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Downwelling surface shortwave flux (DSSF) is a key parameter to addressingmany climate, meteorological, and solar energy issues. Under clear sky conditions,DSSF is particularly sensitive to the variability both in time and space ofthe aerosol load and chemical composition. Hitherto, this dependence has not beenproperly addressed by the Satellite Application Facility on Land Surface Analysis(LSA-SAF), which operationally disseminates instantaneous DSSF products over thecontinents since 2005 considering constant aerosol conditions. In the presentstudy, an efficient method is proposed for DSSF retrieval that will overcomethe limitations of the current LSA-SAF product. This method referred to asSIRAMix (Surface Incident Radiation estimation using Aerosol Mixtures) isbased upon an accurate physical parameterization coupled with a radiativetransfer-based look up table of aerosol properties. SIRAMix considers a troposphericlayer composed of several major aerosol species that are conveniently mixedto reproduce real aerosol conditions as best as possible. This feature of SIRAMix allows it toprovide not only accurate estimates of global DSSF but also the direct anddiffuse DSSF components, which are crucial radiative terms in many climatologicalapplications. The implementation of SIRAMix is tested in the present articleusing atmospheric analyses from the European Center for Medium-Range WeatherForecasts (ECMWF). DSSF estimates provided by SIRAMix are compared againstinstantaneous DSSF measurements taken at several ground stations belongingto several radiation measurement networks. Results show an average rootmean square error (RMSE) of 23.6, 59.1, and 44.9 W m<sup>−2</sup> for global, direct,and diffuse DSSF, respectively. These scores decrease the average RMSEobtained for the current LSA-SAF product by 18.6%, which only providesglobal DSSF for the time being, and, to a lesser extent, for the stateof the art in the matter of DSSF retrieval (RMSE decrease of 10.9, 6.5,and 19.1% for global, direct, and diffuse DSSF with regard to the McClearalgorithm).The main limitation of the proposed approach is its high sensitivity to the quality of the ECMWF aerosolinputs, which is proved to be sufficiently accurate for reanalysesbut not for forecast data.Given the proximity of DSSF retrieval to the modeling of the atmospheric direct effect,SIRAMix is also able to quantify the direct radiative forcing at the surface due to a given atmosphericcomponent (e.g., gases or aerosols)

atmospheric chemistry and physics

Improved retrieval of direct and diffuse downwelling surface shortwave flux in cloudless atmosphere using dynamic estimates of aerosol content and type: application to the LSA-SAF project