Climate Anomaly Detection

Climate Anomaly Detection is a methodological framework within climate science that identifies statistically significant deviations of paleoclimatic or instrumental climate observations from established baseline conditions, distinguishing itself by its focus on detecting non-stationary, extreme, or unprecedented climatic events in spatial and temporal records.

74

Publications

5.3K

Citations

223

Authors

139

Institutions

Publications per year

2017–2026

23

Authors

223

  1. JK
    Jaya Kawale

    University of Minnesota, United States

    3 publications · 65 citations

    3

    h-index

  2. VK
    Vipin Kumar

    University of Minnesota, United States

    3 publications · 65 citations

    3

    h-index

  3. SL
    Stefan Liess

    University of Minnesota, United States

    2 publications · 39 citations

    2

    h-index

  4. MS
    Michael Steinbach

    University of Minnesota, United States

    2 publications · 46 citations

    2

    h-index

  5. TJ
    Timothy J. Osborn

    University of East Anglia, United Kingdom

    2 publications · 237 citations

    2

    h-index

1–5 of 223

Venues

  1. Geophysical Research Letters

    4 publications · 1.4K citations

    4

    h-index

  2. Climate Dynamics

    3 publications · 199 citations

    3

    h-index

  3. Science

    2 publications · 220 citations

    2

    h-index

  4. Journal of Geophysical Research Atmospheres

    JGR · 2 publications · 243 citations

    2

    h-index

  5. 2

    h-index

1–5