the potential impacts of climate change on the hydrography of the northwest european continental...

Progress in Oceanography 86 (2010) 361–379

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Progress in Oceanography

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The potential impacts of climate change on the hydrography of the northwestEuropean continental shelf

Jason Holt a,*, Sarah Wakelin a, Jason Lowe b, Jonathan Tinker c

a National Oceanography Centre, 6 Brownlow Street, Liverpool L3 5DA, UKb Met Office Hadley Centre (Reading Unit), Department of Meteorology, The University of Reading, Earley Gate, Reading RG6 6BB, UKc Met Office Hadley Centre, FitzRoy Road, Exeter, Devon EX1 3PB, UK

a r t i c l e i n f o a b s t r a c t

Article history:Received 11 December 2009Received in revised form 24 May 2010Accepted 30 May 2010Available online 15 June 2010

0079-6611/$ - see front matter Crown Copyright � 2doi:10.1016/j.pocean.2010.05.003

* Corresponding author.E-mail address: [email protected] (J. Holt).

Changes in global atmospheric conditions have the potential to substantially influence shelf sea environ-ments with far reaching consequences for their ecosystems. Here we focus on the northwest Europeancontinental shelf, and review the mechanisms by which climate change might affect the temperature,salinity and stratification of this shelf sea. We explore results from a single pair of Proudman Oceano-graphic Laboratory Coastal Ocean Modelling System (POLCOMS) simulations forced by the Hadley Centreregional climate model, for conditions typical of 1961–1990 and 2070–2098, under a ‘business as usual’emissions scenario (SRES A1B). This provides a single, physically plausible, representation of the futureand a consistent representation of the recent past. Comparing these simulations, the shelf sea regionsof this model are shown to warm substantially more than the open-ocean, by between 1.5 and 4 �Cdepending on location. Across the whole domain the surface waters are projected to be �0.2 p.s.u. fresherby the end of the 21st century. The strength of seasonal stratification is shown to increase by �20% on theshelf, compared with 20–50% in the open-ocean. The former being controlled by temperature and the lat-ter by salinity. In shelf seas away from the direct influence of river discharge, stratification is projected tostart �5 days earlier and breakdown �5–10 days later each year, hence extending the stratified period.An ERA-40 re-analysis forced simulation provides a reference, along with validation from griddedmonthly mean data from the ICES data base.

Crown Copyright � 2010 Published by Elsevier Ltd. All rights reserved.

1. Introduction

Shelf sea and coastal marine environments are exceptionallyvulnerable to climate change; their dynamics and ecosystems arecoupled systems that are highly constrained by external forcingfrom atmospheric, oceanic and terrestrial vectors. Surface fluxes,horizontal transports and vertical mixing all determine the distri-bution (in space and time) of water properties (e.g. temperature,salinity and nutrients), which in turn control many biological pro-cesses. Examples include nutrient supply to support phytoplanktongrowth (e.g. Hydes et al., 2004) and the distribution of planktonspecies (Beaugrand et al., 2002). Since coastal/shelf seas are regionsof immense socio-economic importance (e.g. a large majority ofthe world fish catches are made in coastal seas (Watson and Pauly,2001)), understanding how their structure and dynamics havechanged in recent decades and might change into the next centuryis of considerable interest to marine planners, managers and policymakers. There is already substantial evidence for the warming ofthe shallow seas of the northwest European shelf over the past

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decades based on analysis of satellite radiometer data (e.g.Gomez-Gesteira et al., 2008) and long term monitoring of pointtime series and repeat sections (Holliday et al., 2009; van Leussenet al., 1996). Trends in the salinity are less clear, but the evidencesuggests a freshening to a minimum in the 1980’s–1990’s followedby an increase in salinity after that (Evans et al., 2003; Hollidayet al., 2008). However, the year to year variation tends to dominatethe salinity variability.

Here we investigate how climate forcing late in the 21st centurymight influence the temperature, salinity and stratification of thenorthwest European continental shelf seas (Fig. 1) through numer-ical model simulations using Proudman Oceanographic LaboratoryCoastal Ocean Modelling System (POLCOMS; Holt and James,2001). The future period of interest is 2070–2098 (indentified asRCM-F, see Section 2) and is compared with conditions typical of1961–1990 (identified as RCM-P).

Investigations of potential future climate change impacts on thehydrography of shelf seas through dynamical downscaling are atan early stage of development; examples include Meier (2006)working in the Baltic, and Adlandsvik and Bentsen (2007) andAdlandsvik (2008) in the North Sea. Hence, an important aspectof our current study is validation of the model behaviour during

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Fig. 1. The model domain, bathymetry and location of time series (NEA: North East Atlantic and NS: central North Sea).

362 J. Holt et al. / Progress in Oceanography 86 (2010) 361–379

the period when observations are available. Moreover, we mustconsider carefully the robustness of the climate change conclu-sions we reach. The atmospheric component of the scenario forcingis derived from a version of the Met Office Hadley Centre RegionalClimate model (HadRM3; Murphy et al., 2009). This an atmosphereonly model (Fig. 2 shows some example fields, discussed later),which is forced at its lateral boundaries and sea surface by outputfrom a global coupled ocean–atmosphere model (HadCM3 PPE;specifically the ‘‘unperturbed” member of the UKCP perturbedparameter ensemble (Murphy et al., 2009)) using a ‘medium’ busi-ness as usual emissions scenario (SRES A1B; Nakicenovic andSwart, 2000). Since we present only a single realisation of futureconditions we cannot assign a likelihood to the future simulation,so the results presented here should be seen as a physically plau-sible projection, rather than a prediction.

The next section is devoted to exploring the potential mecha-nisms by which large scale atmospheric and oceanic change mightinfluence the northwest European continental shelf. Section 3 de-scribes the model simulations, Section 4 the effects on temperatureand salinity, and Section 5 describes the effects on stratification.Conclusions are discussed in Section 6.

2. Mechanisms for climatic influence on shelf seas

Atmospheric, oceanic and riverine forcing all have a role in con-trolling the temperature, salinity and circulation of shelf seas.Atmospheric forcing is in the form of surface fluxes of heat (turbu-lent and radiative), momentum and freshwater (precipitationminus evaporation). Since 90% or more of the extra heat trappedin the climate system (by anthropogenic greenhouse gas

emissions) is contained in the ocean (Bindoff et al., 2007; Levituset al., 2000), it is natural to expect significant temperature changesin seas over the next 100 years.

2.1. Heat content

The heat content of a shelf sea (such as the northwest Europeancontinental shelf) is determined by the surface heat flux and thelateral transport of heat. The surface heat flux consists of severalcomponents: net downward short-wave radiation, sensible heatflux, latent heat flux and the emission of long-wave radiation.These are determined by atmospheric conditions including thetemperature, radiative transfer, wind speed and humidity; see Gill(1982) for a simple set of relationships between these and Fairallet al. (2003) for a more advanced formulation. The latent andlong-wave heat fluxes are non-linearly related to the air and watertemperatures, so even if we assume the sea is well mixed and othercomponents constant, the temperature response of a sea region toa change in air temperature is not straightforward and requires anumerical solution.

To make a first estimate of the relative magnitude of the atmo-spheric and oceanic influence on the shelf sea temperature, it isuseful to consider the case of a well mixed sea region, area A, meantemperature T and typical velocity of exchange with the open-ocean, V over a length of shelf break, L and depth, H. Here we con-sider the case where only the sensible heat flux is important,qa = CHWCaqa(Ta � T); (W m�2; Gill, 1982), as is common practicein simple bulk temperature models (Elliott and Clarke, 1991; Laneand Prandle, 1996). Here Ta is the near surface atmospheric tem-perature, W the wind speed, CH the Stanton Number (taken to be

Fig. 2. Mean air temperature (at 1.5 m), surface freshwater forcing (evaporation minus precipitation) and wind stress from HadRM3 for the period 1961–1990 (RCM-F), andthe difference between the future time slice (RCM-F 2070–2098) and this period.

J. Holt et al. / Progress in Oceanography 86 (2010) 361–379 363

1.45 � 10�3), qo/a the water/air density and Co/a the specific heatcapacity for water/air. For the oceanic component, we assume avolume flux, Q = VLH, of water enters the region with a tempera-ture To and leaves with temperature, T, and the correspondingadvective heat flux (per unit cross-section of the exchange) is:qo = VCoqo(To � T). The change in heat content (C) of the region isthen dC/dt = Aqa + HLqo and a steady state temperature can beinferred:

T ¼ QTo þ FTa

Q þ Fð1Þ

where F = rCHWA is the volume flux equivalent for the heatexchange with the atmosphere, expressed as a ‘piston velocity’times the area of the sea. Here r = Caqa/Coqo � 3.1 � 10�4.

For example, a broad shelf with L = 2000 km, H = 100 m,A = 1.2 � 1012 m2, V = 0.0125 ms�1 gives Q = 2.5 Sv (=1 � 106 m3

s�1), chosen to match the estimates of ocean-shelf exchange forthe northwest European shelf given by Huthnance et al. (2009).For a typical wind speed of W = 9 ms�1, the corresponding air–sea volume flux equivalent is F = 4.7 Sv. So for broad shelves(A� LH) with frequent high wind speeds, where the sea–air tem-perature difference is comparable to the sea–ocean temperaturedifference, we would expect atmospheric effects to be greater than

oceanic in determining the shelf-wide mean heat content, but onlyby a factor of �2. So ocean-shelf heat transport would be expectedto be important close to the ocean margin but of decreasing impor-tance across the shelf towards, for example, the southern NorthSea. Hence shelf sea geography plays a crucial role in setting therelative importance of oceanic and atmospheric influence: in thecase of a narrow shelf with a deeper exchange with the open-ocean, this balance would be expected to be reversed.

