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Total cloud cover from satellite observations and climate models

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Probst, P., Rizzi, R., Tosi, E., Lucarini, V., & Maestri, T. (2012). Total cloud cover from satellite observations and climate models. ATMOSPHERIC RESEARCH, 107, 161-170. doi:10.1016/j.atmosres.2012.01.005.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0019-B6A9-A
Abstract
Global and zonal monthly means of cloud cover fraction for total cloudiness (CF) from the ISCCP D2 dataset are compared to same quantities produced by the 20th century simulations of 21 climate models from the World Climate Research Programme's (WCRP's) Coupled Model Intercomparison Project phase 3 (CMIP3). The comparison spans the time frame from January 1984 to December 1999 and the global and zonal averages of CF are studied. It is shown that the global mean of CF for the PCMDI-CMIP3 models, averaged over the whole period, exhibits a considerable variance and generally underestimates the ISCCP value. Large differences among models, and between models and observations, are found in the polar areas, where both models and satellite observations are less reliable, and especially near Antarctica. For this reason the zonal analysis is focused over the 60 degrees S-60 degrees N latitudinal belt, which includes the tropical area and mid-latitudes. The two hemispheres are analysed separately to show the variation of the amplitude of the seasonal cycle. Most models underestimate the yearly averaged values of CF over all the analysed areas, whilst they capture, in a qualitatively correct way, the magnitude and the sign of the seasonal cycle over the whole geographical domain, but overestimate the amplitude of the seasonal cycle in the tropical areas and at mid-latitudes, when taken separately. The interannual variability of the yearly averages is underestimated by all models in each area analysed, and also the interannual variability of the amplitude of the seasonal cycle is underestimated, but to a lesser extent. This work shows that the climate models have a heterogeneous behaviour in simulating the CF over different areas of the Globe, with a very wide span both with observed CF and among themselves. Some models agree quite well with the observations in one or more of the metrics employed in this analysis, but not a single model has a statistically significant agreement with the observational datasets on yearly averaged values of CF and on the amplitude of the seasonal cycle over all analysed areas. (C) 2012 Elsevier B.V. All rights reserved.