Error Growth Diagnostics

Error Growth Diagnostics is a methodological framework within the study of dynamical systems that systematically identifies, quantifies, and analyzes the sources and evolution of errors in predictive models over time, distinguishing itself by focusing on the diagnostic decomposition of error growth mechanisms rather than mere error measurement or correction.

23

Publications

2.2K

Citations

65

Authors

38

Institutions

Publications per year

2017–2026

8

Authors

65

  1. DP
    David P. Baumhefner

    NSF National Center for Atmospheric Research, United States

    2 publications · 157 citations

    2

    h-index

  2. SP
    Samuel P. Lillo

    University of Oklahoma, United States

    2 publications · 62 citations

    2

    h-index

  3. DO
    David Orrell

    Institute for Systems Biology, United States

    2 publications · 63 citations

    2

    h-index

  4. DB
    David B. Parsons

    NSF National Center for Atmospheric Research, United States

    2 publications · 62 citations

    2

    h-index

  5. GC
    George C. Craig

    Ludwig-Maximilians-Universität München, Germany

    2 publications · 123 citations

    2

    h-index

1–5 of 65

Venues

  1. 4

    h-index

  2. Monthly Weather Review

    4 publications · 266 citations

    4

    h-index

  3. Advances in Atmospheric Sciences

    2 publications · 31 citations

    2

    h-index

  4. Tellus A Dynamic Meteorology and Oceanography

    2 publications · 63 citations

    2

    h-index

  5. Journal of the Atmospheric Sciences

    2 publications · 1.4K citations

    2

    h-index

1–5