The key assumption in this analysis is that the sea is well mixedhorizontally and vertically, so that the water leaving the region isat the mean temperature of the region, and that this is the sametemperature as mediates the air–sea heat flux. Important distinc-tions can be made between downwelling and upwelling shelves,and between those that are only seasonally stratified and thosewhich are stratified throughout the year. The northwest Europeancontinental shelf has a predominantly downwelling circulationnorth of the southern coast of Ireland (Holt et al., 2009) and depthsless than 200 m are vertically mixed from approximately Decem-ber–March. Hence water is brought on-shelf in contact with theatmosphere either in a well mixed water column or in the surfacelayer of summer stratification. Hence, temperature variability orig-inating in the open-ocean is damped by atmospheric exchange onseasonal time scales as water is moved on-shelf, and the above


analysis underestimates the importance of atmospheric tempera-ture relative to oceanic in determining the steady state tempera-ture of the sea region. In contrast, on an upwelling shelf ifoceanic water arrives on-shelf below a pycnocline its propertiesare isolated from atmospheric fluxes and this analysis will tend tounderestimate the oceanic influence compared with the atmo-spheric. An example in this context is the Norwegian Trench: NorthAtlantic water enters the trench at depth on the western flank, trav-els south and re-circulates in the Skagerrak, where it periodicallyupwells and joins the Norwegian Coastal Current (Danielssenet al., 1997). Since the Norwegian Trench is permanently stratified,this water has only limited exchange with the atmosphere and oce-anic temperatures will have a much greater influence on the steadystate temperature than in other regions of the northwest Europeancontinental shelf.

2.2. Mixing and seasonal stratification

In many shelf seas, tides provide the most energetic process fortransport and mixing. They are determined by well establishedastronomical forces and the propagation of coastal trapped wavesonto the shelf. These waves are affected by the bathymetry andcoastline, which can change by sediment erosion, deposition andsea level change on time scales appropriate for his study (e.g.Nicholls, 2004), but these processes are beyond the scope of thecurrent work. On this basis we also do not consider changes in tidalnodal factors (e.g. to account for the 18-year cycle (Pugh, 1987)).

The spatial distribution of temperature on the northwest Euro-pean continental shelf is to a large extent determined by the effectsof vertical mixing processes on the water column, with horizontalheat transport playing a more minor role (as discussed above andquantified later). Features of particular importance in tidally activeseas are the seasonal thermal stratification (Fig. 3) and the forma-tion of tidal mixing fronts (Holt and Umlauf, 2008; Pingree andGriffiths, 1977). Thermal stratification arises where tidal and windgenerated turbulence is insufficiently energetic to mix the surfaceflux of potential energy (Simpson and Hunter, 1974). Tidal mixingfronts occur where these energy fluxes balance, at a constant valueof h/u3; empirically the critical value of h/u3 is 500 m�2 s3 (rangingfrom 200 to 1260 m�2 s3; Bowers and Simpson, 1987). Since cur-rent speed, u, tends to increase with decreasing local water depth,h, this strongly constrains the location of these fronts, and they areobserved to be very sharp. In regions of high gradients in energydissipation, the frontal locations show very little inter-annual var-iability (Connor et al., 2006; Young and Holt, 2007). The model dataused by Connor et al. (2006) to defined shelf sea frontal locationsshows a notable exception: the frontal positions in the GermanBight show a high degree of inter-annual variability, owing to theweak tides and also the importance of salinity stratification here.Hence in many regions tidal mixing has the potential to limit someof the effects of varying atmospheric forcing.

In seasonally stratified locations on-shelf (Fig. 3), well mixedwinter conditions are followed in spring by approximately two-layer stratification, sharpened from below by tidal mixing. Becausethis figure shows a multi-year mean annual cycle, the profiles aremore diffuse than in any particular year. The surface layer warmsrapidly under increased summer-time heat flux, while the lowerlayer remains close to winter temperatures, warming only slowly.The stratification of the water column breaks down in the late au-tumn with increased wind and convective mixing. Given that thewhole water column is in rapid communication with the atmo-sphere for a large fraction of the year, simply increasing the airtemperature does not necessarily lead to an increase in the sum-mer-time thermal stratification. In the case of shallow seas the var-iation of stratification is dependent on the temperature differencebetween winter and summer, and hence on changes in the sea-

sonal variation of the surface heat flux. An increase in summer heatfluxes relative to those in winter would tend to increase the sea-sonal thermal stratification. In addition, the non-linear dependenceof the water density on temperature (the thermal expansivity in-creases with temperature) is such that if the whole water columnis warmed then the same seasonal increase in heating will result ingreater density stratification.

In the open-ocean there is an analogous process, except in thiscase stratification has a different structure. The depth of wintermixing determines a permanent pycnocline where the densitystarts increasing gradually with depth (Fig. 3). Above this, seasonalstratification occurs between spring and autumn much as on thecontinental shelf; with the strength of stratification (and its varia-tion) being determined by the difference between winter and sum-mer heat fluxes. The major difference in this case, however, is thatthe depth of winter mixing is itself a dynamic property, which issubject to climatic variation; as distinct from the mean waterdepth which is not (eustatic sea level rise is not included in thisstudy). Hence we might expect shelf sea and open-ocean stratifica-tion to respond very differently to changes in climatic forcing.

2.3. Salinity distribution

The salinity distribution of this shelf sea is primarily determinedby the balance between inputs of fresh river water and saline oce-anic water. The surface forcing (precipitation and evaporation) playsa role in setting the overall salinity budget and large scale gradients.The nature of a riverine discharge is determined by the details ofcoastal geometry and mixing environments but generally riverplumes are associated with an along coast (cyclonic) transport.Changes in evaporation and precipitation not only affect the salinitybudget but also the saline component of the vertical density struc-ture; evaporation tending to destabilise the water column and pre-cipitation tending to stabilise it. This is often seen as a small effect(e.g. Horsburgh et al., 2000), but can play a significant role in ‘pre-conditioning’ the vertical density structure and influence the onsetof thermal stratification. In contrast, river discharges can have a dra-matic effect on near-coastal regions (up to�20 km from the coast inthis region), introducing large variations of salinity over short timescales (hours to weeks) and high frequency variations in stratifica-tion (Sharples and Simpson, 1995). Hence, changes in runoff (fromprecipitation over land) would be expected to have a large effecton near coastal stratification and transports. For example, increasesin river discharge may, not only reduce the local salinity, but alsochange the character of a river plume from being full depth to beingsurface limited (Chapman, 2000). Since rivers also carry nutrientsand constituents that affect the optical properties of the water(sediment and coloured dissolved organic matter), their variabilitycan have wide ranging implications for coastal ecosystems andbiogeochemistry. Other interactions with the terrestrial environ-ment, such as ground water, sediment input from coastal erosionand pollutant fluxes, are all potential vectors of climatic variabilitybut are not considered here. On a larger scale, the combined effectof river discharges is to generate coastal currents (e.g. theNorwegian Coastal Current), which can form a substantial part ofthe circulation of shelf seas.

2.4. Ocean-shelf coupling

Oceans influence shelf/coastal seas through the impingement oflarger scale currents onto the shelf and a number smaller scale(generally friction) processes that mediate the ocean-shelf ex-change (Huthnance, 1995). The oceanic conditions also controlthe large scale (barotropic and baroclinic) pressure gradient acrossa shelf sea region and can have a considerable effect on aspects ofits circulation (Holt and Proctor, 2008). Since geostrophic flows in

Fig. 3. Mean annual cycle time series of temperature and salinity profiles in the North East Atlantic (NEA) and central North Sea (NS) from POLCOMS runs RCM-P and RCM-F.


the large scale ocean circulation tend to follow the shelf breakrather than crossing it, the northwest European shelf and in partic-ular its coastal regions can be seen as an quasi-isolated system ontime scales of �1 year (Wakelin et al., 2009). This is particularlyapplicable to properties that are strongly constrained by surfaceforcing, most notably the temperature field. In this case, wherethe transit time across shelf seas is slow compared with the sea-sonal cycle, temperature fluctuations arising from variability inthe open-ocean temperature are generally lost (Sharples et al.,2006). In contrast, there is no direct feedback between the surfacesalinity and the atmosphere, so the salinity field is highly depen-dent on the exchange of water with the open-ocean (Huthnance,1997). Ocean-shelf exchange is also responsible for a substantialproportion of the on-shelf nutrient budget and the slope currentin this region has a particularly important role in this exchange(Holt et al., 2009; Souza et al., 2001). Hence, climatic factors affect-ing the slope current are likely to have a substantial influence on

the ecosystems on-shelf. Huthnance (1984) demonstrates that thiscurrent is generated and maintained by a combination of polewarddensity gradient, friction and sloping topography. Hence changesin this density gradient will significantly modify this current. How-ever, owing to the limited size of the shelf model domain consid-ered here (Fig. 1) we do not consider this aspect further in anydetail.

3. The model simulations

3.1. The climate model forcing

A version of the global ocean–atmosphere general circulationmodel (OA-GCM) HadCM3 (identified here as HadCM3 PPE) is ini-tialised by first running for an extended period with pre-industrial(taken as 1860) concentrations of greenhouse gases. It is then run

1 http://www.ncof.co.uk/Coastal-Seas-Modelling.html.


forward using historic values for these gases and estimates ofanthropogenic sulphur emissions. From 2000 until 2100 the green-house gas concentration and sulphur emissions follow the SRESA1B emissions scenario (Nakicenovic and Swart, 2000). This is a‘business as usual’ scenario representing a world with significanteconomic growth and a balance between fossil fuel and non-fossilfuel energy sources. The HadCM3 model has an atmospheric reso-lution of 3.75� � 2.5� and 19 vertical levels (Pope et al., 2000) andan ocean resolution of 1.25� � 1.25� with 20 vertical z-levels(Gordon et al., 2000). It is run here as part of a perturbed physicsensemble (Murphy et al., 2009) of 17 model variants but onlyone ensemble member, with the standard HadCM3 parametersettings, is used in the current study.

