Covariance Localization

Covariance Localization is a statistical filtering technique in data assimilation that belongs to the class of covariance regularization methods, distinguished by its use of spatially dependent weighting to suppress spurious correlations arising from limited ensemble sampling in ensemble-based state estimation, particularly when assimilating radar observations into numerical weather prediction models.

89

Publications

4.4K

Citations

162

Authors

92

Institutions

Publications per year

2017–2026

26

Authors

162

  1. CH
    Craig H. Bishop

    United States Naval Research Laboratory, United States

    9 publications · 753 citations

    9

    h-index

  2. DH
    Daniel Hodyss

    United States Naval Research Laboratory, United States

    7 publications · 545 citations

    7

    h-index

  3. TM
    Takemasa Miyoshi

    University of Maryland, College Park, United States

    7 publications · 331 citations

    7

    h-index

  4. JS
    Jeffrey S. Whitaker

    NOAA Earth System Research Laboratory, United States

    6 publications · 236 citations

    6

    h-index

  5. AA
    Alexandre A. Emerick

    Petrobras (Brazil), Brazil

    5 publications · 307 citations

    5

    h-index

1–5 of 162

Venues

  1. Monthly Weather Review

    30 publications · 1.6K citations

    25

    h-index

  2. 9

    h-index

  3. Tellus A Dynamic Meteorology and Oceanography

    8 publications · 554 citations

    8

    h-index

  4. SOLA

    5 publications · 253 citations

    5

    h-index

  5. SPE Journal

    3 publications · 106 citations

    3

    h-index

1–5