APS Logo

Statistical Methods and Extreme Events in Climate

FOCUS · MAR-C45 · ID: 3091961

Presentations

  • Title: Predicting extreme events from time series data using machine learning

    ORAL · Invited

    –

    Publication: Revealing the statistics of extreme events hidden in short weather forecast data, Justin Finkel, Edwin P. Gerber, Dorian S. Abbot, Jonathan Weare, AGU Advances 2023, Volume 4, Issue 2 e2023AV000881<br><br>The surprising efficiency of temporal difference learning for rare event prediction, Xiaoou Cheng, Jonathan Weare, Advances in Neural Information Processing (NeurIPS) 2024<br><br>Can AI weather models predict out-of-distribution gray swan tropical cyclones? Y. Qiang Sun, Pedram Hassanzadeh, Mohsen Zand, Ashesh Chattopadhyay, Jonathan Weare, Dorian S. Abbot, submitted

    Presenters

    • Jonathan Weare

      NYU

    Authors

    • Jonathan Weare

      NYU

    • Dorian S Abbot

      University of Chicago

    • Ashesh K Chattopadhyay

      University of California, Santa Cruz

    • Xiaoou Cheng

      Courant Institute, New York University

    • Justin M Finkel

      MIT

    • Edwin P Gerber

      Courant Institute, New York University

    • Pedram Hassanzadeh

      University of Chicago

    • Y. Qiang Sun

      University of Chicago

    • Mohsen Zand

      University of Chicago

    View abstract →

  • Simulation of extreme events and rare transitions in climate models with rare event algorithms

    ORAL · Invited

    –

    Publication: - Sauer J., Massonnet F., Zappa G., Ragone F., Ensemble design for seasonal climate predictions: Studying extreme Arctic sea ice lows with a rare event algorithm, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2024-3082 (2024);<br>- Sauer J., Demaeyer J., Massonnet F., Zappa G., Ragone F., Extremes of summer Arctic sea ice reduction investigated with a rare event algorithm, Climate Dynamics 62, 5219–5237 (2024);<br>- Cini M., Zappa G., Ragone F., Corti S., Simulating AMOC tipping driven by internal climate variability with a rare event algorithm, npj Clim Atmos Sci 7, 31 (2024);<br>- Ragone F., Bouchet F., Rare event algorithm study of extreme warm summers and heatwaves over Europe, Geophysical Research Letters, 48, e2020GL091197 (2021);<br>- Ragone F., Bouchet F., Computation of extremes values of time averaged observables in climate models with large deviation techniques, J. Stat. Phys., 179, 1637-1665 (2020);<br>- Ragone F., Wouters J., Bouchet F., Computation of extreme heat waves in climate models using a large deviation algorithm, Proc. Natl. Acad. Sci. U.S.A., 115(1), 24-29 (2018).

    Presenters

    • Francesco Ragone

      University of Leicester

    Authors

    • Francesco Ragone

      University of Leicester

    View abstract →

  • Agnostic detection of large-scale weather patterns in the northern hemisphere: from blockings to teleconnections

    ORAL

    –

    Publication: Springer, S., Laio, A., Galfi, V.M., and Lucarini, V., Unsupervised detection of large-scale weather patterns in the northern hemisphere via Markov State Modelling: from blockings to teleconnections. npj Clim Atmos Sci 7, 105 (2024). https://doi.org/10.1038/s41612-024-00659-5

    Presenters

    • Valerio Lucarini

      University of Leicester

    Authors

    • Valerio Lucarini

      University of Leicester

    • Alessandro Laio

      SISSA, SISSA, Trieste, Italy

    • Sebastian Springer

      SISSA

    • Vera Melinda Galfi

      Vrije Universiteit Amsterdam

    View abstract →