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Data Assimilation for Numerical Weather Prediction: A Review

  • Ionel M. Navon

Abstract

During the last 20 years data assimilation has gradually reached a mature center stage position at both Numerical Weather Prediction centers as well as being at the center of activities at many federal research institutes as well as at many universities.

The research encompasses now activities which involve, beside meteorologists and oceanographers at operational centers or federal research facilities, many in the applied and computational mathematical research communities. Data assimilation or 4-D VAR extends now also to other geosciences fields such as hydrology and geology and results in the publication of an ever increasing number of books and monographs related to the topic.

In this short survey article we provide a brief introduction providing some historical perspective and background, a survey of data assimilation prior to 4-D VAR and basic concepts of data assimilation.

I first proceed to outline the early 4-D VAR stages (1980–1990) and addresses in a succinct manner the period of the 1990s that saw the major developments and the flourishing of all aspects of 4-D VAR both at operational centers and at research Universities and Federal Laboratories. Computational aspects of 4-D Var data assimilation addressing computational burdens as well as ways to alleviate them are briefly outlined.

Brief interludes are provided for each period surveyed allowing the reader to have a better perspective A brief survey of different topics related to state of the art 4-D Var today is then presented and we conclude with what we perceive to be main directions of research and the future of data assimilation and some open problems. We will strive to use the unified notation of Ide et al. (J Meteor Soc Japan 75:181–189, 1997).

Keywords

4-D VAR data assimilation 3-D VAR parameter estimation minimization methods 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Ionel M. Navon
    • 1
  1. 1.Department of Scientific ComputingThe Florida State UniversityTallahasseeUSA

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