Predictability Horizon

Predictability Horizon is a metric in dynamical systems theory that quantifies the maximum time interval over which the evolution of a chaotic system can be accurately forecasted despite sensitive dependence on initial conditions, as characterized by positive Lyapunov exponents.

19

Publications

797

Citations

81

Authors

67

Institutions

Publications per year

2017–2026

9

Variants

Predictability Time

Authors

81

  1. RS
    Roland Séférian

    Centre National de la Recherche Scientifique, France

    3 publications · 133 citations

    3

    h-index

  2. TI
    Tatiana Ilyina

    Max Planck Institute for Meteorology, Germany

    3 publications · 108 citations

    3

    h-index

  3. AS
    Aaron Spring

    Max Planck Institute for Meteorology, Germany

    3 publications · 108 citations

    3

    h-index

  4. GD
    Gökhan Danabasoglu

    NSF National Center for Atmospheric Research, United States

    2 publications · 72 citations

    2

    h-index

  5. MO
    M. O. Chikamoto

    Japan Agency for Marine-Earth Science and Technology, Japan

    2 publications · 72 citations

    2

    h-index

1–5 of 81

Venues

  1. Geophysical Research Letters

    4 publications · 178 citations

    4

    h-index

  2. The Journal of the Acoustical Society of America

    JASA · 2 publications · 110 citations

    2

    h-index

  3. 1

    h-index

  4. Empirical Economics

    1 publications · 62 citations

    1

    h-index

  5. Science Advances

    1 publications · 46 citations

    1

    h-index

1–5