Bias Correction

Bias Correction is a statistical post-processing and data assimilation technique that estimates and removes systematic errors (biases) from numerical weather prediction model outputs or assimilated observations by adjusting their statistical properties toward reference data, thereby improving the quality of initial conditions and subsequent forecasts.

2.3K

Publications

179.2K

Citations

6.3K

Authors

1.7K

Institutions

Publications per year

2017–2026

783

Authors

6.3K

  1. AS
    Ashish Sharma

    UNSW Sydney, Australia

    32 publications · 1.9K citations

    23

    h-index

  2. MV
    Mathieu Vrac

    Laboratoire des Sciences du Climat et de l'Environnement, France

    17 publications · 1.4K citations

    17

    h-index

  3. JC
    Jie Chen

    Wuhan University, China

    15 publications · 1.4K citations

    15

    h-index

  4. RM
    Rajeshwar Mehrotra

    UNSW Sydney, Australia

    14 publications · 700 citations

    14

    h-index

  5. JM
    José Manuel Gutiérrez

    Universidad de Cantabria, Spain

    13 publications · 1.4K citations

    13

    h-index

1–5 of 6.3K

Venues

  1. Hydrology and earth system sciences

    60 publications · 8.3K citations

    42

    h-index

  2. 42

    h-index

  3. Monthly Weather Review

    95 publications · 5.8K citations

    42

    h-index

  4. Journal of Climate

    66 publications · 17K citations

    39

    h-index

  5. Journal of Geophysical Research Atmospheres

    JGR · 59 publications · 7K citations

    35

    h-index

1–5