Simulation of surface and top of atmosphere thermal fluxes and radiances from the radiative atmospheric divergence using the ARM Mobile Facility, GERB data, and AMMA Stations experiment

摘要

Simultaneous observations of thermal radiative fluxes and radiances from the surface (Atmospheric Radiation Measurement Mobile Facility, Niamey) and top of atmosphere (Geostationary Earth Radiation Budget (GERB) instrument) during the Radiative Atmospheric Divergence using ARM Mobile Facility, GERB data, and AMMA Stations experiment are compared with results from a radiative transfer model (Edwards-Slingo). Emphasis is placed on diagnosing the accuracy of the cloud-free radiation measurements using multiple instruments at the surface. The surface forcing from aerosol is found to regularly exceed 20 Wm -2, and reached -100 Wm-2 during the March 2006 dust storm. Equivalent comparisons are made with top of atmosphere (TOA) measurements but here radiance closure is not achieved. A disagreement is found between the angular anisotropy derived from GERB products and that from radiative transfer (RT) calculations. A hybrid TOA radiative flux time series is created using RT-calculated TOA anisotropy and GERBobserved TOA radiance. At 1100 UT (local noon), this hybrid flux differs from the Edition 1 GERB product by a positive difference in the range ,-,0-10 Wm -2 . Three collections of fluxes exist to calculate column-integrated atmospheric heating (divergence) from surface and TOA fluxes. The first two are fluxes from observations only or from RT calculations only. The third is a combination of RT calculation and observed fluxes that includes the hybrid flux. The resulting divergences are binned by sonde launch times and averaged over the year. The range of divergence during a day depends on the flux collection used (-200 to -111 Wm -2, -212 to -116 Wm -2, or -205 to -112 Wm-2) for observations only, for RT calculations only, or for observationcalculation fluxes. All estimates agree as to the interday variation being larger than that of intraday variability.