Multi-model Ensemble Forecasting

Multi-Model Ensemble Forecasting is a forecasting methodology that, as an ensemble technique, integrates predictions from multiple distinct numerical models to improve predictive skill and quantify uncertainty, distinguishing itself from single-model approaches by leveraging inter-model diversity to enhance robustness and reliability in medium-range and seasonal climate predictions.

554

Publications

34.5K

Citations

2.7K

Authors

909

Institutions

Publications per year

2017–2026

314

Variants

Multi-model Ensemble Prediction

Authors

2.7K

  1. FJ
    Francisco J. Doblas‐Reyes

    Institució Catalana de Recerca i Estudis Avançats, Spain

    22 publications · 4.5K citations

    19

    h-index

  2. TN
    T. N. Palmer

    European Centre for Medium-Range Weather Forecasts, United Kingdom

    12 publications · 4K citations

    12

    h-index

  3. MK
    Michael K. Tippett

    Columbia University, United States

    8 publications · 572 citations

    8

    h-index

  4. RH
    Renate Hagedorn

    European Centre for Medium-Range Weather Forecasts, United Kingdom

    8 publications · 3.3K citations

    8

    h-index

  5. NG
    Nicholas G Reich

    University of Massachusetts Amherst, United States

    7 publications · 891 citations

    7

    h-index

1–5 of 2.7K

Venues

  1. Climate Dynamics

    50 publications · 3.3K citations

    30

    h-index

  2. Tellus A Dynamic Meteorology and Oceanography

    23 publications · 2.6K citations

    18

    h-index

  3. Journal of Hydrology

    18 publications · 812 citations

    17

    h-index

  4. Geophysical Research Letters

    14 publications · 1.1K citations

    14

    h-index

  5. Environmental Research Letters

    ERL · 14 publications · 1.4K citations

    13

    h-index

1–5