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Modelled & Observed Atmospheric Radiation Balance during the West African Dry Season.

Modelled & Observed Atmospheric Radiation Balance during the West African Dry Season. Sean Milton, Glenn Greed, Malcolm Brooks, R.Allan* & A. Slingo* Met Office, Exeter, UK *ESSC, Reading University. AMMA SOP0 Meeting 15 May 2007. Outline

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Modelled & Observed Atmospheric Radiation Balance during the West African Dry Season.

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  1. Modelled & Observed Atmospheric Radiation Balance during the West African Dry Season. Sean Milton, Glenn Greed, Malcolm Brooks, R.Allan* & A. Slingo* Met Office, Exeter, UK *ESSC, Reading University AMMA SOP0 Meeting 15 May 2007

  2. Outline • Systematic Errors in current NWP models & Role of Aerosols • Global Model evaluation vs ARM (Niamey) & GERB –Dec 05 to Mar 06 • Evaluating a dust parametrization. • 6-9 March Saharan Dust event • Performance in Saharan regional Model

  3. Aerosol Optical Depth Conclusion: OLR errors over the Western Sahara at 1200 UTC during May-August 2004 can be explained by failure to include the strong greenhouse effect of high amounts of desert dust in the model …see Haywood et al. (2004) JGR OLR Errors & Saharan Dust

  4. SOP3 SOP1&2 Jan-Feb 2006 DABEX/DODO Aug 2006 DODO2 ARM mobile facility - Niamey Observations available over Africa during 2006 RADAGAST

  5. 50 levels NWP Forecast Systems – Unified Model UK 4km Regional 12km Saharan Regional Model 20km • Global 40km • 60 hour forecast twice/day • 144 hour forecast twice/day • +EPS 24member, 90km

  6. Atmospheric Radiation Balance

  7. SW Radiation Balance – SurfaceMidDec 2005 – mid Apr 2006 Accuracy +/- 9Wm-2

  8. Surface Albedo (Annual): Model – MODIS UM too bright UM too dark

  9. Global UM - ARM AOT 440nm Banizoumbou Importance of Aerosols for NWP 8 Mar Dust Event AOT 440nm

  10. Near surface Temperatures – Model vs ARM

  11. Dust Parametrization – Woodward 2001 Six dust sizes 0.03 -30 microns Conv BL mixing • Threshold friction velocity defined for particles from .06 to 2000 microns (previously .06 to 60) • 9 Bins in Horizontal Flux (3 sand) • Inhibition of dust from steep slopes – numerical issues • Use of IGBP (1km) soil source data in place of Wilson-Henderson-Sellers (1985) 1 deg data (NWP only). • Reduce threshold friction velocity by 0.15 m/s in NWP • Use global “nudged” soil moisture to initialise Saharan CAMM. Transport Deposition Gravitational Settling Uplift (v*, soil moisture) Wet Soils Data

  12. 08 March 12Z 07 March 12Z 06 March 12Z 06 March 00Z SEVERI Images of Dust 6-9 March 2006

  13. 1-5 day global model forecast N216 L38 Initialised 12UTC 4 March 2006

  14. Impact of Dust on Radiation balance – Day 4 Forecasts 12 UTC 8th March

  15. ARM 200 Wm-2 Reduction SW Model 100 Wm-2 Reduction In SW due to inclusion of dust Net SW Net LW

  16. Saharan CAMM Dust loading – Aug 2006 TOMS AI (1980-92) Saharan CAMM B B A A C C (TOMS AI from Engelstaedter et. al, Earth Science Reviews, 2006)

  17. Comparisons of Saharan CAMM with AERONET Andreas Keil Glenn Greed

  18. Summary • Aerosols – Failure to account for dust (and biomass burning?) in current NWP versions causes significant errors in the radiation balance over Africa. • Specification of surface albedo over Africa is poor leading to systematic underestimates of reflected SW- review • Mineral Dust Parametrization • Performs well in both Global and Saharan Model – major Saharan dust outbreak predictable 4 days in advance. • Uncertainties • Dust optical properties • Dust uplift • Vertical distribution • Predicted Size distributions

  19. Future • Further comparison of Dust in model with aircraft data from DODO/DABEX and GERBIL. • Tuning of dust radiative properties – single scatter albedo. • More work on dust uplift (PDRA Reading D.Ackerley) • Impacts on the circulation – test in THORPEX. • Dust operational in Southern Asia Model by 2008. • Global NWP Model? – simplified dust parametrization.

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