The global climate model is used to provide lateral boundaryforcing and sea surface temperature (SST) forcing for the atmo-spheric regional model, HadRM3 (Murphy et al., 2009). HadRM3uses a rotated pole so that the model’s equator passes throughthe region being considered, and horizontal resolution of 0.22� �0.22� (�25 km). Like the driving global model it has 19 verticallevels. Parameter values within the regional model are set to corre-spond to those in the global model, allowing for scale dependen-cies where appropriate. This regional model has been extensivelyused over the European region to downscale variability and climatechange signals from the global model, for instance during the PRU-DENCE project (Déqué et al., 2007). In our current study HadRM3provides surface forcing for the shelf sea model, POLCOMS.

Fig. 2 shows annual mean air temperature (at 1.5 m), evapora-tion minus precipitation (E � P) and wind stress (magnitude) fromRCM-P (1961–1990) and the change RCM-F (2070–2099) minusRCM-P. It shows a mean increase in near surface air temperatureof 2.2 �C (excluding land regions). This is generally larger towardsthe east and south with the largest values in the Southern Bight ofthe North Sea, German Bight, Skaggerak and Kattergat. The fresh-water forcing shows that precipitation tends to dominate overevaporation over the European shelf seas in the present day(P > E) and there is an increase (in RCM-F compared with RCM-P)in this tendency in the future in the north and west regions, buta decrease in the south and east. The change in wind stress seenin Fig. 2 is small in many of the on-shelf regions of this domainand shows a modest decrease in the Irish Sea and the north andwest regions of the model. This change reflects a slight reductionin the strength of the storm track in the future time slice, and asubstantial southward movement of 4.25� in latitude (Lowe et al.,2009).

In this work we only consider one-way coupling between thisatmospheric climate model and the shelf sea model (described be-low). The intention is to move to two-way coupling in future workand hence explore dynamic sea–atmosphere coupling. For exampleSchrum et al. (2003) demonstrate a significant improvement in SSTin a fully coupled ocean–atmosphere–ice model of the North andBaltic Seas.

Freshwater discharges from the rivers flowing into this regionare taken from a hydrological model (run at the Centre for Ecologyand Hydrology; Bell et al., 2007) forced by the same HadRM3 sim-ulations described above. The projected river discharge rates inwinter and autumn consistently increases north of 48.5�N betweenthe future and past time slices by typically 21%. The fractional in-crease in discharge is smallest on the continental coast and largestin the relatively small flows from Great Britain to the English Chan-nel and Irish Sea. The summer discharges generally show a de-crease (e.g. by ��18% from continental Europe to the North Sea).The exceptions are the flows from Norway to the North Sea, whichincrease by �7% in summer. River flows from the coasts of westernFrance and northern Spain show a consistent decrease particularlyin the spring (�26%) and summer (�39%), compared with �4% inwinter.

3.2. The POLCOMS hydrodynamic model

The Atlantic Margin (AMM) application of POLCOMS (Holt andJames, 2001) has been run operationally by the UK Met Office since20021, using a 1/9� latitude by 1/6� longitude grid (�12 km) with 34levels in the vertical (Wakelin et al., 2009). In the present study thismodel is modified to accommodate forcing by HadRM3; specificallythe domain is reduced to that shown in Fig. 1, from its usual south-ern and western limits (40�N and 20�W respectively). The modelsimulations are then forced in a similar fashion to those in the oper-ational implementation. Three-hourly surface winds and pressureare used to drive the dynamics and 6-hourly turbulent and radiativeheat fluxes together with precipitation and evaporation fields pro-vide surface temperature and salinity boundary conditions. The tur-bulent heat fluxes are adjusted to take account of the differencebetween the HadRM3 (Thad) and the POLCOMS (Tpol) SST by the addi-tion of terms correcting the sensible and latent heat fluxes:

qs ¼ 1:42WðThad � TpolÞ and ql ¼ 4688WðEðThadÞ � EðTpolÞÞð2Þ

where E(T) is the specific humidity calculated following Gill (1982).These expressions are taken without modification from the opera-tional implementation this model (Siddorn et al., 2007).

Lateral open boundary conditions of temperature, salinity andresidual depth mean currents and sea surface height are derivedfrom a mean annual cycle of a 40-year (1960–1999) simulationof the AMM model, which in turn takes boundary conditions froma mean annual cycle of the Met Office FOAM North Atlantic Model(Bell et al., 2000). In the simulation of the future (RCM-P), the tem-perature and salinity profiles are modified to account for climatechanges in the Atlantic Ocean using results from HadCM3 PPE. Fif-teen tidal constituents from a North Atlantic tidal model (Flather,1976) are also used in lateral boundary conditions. Riverine fresh-water discharges use the hydrological model described above. Inthese experiments the exchange with the Baltic is treated as a sim-ple freshwater inflow based on a mean annual cycle. Hence no ac-count is made for changes in this exchange under future climateconditions. While the hydrological model data does includes riverinputs into the Baltic, the changes in these flows are significantlysmaller in magnitude than the variability of the exchange withthe Baltic. In the absence of a coupled North Sea-Baltic model to ac-count for future changes in this variability, we opt not to adjust theBaltic inflow in the future time slice. This approach is unlikely tosignificantly affect the results across most of the on-shelf modeldomain, but would almost certainly have a significant impactaround the coast of Norway.

Three model experiments using the same shelf sea model areconsidered here forced by both the Hadley Centre regional climatemodel (HadRM3) data and European Centre for Medium-rangeWeather Forecasting (ECMWF) re-analysis data (ERA-40):

1.
RCM-P Recent past 1961–1990 HadRM3 forcing 2. RCM-F Future scenario 2070–2098 HadRM3 forcing 3. ERA-P Recent past 1961–1990 ERA-40 forcing
In the experiments to simulate the recent past (RCM-P and ERA-P)the shelf sea model is initialised from rest with a present day tem-perature and salinity climatological initial condition. For the futurescenario experiment (RCM-F) a mean depth profile of the change intemperature and salinity between the future period and the simu-lated past is added to the shelf sea initial conditions and the bound-ary conditions described above (a single anomaly profile is used).This profile is taken from the ocean component of the OA-GCM used

http://www.ncof.co.uk/Coastal-Seas-Modelling.html


here (HadCM3 PPE). In both cases a single year spin-up is carriedout for POLCOMS (and discarded). This spin-up time is adequatefor the salinity across most of the continental shelf (Wakelinet al., 2009) and is more than sufficient for variables determinedby seasonal and higher frequency processes (including temperatureand currents). The re-analysis forced experiment serves as a guideto the validation process and as to how well the RCM forced shelfsea model reproduces recent past conditions.

3.3. Hydrodynamic model validation

The hydrography of the RCM-P near present day simulation isvalidated using temperature and salinity observations from theICES data base.2 Approximately 190,000 profiles are available inthe region considered here for the period 1961–1990. Previous vali-dation of POLCOMS hindcast simulations has focused on compari-sons of model and observations co-located in space and time (e.g.Holt et al., 2005). A direct comparison such as this is not availablefor climate model forced simulations because of the different phaseof natural variability in the climate simulations compared to theobservations. Hence, the approach adopted here is to average ob-served data from each month onto the model grid and comparethese with the corresponding average values for that month fromthe model. This provides a gridded monthly comparison betweenthe model and observed temperature and salinity; cells in anymonth where there are no observations are not included in the sta-tistics. An identical approach is used for RCM-P and ERA-P, and val-ues for surface and near bed temperature and salinity are consideredhere. The data available for validation is concentrated in the NorthSea with only sparse coverage in the Celtic Sea and open-ocean re-gions of the model. Inter-annual variability is not well sampled bythis data, with observations in many cells only coming from a smallnumber of years for any month. Hence caution is needed when com-paring these results to previous direct comparisons with contempo-rary observations.

Spatial correlations between monthly model surface fields andobservations are promising, being typically r2 � 0.7 for temperatureand r2 � 0.8 for salinity. However, a more detailed examination overfour water column depth ranges (D1: h > 600 m, D2: 600 > h >200 m, D3: 200 > h > 40 m, D4: h < 40 m) reveals some key differ-ences, summarized in Tables 1 and 2. These give mean (model minusobservations) and root-mean-squared (RMS) deviations, and thecost function (v2), defined by

v2 ¼ 1nr2

o

XðAm � AOÞ2 ð3Þ

where n is the number of cells in each depth class and month wheredata is available, Am,o are the gridded modelled and observedmonthly mean variables, and r2

o is the spatial variance of the grid-ded monthly mean observations, which reflects the spatial variabil-ity in each depth class. These statistics are combined into seasonalvalues.

Both the RCM-P and the ERA-P simulations show a negative sur-face temperature bias (model too cold). The RMS errors in temper-ature show little seasonality or variation between water depthclasses; although the open-shelf regions (depth class D3) are gen-erally the most accurately modelled. The salinity errors also showlittle seasonality, but in this case there is a marked variation withdepth class. Both ERA-P and RCM-P generally show a positive bias(model too saline) in surface salinity and a negative bias in near seabed salinity. An exception is the open-ocean depth class (D1),which shows a consistent negative bias. Again the open-shelf re-gions (D3) have the smallest RMS salinity errors. The shallowest

2 http://www.ices.dk/ocean/aspx/HydChem/HydChem.aspx.

water depth regions (class D4) show substantially increased RMSsalinity error, but are no more biased than the deeper water re-gions. This reflects the much higher degree of salinity variationin the shallow coastal regions, and when the cost function is con-sidered the salinity in near-coastal regions is seen to be bettermodelled (relative to the variability here) than in other depth clas-ses. Generally surface salinities and surface temperatures are wellmodelled, near bed temperatures less so and near bed salinitiesneed to be treated with some caution.

