicting future soil change trends in China.

18. Socio-economic scenarios were developed and refined over the year(e.g. considering the economic impact of China joining the World TradeOrganisation).

Publications/papers

19. Dr. Li Yue and Professor Ian Holman prepared a paper arising from the workcarried out during her study visit to Cranfield University. This was the basis forher presentation in Beijing and is now on the web site with other contributionsto the workshop: www.ami.ac.cn/Sino UK/workshop.htm

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Chapter 9

Climate change – responsestrategies

Contract No: EPG: 1/1/152Title: CO2 and energy use in UK buildingsContractor: Building Research Establishment PI: Christine Pout

Aims and objectives

1. The Building Research Establishment (BRE) provides estimates for the UK domesticand non-domestic building stock of energy consumption and CO2 emissionssavings potentials and policy effectiveness disaggregated by sector, fuel type andend use.

Results: domestic sector

2. Domestic sector work between April 2002 and March 2003 has consisted of twomain activities

i. A paper has been prepared summarising the key conclusions of theextensive report that was published in December 20011, and focusing onthe prospects for achieving the Climate Change Programme savings for thedomestic sector. This paper2 was presented at the 3rd European Conferenceon Energy Performance and Indoor Climate in Buildings in October 2002;and

ii. Analysis has been undertaken and a paper prepared on the decompositionof the changes in domestic sector carbon emissions from 1970 to 2001.This paper3, which will be presented at the ECEEE (European Council foran Energy Efficient Economy) Summer Study in June, identifies the effectof seven key factors that have influenced carbon emission changes (seeFigure 9.1). The paper highlights the significance of energy efficiencyimprovements, without which carbon emissions would have risen ratherthan fallen, and also demonstrates how the importance of the individualfactors changed from one decade to the next.

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Chapter 9: Climate Change Response Strategies

1 Carbon emission reductions from energy efficiency improvements to the UK housing stock. L D Shorrock,J Henderson, J I Utley and G A Walters. BRE Report BR435. December 2001.

2 UK Climate Change Programme and domestic sector end-use efficiency. L D Shorrock and J I Utley. Published inthe proceedings of the 3rd European Conference on Energy Performance and Indoor Climate in Buildings.October 2002.

3 A detailed analysis of the historical role of energy efficiency in reducing carbon emissions from the UK housingstock. L D Shorrock. To be published in the proceedings of the ECEEE Summer Study. June 2003.

Figure 9.1: Domestic sector carbon emission changes and the factorscontributing to these from 1970 to 2001.

The effect of factors tending to increase domestic sector carbon emissions relative to 1970

0

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The effect of factors tending to decrease domestic sector carbon emissions relative to 1970

External temperature

1970 1975 1980 1990 1995 2000

Year

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Level of service

Household growth

Insulation improvement

Heating efficiencyimprovement

Electricity supplyindustry changes

Other carbonfactor changesExternal temperature

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Overall change in domestic sector carbon emissions relative to 1970

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Climate change – response strategies

Results: non-domestic sector

3. Between April 2002 and March 2003 BRE has continued to develop the Non-Domestic Energy and Emissions Model (N-DEEM) and to build upon the modeland analyses described in a detailed report which was published in March 20024.

4. Figure 9.2 shows energy consumption and carbon emissions by building activitytype and indicates that the two sectors contributing most to UK carbon emissionsare retail and hotels and catering.

Figure 9.2: UK commercial and public sector energy consumption (top)and related carbon emissions (bottom) by sub-sector for 2000.

CommercialOffices11%

Warehouses9%

Retail24%

Sport andLeisure

4%

Communicationand Transport

2%

Education11%

Other13%

Hotel andCatering

16%

Health4%

Government6%

CommercialOffices11%

Warehouses9%

Retail19%

Sport andLeisure

4%

Communicationand Transport

1%

Education13%

Other15%

Hotel andCatering

17%

Health5%

Government6%

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4 Carbon dioxide emissions from non-domestic buildings: 2000 and beyond. C H Pout, F MacKenzie and R Bettle.

5. Assessment of the economic and technical potential for reducing carbonemissions by implementing energy efficiency options or measures has also beenmade. Figure 9.3 shows the cost abatement curve for the UK service sector at a6% discount rate. Whilst the cost abatement curve plots the results for eachindividual measure, Table 9.1 gives a breakdown of the potential savings from asimultaneous application of the measures which takes into account any overlapsand interactions between measures. This shows the cost effective potentialdecreasing as the discount rate increases and that lighting and heating show thegreatest potential for cost effective carbon reductions.

Figure 9.3: Cost abatement curve for individual measures for thecommercial and public sector in 2000 at a 6% discount rate (N.B. this doesnot consider interactions and overlaps).

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Table 9.1: Maximum potential savings achievable from the simultaneousapplication of all energy efficiency measures in 2000 (this accounts foroverlaps and interactions).

Discount rate End-use Cost effective Technical % Savings potential (MtC) potential (MtC) cost effective

6% Computing 0.44 0.45 98%

Lighting 2.08 2.37 88%

Refrigeration 0.15 0.16 94%

Other 0.21 0.35 61%

Heating 1.49 3.88 39%

Cooling 0.23 0.23 100%

Total 4.60 7.43 61%

15% Computing 0.43 0.45 97%

Lighting 1.87 2.37 79%


Other 0.19 0.35 55%

Heating 1.28 3.88 33%

Cooling 0.23 0.23 100%

Total 4.14 7.43 54%

25% Computing 0.42 0.45 94%

Lighting 1.74 2.37 73%


Other 0.19 0.35 55%

Heating 1.26 3.88 33%

Cooling 0.23 0.23 100%

Total 3.97 7.43 52%

6. Three scenarios of potential future carbon emissions disaggregated by sector,end-use and fuel type have also been developed. These are a reference scenario,an efficiency scenario and a policy scenario, which reflect continuation of currenttrends, uptake of all cost effective measures, and the effect of planned climatechange policy actions, respectively. Figure 9.4 shows the results of each scenarioand Figure 9.5 shows the results of the policy scenario disaggregated by buildingactivity type.

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Figure 9.4: Commercial and public sector carbon emissions projections forall scenarios modelled.

Figure 9.5: UK commercial and public sector carbon emissions bysub-sector for the policy scenario.

Conclusions

7. There was a 23% fall in emissions of carbon from domestic sector buildingsduring the period 1970-2001, mainly due to improvements in energy efficiency.In the non-domestic sector, lighting and heating show the greatest potential forcost effective carbon reductions. Work in both the domestic and non-domesticsectors will continue during 2003/04.

