REMOTE SENSING OF CLOUD ALBEDO FROM BACKSCATTERED SUNLIGHT IN CLOUDY ATMOSPHERE

Clouds play an important role in modifying the earth's radiation budget. One part to understand the cloud effects are at which amount clouds reflect incoming sunlight back to space. An algorithm is developed for estimating the cloud albedo which is applicable to MODerate resolution Imaging Spectroradiometer (MODIS) data. The method is based on narrow-to-broadband conversion and radiative transfer model simulations. The model results provide a basis for the derivation of broadband albedo from top of the atmosphere MODIS measurements by use of an artificial neural network. This product was compared with Clouds and Earth's Radiant Energy System (CERES) which is also onboard the Terra satellite. The results of the comparison show an excellent agreement in terms of spatial means, being lower than 13 W/m for the European region. The algorithm provides a higher spatial resolution than CERES products. This makes it possible to study the cloud albedo for smaller grid scales in detail. Furthermore, the cloud albedo from MODIS has been used to validate a climate model. 1