This article presents a climatology of total cloud cover (TCC) in the area of the three inland Eurasian seas (Black, Caspian, and Aral Sea). Analyses are performed on the basis of 20 years of data (1991
2010), collected from almost 200 ground stations. Average TCC is 49%, with broad spatial and seasonal variability: minimum TCC values are found in summer and to the southeast, whereas maximum values correspond to winter and to the northwest. For the whole area, linear trend analyses show that TCC did not vary during the study period. We only detected a statistically significant positive trend (+1.2% decade−1) in autumn. We obtained different results for the regions delimited by means of a principal component analysis: a clear decrease, both for the annual, spring, and summer series, was detected for the south of Black Sea, while increasing TCC was found for the annual, autumn, and winter series in the north Caucasus and the west and north of Black Sea. We also analysed the TCC data from global gridded products, including satellite projects [International Satellite Cloud Climatology Project (ISCCP), Pathfinder Atmospheres Extended (PATMOS-x), cLoud, Albedo & Radiation (CLARA)], reanalyses [ERA-interim, National Centers for Environmental Prediction/Department of Energy (NCEP/DOE), Modern-Era Retrospective Analysis for Research and Applications (MERRA)], and surface observations [Climatic Research Unit (CRU)]. Although all these products capture the seasonal evolution over the study area, they differ substantially both among them and in relation to the ground observations: reanalyses produce much lower values of TCC, while ISCCP and CLARA provide a summer minimum that is too high. Trend analyses applied to these data generally showed a decrease in TCC; only CRU and NCEP/DOE tally with the ground data as regards the absence of overall trends. These results are discussed in relation to previous studies presenting trends of other variables such as sunshine duration, diurnal temperature range, or precipitation; we also discuss the connections with changes in synoptic patterns and environmental changes, in particular in the Aral Sea region

This research was developed under the auspices of, and with funding from, the project ‘CLIMSEAS: Climate Change and Inland Seas: Phenomena, Feedbacks, and Uncertainties. The Physical Science Basis’, of the Seventh Framework Programme, European Union People-Marie Curie Actions, International Research Staff Exchange Scheme (FP7-PEOPLE-2009-IRSES N. 247512). Several authors are involved within the project NUCLIERSOL (CGL2010-18546), funded by the Spanish Ministry of Economy and Competitiveness. Aarón Enriquez-Alonso was given a grant from the FPI program (BES-2011-049095) of the same ministry. Arturo Sanchez-Lorenzo was supported by the ‘Secretaria per a Universitats i Recerca del Departament d'Economia i Coneixement, de la Generalitat de Catalunya i del programa Cofund de les Accions Marie Curie del 7è Programa marc d'R+D de la Unió Europea’ (2011 BP-B 00078) and the postdoctoral fellowship JCI-2012-12508. Partial support was provided to the Hydrometeorological Center of Russia by Russian Foundation for Basic Research (№13-05-00562). The ISCCP-D2 data were obtained from the International Satellite Cloud Climatology Project web site (http://isccp.giss.nasa.gov), maintained by the NASA Goddard Institute for Space Studies, New York. Data from EUMETSAT's Satellite Application Facility on Climate Monitoring (CM SAF) were used. PATMOS-x data are available via ftp from the University of Wisconsin, Space Science and Engineering Center (SSEC), and the Cooperative Institute for Meteorological Satellite Studies (CIMSS). ERA-Interim data are supported by the European Center for Medium-range Weather Forecast (ECMWF). NCEP Reanalysis data are provided by the National Oceanic and Atmospheric Administration (NOAA), Oceanic and Atmospheric Research (OAR). Earth System Research Laboratory (ESRL), Physical Sciences Division (PSD) (http://www.esrl.noaa.gov/psd/). MERRA files were obtained from the NASA Goddard Earth Sciences Data and Information Services Center. CRU TS3.20 Time-Series (TS) of High Resolution Gridded Data were provided by the University of East Anglia Climatic Research Unit (CRU)