A reanalysis of past weather can be obtained by combining observational datasets from surface stations and satellites with a comprehensive Numerical Weather Prediction (NWP) model. Using modern data assimilation methods, a complete estimate of the atmospheric state can be obtained that is both dynamically consistent and optimally close to the observations. The great benefit of a reanalysis is that it provides a complete picture of the atmosphere, covering the whole of the 3-dimensional domain, not only of the observed variables, but also of those that are not directly measured.
Reanalysis records of climate variables extending several decades back in time can be extremely valuable in climate research and climate monitoring.

To fully exploit the potential of reanalyses data requires improvements in data assimilation algorithms, NWP models, and improved recovery, quality control and bias correction of observations. There are several European projects that work on these issues, such as ERA-CLIM and EURO4M.

This session invites papers that:
• Explore and demonstrate the capability of global and regional reanalysis products for applications like weather extremes,
climate assessment and decision making;
• Assess existing products through comparison with independent high quality datasets;
• Diagnose errors/uncertainties;
• Assess the quality of observations and their use in reanalyses and exploit new observational data.