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Contract No: EPG 1/1/125Title: Industrial sector carbon dioxide emissionsContractor: Entec UK Ltd and Cambridge Econometrics PI: Nick Hedges

Aims and objectives

1. The aim of this work is to enable the UK to meet the following requirements:

i. Fulfil the reporting requirements of the United Nations FrameworkConvention on Climate Change (UNFCCC);

ii. Report progress on policies under the European Union MonitoringMechanism;

iii. Continue to develop its own policy response through monitoring andevaluation of the UK Climate Change Programme;

iv. Show ‘demonstrable progress’ in meeting its commitments as required byArticle 3.2 of the Kyoto Protocol; and

v. Assess the scope for further emissions reduction.

2. To meet this aim, the project has the following objectives:

i. Represent, within the GAD model (ENUSIM), Negotiated Agreements, theClimate Change Levy and domestic emissions trading and any other relevantpolicies;

ii. Review the reporting requirements of the UNFCCC and the EU MonitoringMechanism and ensure that the GAD model can quantify policies in terms ofemissions savings by policy at the time horizons required;

iii. Enable the UK to demonstrate progress in meeting commitments byquantifying the effects of policies using ex-post data so far as possible;

iv. Develop the model to include output as well as fuel price sensitivities;

v. Produce projections at sixteen subsector levels by five year horizons to 2020;and

vi. Assess progress by other EU Member States, the US and Japan in abatingindustrial sector emissions.

Progress in the year to April 2003

3. Key activities over the year have been:

i. A detailed review of device technologies for key energy-using sectors of ironand steel, chemicals, paper, cement, resulting in significant revisions to theinput data for the ENUSIM model;

ii. Completion of the extension of the ENUSIM model to cover energy use anddevice technologies for the energy, construction and water sectors;

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iii. Running the ENUSIM model in parallel with Cambridge Econometrics’Multisectoral Dynamic Model (MDM) model to establish the impact ofcurrent policies over each 5 year period to 2020 and incorporate outputsensitivities. Cost curves were developed in ENUSIM to demonstrate thecosts of achieving different levels of carbon dioxide reduction from industrialenergy use in terms of £/tonne of carbon for 2010 and 2020;

iv. Modelling of the impact of Combined Heat and Power (CHP) within thevarious policy measures. This modelling had to be performed outside theENUSIM model, because of limitations in the way ENUSIM models boilerplant;

v. A review of policies relating to industrial carbon dioxide emissions fromother countries including France, Germany, Japan, the Netherlands, Swedenand the USA. Policies examined included Fiscal incentives, Informationprogrammes, Regulation and Voluntary Agreements. Policies were comparedand contrasted across the countries. The UK has a comprehensive range ofpolicies, including the first Emissions Trading Scheme, although a fewadditional opportunities relating to financial incentives were identified; and

vi. Preparation and review of the final report.

4. Key findings are:

(i) The effect of the policies and measures modelled is a reduction of 4.5 milliontonnes of carbon (MtC) in 2010 from a baseline without policies. Keyelements to achieving this reduction are the successful delivery of NegotiatedAgreements and the development of CHP in line with existing Governmentpolicy (including climate change levy exemptions and limited emissionstrading). The cost curves indicate that under certain conditions, and with apermit price of £18.33/tonne of carbon, more extensive emissions tradingcould extend this reduction to 5.8 MtC;

(ii) For reference, the estimated impacts of reducing business emissions ofcarbon dioxide in the 3rd National Communication and Climate ChangeProgramme are 5.8 MtC and 7.0 MtC respectively. These estimates are notdirectly comparable with this study, because of differences in sector coverage,assumptions and modelling methods;

(iii) The ENUSIM model continues to offer a valuable breakdown of cost effectivetechnologies in each sector, including net costs to achieve given levels ofcarbon reduction, although validation of the model through ex-postassessment is recommended to give more confidence in the projections; and

(iv) The current structure of the ENUSIM model is too limited to adequatelyproject the uptake of CHP or the interaction of different sectors with eachother and with the rest of the economy. The MDM model helps to overcomethese limitations.

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Contract No: EPG 1/1/106Title: UK emissions by sources and removals by sinks due to land use,land use change and forestry activitiesContractor: Centre for Ecology and Hydrology (CEH) PI: Dr. R. Milne

Aims and objectives

1. This contract provides Defra with annual estimates of the exchanges of carbonbetween the atmosphere and major natural sources and sinks in the UK.Uncertainties in the estimates are reduced by associated experimental andmodelling studies of the relevant ecosystems

Background

2. All nations that are signatories to the UN Framework Convention of ClimateChange have to submit annual inventories of emissions and removals ofgreenhouse gases. In addition the Kyoto Protocol will, when it comes into force,require reporting of emissions reductions and offsets from carbon sink activities.This contract provides data and advice on land use, land use change and forestryactivities relevant to these requirements.

3. In order to meet the reporting requirements of the UNFCCC and of the EUMonitoring Mechanism submitted data must be based on sound science. Work istherefore carried out within this contract to enhance scientific understanding ofthe cycles of greenhouse gases in appropriate ecosystems.

Activities

4. Work undertaken during the period include:

i. Preparation of UK data for Sector 5 – Land use change and forestry (LUCF)of 2001 UNFCCC Greenhouse Gas Inventory;

ii. Preparation of LUCF data for 2001 Inventory of greenhouse gas emissionsand removals for UK Devolved Administration areas;

iii. Preparation of projections to 2020 of emissions and removals of carbondioxide by LUCF in UK;

iv. Development of improved version of RothC soil carbon turnover model (withUniversity of Aberdeen);

v. Comparison of C-Flow carbon accounting model for forests with alternativeapproaches (with Forest Research);

vi. Modelling the impact of climate change and nitrogen deposition on carbonsequestration of UK plantation forests;

vii. Field measurements of emissions of carbon dioxide from ploughed grasslandon organic soil;

viii. Estimation of deforestation rates for Great Britain;

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ix. Estimation of loss of carbon from afforested peatlands;

x. Assessment of usefulness of remote sensing and field survey methods forKyoto Protocol monitoring and verification of UK forest carbon stocks (withForest Research); and

xi. Contributions to IPCC activity to prepare Good Practice Guidance on LandUse, Land Use Change and Forestry.

Selected Results

5. (a) UK emissions and removals of carbon dioxide by LUCF

i. Removal of atmospheric CO2 to Woody Biomass Stocks caused by expandingUK forests in 2001 was estimated to be 6846 Gg with an additional sink of1298 Gg to forest products. In 1990 5731 Gg were removed to WoodyBiomass stocks and 1573 Gg to forest products;

ii. For 2001 the net Emission of CO2 from soils due to land use change wasestimated to be 11640 Gg compared to 14186 Gg in 1990; and

iii. The Land Use Change and Forestry Sector of the UK is estimated in 2001 tohave been an overall emitter of carbon dioxide of 3219 Gg due to Emissionsof 14835 Gg offset by 11616 Gg of Removals.

