Land Data Assimilation

Land Data Assimilation is a systematic methodology within numerical weather prediction data assimilation that specifically integrates observational data over land surfaces with model forecasts to improve the representation of land-state variables such as soil moisture, surface temperature, and vegetation conditions.

509

Publications

40.4K

Citations

1.7K

Authors

599

Institutions

Publications per year

2017–2026

263

Variants

Land Data Assimilation SystemLdas

Authors

1.7K

  1. SV
    Sujay V. Kumar

    Goddard Space Flight Center, United States

    29 publications · 3K citations

    26

    h-index

  2. CD
    C. D. Peters‐Lidard

    Goddard Space Flight Center, United States

    26 publications · 3K citations

    24

    h-index

  3. PR
    Paul R. Houser

    George Mason University, United States

    22 publications · 9.8K citations

    21

    h-index

  4. JC
    Jean‐Christophe Calvet

    Météo-France, France

    20 publications · 1.3K citations

    19

    h-index

  5. RH
    Rolf H. Reichle

    Goddard Space Flight Center, United States

    20 publications · 2.3K citations

    19

    h-index

1–5 of 1.7K

Venues

  1. Journal of Hydrometeorology

    61 publications · 4.9K citations

    37

    h-index

  2. Journal of Geophysical Research Atmospheres

    JGR · 25 publications · 5.9K citations

    24

    h-index

  3. Remote Sensing

    40 publications · 1.6K citations

    23

    h-index

  4. Water Resources Research

    22 publications · 2.3K citations

    21

    h-index

  5. Hydrology and earth system sciences

    20 publications · 1.3K citations

    19

    h-index

1–5