meteorological and photochemical modelling at the csir · 2014. 3. 17. · •new group, seasoned...
TRANSCRIPT
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© 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.
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© 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
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© CSIR 2010 Slide 3
• 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
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© CSIR 2010 Slide 4
• 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)
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© CSIR 2010 Slide 5
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
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© CSIR 2010 Slide 6
• 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)
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© CSIR 2010 Slide 7
• 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
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© CSIR 2010 Slide 8
• Results used previously
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
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© CSIR 2010 Slide 9
• Results used previously
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
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© CSIR 2010 Slide 10
• Results currently generated, e.g 8km Limpopo basin run
Climate modelling
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© CSIR 2010 Slide 11 www.csir.co.za
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)
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© CSIR 2010 Slide 12 www.csir.co.za
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
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© CSIR 2010 Slide 13 www.csir.co.za
Air Quality modelling – Current domains
© CSIR 2013
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© CSIR 2010 Slide 14 www.csir.co.za
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)
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© CSIR 2010 Slide 15 www.csir.co.za
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
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© CSIR 2010 Slide 16 www.csir.co.za
Air Quality modelling – Camden monitoring station
© CSIR 2013
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© CSIR 2010 Slide 17 www.csir.co.za
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
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© CSIR 2010 Slide 18 www.csir.co.za
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
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© CSIR 2010 Slide 19 www.csir.co.za
Results – Annual average surface ozone (1989-2009)
© CSIR 2013
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© CSIR 2010 Slide 20 www.csir.co.za
Results – Seasonal average surface ozone (1989-2009)
© CSIR 2013
SPRING
SPRING SUMMER
AUTUMN WINTER
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© CSIR 2010 Slide 21 www.csir.co.za
Results – Annualar slope of linear regression (1989-2009)
© CSIR 2013
aka “trend”
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© CSIR 2010 Slide 22 www.csir.co.za
Results – Seasonal slope of linear regression (1989-2009)
© CSIR 2013
SPRING
SPRING SUMMER
AUTUMN WINTER
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© CSIR 2010 Slide 23
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
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© CSIR 2010 Slide 24
Thank you for your time