(b) Deforestation

i. Independent estimates of the total GB forest deforestation rate have nowbeen obtained from several sources but with significant variation, rangingfrom 500 to 18000 ha y-1. Specifically information has been obtained onUnconditional Felling licenses for GB from the Forestry Commission and onland use change in England from The Ordnance Survey;

ii. Over the last decade the average rate of deforestation in GB resulting inrural land uses is estimated to have been 449 ha y-1 based on FellingLicences and for non-rural uses 926 ha-1 from OS data; and

iii. In the absence of better information, our best estimate of the GBdeforestation rate is the sum of these i.e. 1375 ha y-1.

(c) Effect of climate change on forest growth

i. The Edinburgh Forest model has been used to investigate variation in pastand present growth of Sitka spruce and beech at different locations in GreatBritain;

ii. Changes in the three primary driving forces for forest growth, namely Ndeposition rates, atmospheric CO2 concentration and climate change havehad, and will continue to have, a significant impact on Net PrimaryProductivity (NPP) in the UK;

iii. The influence of atmospheric CO2 concentrations on future NPP values willbe greater than that of nitrogen deposition;

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iv. For Sitka spruce the increase in NPP across six locations will be similar(averaging around 12.5 %) although the relative importance of eachenvironmental driving variable differs; and

v. The response of Beech varied according to location, with the largestresponse estimated to be at Cardigan Bay (16 %). At the two most southerlylocations growth response will be smaller due to changes in climate,particularly precipitation, patterns.

(d) Afforestation of peatlands

i. Analyses were completed of carbon dioxide flux measurements from achronosequence of young Sitka spruce plantations (from undisturbed moorto 26 year-old forest). These showed that undisturbed peat accumulatedabout 0.25 tC ha-1 y-1. Newly drained peatland (2-4 years after ploughing)emitted between 2 and 4 tC ha-1 y-1, but when ground vegetationrecolonised, the peatland became a sink again, absorbing about 3 tC ha-1 y-1

4-8 years after tree planting. Thereafter, the trees dominated the budget andafforested peatlands absorbed up to 5 tC ha-1 y-1. Assuming that the treesaccumulated carbon at rates commensurate with Yield Class 10 m3 ha-1 y-1,the peat beneath the trees after canopy closure was estimated to bedecomposing at less than 1 tC ha-1 y-1 or less. This is slower than previouslybelieved. The pattern of the emissions and removals is shown in Figure 9.6;and

ii. A first estimate of the effect of these new results on annual removal ofatmospheric carbon dioxide to UK forests was made (Table 9.2).

Figure 9.6: Pattern of losses and gains from deep peat after afforestation.

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Table 9.2: Effect of incorporation of new data on losses from afforesteddeep peats into estimates of emissions and removals of atmosphericcarbon for UK forests.

Gg CO2 2001 Inventory method With new peat model

1990 Removals1 -9456 -14261

1990 Emissions2 1467 133

1995 Removals1 -10431 -15150

1995 Emissions2 1467 3

2001 Removals1 -10515 -15245

2001 Emissions2 1467 111

1. Removals (-ve) from atmosphere due to build up of carbon in new trees, litter and soil organic matter

2. Emissions (+ve) from deep peat soil pre-existing forest establishment

(e) Field measurements of carbon loss due to ploughing:

i. Measurements began over unploughed field in March 2002 at PoldeanFarm;

ii. Field ploughed on 5 June 2002;

iii. Flux measurements for the site for period after ploughing are discussed andthe pattern of cumulative carbon loss until January 2003 is presented; and

iv. The cumulative loss was 0.3 kgC m-2 (3 tC ha-1), equivalent to about 2% ofthe pre-ploughing stock of carbon in the top 15cm of soil.


Website maintained at http://www.edinburgh.ceh.ac.uk/ukcarbon(with contract reports)

Salway, A.G., Murrells, T.P., Milne, R and Ellis, S. (2002). UK Greenhouse GasInventory, 1990 to 2000 Annual Report for submission under FrameworkConvention on Climate Change. National Environmental Technology Centre,AEA Technology Centre AEAT/R/ENV/1000 Issue 1. ISBN 0-7058-1805 -5.

Salway, A.G., Murrells, Milne, R. and Hidri, S. (2003). Greenhouse Gas Inventoriesfor England, Scotland, Wales and Northern Ireland: 1990 – 2000. NationalEnvironmental Technology Centre, AEA technology Centre.

Patenaude, G.L., Hill, R.A. Milne, R., Rowland, C.S., and Dawson, T.P. (2002)Forest carbon accounting using Airborne Laser Scanning remote sensing andmodelling approaches. Presented at ForestSat 2002 Symposium (OperationalTools in Forestry using Remote Sensing Techniques), Edinburgh August 2002.

R. Milne and M. G.R. Cannell (2003) Estimating forest and other terrestrialcarbon fluxes at a national scale: The UK experience. In: The Carbon Balance ofForest Biomes. SEB Conference, April 2003, Southampton.

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Hargreaves, K.J., Milne, R. and Cannell, M.G.R. (2003). Carbon balance ofafforested peatland in Scotland. Forestry. (In press)

Patenaude, G.L., Briggs, B.D.J., Milne, R., Rowland, C.S., Dawson, T.P. and Pryor,S.N. (2003) The carbon pool in a British semi-natural woodland. Forestry (In press).

Baggott, S.L., Davidson, I., Dore, C., Goodwin, J., Milne, R., Murrells, T.P., Rose,M., Watterson, J.D., Underwood, B. (2003). UK Greenhouse Gas Inventory, 1990to 2001 Annual Report for submission under Framework Convention on ClimateChange. National Environmental Technology Centre, AEA Technology CentreAEAT/ENV/R/1396.

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Contract No: EPG 1/1/120Title: UK greenhouse gas inventory and regional inventories for England,Northern Ireland, Scotland and WalesContractor: Netcen (AEAT) PI: John Watterson

Aims and objectives

1. To produce annual greenhouse gas inventories to fulfil the UK’s internationalreporting requirements, and for the devolved administrations.

Introduction

2. To fulfil UNFCCC1 requirements and to underpin the development of a nationalprogramme, the UK is required to develop, publish and regularly update nationalinventories of all greenhouse gases not controlled by the Montreal Protocol, usingcomparable methodologies. The UK is also required to submit an annualgreenhouse gas inventory to the EU Monitoring Mechanism, which separatelyreports an inventory for the European Community as a whole to the UNFCCC.UK inventory estimates are reviewed annually and updated to reflectimprovements in methodology or availability of new information.

