Radiative Atmospheric Divergence using ARM Mobile Facility, GERB data and AMMA stations –led by Tony Slingo, ESSC, Reading University, UK Links the ARM.

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Presentation transcript:

Radiative Atmospheric Divergence using ARM Mobile Facility, GERB data and AMMA stations –led by Tony Slingo, ESSC, Reading University, UK Links the ARM Mobile Facility with GERB (Geostationary Earth Radiation Budget instrument on Meteosat) & AMMA The objective is to derive the divergence of radiation across the atmosphere: –by combining the AMF measurements of the surface radiative fluxes and vertical structure of the atmosphere with GERB data from the top of the atmosphere and AMMA observations –study the radiative properties of aerosols (desert dust, biomass), water vapour and clouds –provide comprehensive observations for testing radiation codes The RADAGAST project

Red: Aerosol Optical Thickness at 675nm from the AERONET site at Banizoumbou Black: Angstrom exponent Downward Solar flux (daily averages Wm -2 ) Purple: Total Green: Diffuse Grey bands: clouds Downward solar fluxes are controlled by clouds and by aerosol Dust storm

Downward Thermal flux Wm -2 Black: Daily average Red: variability Grey bands: clouds Column water vapour (cm) Green: Radiometer Red: Sonde Downward thermal fluxes are controlled by clouds, column water vapor, atmospheric temperatures and aerosol (see later) Dust storm

GERB reflected solar Wm -2 ARG: Standard product (50km resolution) HR: High Resolution hybrid product using SEVIRI imager data (10km resolution) Downward Solar flux (daily averages Wm -2 ) Purple: Total Green: Diffuse Grey bands: clouds GERB and AMF fluxes will be combined to calculate atmospheric divergence

Downward Thermal flux Wm -2 Black: Daily average Red: variability Grey bands: clouds GERB OLR Wm -2 ARG: Standard product (50km resolution) HR: High Resolution hybrid product using SEVIRI imager data (10km resolution) GERB and AMF fluxes will be combined to calculate atmospheric divergence

Comparisons with the Edwards/Slingo radiation code One of the main RADAGAST objectives is to provide comprehensive observations for testing radiation codes We have compared longwave simulations by the Edwards and Slingo (1996) radiation code with observed fluxes from the AMF broad-band radiometers and (in radiance mode) with AERI radiances, for cloud-free conditions Unlike the NWP comparisons shown earlier, these are stand-alone tests, running the code with input from the observed thermodynamic profiles This has produced some very interesting differences The work has benefitted from collaboration with Eli Mlawer (AER), who carried out parallel calculations with LBLRTM

Comparisons with Edwards/Slingo radiation code The large reduction in column water vapour in October controls the downward longwave fluxes, as shown earlier, but not the differences. Could aerosol be causing the flux differences during the dry season? Downward thermal flux (Wm -2 ) Observed minus modelled (Wm -2 ) Red: observed Blue: modelled

Every peak in the Banizoumbou AOT time-series after September has a corresponding peak in the downward thermal flux difference. However, that doesn’t necessarily mean that the cause of the differences is aerosol; it could still be thin and/or high cloud that becomes relatively more important because of the dry atmosphere (and which also fools the aerosol retrieval).

MPL corrected backscatter MPL calculated extinction profile January 21

Calculated daily average SW and LW radiative effects at surface due to aerosol only (Jan-Apr 2006) Daily average effect of aerosol on surface fluxes during dry season is Wm -2 on SW and Wm -2 on LW Shortwave (Wm -2 )Longwave (Wm -2 )

Summary and future work Over a year of data from the AMF, GERB and SEVIRI –several articles and press releases: –major dust storm in March 2006 (Slingo et al., Geophysical Research Letters, 30 December 2006) –overview paper by Miller and Slingo in Bulletin of the American Meteorological Society (scheduled for August 2007) Aerosol has a large influence on solar fluxes (expected) and appears to have a significant influence on thermal fluxes (unexpected) Ongoing work includes: –analysis of AMF and GERB fluxes throughout 2006, for clear and cloudy conditions, and comparisons with radiation and NWP models –developing the methodology to derive area-average surface fluxes, including exploiting the data from the second site at Banizoumbou –combining AMF and GERB data to derive atmospheric divergence –Radagast website;