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Overview of DARC: Training, Model Evaluation, and Data Assimilation Methods

This document provides a comprehensive overview of the DARC (Data Assimilation Research Centre) training program. It covers various aspects of model evaluation in atmospheric and oceanic sciences, including inverse modeling techniques to understand physical processes. The interface between observation and assimilation is discussed, along with re-analysis techniques for both the atmosphere and ocean. Key topics include theoretical foundations of data assimilation, algorithm development, error modeling, and bias correction. The analysis includes observations from MIPAS L2 ozone assessments and highlights findings from ECMWF's first 40-year reanalysis.

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Overview of DARC: Training, Model Evaluation, and Data Assimilation Methods

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  1. Quick Overview of DARC • Training. • Evaluating models: atmosphere and ocean. • Inverse modelling (understanding processes). • Observation-assimilation interface. • “Re-analysis” for the atmosphere and ocean. • Theory of data assimilation, e.g. • algorithm development & improvement • error modelling & error propagation (incl. biases)

  2. O-B statistics for MIPAS L2 ozone DARC analyses, 11-17th September 2002 Global mean O-B

  3. 1st Salinity increment from Salinity data ST ST +SS First 40 yr reanalysis at ECMWF Mean N Pacific Salinity 300m Ocean assimilation research in DARC

  4. Explicit B-matrix MetO B-matrix WS B-matrix (4 bands) Modelling the B matrix Vertical T corrs (fn. of posn.)

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