© University of Reading Richard Allan Department of Meteorology, University of Reading Thanks to: Jim Haywood and Malcolm Brooks (Met Office) Using Geostationary Earth Radiation Budget data to evaluate global models and radiative processes

All-sky Clear-sky ShortwaveLongwave Radiative biases in Met Office global NWP model

All-sky Clear-sky ShortwaveLongwave Convective cloud Radiative biases in Met Office global NWP model Convective outflow

All-sky Clear-sky ShortwaveLongwave Convective cloud Radiative biases in Met Office global NWP model Convective outflow Mineral dust Surface albedo

All-sky Clear-sky ShortwaveLongwave Convective cloud Radiative biases in Met Office global NWP model Convective outflow Mineral dust Surface albedo Marine stratocumulus

Marine stratocumulus Key in determining model uncertainty in climate sensitivity e.g. Bony and Dufresne (2005); Clemment et al. (2010) Model biases in physical properties Commonality: NWP and climate parametrizations © University of Reading CERES FM3 (Aqua) -SSF Albedo 13:11 Model albedo 5 June :00 GERB albedo

Model stratocumulus cloud: too bright, too much water - Implications for Cloud Feedback, e.g. Stephens (2010) © University of Reading Allan et al. (2007) QJRMS

NWP model cloud radiative bias: overcast Sc-cover pixels only ( ) © University of Reading LW cloud effect too small (~ -5 Wm -2 ) SW cloud effect too large yet too little stratocumulus cloud cover

Systemic bias in climate models? Radiative bias: climate models minus ERBS

Mineral dust and surface albedo (model-GERB) Progressive reduction in model biases through continual evaluation and improvement See also poster by Margaret Woodage for evaluation of dust scheme in HiGEM model

© University of Reading GERBILS aircraft campaign Lead by Jim Haywood June 2007

© University of Reading Persistent contrail cirrus case study Combining satellite data with models to understand physical processes

© University of Reading Persistent contrail cirrus case study Combining satellite data with models to understand physical processes

© University of Reading Persistent contrail cirrus case study Combining satellite data with models to understand physical processes

© University of Reading Persistent contrail cirrus case study Combining satellite data with models to understand physical processes

© University of Reading Persistent contrail cirrus case study Combining satellite data with models to understand physical processes

© University of Reading Persistent contrail cirrus case study Combining satellite data with models to understand physical processes

© University of Reading Persistent contrail cirrus case study Combining satellite data with models to understand physical processes

© University of Reading CERES FM3 (Aqua) FLASH fluxes 13:25 Contrail induced cirrus? Window flux Inverse greenhouse parameter SW fluxes (Wm -2 ) Using GERB/NWP model estimate radiative effect of contrail cirrus: LW ~ 40 Wm -2 SW up to 80 Wm -2 stratocumulus LW fluxes (Wm -2 )

© University of Reading Cloud effective radius Cloud optical thickness Contrail region: higher optical thickness, smaller effective radius SEVIRI cloud properties (0.8 and 1.6 μm channels) Water cloud

© University of Reading Haywood et al. (2009) JGR Using GERB-like/SEVIRI and 4km forecast model to quantify contrail radiative effects: example at 14:00, 20 March 2009

Case II: 25-26/06/2010

LW and SW cloud radiative effect Estimated using GERB/SEVIRI minus NCEP clear-sky LW and SW cloud radiative effect up to 80 Wm -2 (small net effect at midday) But would cirrus have formed anyway? © University of Reading UTC

Summary Mineral dust aerosol –Systematic model LW radiative bias at TOA up to 40 Wm -2 –GERBILS field campaign Model Cloud –Subtropical stratocumulus too bright, too much liquid water –Cannot tune to TOA radiation; need to get bulk physical properties right. Issues with LWP retrievals (μ-wave/visible) –Highly sensitive to model changes (e.g. convection) Persistent contrail cirrus events –Up to 80 Wm -2 LW and SW cirrus radiative effect –Small net effect, but large dynamical and diurnal forcing –Would cirrus have formed anyway? –Any contrail effect following Iceland volcano aircraft shutdown? © University of Reading

Was there any contrail effect following the Iceland Volcano? © University of Reading Airspace closureAirspace reopens

Was there any contrail effect following the Iceland Volcano? © University of Reading Airspace closureAirspace reopens...unlikely! Probably more related to advection of dry air and subsequent encroachment of mid-latitude system. GERB HR (V003) LW fluxes

Major update to model parametrizations 15 July 2010 Stratocumulus cloud now too extensive © University of Reading GERBModel 12 July 19 July Continuous monitoring

LW bias in climate models May-July Average clear-LW bias over whole region 3-15 Wm -2 depending upon model & satellite dataset/period

Ongoing evaluation: diurnal cycle of convection in high resolution models © University of Reading Pearson et al. (2010) JGR in press (CASCADE project)