Remote sensing of total direct aerosol radiative forcing from MERIS measurements: A comparison of two different retrieval schemes

Abstract

The global distribution of aerosol radiative forcing is a large uncertainty in present climate models. Aerosol retrieval from spaceborne sensors can help to fill this gap at least over the ocean. For present satellite sensors like AVHRR, MOS, SeaWiFS or POLDER and future sensors, such as MERIS, MODIS and GLI, algorithms have been developed to derive optical and physical aerosol parameters like optical depth, particle size distribution or aerosol type. Different authors proposed to derive the climatically important aerosol effect on the upward radiative flux directly from satellite measurements of upward radiance instead of deriving aerosol parameters subsequently used for the assessment of the aerosol radiative forcing. By such an approach, retrieval errors due to absorption and not well defined phase functions can be reduced. In this paper, two different algorithms for the direct retrieval of the top of atmosphere upward radiative flux in the solar spectral region over the ocean are compared. Based on radiative transfer calculations, a regression algorithm and a Neural Net algorithm have been developed for the use of present MOS and future MERIS measurements. Sensitivity tests according to sensor noise were performed for both algorithms. The low noise sensitivity of the Neural Net algorithm makes this type of algorithm more promising. The retrieval scheme is applied to MOS scenes of the North Sea and the North Atlantic.