The experiment RCM-P gives generally poorer results than ERA-P in terms of RMS error and also some significant increases in bias.This is most noticeable for temperature in the open-shelf sea class(D3), where the RMS errors in surface and near bed values increaseby 20% and 30% respectively. Notable increases in salinity RMS er-ror are near the sea bed in D2 (15%) and D3 (16%). The salinities inD1, D2 at the surface and D4 at the sea bed are improved (by �5%)in RCM-P compared with ERA-P. The temperatures and salinityRMS errors in the open-ocean class (D1) differ only slightly (by�4% to 8%) between RCM-P and ERA-P. That ERA-P is more accu-rate than RCM-P is to be expected since the forcing model forERA-P (ERA-40) includes SST assimilation and hence the resultingheat fluxes would be expected to have smaller biases than thosefrom the HadRM3 forced simulation.

Across the whole model domain, the surface mean and RMS er-rors are �0.4 �C and 1.2 �C for ERA-P, and �0.5 �C and 1.4 �C forRCM-P respectively. Overall salinity errors are not significantly dif-ferent for both experiments: mean�0.4 p.s.u. and RMS 1.6 p.s.u. Ex-cept for a reduced bias in ERA-P, the near bed temperature errors aresomewhat greater than at the surface: mean and RMS errors are�0.2 �C and 1.4 �C for ERA-P, and �0.6 �C and 1.6 �C for RCM-Prespectively. Again near bed salinity errors are not significantly dif-ferent for both experiments: mean 0.2 p.s.u. and RMS 1.5 p.s.u. Thatmost of the cost function values listed in Tables 1 and 2 are less thanone indicates that the uncertainties are not generally greater thanthe natural spatial variability of the monthly mean observations,and hence this model has some skill in predicting spatial patterns.Assessing the models ability to reproduce inter-annual variabilityis the subject of on-going work (Holt et al., in preparation).

The RMS model errors seen in this comparison are similar tothose seen in several other assessments of operational model orre-analysis forced simulations (discussed in Holt et al., 2005),although the biases are generally greater. This may well reflect ali-asing of the inter-annual variability when the observations fromeach month are averaged onto the model grid. Overall, theseresults indicate that the nature of the forcing considered here(climate model instead of weather forecast model) does not undulycompromise the simulation (some biases accepted), but rather thatRCM-P is subject to similar uncertainties in the forcing fields andsub-grid scale parameterizations as previous simulations, e.g. inthe heat flux and vertical turbulence (see Holt and Umlauf,2008). Hence, we can conclude that the modelling system demon-strates some skill at simulating the shelf sea variables of interest.

4. Projected changes in temperature and salinity

The model simulations considered here allow us to explore insome detail how the currently observed warming trend on thenorthwest European continental shelf (Holliday et al., 2009) mightcontinue into the next century. The seasonal3 mean sea surfacetemperatures (Fig. 4) show a substantial warming between RCM-P(1961–1990) and RCM-F (2070–2098) throughout the year of�1.5–2.5 �C in the open-ocean, shelf edge regions and northern

3 Seasons are defined as: winter is December–February; spring is March–May;summer is June–August; and autumn is September–November.

http://www.ices.dk/ocean/aspx/HydChem/HydChem.aspx

Table 1Summary of model uncertainties for run ERA-P. Mean (model minus observations), root-mean-squared (RMS) errors and cost function (v; Eq. (3)) comparing monthly meanmodel results and gridded monthly mean observations. The water depth classes are: D1: h > 600 m, D2: 600 > h > 200 m, D3: 200 > h > 40 m, D4: h < 40 m, and the variables aresurface and near bed temperature (TS, TB) and salinity (SS, SB).

Depth Winter Spring Summer Autumn

Mean RMS v Mean RMS v Mean RMS v Mean RMS v

TS, �CD1 �1.04 1.53 0.68 �1.17 1.50 0.71 �0.59 1.08 0.44 �0.67 1.18 0.44D2 �0.20 1.41 0.72 �0.47 1.31 0.61 �0.61 1.41 0.61 �0.63 1.09 0.73D3 �0.21 0.85 0.55 �0.14 1.02 0.55 �0.04 1.17 0.64 �0.16 0.88 0.62D4 �0.48 1.30 0.76 �0.87 1.68 0.98 �0.56 1.49 0.82 �0.10 1.16 0.71

TB, �CD1 �0.45 2.45 0.83 �0.67 2.41 0.82 �0.22 2.45 0.85 �0.30 2.49 0.94D2 0.16 1.44 0.72 �0.47 1.30 0.66 �0.20 1.66 0.71 0.18 1.72 0.79D3 �0.23 0.81 0.62 �0.31 0.86 0.55 �0.23 1.03 0.54 �0.08 1.26 0.63D4 �0.44 1.38 0.91 �0.58 1.48 0.84 0.24 1.98 0.66 0.16 1.46 0.72

Ss, p.s.u.D1 �0.15 0.27 0.56 �0.11 0.88 0.84 �0.10 0.50 0.67 �0.08 0.89 0.92D2 0.62 1.21 0.77 0.62 1.54 0.65 1.09 2.16 0.77 1.01 1.74 0.96D3 0.16 0.79 0.49 0.23 0.98 0.47 0.49 1.32 0.65 0.26 0.95 0.58D4 0.35 2.47 0.54 0.49 2.25 0.41 0.76 2.60 0.49 0.30 2.28 0.47

SB, p.s.u.D1 �0.45 0.15 0.65 �0.67 0.13 0.63 �0.22 0.12 0.73 �0.30 0.90 0.99D2 0.16 0.22 1.23 �0.47 0.21 1.25 �0.20 0.19 1.20 0.18 0.21 1.34D3 �0.23 0.36 0.82 �0.31 0.32 0.76 �0.23 0.35 0.79 �0.08 0.33 0.84D4 �0.44 2.41 0.91 �0.58 3.06 1.18 0.24 3.19 1.16 0.16 2.78 1.05

Table 2Summary of model uncertainties for run RCM-P (see Table 1).

Depth Winter Spring Summer Autumn

Mean RMS v Mean RMS v Mean RMS v Mean RMS v

TS, �CD1 �1.17 1.63 0.72 �1.34 1.65 0.79 �0.54 1.11 0.45 �0.73 1.31 0.49D2 �0.97 1.57 0.80 �0.97 1.50 0.70 �0.64 1.53 0.67 �0.93 1.37 0.92D3 �0.84 1.17 0.75 �0.60 1.20 0.65 0.19 1.29 0.71 �0.19 1.01 0.71D4 �1.15 1.74 1.02 �1.00 1.78 1.03 �0.04 1.47 0.80 �0.39 1.20 0.74

TB, �CD1 �0.69 2.54 0.86 �0.83 2.46 0.84 �0.42 2.51 0.87 �0.65 2.66 1.01D2 �0.39 1.43 0.71 �1.01 1.58 0.80 �0.70 1.78 0.76 �0.39 1.73 0.79D3 �0.85 1.15 0.88 �0.97 1.27 0.81 �0.73 1.28 0.67 �0.46 1.37 0.68D4 �1.18 1.92 1.27 �0.86 1.73 0.98 0.41 2.08 0.70 �0.13 1.45 0.72

Ss, p.s.u.D1 �0.15 0.25 0.52 �0.10 0.89 0.85 �0.11 0.47 0.64 �0.09 0.86 0.89D2 0.42 1.05 0.67 0.63 1.63 0.68 1.06 2.15 0.77 0.81 1.51 0.83D3 0.19 0.82 0.52 0.29 1.08 0.52 0.46 1.32 0.65 0.23 0.91 0.55D4 0.46 2.34 0.52 0.57 2.34 0.43 0.47 2.67 0.50 0.07 2.25 0.46

SB, p.s.u.D1 �0.69 0.16 0.67 �0.83 0.14 0.64 �0.42 0.13 0.74 �0.65 0.90 0.99D2 �0.39 0.27 1.50 �1.01 0.24 1.42 �0.70 0.21 1.35 �0.39 0.23 1.51D3 �0.85 0.44 0.99 �0.97 0.38 0.91 �0.73 0.40 0.89 �0.46 0.37 0.93D4 �1.18 2.36 0.88 �0.86 2.95 1.14 0.41 3.09 1.13 �0.13 2.76 1.04


North Sea, and �2.5–4 �C in the Celtic, Irish and southern North Seas.The latter amounts to a 21st century trend of �0.3 �C/decade, withincreases generally being largest in the autumn. The bottom waterin seasonally stratified regions of the Celtic Sea and central NorthSea (not shown) are warming less rapidly than the surface, with aconsequent increase in this stratification (discussed below).

The results in RCM-P in winter and spring show the character-istic transport of warm water from the Celtic Sea and Biscay fol-lowing the shelf break north of Scotland and turning south intothe North Sea (see e.g. Holt and James, 2001). This pattern reflectsthe poleward shelf (Pingree et al., 1999) and slope (Burrows et al.,1999) currents. As noted above, the latter is an important controlon ocean-shelf exchange in this region. The transport pattern inSST is less clear in summer and autumn. A notable feature in thechange in SST between RCM-F and RCM-P is that the SST increase

is reduced (by �1 �C) around the shelf break north of 49�N and inthe northwest regions of the model. This reflects changes in the lat-eral heat transport and stratification discussed below, and resultsin a reduction in the temperature contrast between the shelf,shelf-slope and northern open-ocean regions, particularly in thewinter and spring.

A simple heat budget can be inferred by calculating the seasonalmean surface heat flux and the depth integrated change in heat byhorizontal transport (the divergence of the advective heat flux).The latter is not so meaningful in deep water (where vertical struc-ture must be accounted for), so is not considered at water depthgreater than 500 m.

Comparing the seasonal surface heat flux and the transport heatflux (Fig. 5) demonstrates that the former dominates over much ofthe domain (as simple arguments based on a well mixed sea also

Fig. 4. Seasonal mean sea surface temperature (SST) for RCM-P (1961–1990) and RCM-F (2070–2098) and the difference between them.

