Atmospheric Chemistry and Physics Discussions www.atmos-chem-phys-discuss.net 1680-7367 1680-7375 7 6 2007 10.5194/acpd-7-17117-2007 http://www.atmos-chem-phys-discuss.net/7/17117/2007/ http://www.atmos-chem-phys-discuss.net/7/17117/2007/acpd-7-17117-2007.html http://www.atmos-chem-phys-discuss.net/7/17117/2007/acpd-7-17117-2007.pdf 17117 17146 2007-11-23 Dependence of cloud fraction and cloud top height on surface temperature derived from spectrally resolved UV/vis satellite observations T. Wagner thomas.wagner@mpch-mainz.mpg.de S. Beirle T. Deutschmann M. Grzegorski U. Platt MPI for Chemistry, Mainz, Germany Institut für Umweltphysik, University of Heidelberg, Heidelberg, Germany Cloud climate feedback constitutes the most important uncertainty in climate modelling, and currently even its sign is still unknown. In the recently published report of the intergovernmental panel on climate change (IPCC), from 20 climate models 6 showed a positive and 14 a negative cloud radiative feedback in a doubled CO₂ scenario. The radiative budget of clouds has also been investigated by experimental methods, especially by studying the relation of satellite observed broad band shortwave and longwave radiation to sea surface temperature. Here we present a new method for the investigation of the dependence of cloud properties on temperature changes, derived from spectrally resolved UV/vis satellite observations. Our study differs from previous investigations in three important ways: first, we directly extract cloud properties (amount and altitude) and relate them to surface temperature. Second, we retrieve the cloud altitude from the atmospheric O₂ absorption instead from thermal IR radiation. Third, our correlation analysis is performed using 7.5 years of global monthly anomalies (with respect to the average of the same month for all years). For most parts of the globe (except the tropics) we find a negative correlation of cloud fraction versus surface-near temperature. In contrast, for the cloud top height a positive correlation is found for almost the whole globe. Both findings might serve as an indicator for an overall positive cloud climate feedback. Another peculiarity of our study is that the cloud-temperature relationships are determined for fixed locations (instead to spatial variations over selected areas) and are based on the "natural" variability over several years (instead the anomaly for a strong El-Nino event). Thus our results might be especially representative for the extrapolation to long term climate changes. 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