Fog Data Assimilation

Fog Data Assimilation is a computational methodology within atmospheric data assimilation that specifically integrates heterogeneous observational data with numerical weather prediction models to improve the accuracy of fog onset, duration, and dissipation forecasts.

24

Publications

1.1K

Citations

82

Authors

53

Institutions

Publications per year

2017–2026

9

Authors

82

  1. PM
    Pauline Martinet

    Centre National de la Recherche Scientifique, France

    4 publications · 107 citations

    4

    h-index

  2. VU
    Vinciane Unger

    Centre National de la Recherche Scientifique, France

    3 publications · 89 citations

    3

    h-index

  3. FB
    Frédéric Burnet

    Météo-France, France

    3 publications · 89 citations

    3

    h-index

  4. TB
    Thierry Bergot

    Météo-France, France

    3 publications · 64 citations

    3

    h-index

  5. BM
    Benjamin Ménétrier

    Météo-France, France

    3 publications · 112 citations

    3

    h-index

1–5 of 82

Venues

  1. Pure and Applied Geophysics

    PAGEOPH · 4 publications · 159 citations

    4

    h-index

  2. Atmospheric Research

    3 publications · 161 citations

    3

    h-index

  3. Monthly Weather Review

    2 publications · 64 citations

    2

    h-index

  4. Weather and Forecasting

    2 publications · 122 citations

    2

    h-index

  5. Atmospheric measurement techniques

    2 publications · 80 citations

    2

    h-index

1–5