Using GERB and CERES data to evaluate NWP and Climate models over the Africa/Atlantic region Richard Allan, Tony Slingo, Ali Bharmal Environmental Systems Science Centre, University of Reading Sean Milton, Malcolm Brooks, Mark Ringer Met Office, Exeter
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Using GERB and CERES data to evaluate NWP and Climate models over the Africa/Atlantic region
Using GERB and CERES data to evaluate NWP and Climate models over the Africa/Atlantic region. Richard Allan, Tony Slingo, Ali Bharmal Environmental Systems Science Centre, University of Reading Sean Milton, Malcolm Brooks, Mark Ringer Met Office, Exeter. Outline. - PowerPoint PPT Presentation
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Using GERB and CERES data to evaluate NWP and Climate models
over the Africa/Atlantic region
Richard Allan, Tony Slingo, Ali Bharmal
Environmental Systems Science Centre, University of Reading
• Biases due to cloud and surface albedo• Also models overestimate OLR over W. Sahara
OLR bias
• OLR bias present for clear-sky also
• Smaller for EBAF (MODIS enhanced)
OLR bias
• OLR bias present for clear-sky also
• Smaller for EBAF (MODIS enhanced)
• Bias present for ERBE-like processing
Use of CERES/GERB at the Met Office/Hadley Centre (Mark Ringer)
• HadGEM1 was model used for IPCC AR4• HadGEM2 will be submitted to AR5
– Basic physics as HadGEM1 but will include many ‘Earth System’ processes such as C-cycle, chemistry, etc
• HadGEM3 is currently being developed– Focus on regional climate and decadal prediction– Includes completely new prognostic cloud scheme
• CERES data fully integrated into model development and evaluation– Evolving model versions and tests of parameterizations are
systematically evaluated using CERES products• GERB: Monthly mean and monthly mean diurnal cycle
would be of most use initially• Also note that these data are an important part of our work
on feedbacks and attempts to constrain climate sensitivity
EXPERIMENTEXPERIMENT
minus
CONTROL
CONTROL
minus
CERES
EXPERIMENT
minus
CERES
Development of HadGEM3:Use of CERES SW cloud forcing, impact of removing new cloud scheme.
Comparison of GERB with HadGEM1:Model forced with climatological SSTs
GERB
HadGEM1
OLR RSW
Liquid Water Content
TOA LW up
TOA SW up
Ice Water Content
retrieval
0 3 6 9 12 15 18 21 24 Time [Hours]
GERB
Lindenberg
Simulating radiative fluxes using ground-based retrievals Nicky Chalmers, Robin Hogan
LindenbergClearCloudyHigh cloud
SU
RF
AC
E
TO
A
CERES clear
-40°C
0°C
-40°C
0°C
Using methodology to evaluate NWP clouds
ClearCloudy
Cloud at all levels
ECMWF: surface LW comparison
Angular conversion factor for the Niamey GERB ARG pixel shows thataerosol alone cannot explain the discrepancy between ES96 & GERB.
Comparison of radiance and flux: Edwards/Slingo vs GERB
N. Ali Bharmal (ESSC)
Ali Bharmal in collaboration with Helen Brindley
Preliminary results comparing SBDART and ES96 RT radiances at TOAusing aerosol-free profiles suggests a disagreement in relation to thesurface/skin temperature difference.
Skin T > sfc T
Time of agreement
Conclusions• Continued near-real time comparisons between
GERB-1/SEV2 and Met Office forecast model• Large model biases have been reduced
– Surface albedo (MODIS bare soil and seasonal vegetation)– Convective cloud (convective decay time-scale)– Seasonal dust climatology likely
• Remaining problems– Marine stratocumulus too reflective
• Appears to relates to bulk water properties– Detrainment of cirrus cloud over Gulf of Guinea– Continued monitoring using GERB data
• www.nerc-essc.ac.uk/~rpa/GERB• Paper detailing previous Edition 1 comparisons published in QJRMS• www.nerc-essc.ac.uk/~rpa/PAPERS/allan_et_al07QJ.pdf• Initial comparisons between GERB/CERES and climate models• Combining surface and top of atmosphere radiation data to evaluate