Fig. 5. Seasonal heat flux for RCM-P (1961–1990): surface heat flux (top) and depth integrated horizontal transport heat flux (bottom). Positive values indicate a flux of heatinto the water column.


show, see Section 2). However, the transport term generally warmsthe whole region. Notable exceptions, which show advective cool-ing, are: the Irish Sea in winter, areas of the English Channel andsouthern North Sea in summer and autumn, and the Norwegian

Trench in winter and spring. The Celtic Sea and most of the NorthSea show only small warming by horizontal heat transportthroughout the year. The main region warmed by the transportheat flux follows the shelf-edge current from Ireland, around west

Fig. 6. Change in seasonal heat flux between RCM-F (2070–2098) and RCM-P (1961–1990): surface (top) and depth integrated horizontal transport heat flux (bottom).


and north Scotland into the northern North Sea. Warmer wateralso enters the Norwegian Trench (at depth) from the northeastAtlantic during the summer and autumn.

When the differences between the future (2070–2098) and past(1961–1990) model experiments are examined (Fig. 6) they showthe surface heat flux increases substantially more in the winterthan the summer in the north of the region. The horizontal trans-port heating in the North Sea is reduced in all seasons except sum-mer, when it is increased. The horizontal transport warming northof Scotland is reduced in winter and spring, but increased in au-tumn. This reflects a reduction in the strength of the slope current(in winter/spring) seen here. In the Norwegian Trench there is astrong increase in advective warming in winter, but a reductionin the rest of the year. This tends to reduce the overall magnitudeof the advective heating/cooling in the future time slice, althoughin spring and autumn the pattern is less clear.

Annually integrating the heat budget on-shelf (h < 200 m)demonstrates a close balance (in RCM-P) between a warming advec-tive flux of 14.3 W m�2 and cooling surface flux, �14.4 W m�2. Thisgives a weak overall cooling trend of �0.11 �C/decade from 1960 to1991. In RCM-F this balance remains close but shifts to an advectiveflux of 9.9 W m�2 and a surface flux of �9.4 W m�2. The differencecorresponds to a warming trend of 0.55 �C/decade (i.e. somewhatgreater than the trend inferred above from the difference in temper-ature between RCM-F and RCM-P).

The conclusion that there is a drop in advective warming frompast to future, compensated by a greater increase in surface heat fluxis generally consistent with the results of Adlandsvik (2008). Theseare based on downscaling the Bergen Climate model using an appli-cation of Regional Ocean Modelling System (ROMS; Shchepetkin andMcWilliams, 2005) to the North Sea, and show that using lateralboundary conditions from a recent past control with surface forcingfrom a SRES A1B future scenario (2070–2075) leads to a larger in-crease in summer temperatures averaged across the North Sea, com-pared with a simulation with lateral condition also from the futurescenario. The detailed processes behind these changes are likely tobe substantially different, however, since Adlandsvik’s (2008) modelhas a reduced coverage (to the south and west) compared with thepresent model. Hence, changes to the northward transport of war-

mer water are dominated by boundary conditions it that modelrather than being directly modelled.

The potential for these changes in surface heat flux to changethe seasonal stratification can be explored by examining how thedifference between summer and winter heat fluxes changes fromRCM-P to RCM-F (Fig. 7). In the northern regions of the model, win-ter heat fluxes increase substantially more than summer indicatinga strong tendency to reduce seasonal thermal stratification. Thesame is true, but less marked, in Biscay. In the North Sea southof �58�N the change in seasonal heat flux difference is small, butincreasing southwards. So in the southern North Sea and CelticSea the changes in heat flux support an increase in seasonal strat-ification (see below). There is a strong increase in the seasonal heatflux difference in the English Channel, but much of this region isstrongly tidally mixed so the effect is only on the seasonal temper-ature cycle and not the stratification. The potential for the changesin advective heat flux to influence the stratification requires athree-dimensional analysis that is left for future work.

The seasonal mean salinity distribution in RCM-P (Fig. 8)divides into three distinct regions: highest salinity water in south-west of the domain, intermediate salinity water in the North, Irishand Celtic Seas and substantially lower salinity water in the Nor-wegian Trench and southeast North Sea. The latter results fromout-flow from the Baltic and the rivers of continental Europe. Aswith the temperature this distribution shows, in winter and spring,the transport of more saline water around the shelf break carriedby the slope and shelf currents.

Comparing RCM-P and RCM-F shows a substantial freshening ofthe surface waters of the northeast Atlantic and the North Sea by�0.2 p.s.u. in RCM-F. In the open-ocean this significantly reducesthe north–south salinity gradient in this time slice and hence thepoleward slope current transport is less obvious in RCM-F. This isan issue that deserves more detailed investigation in the contextof ocean-shelf exchange. In contrast to the North Sea, the Celticand Irish Seas show a significantly weaker change in sea surfacesalinity. The only region showing a consistent increase in salinityis the west coast of France, owing to a substantial reduction in riverdischarge in this region (ranging from ��4% in winter to ��40% insummer).

Fig. 7. The change between RCM-F and RCM-P in the seasonal difference (summer minus winter) in surface heat flux.


The relative importance of the surface, riverine and oceanicforcing on the shelf sea salinity can be inferred from the steady-state salinity balance (see Young and Holt, 2007). The mean (on-shelf) salinity changes from 34.7 to 34.5 p.s.u. from RCM-P toRCM-F. This arises primarily from an increase in the precipitationminus evaporation term from 0.0074 Sv (1 Sv = 106 m3 s�1) to0.009 Sv compared to a smaller increase in river flux from0.0122 Sv to 0.0126 Sv. There is also a reduction in the salinity ofthe oceanic water transported onto the shelf (also by �0.2 p.s.u.),and a steady-state balance implies an associated volume flux ofwater from the open-ocean onto the shelf of 1.3 Sv in RCM-P and1.4 Sv in RCM-F (i.e. not significantly different compared with nat-ural variability). While the precise values depend on the details ofthe transport processes, this analysis demonstrates that changes inatmospheric salinity forcing dominate over changes in riverineforcing on the shelf scale. The same is unlikely to be true in the re-gions directly effect by the river out-flow (e.g. �20 km from thecoast of continental Europe).

5. Projected changes in water column stratification

Profiles of temperature and salinity at two locations (Fig. 3), onein the central North Sea (NS) and one in the northeast Atlantic(NEA), demonstrate the qualitative difference in the projected ef-fects of climate change between shelf seas and open-ocean.

In the central North Sea the profiles show a qualitatively similarpicture for RCM-P and RCM-F. The most noticeable difference be-tween them is that the stratified period is somewhat longer inRCM-F (this is quantified below). Between RCM-P and RCM-F, thetemperature drop across the thermocline increases slightly from

8.4 �C to 8.7 �C and the across halocline salinity increase changesfrom 0.13 to 0.15 p.s.u..

In the open-ocean, however, the change is more dramatic. It isapparent that run RCM-F has a substantially shallower winter hal-ocline and thermocline and both are substantially sharper than inRCM-P. The halocline is sharper and sits above the thermocline.This arises from the persistently increased precipitation forcing(Fig. 2). The temperature drop across the summer thermocline isabout the same in both RCM-P and RCM-F (�3.8 �C), however inthis case there is a substantial increase in near surface salinitystratification, from 0.06 to 0.13 p.s.u. over the top 64 m.

It is interesting to compare the results at these two locations inPOLCOMS with the corresponding results (albeit on a much coarsergrid) from the global climate model used to provide boundary con-ditions (HadCM3 PPE; Fig. 9). There is generally qualitative agree-ment between the two, particularly in the introduction, in thefuture time slice, of a shallow halocline in the northeast Atlantic.This persists throughout the year and is apparent in both models.The salinity in the North Sea is greatly reduced in HadCM3 PPE,presumably owing to a much increased flushing time in the globalclimate model. The stratification in HadCM3 PPE in the North Seatends to extend deeper and to persist longer, owing to the lack oftidal mixing (discussed further below).

To characterise the seasonal and spatial distribution of stratifi-cation we consider the potential energy anomaly (PEA) defined as:

/ ¼ � gh

Z 0

z¼�hzðqðT; SÞ � qðT; SÞÞdz ð4Þ

where h is the water depth (here the integration is limited to400 m), g is the gravitational acceleration, q the density and z the

Fig. 8. Seasonal mean sea surface salinity (SSS) for RCM-P (1961–1990) and RCM-F (2070–2098) and the difference between them.


(positive up-wards) vertical coordinate. An overbar indicates anaverage over the same depth as the integration. Temperature andsalinity components of potential energy anomaly (/T,S) can be de-fined by recalculating / using the depth mean salinity and temper-ature respectively. For convenience the potential energy anomaly isdefined to be positive for stable stratification. Hence, the physicalinterpretation of this metric is the potential energy (per unit depth)that must be added to completely mix to the sea bed or the top400 m of the water column (whichever is shallower). We choose adepth limit of 400 m since it allows a consistent comparison be-tween conditions on- and off-shelf, while still revealing changesin deep winter mixing.

The potential energy anomaly in RCM-P shows a distinct sea-sonal cycle. On-shelf waters are well mixed in winter and thenortheast corner of the domain is mixed to below 400 m. The otherregions show weak stratification, strongest in the Skagerrak andBiscay. In spring, the stratification in the open-ocean regions re-duces, while it increases on-shelf and in the Norwegian Trench.Seasonal stratification is established in summer. In autumn strati-fication in the open-ocean tends to increase while that on-shelfdecreases.

The potential energy anomaly gives a measure of the enduranceof stratification to mixing over the whole water column (or to400 m). By this metric the on-shelf stratification is significantlyweaker than in the open-ocean and Norwegian Trench because ti-dal mixing leads to a well mixed lower layer and can erode thebase of the thermocline. This does not necessarily show differencesin the sharpness of the thermocline (i.e. its effectiveness as a bar-rier to local mixing); indeed mixing from below tends to sharpenthe thermocline. This highlights the need to consider a wider rangeof stratification parameters than can be treated here (e.g. thermo-

cline thickness, maximum gradient and depth); defining thesemetrics is the subject of on-going work.

