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Tom Beucler

  1. ClimSim-Online: A Large Multi-scale Dataset and Framework for Hybrid ML-physics Climate Emulation
    2023/06/14 by Sungduk Yu, Yu, Sungduk, Z W Hu +91 · 5 citations
    Earth and Planetary Sciences · Physics and Astronomy · Environmental Science · #Meteorological Phenomena and Simulations #Model Reduction and Neural Networks #Hydrological Forecasting Using AI
  2. Distilling Machine Learning's Added Value: Pareto Fronts in Atmospheric Applications
    2024/08/04 by Tom Beucler, Arthur Grundner, Beucler, Tom +9 · 3 citations
    Decision Sciences · Earth and Planetary Sciences · Environmental Science · #Air Quality Monitoring and Forecasting #Atmospheric and Oceanic Physics (physics.ao-ph) #Big Data Technologies and Applications #Computational Physics (physics.comp-ph) #FOS: Computer and information sciences #FOS: Physical sciences #Machine Learning (cs.LG) #Meteorological Phenomena and Simulations
  3. Navigating the Noise: Bringing Clarity to ML Parameterization Design with O(100) Ensembles
    2023/09/28 by Y. S. Lin, Sungduk Yu, Lin, Jerry +11 · 2 citations
    Environmental Science · Earth and Planetary Sciences · #Climate variability and models #Meteorological Phenomena and Simulations #Hydrology and Watershed Management Studies
  4. Improving Predictions of Convective Storm Wind Gusts through Statistical Post-Processing of Neural Weather Models
    2025/03/31 by Antoine Leclerc, Leclerc, Antoine, Erwan Koch +7 · 1 citation
    Earth and Planetary Sciences · Environmental Science · #Atmospheric and Oceanic Physics (physics.ao-ph) #Climate variability and models #FOS: Computer and information sciences #FOS: Physical sciences #Machine Learning (cs.LG) #Meteorological Phenomena and Simulations #Wind and Air Flow Studies
  5. Maximum updraft velocity beyond CAPE: the role of boundary layer dynamics and pressure perturbations
    2026/07/26 by Bety Pechacova, Alejandro Casallas, Tom Beucler +2
    #physics.ao-ph