3. The annual UK inventory is compiled by the National Environmental TechnologyCentre (Netcen) on behalf of Defra. Inventory estimates cover the six directgreenhouse gases (namely carbon dioxide, methane, nitrous oxide,hydrofluorocarbons, perfluorocarbons and sulphur hexafluoride), and the latestavailable published data are for the period 1990-2001. The regional inventory isbased on the UK inventory, and provides separate emission estimates for England,Scotland, Wales and Northern Ireland.


4. UK Inventory estimates for the six gases are calculated using a top-downapproach, using activity data and emissions factors, and adhering to IPCC2 GoodPractice Guidance. Removals by sinks are calculated by the Centre for Ecologyand Hydrology (CEH) and are published separately, within the inventory.

5. A regional inventory of greenhouse gases has also been produced, whichpresents estimates of greenhouse gas emission inventories for the devolvedadministrations of the UK. Separate greenhouse gas emission inventories wereestimated for England, Scotland, Wales and Northern Ireland for the years 1990,1995, 1998, 1999 and 2000. The estimates are consistent with the UnitedNations Framework Convention on Climate Change (FCCC) reporting guidelinesand the 2000 UK Greenhouse Gas Inventory (Salway et al, 2002). Someemissions, mainly mobile and offshore sources, are not allocated to any region,so an unallocated category is used to report these.

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1 United Nations Framework Convention on Climate Change2 Intergovernmental Panel on Climate Change

Results

6. A summary of the latest UK inventory estimates, by gas, is given in Table 9.3.Emissions (not including CO2 removals) of the basket of six greenhouse gases,weighted by global warming potential, fell by 12.3% between the 1990 baseyear and 2001. Over the same period there was a 5.3% fall in emissions of CO2.

Table 9.3: Estimated total UK emissions of the ‘basket’ of six greenhousegases on an IPCC basis(i) weighted by Global Warming potential: 1990and 2001 Expressed in million tonnes carbon equivalent (MtC).

Gas 1990 base year(ii) 2001 % change from 1990base year(ii)(iii)

Carbon dioxide 164.8 156.1 -5.3

Methane 21.0 12.6 -40

Nitrous oxide 18.5 11.6 -38

Hydrofluorocarbons 4.1 2.4 -43

Perfluorocarbons 0.3 0.2 -36

Sulphur hexafluoride 0.3 0.5 +56

Total 209.1 183.3 -12.3

7. It should be noted that:

i. Emission inventories based on the methodology developed by theIntergovernmental Panel on Climate Change (IPCC) are used to report UKemissions to the Climate Change Convention;

ii. 1995 is used as the base year for emissions of fluorinated compounds –HFCs, PFCs and SF6, in accordance with Article 3.8 of the Kyoto Protocol;and

iii. The percentage changes presented in this table are calculated from inventoryemission estimates held at full precision. The emission estimates quoted inthe table are values rounded from emission estimates held at full precision.The percentages quoted in this table may therefore differ slightly frompercentages that could be calculated from the emission estimates presentedin the table.

8. All UNFCCC and EU inventory reporting requirements were met during 2000-2003. In addition, the inventories for 1990-2001 have been updated andreported to Convention in the Common Reporting Format (CRF).

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Figure 9.7: UK Greenhouse gas emissions, 1990 base year(i) to 2001, MtC(million tonnes of carbon equivalent).

Conclusions

9. Emissions (not including CO2 removals) of the basket of six greenhouse gases,weighted by global warming potential, fell by 12.3% between the 1990 baseyear and 2001. Over the same period there was a 5.3% fall in emissions of CO2.

10. All UNFCCC and EU inventory reporting requirements were met during 2000-2003. In addition, the inventories for 1990-2001 have been updated andreported to Convention in the Common Reporting Format (CRF).


UK Greenhouse Gas Inventory 1990 to 2001: Annual Report for submissionunder the Framework Convention on Climate Change. Baggott, SL, Davidson, I,Dore, C, Goodwin, J, Milne, R, Murrells, TP, Rose, M, Watterson, JD, Underwood,B. AEAT/ENV/R/1396/Issue 1.

Greenhouse Gas Inventories, for England, Scotland, Wales and Northern Ireland:1990 – 2000. AG Salway, TP Murrells, R Milne, S Hidri. AEAT/R/ENV/1182 Issue 2.

Presentation for a Workshop on Energy Balances and Energy related GreenhouseGas Emission Inventories, 24 to 25 June 2003, EEA, Copenhagen. Presentationproduced for Working Group I of the EU Greenhouse Gas Monitoring MechanismCommittee. Presentation compiled by Sarah Baggott, John Watterson and JustinGoodwin (netcen), with additional contributions from Chris Bryant (UK DTI) andSusan Donaldson (UK Defra).

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Internet

The National Inventory Report for 2003 (UK Greenhouse Gas Inventory 1990to 2001) and associated data tables can be found atwww.naei.org.uk/report_link.php?report_id=191

The regional inventory report and associated data tables can be found atwww.naei.org.uk/report_link.php?report_id=206

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Contract No: EPG 1/1/128Title: Emissions and projections of fluorinated gases for the UKContractor: AEA Technology Environment PI: Heather Haydock

Aims and objectives

1. The main objective of this project was to estimate annual UK and constituentcountry emissions of HFCs, PFCs and SF6 for the period 1990 to 2025, therebyupdating previous emissions inventory estimates and projections prepared byMarch (now EnvirosMarch) in 1999. The project also assesses additional optionsfor reducing future emissions of HFCs, PFCs and SF6, quantifies the effects onfuture emissions of any additional measures and assesses the cost implications ofadditional emission reduction options. In addition, the project provides emissionestimates and projections for nitrogen trifluoride (NF3), which is a greenhousegas that is not included in the Kyoto basket. This project involved extensivestakeholder interaction, with over 90 experts contributing through personalcommunication and participation at stakeholder workshops in September 2002and March 2003. The final report was published in September 2003.

Results

2. In 2000, HFCs contributed 81% of the total GWP-weighted emissions of HFC,PFC and SF6 while PFCs contributed 4% and SF6 contributed 15%. The totalemissions of HFC, PFC and SF6 of 12,223 kt CO2 eq. in 2000 represent about 2%of total UK greenhouse gas emissions in that year.

