meteorological and photochemical modelling at the csir · 2014. 3. 17. · •new group, seasoned...

© CSIR 2010 Slide 1 www.csir.co.za

Meteorological and Photochemical Modelling at the CSIR

Mogesh Naidoo Climate Studies, Modelling and Environmental Health

Natural Resources and the Environment

CSIR

Dialogue on Integrated Local and Regional Scale Air Quality Modelling

using the GAINS Model 14th February 2014

Knowledge Commons, CSIR, Pretoria.

© CSIR 2010 Slide 2

• New group, seasoned scientists (atmospheric, environmental, health)

• Modelling = Atmospheric (Climate and Air Quality)

• Climate modelling output (present day + projections) • Hydrological studies

• Agriculture impact

• Land-surface processes

• Seasonal forecasting

• Adaptation planning

• Vulnerability studies

• Air quality modelling output (present day + projections) • Environmental health

• Regional tropospheric chemistry research

• Industrial and municipal impact studies

Research at CSM&EH


• NWP and RCM based on the Conformal Cubic Atmospheric Model

(CCAM). Developed at CSIRO

• CCAM is a cube-based global model; semi-Lagrangian semi-implicit

solution of the hydrostatic primitive equations

Climate modelling


• Can run in quasi-uniform (previous slide) or stretched grid mode

Climate modelling

CCAM applied in stretched-grid mode Modest stretching provides a resolution

of about 0.5 degrees over tropical and

southern Africa; decreases to about 4

degrees in the far-field. Options for

spectral nudging, gridpoint nudging or

no nudging from the host model

(atmospheric fields)


Climate modelling

CGCMs: A2 SRES and RCP4.5 & 8.5 Simulation period: 1961 - 2100

Global simulations,

quasi-uniform C192

resolution (~ 50 km)

Very high-resolution

simulations over

areas of interest (~ 8

km).

Bias corrected SST and SIC

SST, sea ice, atmospheric

nudging

User applications Regrid to

lat/lon


• Model verification

Climate modelling

Intra-annual cycle in rainfall and circulation

(Engelbrecht et al., 2009; IJC)

Closed-low tracks and extreme rainfall

events (Engelbrecht et al., 2012; IJC)

Inter-annual variability in AMIP-style runs

(Landman et al., 2010; WRC Report)

Accuracy and skill in short-range weather

forecasting (Potgieter 2006; Engelbrecht et

al., 2011; Water SA)


• Results used previously

Climate modelling

CCAM ensemble: projected change in annual average

temperature for 2071-2100 vs 1961-1990

Under the A2 emission scenario, temperature increases of more

than 4oC are projected for the region, ~x2 the global rate.

This occurs in response to the strengthening of high-pressure

systems in the mid-troposphere over South Africa



Climate modelling

CCAM ensemble: projected change in the number of very hot

days (annual totals) for 2071-2100 vs 1961-1990

Under the A2 emission scenario, it is plausible that drastic

increases in the annual number of very hot days will occur over

the region – the number of such days is projected to increase by

90 to 120 over north-eastern South Africa



Climate modelling

CCAM ensemble: projected change in the number of extreme

rainfall events for 2071-2100 vs 1961-1990

A general increase in the frequency of occurrence of extreme

rainfall events (20 mm of rain falling within 24 hours over an area

of 50 km x 50 km) is projected for South Africa


• Results currently generated, e.g 8km Limpopo basin run

Climate modelling


Air Quality modelling

© CSIR 2013

• A changing climate effect on air quality?

• Rainfall, temperature, cloud cover, inversions, advection

• CCAM climate model forcing CAMx photochemical air quality model

• CAMx = ozone (NOx, VOC species, PM species)

• Model period 1989 – 2009 (20 years)

• Inter-annual variability

• 20 years not enough (Large ENSO cycles)

• Earliest is 1989 due to input required (TOMS)


Air Quality modelling – CCAM-CAMx

© CSIR 2013

CAMx

Surface and 3D concentrations

Source apportionment

Process analysis

Deposition (wet and dry)

CCAM Meteorology NCEP

Reanalysis (FNL)

EPS Emissions Emissions data

(Spatial, temporal, speciated)

Initial / Boundary ICBC

Cape GAW data

Photolysis rates NCAR TUV

TOMS / OMI Total column

ozone


Air Quality modelling – Current domains

© CSIR 2013


Air Quality modelling – Emissions inventory

© CSIR 2013

• Previous research emission inventory (ozone formation over the Highveld)

o National at 12km resolution

o NOx, VOC, PM, SO2, CO and NH3

• Large industry (Sasol + Eskom + Coastal refineries)

• Small industry (Scheduled processes)

• Transport sector (SANRAL ADT + Arrive Alive)

• Residential fuel combustion (Census 2001)

• Biogenic emissions (GLOBEIS)


Air Quality modelling – Ancillary data

© CSIR 2013

• Photolysis rates

o NCAR TUV radiative transfer model (results for CB4)

o TOMS/OMI total column ozone

• No total column ozone measurements for 1995/96

• Lateral boundary and initial conditions

o Cape Point GAW data

o Model initialize beginning of every month


Air Quality modelling – Camden monitoring station

© CSIR 2013


Results – Camden comparison 2006 (Annual average diurnal)

© CSIR 2013

0

10

20

30

40

50

60

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Ave

rag

e s

urf

ac

e o

zo

ne

(p

pb

)

Hour of day

OBS

CAMx


Results – Camden comparison 2006 (Seasonal diurnal average)

© CSIR 2013

0

10

20

30

40

50

60

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Ave

rage

su

rfac

e o

zon

e (p

pb

)

Hour of day

OBS

CAMx

0

10

20

30

40

50

60

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Ave

rage

su

rfac

e o

zon

e (p

pb

)

Hour of day

OBS

CAMx

0

10

20

30

40

50

60

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Ave

rage

su

rfac

e o

zon

e (p

pb

)

Hour of day

OBS

CAMx

0

10

20

30

40

50

60

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Ave

rage

su

rfac

e o

zon

e (p

pb

)

Hour of day

OBS

CAMx

SPRING WINTER

SUMMER AUTUMN


To be completed…

• Complete selected 2010-2100 runs

• Correlate ozone trends to climate trends (establish mechanisms)

• Cloud cover (UV)

• Rainfall (Deposition/Chemistry)

• Temperature inversions (Transport)

• CAMx input optical depth

• ENSO (???) - AMT


Thank you for your time

meteorological and photochemical modelling at the csir · 2014. 3. 17. · •new group, seasoned...

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