Data Assimilation

Data Assimilation is a mathematical and computational framework within the broader class of state estimation methods that systematically integrates observational data with numerical models to improve the accuracy of the modeled system state by minimizing uncertainties arising from model errors and incomplete initial conditions, particularly in dynamic geophysical systems such as the atmosphere and hydrosphere.

14.7K

Publications

1.1M

Citations

30.6K

Authors

4.2K

Institutions

Publications per year

2017–2026

4.6K

Authors

30.6K

  1. RH
    Rolf H. Reichle

    Goddard Space Flight Center, United States

    85 publications · 26.6K citations

    55

    h-index

  2. JG
    J. G. Anderson

    NSF National Center for Atmospheric Research, United States

    100 publications · 11.5K citations

    49

    h-index

  3. EK
    Eugenia Kalnay

    University of Maryland, College Park, United States

    99 publications · 41.9K citations

    49

    h-index

  4. TM
    Takemasa Miyoshi

    University of Maryland, College Park, United States

    103 publications · 7K citations

    47

    h-index

  5. WT
    Wade T. Crow

    Agricultural Research Service, United States

    67 publications · 6.4K citations

    44

    h-index

1–5 of 30.6K

Venues

  1. Monthly Weather Review

    1.2K publications · 119.4K citations

    146

    h-index

  2. Quarterly Journal of the Royal Meteorological Society

    824 publications · 134.9K citations

    129

    h-index

  3. Journal of Geophysical Research Atmospheres

    JGR · 606 publications · 59.4K citations

    118

    h-index

  4. Geophysical Research Letters

    319 publications · 24.2K citations

    85

    h-index

  5. Atmospheric chemistry and physics

    283 publications · 23.8K citations

    81

    h-index

1–5