Advancing our understanding of the dynamics and composition of the middle atmosphere in the context of the changing climate requires accurate knowledge of the global state of the atmosphere spanning time scales from daily to multidecadal. Individual and “merged” datasets, both satellite and conventional, when used together with modern atmospheric reanalyses afford an opportunity to study variability and long-term changes of the climate system, including stratospheric composition and, at the same time, to identify the mechanisms for that variability. In particular, over the last decade, reanalysis datasets have become a widely used tool for addressing multiple questions in weather and climate sciences. Observational datasets and reanalyses complement each other: observations not only provide the input for reanalyses but also serve as a benchmark for their evaluation. Reanalyses are in turn powerful tools for interpreting the often sparsely sampled data in the context of the meteorological conditions. Although reanalyses are uniquely valuable tools for analyzing long-term data records, their use in identifying and assessing possible trends is complicated by changes in the observing systems used for data inputs; understanding how reanalyses can best be used to further trend studies is a challenging but important area of research.

The session welcomes contributions on new developments, evaluation, intercomparison, and applications of reanalyses and long-term observational datasets that are relevant to the middle atmosphere. We encourage contributions using reanalyses in conjunction with satellite data and long-term “merged” datasets, and studies using novel methods to compare reanalyses with observations, as well as studies exploring the use of reanalyses and long-term datasets in assessing trends and the mechanisms causing them.  

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