Three-dimensional Variational Data Assimilation

Three-Dimensional Variational Data Assimilation is a data assimilation method that belongs to the class of variational techniques and is distinguished by its formulation of a cost function minimized over a three-dimensional spatial domain to produce an optimal analysis of the atmospheric state at a given time.

336

Publications

24.6K

Citations

998

Authors

273

Institutions

Publications per year

2017–2026

62

Variants

3D-var Data Assimilation3Dvar Data Assimilation

Authors

998

  1. JG
    Jidong Gao

    University of Oklahoma, United States

    15 publications · 1.2K citations

    15

    h-index

  2. MX
    Ming Xue

    University of Oklahoma, United States

    15 publications · 951 citations

    15

    h-index

  3. JS
    Juanzhen Sun

    NSF National Center for Atmospheric Research, United States

    14 publications · 1.5K citations

    14

    h-index

  4. PC
    Philippe Courtier

    European Centre for Medium-Range Weather Forecasts, United Kingdom

    11 publications · 1.8K citations

    11

    h-index

  5. DB
    Dale Barker

    NSF National Center for Atmospheric Research, United States

    9 publications · 1.3K citations

    9

    h-index

1–5 of 998

Venues

  1. Monthly Weather Review

    87 publications · 8.8K citations

    46

    h-index

  2. 31

    h-index

  3. Weather and Forecasting

    24 publications · 1.8K citations

    22

    h-index

  4. Tellus A Dynamic Meteorology and Oceanography

    16 publications · 919 citations

    14

    h-index

  5. Journal of Atmospheric and Oceanic Technology

    13 publications · 740 citations

    13

    h-index

1–5