Evaluating the Met Office global forecast model using Geostationary Earth Radiation Budget GERB data

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Evaluating the Met Office global forecast model
using Geostationary Earth Radiation Budget (GERB)
data
Richard Allan, Tony Slingo Environmental Systems
Science Centre, University of Reading Sean
Milton, Malcolm Brooks Met Office, Exeter
Thanks to the GERB International Science Team
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Objectives

• Improve experience with satellite datasets
  including GERB
• Timely Model Evaluation
• using geostationary data independent of the
  assimilation system
• Understanding of physical processes

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GERB June 2007 OLR Animation
Model
Sinergee project www.nerc-essc.ac.uk/rpa/GERB/ge
rb.html
Harries et al. (2005) BAMS Allan et al. (2005)
JGR
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All-sky Clear-sky
Mean model bias 2006
Shortwave Longwave
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All-sky Clear-sky
Mineral dust aerosol
Shortwave Longwave
Surface albedo
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Dust impact on longwave radiation
Model minus GERB OLR July 2006, 12-18 UTC
All-sky Clear-sky dust aerosol

• Large perturbation to Met Office model OLR during
  summer over west Sahara
• Correlates with high mineral dust aerosol optical
  depth (see also Haywood et al. 2005, JGR)
• GERBIL aircraft campaign (Jim Haywood)

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All-sky Clear-sky
Radiative biases in the Met Office global model
Convective outflow
Shortwave Longwave
Convective cloud
Marine stratocumulus
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Marine Stratocumulus
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• Curious banding structure
• Transition across model levels
• (see Lock et al. 2001, MWR)
• Cloud reflectivity bias
• Model low-altitude stratiform clouds are too
  reflective

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Cloud liquid water path
Bias model minus GERB SSM/I SEVIRI Albedo
Liquid Water Path Cloud
Reduction in model bias from June to July 2006 -
relates to cloud liquid water
but see also Horvath and Davies (2007) JGR
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Convective cloud
5th June 2006
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Convective Decay Time-scale

• Unrealistically low levels of convective cloud
• On-off common problem in models
• Simple fix

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Improved shortwave reflectivity
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• Increased convective cloud cover
• But is the physics any better?
• Future work Comparisons with CloudSat

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Conclusions

• Top down-bottom up approach
• Satellite data independent of assimilation system
• Good feedback for modellers and satellite team
• Mineral dust aerosol over Sahara
• Monthly longwave radiative effect up to 50 Wm-2
• Large effect of single events (Slingo et al.
  2006, GRL)
• Marine stratocumulus
• Reflectivity and seasonal variability issues
• Deep convection
• Intermittent in models issues with detrainment