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Comparisons between GERB and the Met Office NWP model Richard Allan, Tony Slingo Environmental Systems Science Centre, University of Reading Sean Milton,

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Presentation on theme: "Comparisons between GERB and the Met Office NWP model Richard Allan, Tony Slingo Environmental Systems Science Centre, University of Reading Sean Milton,"— Presentation transcript:

1 Comparisons between GERB and the Met Office NWP model 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

2 Sinergee project: GERB Model Harries et al. (2005) BAMS; Allan et al. (2005) JGR

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

4 ShortwaveLongwave Mean model bias: 2006 All-sky Clear-sky Allan et al. (2007) QJRMS

5 All-sky Clear-sky ShortwaveLongwave Marine stratocumulus Convective cloud Radiative biases in the Met Office global model Convective outflow Surface albedo

6 All-sky Clear-sky ShortwaveLongwave Mineral dust aerosol

7 Dust impact on longwave radiation Large perturbation to Met Office model OLR during summer over west Sahara –Consistent with high mineral dust aerosol optical depth (see also Haywood et al. 2005, JGR) –Used in planning of GERBILS Model minus GERB OLR: July 2006, UTC All-skyClear-skydust aerosol

8 CLEAR Model-GERB OLR difference time series 15 o W-5 o E, o N

9 Dust impact on longwave radiation Model minus GERB OLR: UTC All-skyClear-skydust aerosol June July 2006

10 19 June

11 21 June

12 Conclusions Model evaluation –Satellite data independent of assimilation system –Good feedback for modellers and satellite team –Identified biases relating to cloud and surface Mineral dust aerosol over Sahara –Monthly longwave radiative effect up to 50 Wm -2 –Large effect of single events (Slingo et al. 2006, GRL) –June : smaller dust events than previous years but detectable OLR bias

13 Marine Stratocumulus

14 Curious banding structure –Transition across model levels (see Lock et al. 2001, MWR) Cloud reflectivity bias –Model low-altitude stratiform clouds are too reflective

15 Cloud liquid water path Bias: model minus GERB; SSM/I; SEVIRI Albedo Liquid Water Path Cloud Reduction in model bias from June to July relates to cloud liquid water …but see also Horvath and Davies (2007) JGR

16 Convective cloud 5 th June 2006

17 Convective Decay Time-scale Unrealistically low levels of convective cloud On-off; common problem in models Simple fix…

18 Improved shortwave reflectivity

19 Increased convective cloud cover But is the physics any better? Future work: Comparisons with CloudSat


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