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Dust and vapour cloud the view Richard Allan Environmental Systems Science Centre, University of Reading, UK Thanks to Tony Slingo, Ruth Comer, Sean Milton,

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Presentation on theme: "Dust and vapour cloud the view Richard Allan Environmental Systems Science Centre, University of Reading, UK Thanks to Tony Slingo, Ruth Comer, Sean Milton,"— Presentation transcript:

1 Dust and vapour cloud the view Richard Allan Environmental Systems Science Centre, University of Reading, UK Thanks to Tony Slingo, Ruth Comer, Sean Milton, Malcolm Brooks, and the GERB International Science Team

2 Introduction Climate and NWP models Model evaluation: –Top down/bottom up approach Diagnosing variability and feedbacks Nuts and bolts: model parametrizations and physical processes –fast feedbacks Limitations of the observing systems

3 Intro 3 Clouds and climate Bony and Dufresne (2005) Clouds and Climate

4 Objectives Validation of new datasets (GERB/SEVIRI) Timely Model Evaluation Understanding of physical processes

5 GERB July 2006 OLR Animation Model Sinergee project:

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

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

8 All-sky Clear-sky ShortwaveLongwave Mineral dust aerosol

9 Dust

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

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

12 1200GMT, 6 March 2006 In these false-colour images, the dust appears pink or magenta, water vapour dark blue, thick high-level clouds red-brown, thin high-level clouds almost black and surface features pale blue or purple. On 6 March, unusually strong northerly winds bring cold air at low levels over the desert, creating a broad front of dust as the air moves south. The location of Niamey is marked by a cross. RADAGAST project:

13 1200GMT, 7 March 2006 The shallow layer of cold air cannot rise over the mountains of the central Sahara (light blue in colour), so it is forced to follow the valleys. Streaks appear where it accelerates through gaps in the topography. The dust reached Niamey at 0930 on 7 March. In these false-colour images, the dust appears pink or magenta, water vapour dark blue, thick high-level clouds red-brown, thin high-level clouds almost black and surface features pale blue or purple. RADAGAST project:

14 1200GMT, 8 March 2006 By 8 March, dust covers the whole of West Africa and is moving out over the Atlantic. In these false-colour images, the dust appears pink or magenta, water vapour dark blue, thick high-level clouds red-brown, thin high-level clouds almost black and surface features pale blue or purple. Animation available:

15 SurfaceTop of Atmosphere et al…

16 Radiative transfer models underestimate the solar absorption in the atmosphere during March 2006 dust storm Slingo et al. (2006) GRL, 33, L24817

17 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 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

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

20 Marine Stratocumulus

21 Curious banding structure –Transition across model levels Cloud reflectivity bias

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

23 Stratocumulus composites

24 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

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

26 Convective cloud 5 th June 2006

27 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

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

29 Improved shortwave reflectivity

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

31 Gulf of Guinea ModelCloudSat 5 th July th July 2006

32 Clouds and water vapor Combine GERB/SEVIRI Diurnal changes in cloud and humidity Radiatively driven subsidence work by Ruth Comer

33 2-3 hr lag between tropical convection and upper tropospheric water vapor (Soden 2000, 2004) above: central/South America right: Lagrangian tracking

34 Tracking over Africa difficult? Complex picture locally due to propagating disturbances

35 Clouds and Water Vapor: Africa ~3-hour lag Work by Ruth Comer

36 Clear-sky radiative cooling and the atmospheric hydrological cycle Clear-sky radiative cooling: –radiative convective balance –atmospheric circulation Earths radiation budget –Understand clear-sky budget to understand cloud radiative effect Datasets: –Reanalyses – observing system –Satellites – calibration and sampling –Models – wrong by definition

37 Links to precipitation

38 Tropical Oceans Ts CWV LWc SFC ERA40 NCEP SRB HadISST SMMR, SSM/I Derived: SMMR, SSM/I, Prata) Allan (2006) JGR 111, D22105

39 Surface LWc and water vapour dLWc/dCWV ~ 1.5 Wkg -1 ERA40 NCEP dCWV/dTs ~ 3 kgm -2 K -1 Allan (2006) JGR 111, D22105

40 Clear-sky OLR with surface temperature: + ERBS, ScaRaB, CERES; SRB Calibration or sampling?

41 Tropical Oceans Surface Net LWc Clear-sky OLR Clear-sky Atmos LW cooling Q LWc ERBS, ScaRaB, CERES Derived ERA40 NCEP SRB HadISST Allan (2006) JGR 111, D22105

42 Linear least squares fit Tropical ocean: descending regime DatasetdQ LWc /dTs Slope ERA-403.7±0.5Wm -2 K -1 NCEP4.2±0.3Wm -2 K -1 SRB3.6±0.5Wm -2 K -1 OBS4.6±0.5Wm -2 K -1 ERA40 NCEP

43 Implications for tropical precipitation (GPCP)? ERA40 Q LWc GPCP P OBS Q LWc Pinatubo?

44 IPCC AR4 models: tropical oceans CWV Net LWc OLRc Q_ LWc

45 IPCC AR4 models: tropical oceans Q LWc Precip Ongoing work…

46 Ongoing work…CMIP3 models

47 Also considering coupled model experiments including greenhouse gas and natural forcings

48 Conclusions Top down-bottom up approach –Good for feedback to modelers 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 Clear-sky radiative cooling –Links to atmospheric hydrological cycle –Need to understand before can understand changes in cloudiness Observing systems: capturing decadal variability problematic

49 Spurious variability in ERA40 Improved performance in water vapour and clear-sky radiation using 24 hour forecasts Reduced set of reliable observations as input to future reanalyses?

50 Clear-sky vs resolution

51 Sensitivity study Based on GERB- SEVIRI OLR and cloud products over ocean: dOLRc/dRes ~0.2 Wm -2 km -0.5 Suggest CERES should be biased low by ~0.5 Wm -2 relative to ERBS

52 Links to precipitation


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