3. Figure 9.8 below summarises projected trends in UK emissions by sector, showingthe GWP-weighted aggregated HFC, PFC and SF6 emissions. Emissions arise froma wide range of manufacturing sectors and end-use applications. The mainsources in descending order of UK emissions in 2000 are stationary refrigerationand air conditioning (HFCs, PFCs), halocarbon manufacture (HFCs, PFCs), aerosols(HFCs), magnesium production (SF6), metered dose inhalers (HFCs), mobile airconditioning (HFCs), electrical transmission and distribution equipment (SF6),aluminium production (PFCs), the electronics industry (HFCs, SF6, NF3), foamblowing (HFCs) and fire fighting equipment (HFCs).

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Figure 9.8: HFC, PFC and SF6 emissions for the UK by sector (ktonnes CO2 equiv).

4. Figure 9.9 shows the breakdown of emissions by sector in 1995 and 2000 asestimated by this study compared with estimates produced by an earlier studyby Enviros March (formerly March Consulting) in 1999. The main reasons fordifferences in emissions estimates between the two studies are summarisedin Table 9.4 below.

Figure 9.9: Comparison of emissions estimates for 1995 and 2000.

Emis

sion

s (k

t C

O2

eq.)

One Component Foams

Solvents

Other

Fire fighting

Foams

Electronics

Aluminium production

Electrical T&D

Mobile air con

Metered Dose Inhalers

Magnesium production

Aerosols

Fluid manufacture

Stationary refrigeration0

2000

4000

6000

8000

10000

12000

14000

16000

18000

20000

1995 March 1995 AEAT 2000 March 2000 AEAT

Emis

sion

s (k

t C

O2

eq.)

One Component Foams

Solvents

Other

Fire fighting

Foams

Electronics

Aluminium production

Electrical T&D

Mobile air con

Metered Dose Inhalers

Magnesium production

Aerosols

Fluid manufacture

Stationary refrigeration0

2000

4000

6000

8000

10000

12000

14000

16000

18000

20000

1990 1995 2000 2005 2010 2015 2020 2025

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Table 9.4: Comparison of emissions estimates for 1995 and 2000: Mainreasons for the changes.

Sector % change compared Main reasons for with March (1999) change

1995 2000

Stationary 32 39 Revised activity and equipment life-time data forrefrigeration certain sub-sectors; changes to calculation

methodology; changes to emissions factors.

Mobile air 36 63 Faster penetration of MAC in vehicle fleet assumed conditioning than previously; changes to emission factors.

Foam blowing 0 -49 Revised activity data as a result of furtherdevelopments in alternative technologies and greateruse of HFC blends.

Electrical T&D 298 11 Revised manufacturing and in-use emissions factors dueto new information from industry.

Aerosols 0 6 Revised activity data supplied by trade association;changes to import / export assumptions.

Metered dose 0 175 Revised estimates of bank size based on data from inhalers individual manufacturers, consistent with EU estimates.

Aluminium -23 26 Emissions data from industry revised, with actual 2000 production estimate provided.

Magnesium -20 92 Emissions data from industry revised, with actual 2000 production estimate provided.and casting

Fire fighting -14 187 Revised bank size; changes to emission factors.

Electronics -88 -56 Revised fluid consumption data provided by industry.

Halocarbon 1 -36 Changes in emission factors due to new pollution manufacture abatement equipment installed at one plant; updated

information from industry.

Other end-use -94 -84 Sector activity data revised, including new data from applications Nike on sports shoes.

5. Many of these sectors have already introduced measures to reduce emissions orare planning to do so. Measures include voluntary agreements between industryand Government, industry-led leak reduction programmes, installation ofabatement equipment for process emissions and the introduction of alternativefluids. Of particular significance is a proposed UK scheme for the mandatoryregistration of refrigerant fluid handlers that is expected to reduce annualemissions of HFCs from this sector by about 20% in 2010 and more insubsequent years.

6. A cost-effectiveness analysis of illustrative measures for emissions reductionsuggests that reductions of about 530 kt CO2 eq. in 2010 may be achieved at acost of less than £100/tonne carbon equivalent. Many abatement options achievesome or all of their impacts in the disposal phase. This means the effect is notseen for up to 50 years from manufacture for some building foams. Because ofthis, cumulative costs and emissions savings to 2025 provide a more realisticmeasure of cost-effectiveness. The cost-effectiveness estimates of each measure

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on this cumulative basis are summarised in Table 9.5 below. This assessment issubject to significant uncertainties and further detailed analysis would be requiredbefore attempting to implement any of the measures.

Table 9.5: Cost-effectiveness of illustrative measures based on cumulativeemission savings to 2025.

Measure Emissions Cost of Cost-saving measure effectiveness

(kt C equiv) (£k2000 (£/tC eq.)discounted

@3.5%)

Registration scheme for refrigerant handlers 3236 51038 16

HFC replacement for domestic and small refrigeration units 68 2167 32

HFC replacement (by CO2) by 2010 for mobile air conditioning units 3733 566054 152

Voluntary agreement on leakage reduction from mobile air conditioning 1369 160987 118

Phase-out of novelty aerosol products 1041 59629 57

Voluntary agreement on emissions reduction from fire-fighting equipment 1099 1912 2

Installation of thermal oxidiser abatement technology for halocarbon production 5760 14561 3

Phase-out of one component foams (OCFs) fornon-retail applications 528 3619 7

Recovery of HFCs from recycled OCF cans 12 18239 1497

Recovery of HFCs from reject metered dose inhalers (MDIs) 262 492 2

Destruction of used MDI units 253 21437 85

Voluntary agreement on HFC-based aerosols 69 605 9

Conclusions

7. Based on best estimates, total UK GWP-weighted emissions of HFC, PFC and SF6fell from about 17,200 kt CO2 equivalent (eq.) in 1995 to about 12,100 kt CO2eq. in 2000. Emissions are expected to increase again to about 14,500 kt CO2 eq.by 2005, largely due to increased use of HFCs for stationary refrigeration, mobileair conditioning, metered dose inhalers and foam blowing as replacements forCFCs and HCFCs, and then steadily decrease to about 11,300 kt CO2 eq. in2025. There is expected to be a 25% emissions reduction in 2010 compared withthe 1995 baseline. These overall trends and the associated uncertainties inemissions and projections are shown in Figure 9.10 below.

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Figure 9.10: HFC, PFC and SF6 emissions for the UK (ktonnes CO2 equiv).


Final report published in September 2003, “Emissions and projections of HFCs, PFCsand SF6 for the UK and Constituent Countries”.

0

5000

10000

15000

20000

25000

1990 1995 2000 2005 2010 2015 2020 2025

Emis

sio

ns

(kt

CO

2 eq

.)

