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Through their significant impact on the short- and longwave radiation and their pivotal role in the hydrological cycle, clouds and their response to climate change are a key component in present-day and future climate. As part of the SPARC Reanalysis Intercomparison Project (S-RIP) phase 2, we analyze cloud climatologies from twelve reanalysis datasets including, for instance, ERA5, MERRA2 and JRA-55. The study focuses on parameters that are available from most reanalysis datasets such as cloud fraction, cloud liquid and ice water content as well as cloud radiative effects on monthly to multi-year time scales. Geographical distributions, variability and statistical properties of the cloud parameters from the reanalyses for specific cloud regimes and regions are compared and put into context with satellite observations. First results show that more recent reanalysis products are in closer agreement with the satellite data and that in contrast to multi-model means of models participating in the Coupled Model Intercomparison Project (CMIP), multi-reanalysis means do not outperform individual reanalyses. For a consistent processing of all reanalysis and satellite datasets, the Earth System Model Evaluation Tool (ESMValTool) is applied. ESMValTool is a community developed open-source software tool that provides common operations such regridding data onto the same grid, masking of missing values, area extraction, and basic statistics such as seasonal means, annual means, area means, etc. which facilitates analysis and a fair intercomparison of the datasets. For comparison with satellite data, multiple products for each parameter are used to estimate observational uncertainties.
Lauer et al. (Fri,) studied this question.