Evaluating the Met Office global forecast model using GERB data Richard Allan, Tony Slingo Environmental Systems Science Centre, University of Reading.

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Presentation transcript:

Evaluating the Met Office global forecast model using GERB data Richard Allan, Tony Slingo Environmental Systems Science Centre, University of Reading Sean Milton, Malcolm Brooks Met Office, Exeter

Objectives Improve experience with satellite datasets including GERB Timely Model Evaluation Understanding of physical processes

ShortwaveLongwave Mean model bias: 2006 All-sky Clear-sky

ShortwaveLongwave Convective cloud Surface albedo Mineral dust aerosol Marine stratocumulus Cirrus outflow

All-sky Clear-sky ShortwaveLongwave Mineral dust aerosol

Dust impact on longwave radiation Large perturbation to Met Office model OLR during summer over west Sahara Correlates with high mineral dust aerosol optical depth Model minus GERB OLR: July 2006, UTC

18 UTC model-GERB OLR over West Sahara GERBILGERBIL – aircraft campaign (Jim Haywood) GERB Intercomparison of Longwave Radiation: June

Consistent with calculations of dust longwave radiative effect Clear-sky OLR bias (Wm-2) in 2003 Calculations: Direct radiative effect Direct plus shortwave feedback effect Haywood et al. (2005) JGR 110, D05105

- Major dust source for Amazon - Large component from March 2004 dust storms

March 2004: an interesting month Loeb et al. (2007) J. Climate, 20, p.582 March 2006 was interesting too…

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

Marine Stratocumulus

Curious banding structure –Transition across model levels Cloud reflectivity bias –Model low-altitude stratiform clouds are too reflective

Changes in albedo bias (ocean) Model upgrade (March 2006) reduced but did not remove albedo bias –Compensating errors: ITCZ/stratocumulus

Stratocumulus composites

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

LWP Wentz : overestimate for low cloud fraction? TMI Wentz /MODIS LWP Overcast boundary layer clouds: good agreement Horváth and Davies (2007) JGR 112, D01202

Convective cloud 5 th June 2006

Model evaluation: near-real time Change in model minus GERB flux differences Relate to change in model physics implementation 13 th March | 14 th March Model SW albedo

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

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

Improved shortwave reflectivity

Gulf of Guinea ModelCloudSat 19 th July th July 2006

Conclusions Top down-bottom up approach –Good for feedback to modellers Mineral dust aerosol –Shortwave absorption; longwave radiative effect –Large effect of single events Marine stratocumulus –Reflectivity and seasonal variability: issues Deep convection –Intermittent in models; issues with detrainment