Low

Mid

High

UK HFC/PFC/SF6 emissions with uncertainties

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Contract No: GA 4/2/207Title: Development of a methodology for estimating methane emissionsfrom abandoned coal mines in the UKMain Contractor: IMC Group Consulting Ltd PI: Steve KershawSub-contractor: Centre for Ecology and Hydrology

Aims and objectives

1. To produce a verifiable methodology for generating accurate and reliableestimates of methane emissions from abandoned coal mines in the UK, to beconsidered for inclusion in the UK greenhouse gas inventory.

2. The overall aim of the project can be sub-divided into five tasks:

i. Establish a database of abandoned mines in the UK;

ii. Stratify the database by representative types of mine, suitable for selectingsites for measurement purposes and for emissions modelling and coveringsites with and without exploitation;

iii. Measure emissions and linked meteorological data at representative sitesincluding emissions from vents (where present) and diffuse emissions;

iv. Establish mathematical representation of time dependence since closure forrepresentative types of mine within the database stratification; and

v. Use the mathematical representation and the database to calculate annuallyupdateable emissions estimates.

Background

3. A 2001 review for UK DETR (now Defra) found that annual methane emissionsfrom abandoned coal mines in the UK could be in the range 20 to 300 kt. Morerecently the Association of Coal Mine Methane Operators (ACMMO) hassuggested that emissions might exceed 600 kt/yr. This estimate has also beenreviewed, in work published for Defra in 2002. This source category is currentlynot included in the UK greenhouse gas emissions inventory (UKGHGI). Despite thecomplexities and for the purposes of completeness there is interest in includingmethane from abandoned mines in the UKGHGI, provided a methodology can beidentified which would be acceptable to international review.

Activities

4. The activities carried out over the period fall under three main headings, which are:

i. Mine database and classification of mines (IMC);

ii. Point Source Monitoring (IMC); and

iii. Balloon Monitoring (CEH under sub-contract).

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5. Following discussions between Defra and the Coal Authority, the data from theMining Records Database System (MRDS) has been provided in digital format.The data covers the seams worked, the seam thickness and the level of workingsfor nineteen separate coalfield areas and has now been converted to AutoCad.The data has been divided up into coalfield areas and further into sub-areas ofinterconnected groups of mines, or in some cases single mines, which form thebasis of the methane emissions database. For each sub area, type geologicalsections, seam gas content data and surface geological data is collected forinclusion in the coalfield models.

6. The classification of mines (mining areas) has been completed for Scotland.The areas where modelling has been undertaken are Sanquhar, Ayrshire, theCentral Coalfield (West) and Central Fife. Ayrshire and the Central Coalfield weresubdivided into several smaller units for the modelling. Previous modelling workusing monitored mine water recovery data has been used to classify the rest ofthe major Scottish mining units of East Fife, Midlothian, East Lothian and theCentral Coalfield (East).

7. Point source monitoring has been carried out on eight vents at seven sites.The sites are located in West Yorkshire, South Yorkshire, Nottinghamshire, andCumbria. The vents are connected into abandoned mine workings and wereinstalled by the Coal Authority to prevent any build-up of gas pressure.Monitoring at the sites consists of measurements of gas concentration, flow anddifferential pressure within the vents as well as barometric pressure. Gas samplesare also taken for calibration purposes.

8. Balloon monitoring consists of taking a samples of ambient air, which iscontinuously pumped at a low flow rate into an inflatable bag which is filledover a period of a month. Bags are changed when full. The balloon monitoringis carried out at locations within exposed coalfields where gas could possiblyleak to the surface. The purpose of the monitoring is to ascertain any generalenrichment of methane in the air due to a flux of methane from the ground.

Interim results

9. Mine water modelling has shown that the mine water in the majority of theScottish areas assessed recovered to surface outflow in the 1990s or earlier.Therefore surface methane emissions in these mining units will have reducedconsiderably or stopped at this time. Residual, unsaturated mining voids andpotential methane reserves they contain above the recovered mine water levelhave then been assessed.

10. Figure 9.11 shows the mine water recovery in part of the Scottish CentralCoalfield (West) in the Limestone Coal Group of workings around Kirkintilloch andKilsyth. Abandonment of the mines in this area in 1983 was followed by recoveryof water in the mines until water was discharged at a surface level of about 50mAOD. The modelling shows the recovery date to have been about 1994.

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Figure 9.11

11. Compared with earlier monitoring results, the result of monitoring at the minevents has shown a general decrease of emission over recent years, with theexception of Kirkby vent in Nottinghamshire. Gas monitoring results can be seenin Figure 9.12 for Kirkby vent. The graph shows the methane concentrationwithin the vent and the total and methane flows from the vent. The changes inflow are caused by changes in atmospheric pressure. Monitoring has shown thattwo vents in Cumbria (Howgill and Bearmouth) which until recent years used torelease methane now no longer do so. Monitoring of the Roughwood Drift ventnear Rotherham has also shown a significant reduction in methane flow.

Figure 9.12

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12. At present, balloon monitoring data from nine sites is available. Recentmeasurements from a national network have shown that an average level ofmethane in ambient air is about 1960 ppb. However, the methane concentrationsin the mining areas have an average of 2440ppb which is significantly higher.

Conclusions

13. The Scottish coalfields have now largely been modelled for the effects of risingwater and accessible gas in place. The Yorkshire coalfield, which is the largest,will be the next to be modelled.

14. Where previous flow data from vents is available, methane flows have generallybeen found to have decreased or terminated due to due to the combined effectsof water level variation and gas depletion.

15. Balloon monitoring results seem to indicate that ambient methane levels inexposed coalfields may be higher due to leakage from old mines.

16. Work in all these areas will continue until February 2005, when the contractis due to end.

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Contract No: EPG 1/1/144Title: Methane emissions from UK landfill sites and impact of EUlandfill directive and national strategies on UK greenhouse gas emissionsContractor: Land Quality Management Ltd and EnvironmentalResources Management PI: B Gregory (LQM), S Aumonier (ERM)

Aims and objectives

1. These two projects were carried out in parallel under Defra Contract EPG1/1/145. LQM revised the UK National Assessment Model, producing newestimates of national emissions and forecasts under a number of wastemanagement scenarios. Estimates of methane emissions from landfill informedthe study conducted by ERM, which examined the wider effects and impacts ofwaste-related policies on emissions of greenhouse gases (GHG) and ammoniaarising from the life cycle of waste management systems. The two studies aresummarised separately below.

