Temperature Anomaly Forecasting

Temperature Anomaly Forecasting is a predictive modeling task within climate and meteorological science that involves estimating deviations of future temperature values from their long-term historical averages, distinguishing it from general temperature forecasting by focusing specifically on anomalous departures rather than absolute temperature levels.

41

Publications

1.8K

Citations

136

Authors

91

Institutions

Publications per year

2017–2026

15

Authors

136

  1. MU
    Matthias Uhl

    University of Zurich, Switzerland

    3 publications · 143 citations

    3

    h-index

  2. SS
    Samuel S. P. Shen

    University of Alberta, Canada

    2 publications · 84 citations

    2

    h-index

  3. GD
    Gökhan Danabasoglu

    NSF National Center for Atmospheric Research, United States

    2 publications · 28 citations

    2

    h-index

  4. EH
    Ed Hawkins

    University of Reading, United Kingdom

    2 publications · 57 citations

    2

    h-index

  5. EM
    Elizabeth Maroon

    University of Wisconsin–Madison, United States

    2 publications · 28 citations

    2

    h-index

1–5 of 136

Venues

  1. Climate Dynamics

    4 publications · 111 citations

    4

    h-index

  2. Journal of Climate

    4 publications · 101 citations

    4

    h-index

  3. Monthly Weather Review

    3 publications · 158 citations

    3

    h-index

  4. Geophysical Research Letters

    2 publications · 161 citations

    2

    h-index

  5. Neural Computing and Applications

    2 publications · 34 citations

    2

    h-index

1–5