Comparing the seasonal mean potential energy anomaly(Fig. 10) between the future time slice (RCM-F) and the recent past(RCM-P) shows the future forcing produces a substantial increasein stratification across the whole region, except in those areas thatare permanently well mixed; and that this increase is largest in theautumn. The extent of the stratification (indicated on the figure bythe 10 J m�3 contour) does not greatly change, but where stratifica-tion does occur, its strength increases under the future forcing. Theincrease in stratification is substantially larger in the open-ocean(typically 20–50%) than the shelf regions (typically 20%).

On the continental shelf, the temperature fraction (/T//;Fig. 11) is the dominant component of the PEA and contributesthe greatest increase between RCM-F and RCM-P. The fractionalsalinity component of the PEA can be inferred from Fig. 11 since/S// � 1 � /T// and the change between time slices, D/S//� �D/T//. In RCM-P the salinity component makes a significantcontribution to the total around the Norwegian Trench, near thecoast of continental Europe and in the Skaggerrak. Its contributionto the change between RCM-F and RCM-P is patchy and often tend-ing to reduce the overall increase seen in Fig. 10 (apparent whereD/T// > 1.

In the open-ocean the temperature component in RCM-P againdominates the spring to autumn near-surface stratification. In thefuture time slice (RCM-F), however, salinity has a much moreimportant role in near-surface stratification off-shelf. In summerand autumn the salinity component is still less than the tempera-ture, but in winter and spring it makes the dominant contribution.This is also the case for RCM-P in winter, but in RCM-F the absolutemagnitude of the PEA off-shelf in winter is significantly greater. In

Fig. 9. Time series of temperature and salinity profiles for site NEA and NS from the HadCM3 PPE simulation used for initial and boundary conditions.

4 www.nodc.noaa.gov/OC5/WOA05/pr_woa05.html.


fact the temperature component off-shelf in winter is negative; theincreased salinity stratification supports cooler water overlyingwarmer. This reflects the shallower pycnocline depth over whichwinter cooling acts. Hence, the change in near-surface stratifica-tion between RCM-F and RCM-P is dominated by the salinity com-ponent in the open-ocean, with temperature change tending toreduce the stratification (as seen above). An examination of wintermixed layer depths (not shown) demonstrates that regions of deepwinter mixing seen in the northwest region of the domain in RCM-P are absent from RCM-F. Winter mixed layer depths in this regionin RCM-F are much more similar to those in the south of thedomain.

To put these results in the context of previous models of oceanicstratification we compare the PEA (Fig. 12) in POLCOMS with re-sults from the unperturbed member of the HadCM3 PPE (used to

defined the change in boundary temperature and salinity betweenthe future and past time slices) and six models used in the IPCCAR4 (Randall et al., 2007) at the two sites shown on Fig. 1. Hereonly six models are considered for clarity of presentation; themodels are chosen to given a range of storm track behaviour andclimate sensitivities (Lowe et al., 2009). Observations are providedby the World Ocean Atlas4 at NEA and the ICES database at NS. Atthe northeast Atlantic site (NEA) all models cluster around theobservations. A significant deviation from the observations in somemodels (e.g. HadCM3 and CCCMA CGCM) is the tendency to overes-timate wintertime stratification. While POLCOMS does not show thistendency, it is not obvious whether POLCOMS gives significantlyimproved results at NEA for the rest of the year. The change between

http://www.nodc.noaa.gov/OC5/WOA05/pr_woa05.html

Fig. 10. Seasonal mean potential energy anomaly in RCM-P (1961–1990), RCM-F (2070–2098) and the difference between them. The white lines show the 10 J m�3 contour,indicating the extent of the stratified region; on-shore of this tends to be well mixed.

5 Here defined as a sustained surface to bottom density difference equivalent to0.5 �C and a mixed layer of shallower than 50 m.


RCM-F and RCM-P at this location divides the models into threegroups. The two HadCM3 models show a substantial increase instratification throughout the year, but particularly in the autumn.Two IPCC models (CCCMA CGCM and MIUB), along with POLCOMS,show a weaker increase but with a similar seasonal variation. Theother three models all show only weak changes in stratification.

At NS the pattern is very different. POLCOMS gives by far thebest agreement with the observations, whereas the other modelstend to overestimate the stratification, generally in summer, butalso in autumn and winter in some models. The exceptions areGISS ER and MIUB, which show no stratification at NS. The differ-ence between POLCOMS and these models can be attributed toPOLCOMS being the only one that includes tidal mixing, an impor-tant determinant of the seasonal stratification cycle here. Whenthe changes between RCM-P and RCM-F are considered GISS-EHand HadCM3 generally agree with POLCOMS, but the other differwidely.

POLCOMS exhibits a significantly reduced change (RCM-Fminus RCM-P) in stratification than the HadCM3 PPE model usedfor boundary conditions, with the difference being larger in theopen-ocean than on-shelf. For example, the summer change inPEA seen in HadCM3 PPE is 52% for the North East Atlantic and32% for the North Sea, compared with 27% and 19% respectivelyfor POLCOMS. This difference arises from POLCOMS being eddypermitting in deep waters and the inclusion of tides on the shelf.The on-shelf increase in stratification results from several factors:the increased expansivity as the water warms, changes in the hor-izontal heat transport (particularly in the northern North Sea) andchanges in the seasonal heat flux in the southern North Sea andCeltic Sea. This is in contrast to the changes in the open-oceanstratification, which are dominated by surface salinity forcing.

The general conclusion is, therefore, that tidally active shelf seasare likely to experience changes in stratification under future cli-mate conditions that are qualitatively different to changes in theopen-ocean, and generally the increase is less dramatic.

It should be born in mind that there are several processes,important to vertical mixing and shelf sea stratification, are not re-solved here and hence their modification by climate change cannotbe accounted for. Examples include internal tide generation (bothat the shelf break and at on-shelf banks) and strain induced peri-odic stratification in coastal river plumes.

While the increase in the strength of stratification is seen hereto be weaker in shelf seas than the open-ocean, these changesmay still have important implications particularly when/wherethe stratification is weak. For example spring phytoplanktonblooms can be triggered by very small increases in water columnstability. To explore this further, we examine the changes in thetiming of the onset of seasonal stratification5 in the spring and ofthe breakdown in the autumn. Fig. 13 shows the timing (in daysfrom 1st January) of the onset of persistent seasonal stratificationand its breakdown for RCM-P and RCM-F, and the total number ofstratified days. It demonstrates that seasonal stratification occurs�5 days earlier in the future scenario (typically the 5th April) thanthe recent past (typically 10th April) across the whole shelf, with lar-ger changes in the shelf break region west of the Celtic Sea. Thebreakdown of stratification in the autumn occurs about 10 days later(in the future time slice compared with the recent past) across muchof the region (accounting for the stronger SST warming trend in au-tumn noted above). However, the pattern is patchier than the onset

Fig. 11. Seasonal mean potential energy anomaly (temperature fraction, /T//) in RCM-P (1961–1990), RCM-F (2070–2098) and the difference between them. The fractionalsalinity component of the PEA can be inferred from /S// � 1 � /T// and D(/S//) � �D(/T//).


and there are a number of regions that show little variation. Theseinclude the central North Sea, the Celtic Sea and the sea east of Scot-land. Hence, the overall increase in the duration of the stratified per-iod is typically 15 days except in these regions where it closer to5 days. In some near-coastal regions the pattern is very different.In the German Bight from the Netherland to Denmark and off thewest coast of France, the onset of stratification is delayed by�10 days and there is little change in the timing of the end of strat-ification. This results in a reduction of the total stratified period andarises from a reduction in river discharges in spring and summer(described above).

6. Discussion and conclusions

The most noticeable and robust impact of climate change on thenorthwest European shelf in the next century is a temperature in-crease. From these simulations this amounts to about 1.5–4 �C,depending on location, by the end of the 21st century in the SRESA1B emission scenario, with the increase being larger in shelf seasthan the open-ocean. The difference in temperature increase be-tween shelf and open-ocean apparent in these simulations occursbecause shelf seas are shallower than the winter mixed layerdepths of the open-ocean. However, this increase is not propor-tionate with decreasing depth, as would be expected if the surfaceheat flux where to simply increase. This arises because of the ef-fects of surface temperature on the heat flux and the effects ofthe horizontal heat transport. A reduction in salinity of�0.2 p.s.u. is also suggested, but higher uncertainties in the forcing(precipitation, evaporation and river flows) and the ocean-shelftransport imply this conclusion is less robust than the projectedtemperature increase. In the central North Sea (site NS; Fig. 1)

the POLCOMS model gives a temperature increase of 2.7 �C, com-pared with 2.8 �C for the forcing HadCM3 PPE model and the range1.3–2.8 �C for the other IPCC AR4 models used in Fig. 12. The cor-responding changes in salinity are �0.26 for POLCOMS comparedwith �0.6 for HadCM3 PPE and a range of +0.3 to �0.75 for theother models. Hence, the changes of temperature are similar inPOLCOMS to the forcing model, but the changes in salinity differsubstantially.

These simulations specifically omit two-way coupling betweenthe shelf sea model and the atmospheric model. An example ofwhere this may be significant is in the dynamic effect of thenorth–south temperature gradient in the northeast Atlantic indriving the poleward slope current. If this gradient is reduced un-der future forcing then so might the northward heat transport. Thispotentially could provide a negative feedback on the atmospherictemperatures, depending on the relative time scales of air–sea heatexchange and atmospheric heat transport. However, investigatingsuch feedbacks would ideally require a wider area model of theNorth Atlantic than we consider here.

