Top-of-Atmosphere Radiance-to-Flux Conversion in the SW Domain for the ScaRaB-3 Instrument on Megha-Tropiques

Abstract

The earth radiation budget (ERB) is the difference between the solar absorbed flux and the terrestrial emitted flux. These fluxes are calculated from satellite measurements of outgoing shortwave (SW) and longwave (LW) radiances using empirical or theoretical models of the radiation anisotropy, which are called angular distribution models (ADMs). Owing to multidirectional measurement analyses and synergy with multispectral information at subpixel scale, the ADM developed for the NASA Clouds and the Earth?s Radiant Energy System (CERES) mission is presently the best knowledge and has to be taken into account for future ERB missions, such as the Indian?French Megha-Tropiques mission to be launched in 2010. This mission will carry an ERB instrument called the Scanner for Radiation Budget (ScaRaB). To prepare the algorithms for the ScaRaB ADM retrievals, the artificial neural network (ANN) method described by the CERES team has been adopted and improved by replacing the broadband (BB) radiances by narrowband (NB) radiances from the auxiliary channels of ScaRaB as input variables of the ANN. This article is restricted to the SW domain, the most critical case, and shows that the flux error is reduced by 60% compared to the former ERB Experiment?like model. The rms differences with the CERES fluxes are around 8.4 W m?2. ScaRaB/Megha-Tropiques measurements have a 4 times lower spatial resolution than those of the CERES/Tropical Rainfall Measuring Mission (TRMM). The impact of this spatial degradation has also been explored. There is a small systematic bias of about 1.5 W m?2 (or an absolute albedo error of 0.0015) and the rms differences are less than 3 W m?2; this is not significant compared to the overall error budget. For the radiance-to-flux conversion in the SW domain, the BB and NB ANN methods will be implemented in the ScaRaB/Megha-Tropiques data processing in order to provide SW flux estimates with an accuracy that is as consistent as possible with CERES results.