Convective-scale Data Assimilation

Convective-Scale Data Assimilation is a specialized form of numerical weather prediction data assimilation that integrates high-resolution observational data, particularly from radar and other remote sensing systems, into cloud-resolving models at horizontal grid scales of approximately 1–4 km to accurately initialize and improve the representation of convective-scale atmospheric processes such as thunderstorms and shallow or deep convection.

154

Publications

12K

Citations

450

Authors

144

Institutions

Publications per year

2017–2026

70

Authors

450

  1. PB
    Pierre Brousseau

    Météo-France, France

    11 publications · 2.1K citations

    11

    h-index

  2. JG
    Jidong Gao

    University of Oklahoma, United States

    11 publications · 1.1K citations

    11

    h-index

  3. TJ
    Tijana Janjić

    Ludwig-Maximilians-Universität München, Germany

    10 publications · 611 citations

    10

    h-index

  4. XW
    Xuguang Wang

    University of Oklahoma, United States

    10 publications · 399 citations

    10

    h-index

  5. MX
    Ming Xue

    University of Oklahoma, United States

    9 publications · 1.1K citations

    9

    h-index

1–5 of 450

Venues

  1. Monthly Weather Review

    40 publications · 5.3K citations

    28

    h-index

  2. 27

    h-index

  3. Weather and Forecasting

    9 publications · 421 citations

    9

    h-index

  4. Atmospheric Research

    10 publications · 386 citations

    9

    h-index

  5. Tellus A Dynamic Meteorology and Oceanography

    4 publications · 181 citations

    4

    h-index

1–5