Improved reanalyses of past weather can be obtained by retrospectively assimilating reprocessed observational datasets ranging from surface stations and satellites with a up-to-date Numerical Weather Prediction (NWP) model. The resulting time series of the atmospheric state is both dynamically consistent and close to observations. The interest in extracting climate information from reanalysis is rising and creating a request for reanalysis uncertainty estimation at various temporal-spatial scales.
These research questions are adressed in the ERA-CLIM, EURO4M and UERRA projects which are supporting the development of the Copernicus Climate Change Services.

This session invites papers that:
• Explore and demonstrate the capability of global and regional reanalysis data for climate applications
• Compare different reanalysis (global, regional) with each other and/or observations
• Improve recovery, quality control and uncertainty estimation of related observations
• Analyse the uncertainty budget of the reanalyses and relate to user applications