Simplistic Overview of Reanalysis Data Assimilation Methods
Data assimilation is the process of combining observations from a wide variety of sources and forecast output from a weather prediction model. The resulting analysis is considered to be the 'best' estimate of the state of the atmosphere at a particular instant in time. The process of combining the observational and model information is accomplished within a Bayesian statistical framework where probability distributions associated with observations and forecasts are combined with dynamical constraints.
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National Center for Atmospheric Research Staff (Eds). Last modified "The Climate Data Guide: Simplistic Overview of Reanalysis Data Assimilation Methods.” Retrieved from https://climatedataguide.ucar.edu/climate-data/simplistic-overview-reanalysis-data-assimilation-methods on 2023-12-04.
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Schneider, D. P., C. Deser, J. Fasullo, and K. E. Trenberth, 2013: Climate Data Guide Spurs Discovery and Understanding. Eos Trans. AGU, 94, 121–122, https://doi.org/10.1002/2013eo130001
Figure 1 . Representation of four basic strategies for data assimilation, as a function of time. The way the time distribution of observations ("obs") is processed to produce a time sequence of assimilated states (the lower curve in each panel) can be sequential and/or continuous. (Source ECMWF: figure and caption)
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