Methane emissions from landfill sites in the UK

2. The work undertaken in this project reviewed the current methodology, assesseddata quality, considered the impact of methane in landfill operations, revised themethodology, and produced annual emissions estimates and projected emissionsfor 1990-2000 and 2001-2025. These estimates are based on the effect of theLandfill Directive and the new Waste Strategies of the Devolved Administrations.In addition, the balance of methane flared or utilised has been ascertained fromindustry sources, and a methodology to update these was developed. A workingversion of the model allows the user to investigate the effect of the different wastemanagement strategies upon the forecast methane emissions from UK landfills.

Modelling approach

3. The three methane generation rate (k) constants used for the slowly, moderatelyand rapidly degradable waste fractions have been updated using the defaultvalues in the Environment Agency’s GasSim Model (Environment Agency, 2002).Brown et al (1999) considered the degradable organic carbon (DOC, Gg C/Ggwaste) and fraction of the DOC dissimilated to form methane (DOCF) to havewide error limits, and the 1999 model calibrated these to converge with sitemeasurements made by Milton et al (1997). LQM found that the gas yield fromthe model, following calibration, was too low, and a new set of DOC and DOCFparameters were built into the model using the approach developed for GasSim.The new degradable carbon parameter values are based on USEPA research.

4. A new methane oxidation model was developed using an approach employed inGasSim. This builds on simple underlying concepts: methane oxidation in the soilcap is assumed to occur if soil cover depth exceeds 0.3m if an engineered barrieris present, or exceeds 1.0m if an engineered barrier is not present. If neithercondition is met, no oxidation will take place, on the basis that the soil cover is

176


insufficiently thick, and/or the flow of methane is too fast, to permit a significantamount of oxidation to take place in the cap.

Results

5. This model estimates that nearly six times as much methane oxidation may havetaken place in the cap, compared with the IPCC recommended value for well-managed sites of 10%. The new model allows much higher residual oxidation totake place in the capping layers, while permitting no oxidation in fractures. Thismodel reconciles UK emissions from landfills to a level approaching the estimateof Milton et al (1997), based on measured data.

6. The amounts of methane utilised and flared, and the number of flares sold usedas standby units, were identified, in co-operation with industry stakeholders. Anestimated 63% (1750 kt CH4) of the landfill gas generated was flared or utilisedin 2002, and this is forecast to rise to 72% (2465 kt CH4) by 2005. Figure 9.13presents the best-estimate of the historical utilisation and flare capacity, as wellas forecasts to the year 2005. In 2002, an estimated 676 000 m3/h of landfillgas was flared or utilised, expected to rise to 788 000 m3/h by 2005.

Figure 9.13: UK-installed generation capacity and operational/standbyflare capacity.

7. Figure 9.14 presents three base case simulations of landfill gas generation andemissions from the time of implementation of the IPCC Tier Two model. The1996 and 2002 models have similar gas generation curves, whereas the 1999model is calibrated to converge with Milton et al (1997) field data. The Milton etal (1997) UK surface emissions value is derived by extrapolation of emissions froma sample of landfills to match the entire UK inventory of landfills. This bringssignificant uncertainty, but provides an estimate comparable with the modelledapproach, based on modelling gas generation from a known waste mass.

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8. Further emission projections are based on eight Municipal Solid Waste (MSW)and five Commercial and Industrial (C&I) scenarios. These were developed toinvestigate the various waste management options available. Future MSW arisingswere modelled using anticipated levels of growth to reflect the Government’scommitment to waste minimisation. The most significant methane emissionsreduction in an MSW scenario involves paper recycling, which in 2005 shows areduction of 2% of residual landfill methane emissions (8 kt methane abated),growing to a reduction of 19% (31 kt methane abated) of residual landfillmethane emissions by 2025. The least effective MSW scenario (excluding thebase case) involves glass, metal and plastics recycling and gives a forecast residualmethane emissions reduction of 11% (19 kt methane abated) by 2025. However,both sets of figures are small when compared with the amount of methaneabated by flaring or utilisation.

Figure 9.14: Base Case Landfill Gas Generation and Emission Forecasts for(1) Aitchison et al., 1996; (2) Brown et al., 1999 with calibration fromMilton et al., 1997; and (3) LQM 2002 study.

9. A sensitivity analysis was carried out to determine the individual effects of thevarious parameters upon emission projections and then combined to give theupper and lower limits for methane emission projections. The new modelestimates are 938 kt/year (in 1995), with a range of between 458 and 1370kt/year. These compare well with the NPL emissions study data of 887 kt/yearwith a 90% confidence interval of between 652 and 1135 kt/year.

Conclusion

10. On the basis of the ETSU 1996 and LQM 2002 models, it is likely that thegeneration of methane in landfill gas was much higher than had been reportedin Brown et al (1999). The emissions of methane from UK landfills however areforecast to be similar to previous estimates. Flaring, utilisation, and methaneoxidation play important roles in mitigating emissions from landfill. All the MSWmanagement strategies considered showed benefits in methane emissions

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reduction compared with the BAU base case, but the effects were not assignificant as the impact on emissions reduction due to flaring or utilisation. Theimpact of the C&I scenarios compared to the base case were negligible in termsof methane emissions reduction, since there is already significant recovery ofdegradable paper etc from the C&I wastes. The role of flaring and utilisationtechnologies in managing methane emissions, recognised in the Landfill Directiveas a key emissions management tool, should not therefore be underestimated.

Impact of EU Landfill Directive and national strategies on UK greenhousegas emissions

Modelling approach

11. A number of scenarios were defined in order to examine the impact of thedifferent ways in which relevant policy targets might be met for municipal solidwaste (MSW) and for commercial, industrial and other (CIO) wastes. The policiesconsidered included the Landfill Directive and those set out as targets in WasteStrategy 2000, the national strategy for England and Wales. The study predatedthe National Waste Plan for Scotland and the detailed policies contained within it.The scenarios varied in the type and proportion of materials recycled, the rate ofenergy recovery through combustion, and the extent of composting andanaerobic digestion of degradable wastes. The annual rate of growth in thequantity of wastes produced was also varied in some scenarios.

12. A spreadsheet model was developed to estimate GHG emissions, using thescenarios as a basis. Other key issues included in the model were: current wastearisings and management; waste composition; growth rates over time; andemissions factors for each activity within the life cycle. The greenhouse gases forwhich emissions were modelled were the following:

i) carbon dioxide (CO2, fossil) vii) CFC 11 (CFCl3)

ii) CFC 12 (CCl2F2) viii) CFC 22 (CHF2Cl)

iii) methane (CH4) ix) halon 1301 (CF3Br)

iv) CFC 13 (CF3Cl) x) carbon tetrafluoride (CF4)

v) nitrous oxide (N2O) xi) chloroform (CHCl3, HC-20)

vi) CFC 114 (CF2ClCF2Cl) xii) hexafluoroethane (C2F6, FC116)

13. The spreadsheet modelling process followed the IPCC Guidelines on GHGEmissions (1996 Revision) as closely as possible. Emission factors were alsosourced from appropriate life cycle assessment (LCA) databases.