Several of the results presented here (particularly Figs. 7 and 8)show a marked differences between the boundary condition valuesand the internal POLCOMS simulation. This reflects large differ-ences in the response of the vertical structure to changes in theforcing between POLCOMS and the HadCM3 model used for oceanboundary conditions and possibly also differences in surface fluxesforcing in HadCM3 and HadRM3. This mismatch at the boundary isinevitable when using models of such different resolution and pro-cess representation; it may be that the choice of boundary condi-tion formulation needs to be re-addressed in this context. Thismismatch is unlikely to have a great effect across the model do-main, particularly on the continental shelf where the effects are

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likely to be small. This has been demonstrated by experimentswith a variety of different sources of boundary condition informa-tion (Wakelin et al., 2009). Improving the treatment of the oceanicinfluence of the North Atlantic and of the exchange with the Balticin this model is the subject of on-going work.

Particular attention is paid here to validating the RCM forcedsimulations using mean hydrographic data, compared with a sim-ilar validation for the ERA-40 forced simulation. Accepting that thiscomparison is less accurate than a direct comparison with contem-porary data and the methodologies for validating climate modelforced shelf sea simulations require further consideration, theERA-P simulation generally agrees better with monthly meanobservations than RCM-P (the RMS errors in RCM-P can be up to30% greater than ERA-P). The open-shelf regions are the most reli-ably modelled, while the open-ocean and near-coastal regions lessso. The costs-functions (Tables 1 and 2) are generally less than one,indicating the model has some skill in reproducing spatialvariability.

These simulations suggest an increase in stratification in theseshelf seas over the 21st century, but that this is weaker than inthe open-ocean. These results show a substantial increase in nearsurface (�200 m) salinity stratification in the deep-ocean. This actsto reduce deep winter mixing and increase seasonal stratification;a mechanism that is not applicable to shelf seas that are wellmixed in winter. Preliminary investigations with the European Re-gional Seas Ecosystem Model coupled to POLCOMS (Allen et al.,2001) demonstrate that this change in stratification might leadto a substantial reduction in primary production in the deep-oceannot seen on the shelf. However, this conclusion is subject to thehigh level of uncertainty associated with the salinity forcing. Thechange in stratification in the North Atlantic in the forcing model(HadCM3 PPE) is at the upper end of the distribution shown inFig. 12 but the resulting POLCOMS stratification is closer to thecentre of the distribution. The POLCOMS model validates wellagainst observation in the central North Sea, in contrast to the cli-mate models considered here. This is most likely due to the lack of

Fig. 13. Mean timing of seasonal stratification from RCM-P (1961–1990), RCM-F (2070–2098) and the difference between them. The figure shows day of the year (1st Januaryis day 1) when persistent seasonal stratification starts and ends, and the total number of stratified days.


tidal mixing in the climate models; methods of incorporating thisprocess into a coarse resolution climate model are discussed in Al-len et al. (2010).

These results suggest that by the end of the 21st century, sea-sonal stratification might occur �5 days earlier in the year andbreak down later by typically 5–10 days, and hence the durationof the stratified period is increased across the whole shelf. Particu-lar exceptions are regions where stratification is directly influ-enced by river discharge. In these cases changes in the river flowaffect the timing of stratification, for example delaying it on theNorth Sea coast of continental Europe. On average, the locationof fronts and the extent of the stratified regions are not seen togreatly change in the future simulation.

In summary these simulations demonstrate that the northwestEuropean continental shelf seas are likely to experience the effectsof climate change over the next century in a very different way tothe open-ocean. The simulations have demonstrated the ability ofa regional shelf sea model to examine future climate change, andthat the increased resolution and process representation providedby such models gives significant advantages over the global cli-mate models used in IPCC AR4. However, large uncertainties re-main and cannot yet be quantified. For example, the increase intemperature seen in these experiments is generally greater thanthat presented by Adlandsvik (2008), discussed above. In that casethe change in SST (between two similar time slices) in spring was1.5–2 �C in the central North Sea, compared with 2–2.5 �C for

these simulations. Both models agree that the greatest SST in-crease occurs in the German Bight by up to 3 �C in Adlandsvik’s(2008) results and 4 �C in the results presented here. However,the timing of the maximum is different, being in spring and au-tumn respectively. These differences most likely arise from differ-ences in the climate model forcing: the high resolution HadRM3atmospheric model, downscaling the HadCM3 model consideredhere versus the coupled ocean–atmosphere Bergen Climate Model,and details in the model dynamics therein. The two shelf seamodels have technical and configuration differences (e.g. in reso-lution and area covered), but these are unlikely to account forthese particular differences in results, especially since both stud-ies agree that the German Bight is removed from direct oceanicinfluence. The discrepancy between these two cases clearly dem-onstrates the need to explore the uncertainty associated withthese future projections. This requires us to build an ensembleof simulations that can account for a range of factors: the uncer-tainty in future emissions scenarios, the structural and parameteruncertainty in the forcing ocean–atmosphere model, and thestructural and parameter uncertainty in the regional shelf seamodel. Simulations and observations of past conditions (in thiscontext the last 50 years) may allow us to weight ensemble mem-bers according to some measure of their reliability. However,designing such an ensemble that can envelope the range of possi-ble futures in a practical fashion presents us with an extremelychallenging task.


Acknowledgements

This works forms part of the marine component of UK ClimateProjections 09 (http://ukcp09.defra.gov.uk/, where a subset of thedata used in this work is available).

Holt and Wakelin are supported by the NERC core programmein marine science, Oceans 2025. Holt is also support by Theme 6of the EC seventh framework program through the Marine Ecosys-tem Evolution in a Changing Environment (MEECE No. 212085)Collaborative Project. Wakelin is also supported by the NERCNational Centre for Earth Observation. Lowe was supported bythe Joint DECC and Defra Integrated Climate Programme – DECC/Defra (GA01101).

References

Adlandsvik, B., 2008. Marine downscaling of a future climate scenario for the NorthSea. Tellus Series A – Dynamic Meteorology and Oceanography 60, 451–458.

Adlandsvik, B., Bentsen, M., 2007. Downscaling a twentieth century global climatesimulation to the North Sea. Ocean Dynamics 57, 453–466.

Allen, J.I., Blackford, J., Holt, J.T., Proctor, R., Ashworth, M., Siddorn, J., 2001. A highlyspatially resolved ecosystem model for the North West European continentalshelf. SARSIA 86, 423–440.

Allen, J.I., Aiken, J., Anderson, T.R., Buitenhuis, E., Cornell, S., Geider, R., Haines, K.,Hirata, T., Holt, J., Le Quéré, C., Hardman-Mountford, N., Ross, O.N., Sinha, B.,While, J., 2010. Marine ecosystem models for earth systems applications: theMarQUEST experience. Journal of Marine Systems 81, 19–33.

Beaugrand, G., Reid, P.C., Ibanez, F., Lindley, J.A., Edwards, M., 2002. Reorganizationof North Atlantic marine copepod biodiversity and climate. Science 296, 1692–1694.

Bell, M.J., Forbes, R.M., Hines, A., 2000. Assessment of the FOAM global dataassimilation system for real time operational ocean forecasting. Journal ofMarine Systems 25, 1–22.

Bell, V.A., Kay, A.L., Jones, R.G., Moore, R.J., 2007. Development of a high resolutiongrid-based river flow model for use with regional climate model output.Hydrology and Earth System Sciences 11 (1), 532–549.

Bindoff, N.L., Willebrand, J., Artale, V., Cazenave, A., Gregory, J., Gulev, S., Hanawa, K.,LeQuere, C., Levitus, S., Nojiri, Y., Shum, C.K., Talley, L.D., Unnikrishnan, A.S.,2007. Observations: oceanic climate change and sea level. In: Solomon, D.Q.S.,Manning, M., Chen, Z., Marquis, M., Averyt, K.B., Tignor, M., Miller, H.L. (Eds.),Climate Change 2007: The Physical Science Basis. Contribution of WorkingGroup I to the Fourth Assessment Report of the Intergovernmental Panel onClimate Change. Cambridge University Press, Cambridge, UK and New York, NY,pp. 385–432.

Bowers, D.G., Simpson, J.H., 1987. Mean positions of tidal fronts in European ShelfSea. Continental Shelf Research 7, 35–44.

Burrows, M., Thorpe, S.A., Meldrum, D.T., 1999. Dispersion over the Hebrides andShetland shelves and slopes. Continental Shelf Research 19, 49–55.

Chapman, D.C., 2000. Boundary layer control of buoyant coastal currents and theestablishment of a shelfbreak front. Journal of Physical Oceanography 30, 2941–2955.

Connor, D.W., Gilliland, P.M., Golding, N., Robinson, P., Todd, D., Verling, E., 2006.UKSeaMap: the Mapping of Seabed and Water Column Features of UK Seas.Joint Nature Conservation Committee, Peterborough.

Danielssen, D.S., Edler, L., Fonselius, S., Hernroth, L., Ostrowski, M., Svendsen, E.,Talpsepp, L., 1997. Oceanographic variability in the Skagerrak and NorthernKattegat, May–June, 1990. ICES Journal of Marine Science 54, 753–773.

Déqué, M., Rowell, D.P., Luthi, D., Giorgi, F., Christensen, J.H., Rockel, B., Jacob, D.,Kjellström, E., de Castro, M., van den Hurk, B., 2007. An intercomparison ofregional climate simulations for Europe: assessing uncertainties in modelprojections. Climatic Change 81 (Suppl.), 53–70.

Elliott, A.J., Clarke, T., 1991. Seasonal stratification in the northwest European shelfseas. Continental Shelf Research 11 (5), 467–492.

Evans, G.L., Williams, P.J.L., Mitchelson-Jacob, E.G., 2003. Physical andanthropogenic effects on observed long-term nutrient changes in the IrishSea. Estuarine Coastal and Shelf Science 57, 1159–1168.

Fairall, C.W., Bradley, E.F., Hare, J.E., Grachev, A.A., Edson, J.B., 2003. Bulkparameterization of air–sea fluxes: updates and verification for the COAREalgorithm. Journal of Climate 16, 571–591.

