Ensemble Cloud Cover Forecasting

Ensemble Cloud Cover Forecasting is a cloud cover forecasting method that integrates multiple individual predictions from diverse models or perturbed initial conditions to quantify uncertainty and improve prediction accuracy by capturing a range of possible atmospheric states.

8

Publications

382

Citations

22

Authors

16

Institutions

Publications per year

2017–2026

3

Authors

22

  1. FK
    Fanyou Kong

    University of Oklahoma, United States

    1 publications · 102 citations

    1

    h-index

  2. JA
    Jason A. Otkin

    University of Wisconsin–Madison, United States

    1 publications · 102 citations

    1

    h-index

  3. SH
    Stephan Hemri

    Federal Office of Meteorology and Climatology MeteoSwiss, Switzerland

    1 publications · 29 citations

    1

    h-index

  4. RM
    Rebecca M. Cintineo

    University of Oklahoma, United States

    1 publications · 102 citations

    1

    h-index

  5. PC
    Pyramo Costa

    Pontifícia Universidade Católica de Minas Gerais, Brazil

    1 publications · 91 citations

    1

    h-index

1–5 of 22

Venues

  1. Monthly Weather Review

    3 publications · 150 citations

    3

    h-index

  2. Neural Computing and Applications

    1 publications · 34 citations

    1

    h-index

  3. Applied Soft Computing

    1 publications · 91 citations

    1

    h-index

  4. Journal of Applied Meteorology and Climatology

    JAMC · 1 publications · 38 citations

    1

    h-index

  5. Weather and Forecasting

    1 publications · 36 citations

    1

    h-index

1–5