Modelling results

14. Estimates of GHG emissions from the management of MSW and CIO waste, forEngland and Wales, Scotland, Northern Ireland, the Channel Islands and the UKwere presented in chart form. The results are influenced both by the way inwhich policy targets are achieved and by waste growth rates. The contribution of

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landfill methane emissions, provided by LQM’s parallel study, were consistentlypositive over the study’s time horizon. Nevertheless, methane emissions fall overtime as policy measures increase diversion of waste from landfill. Nevertheless,variation in growth has a greater impact on methane emissions than the way inwhich waste policies are interpreted in the scenarios. This is because of theamount of waste that has already been landfilled and that emits methane overtime. These emissions are already ‘committed’.

15. In contrast to the emissions of methane from landfill, the remaining activities inthe MSW management system avoid GHG emissions, i.e. the net emissions arenegative, not positive. This is a result of the GHG benefits of recycling materialsand recovering energy from waste. Recycling and recovery offsets a demand forenergy in processing virgin materials and generating electricity that wouldotherwise have been met through the consumption of fossil fuels. As a result,GHG emissions, notably of carbon dioxide, are avoided. In accordance with LCApractice, a negative GHG emission is allocated to the waste management systemas a result. Overall, the waste management system thus delivers a net benefit interms of GHG emissions.

16. The avoided GHG emissions increase over time, as policy measures lead togrowing diversion of waste from landfill and higher rates of energy and materialsrecovery. As this occurs, there is an increase in the avoided GHG emissions fromenergy production from fossil fuel sources. The results for the MSW scenariosthat were modelled are shown in Figure 9.15. Most scenarios demonstrate anincrease in the avoided GHG emissions year on year. In all scenarios, the wastemanagement system delivers a net benefit over the whole timescale of the study.

Figure 9.15: Net GHG emissions for MSW scenarios 1 – 8 for England andWales (g CO2 equivalent).

-8.00E+12

-7.00E+12

-6.00E+12

-5.00E+12

-4.00E+12

-3.00E+12

-2.00E+12

-1.00E+12

0.00E+0020

01/20

02

2003

/2004

2005

/2006

2007

/2008

2009

/2010

2011

/2012

2013

/2014

2015

/2016

2017

/2018

2019

/2020

2021

/2022

2023

/2024

2025

/2026

MSW 1 MSW 2 MSW 3 MSW 4 MSW 5 MSW 6 MSW 7 MSW 8

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17. In the case of CIO waste, the net benefit was approximately three to eight timesgreater than the benefit associated with MSW systems, depending on the specificscenario assumptions. This is because of the quantity of CIO wastes comparedwith MSW, rather than the mix of materials that can be recovered or recycled.

18. In contrast to GHG emissions, the estimated emissions of ammonia are allpositive, i.e. there are not the same offset emissions from recycling and energyrecovery that were predicted for GHG emissions. The benefit of recycling for GHGemissions is associated with avoiding energy consumption and the use of virginmaterials. Recycling and incineration processes avoid only insignificant releases ofammonia emissions, and hence the benefit is limited.

Cost effectiveness analysis for GHG emissions for England and Wales

19. Indicative total costs for the MSW scenarios were developed for England andWales. Generally, costs increase over time, as more expensive waste managementroutes are pursued. However, the rise in costs is accompanied by a decrease inGHG emissions. An example cost-effectiveness graphic is shown in Figure 9.16.

20. The shape of the cost-effectiveness functions is strongly influenced by the trendof the GHG emissions reductions for each scenario. Continuing cost-effectivenessis demonstrated by most of the scenarios over the period examined, and thereare increased returns as a result of the rising costs of waste management.

21. The costing exercise was not undertaken for the CIO waste scenarios. This isbecause waste disposal in these sectors is a more commercial market, and reliablecost factors are difficult to obtain. Furthermore, recycling and, to an extent,recovery methods have a wide range of prices because of variation in the value ofthe waste itself (e.g. from clean offcuts to a mixed paper waste stream for paper).

Figure 9.16: Cost-effectiveness of GHG emissions for an example scenario.

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22. Because there are no statutory drivers of change, generally waste producers willonly change management route in response to lower prices. Accordingly, manyproducers could be expected to change the preferred management route for theirwastes in response to changes in the landfill tax, and as a result of other increasesin the cost of landfill. The price at which change in management route will occurwill vary depending on the other routes available, and it was not possible to modelthe complexity of these margins within the constraints of this study.

References

Aitchison EM, Milton MJT, Wenborn MJ, Meadows MP, Marlowe IT, Mikkelsen M,Harries C and Pocock R. (1996). A methodology for updating routinely the annualestimate of methane emissions from landfill sites in the UK. ETSU report to DoEFebruary 1996, Contract EPG/1/1/20.

Brown KA, Smith A, Burnley SJ, Campbell DJV, King K and Milton MJT (1999).Methane emissions from UK landfills. Final report for The Department of theEnvironment, Transport and the Regions. Report AEAT-5217.

Environment Agency (2002). GasSim User Manual.

Milton MJT, Partridge RH, Goody BA and Andrews AS (1997). An estimate ofmethane emissions from UK landfills based on direct flux measurements atrepresentative sites. Final Report to Department of the Environment, NPL ReportQM 134.


Final report for both projects under the contract. The LQM report was publishedin October 2002, ERM report was published in October 2003.

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Chapter 10

Further information

The GA Research Programme is headed by:

David WarrilowGlobal Atmosphere Division3/C1 Ashdown House123 Victoria StreetLondon, SW1E 6DE

Tel: 0207 082 8149Fax: 0207 082 8151Email: [email protected]

General enquiries on the programme should in the first instance be directed to theResearch Programme Administrator – Ron Williams ([email protected]).

Enquiries on the technical aspects of the programme should be addressed to therelevant Nominated Officer:

If you want to make contact with the Nominated Officers by email;[email protected]. Telephone numbers are 020 7082 + extension

The Annual Environment Protection (EP) Group Research Newsletter contains furtherinformation on research objectives and titles of proposed new projects. Copies can bedownloaded from: www.defra.gov.uk/environment/research/index.htm

Ozone layer Observations and prediction Cathy Johnson (x8164)and climate change

Climate change Impacts Diana Wilkins (x8163)

Climate change Response strategies Jim Penman (x8152)

184

Chapter 10 Further information

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185

Further information

global atmosphere research programme

Documents