Flather, R.A., 1976. A tidal model of the northwest European continental shelf.M’emoires de la Soci’et’e Royale des Sciences de Li‘ege 10, 141–164.

Gill, A.E., 1982. Atmosphere–Ocean Dynamics. Academic Press, New York.Gomez-Gesteira, M., deCastro, M., Alvarez, I., 2008. Coastal sea surface temperature

warming trend along the continental part of the Atlantic Arc (1985–2005).Journal of Geophysical Research 113. doi:10.1029/2007JC004315.

Gordon, C., Cooper, C., Senior, C.A., Banks, H., Gregory, J.M., Johns, T.C., Mitchell,J.F.B., Wood, R.A., 2000. The simulation of SST, sea ice extents and ocean heattransports in a version of the Hadley Centre coupled model without fluxadjustments. Climate Dynamics 16, 147–168.

Holliday, N.P., Hughes, S.L., Bacon, S., Beszczynska-Moller, A., Hansen, B., Lavin, A.,Loeng, H., Mork, K.A., Osterhus, S., Sherwin, T., Walczowski, W., 2008. Reversal

of the 1960s to 1990s freshening trend in the northeast North Atlantic andNordic Seas. Geophysical Research Letters 35.

Holliday, N.P., Hughes, S.L., Beszczynska-Moller, A., (Eds.) 2009. ICES Report onOcean Climate.

Holt, J.T., James, I.D., 2001. An s-coordinate density evolving model of the NorthWest European Continental Shelf. Part 1 model description and densitystructure. Journal of Geophysical Research 106 (C7), 14015–14034.

Holt, J.T., Proctor, R., 2008. The seasonal circulation and volume transport on thenorthwest European continental shelf: a fine-resolution model study. Journal ofGeophysical Research 113. doi:10.1029/2006JC004034.

Holt, J., Umlauf, L., 2008. Modelling the tidal mixing fronts and seasonalstratification of the Northwest European continental shelf. Continental ShelfResearch 28, 887–903.

Holt, J.T., Allen, J.I., Proctor, R., Gilbert, F., 2005. Error quantification of a highresolution coupled hydrodynamic-ecosystem coastal-ocean model: part 1model overview and assessment of the hydrodynamics. Journal of MarineSystems 57, 167–188.

Holt, J., Wakelin, S., Huthnance, J., 2009. Down-welling circulation of the northwestEuropean continental shelf: a driving mechanism for the continental shelfcarbon pump. Geophysical Research Letters 36.

Holt, J., Wakelin, S.L., Hopkins, J., Proctor, R., Hughes, S., Holliday, N.P., Tattersall,G.R., Ward, B., in preparation. Multi-decadal variability of the temperature ofthe northwest European continental shelf: a model-data synthesis..

Horsburgh, K.J., Hill, A.E., Brown, J., Fernand, L., Garvine, R.W., Angelico, M.M.P.,2000. Seasonal evolution of the cold pool gyre in the western Irish Sea. Progressin Oceanography 46, 1–58.

Huthnance, J.M., 1984. Slope currents and jebar. Journal of Physical Oceanography14, 795–810.

Huthnance, J.M., 1995. Circulation, exchange and water masses at the oceanmargin: the role of physical processes at the shelf edge. Progress inOceanography 35, 353–431.

Huthnance, J.M., 1997. North Sea interaction with the North Atlantic Ocean.Deutsche Hydrographische Zeitschrift 49, 153–162.

Huthnance, J.M., Holt, J.T., Wakelin, S.L., 2009. Deep ocean exchange with west-European shelf seas. Ocean Science 5, 621–634.

Hydes, D.J., Gowen, R.J., Holliday, N.P., Shammon, T., Mills, D., 2004. External andinternal control of winter concentrations of nutrients (N, P and Si) in north-westEuropean shelf seas. Estuarine Coastal and Shelf Science 59, 151–161.

Lane, A., Prandle, D., 1996. Inter-annual variability in the temperature of the NorthSea. Continental Shelf Research 16, 1489–1507.

Levitus, S., Antonov, J.I., Timothy, P.B., Stephens, C., 2000. Warming of the WorldOcean. Science 287, 2225–2229.

Lowe, J.A., Howard, T.P., Pardaens, A., Tinker, J., Holt, J., Wakelin, S., Milne, G., Leake,J., Wolf, J., Horsburgh, K., Reeder, T., Jenkins, G., Ridley, J., Dye, S., Bradley, S.,2009. UK Climate Projections Science Report: Marine and Coastal Projections.Chaos. Met Office Hadley Centre, Exeter, UK.

Meier, H.E.M., 2006. Baltic Sea climate in the late twenty-first century: a dynamicaldownscaling approach using two global models and two emission scenarios.Climate Dynamics 27, 39–68.

Murphy, J.M., Sexton, D.M.H., Jenkins, G.J., Boorman, P.M., Booth, B.B.B., Brown, C.C.,Clark, R.T., Collins, M., Harris, G.R., Kendon, E.J., Betts, R.A., Brown, S.J., Howard,T.P., Humphrey, K.A., McCarthy, M.P., McDonald, R.E., Stephens, A., Wallace, C.,Warren, R., Wilby, R., Wood, R.A., 2009. UK Climate Projections Science Report:Climate Change Projections. Met Office Hadley Centre, Exeter, UK..

Nakicenovic, N., Swart, R. (Eds.), 2000. Special Report on Emissions Scenarios. ASpecial Report of Working Group III of the Intergovernmental Panel on ClimateChange. Cambridge University Press, Cambridge, UK and New York, NY,USA.

Nicholls, R.J., 2004. Coastal flooding and wetland loss in the 21st Century: changesunder the SRES climate and socio-economic scenarios. Global EnvironmentalChange 14 (1), 69–86.

Pingree, R.D., Griffiths, D.K., 1977. Tidal fronts on the shelf seas around the BritishIsles. Journal of Geophysical Research 3 (C9), 4615–4622.

Pingree, R.D., Sinha, B., Griffiths, C.R., 1999. Seasonality of the European slopecurrent (Goban Spur) and ocean margin exchange. Continental Shelf Research19, 929–975.

Pope, V.D., Gallani, M.L., Rowntree, P.R., Stratton, R.A., 2000. The impact of newphysical parameterizations in the Hadley Centre climate model: HadAM3.Climate Dynamics 16 (2–3), 123–146.

Pugh, D.T., 1987. Tides, Surges and Mean Sea Level: A Handbook for Engineers andScientist. John Wiley and Sons.

Randall, D.A., Wood, R.A., Bony, S., Colman, R., Fichefet, T., Fyfe, J., Kattsov, V., Shukla,J., Srinivasan, J., Stouffer, R.J., Sumi, A., Taylor, K.E., 2007. Climate models andtheir evaluation. In: Solomon, D.Q.S., Manning, M., Chen, Z., Marquis, M., Averyt,K.B., Tignor, M., Miller, H.L. (Eds.), Climate Change 2007: The Physical ScienceBasis. Contribution of Working Group I to the Fourth Assessment Report of theIntergovernmental Panel on Climate Change. Cambridge University Press,Cambridge, UK and New York, NY, pp. 385–432.

Schrum, C., Hubner, U., Jacob, D., Podzun, R., 2003. A coupled atmosphere/ice/oceanmodel for the North Sea and the Baltic Sea. Climate Dynamics 21, 131–151.

Sharples, J., Simpson, J.H., 1995. Semi-diurnal and longer period stability cycles inthe Liverpool Bay region of freshwater influence. Continental Shelf Research 15(2), 295–313.

Sharples, J., Ross, O.N., Scott, B.E., Greenstreet, S.P.R., Fraser, H., 2006. Inter-annualvariability in the timing of stratification and the spring bloom in the North-western North Sea. Continental Shelf Research 26, 733–751.

http://ukcp09.defra.gov.uk/

http://dx.doi.org/10.1029/2007JC004315

http://dx.doi.org/10.1029/2006JC004034


Shchepetkin, A.F., McWilliams, J.C., 2005. The regional oceanic modeling system(ROMS): a split-explicit, free-surface, topography-following-coordinate oceanicmodel. Ocean Modelling 9, 347–404.

Siddorn, J.R., Allen, J.I., Blackford, J.C., Gilbert, F.J., Holt, J.T., Holt, M.W., Osborne, J.P.,Proctor, R., Mills, D.K., 2007. Modelling the hydrodynamics and ecosystem ofthe North-West European continental shelf for operational oceanography.Journal of Marine Systems 65, 417–429.

Simpson, J.H., Hunter, J.R., 1974. Fronts in the Irish Sea. Nature 250, 404–406.Souza, A.J., Simpson, J.H., Harikrishnan, M., Malarkey, J., 2001. Flow structure and

seasonality in the Hebridean slope current. Oceanologica ACTA 24, S63–S76.van Leussen, W., Radach, G., vanRaaphorst, W., Colijn, F., Laane, R., 1996. The North-

West European Shelf Programme (NOWESP): integrated analysis of shelf

processes based on existing data sets and models. ICES Journal of MarineScience 53, 926–932.

Wakelin, S.L., Holt, J.T., Proctor, R., 2009. The influence of initial conditions and openboundary conditions on shelf circulation in a 3D ocean-shelf model of the NorthEast Atlantic. Ocean Dynamics 59. doi:10.1007/s10236-10008-10164-10233.

Watson, R., Pauly, D., 2001. Systematic distortions in world fisheries catch trends.Nature 414, 534–536.

Young, E.F., Holt, J.T., 2007. Prediction and analysis of long-term variability oftemperature and salinity in the Irish Sea. Journal of Geophysical Research 112.doi:10.1029/2005JC003386, 002007.

http://dx.doi.org/10.1007/s10236-10008-10164-10233

http://dx.doi.org/10.1029/2005JC003386,002007

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