Adjoint-based Error Growth Analysis

Adjoint-Based Error Growth Analysis is a methodological framework within error analysis that employs adjoint operators to quantify and trace the sensitivity of forecast errors to initial conditions or model perturbations, distinguishing itself by enabling efficient computation of error growth dynamics in high-dimensional systems through backward integration in the dual space.

7

Publications

534

Citations

22

Authors

7

Institutions

Publications per year

2017–2026

0

Authors

22

  1. FR
    Florence Rabier

    Météo-France, France

    3 publications · 405 citations

    3

    h-index

  2. EK
    E. Klinker

    European Centre for Medium-Range Weather Forecasts, United Kingdom

    2 publications · 378 citations

    2

    h-index

  3. RG
    Ronald Gelaro

    Goddard Space Flight Center, United States

    2 publications · 116 citations

    2

    h-index

  4. FF
    F. Fang

    Imperial College London, United Kingdom

    1 publications · 34 citations

    1

    h-index

  5. AH
    A HOLLINGSWORTH

    1 publications · 27 citations

    1

    h-index

1–5 of 22

Venues

  1. 3

    h-index

  2. Computers & Fluids

    1 publications · 17 citations

    1

    h-index

  3. CentAUR (University of Reading)

    Repository · 1 publications · 26 citations

    1

    h-index

  4. Meteorologische Zeitschrift

    1 publications · 52 citations

    1

    h-index

  5. Ocean Modelling

    1 publications · 34 citations

    1

    h-index

1–5