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20182026
most citedFourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators

455 citations · 711 across the 25 of their papers we have counts for

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physics.ao-ph2026

Anomalous Diffusion of Tropical Cyclones Observed in Huge Ensembles of Hindcasts

Abdoul R. Zeba, William D. Collins, Ankur Mahesh +5

We examine whether tropical cyclones (TCs) obey ordinary Brownian or anomalous diffusion using a huge ensemble (HENS) of hindcasts for summer 2023. Anomalous diffusion has been inf…

physics.ao-ph2026

Examining Fast Radiatively Driven Responses Using Machine-Learning Weather Emulators

Ankur Mahesh, William D. Collins, Travis A. O'Brien +10

The response of the climate system to increased greenhouse gases and other radiative perturbations is governed by a combination of fast and slow feedbacks. Slow feedbacks are typic…

physics.ao-ph2024★ 4 cited

Huge Ensembles Part I: Design of Ensemble Weather Forecasts using Spherical Fourier Neural Operators

Ankur Mahesh, William Collins, Boris Bonev +13

Studying low-likelihood high-impact extreme weather events in a warming world is a significant and challenging task for current ensemble forecasting systems. While these systems pr…

physics.ao-ph2022★ 25 cited

FourCastNet: Accelerating Global High-Resolution Weather Forecasting using Adaptive Fourier Neural Operators

Thorsten Kurth, Shashank Subramanian, Peter Harrington +6

Extreme weather amplified by climate change is causing increasingly devastating impacts across the globe. The current use of physics-based numerical weather prediction (NWP) limits…

physics.ao-ph2022★ 455 cited

FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators

Jaideep Pathak, Shashank Subramanian, Peter Harrington +10

FourCastNet, short for Fourier Forecasting Neural Network, is a global data-driven weather forecasting model that provides accurate short to medium-range global predictions at $0.2…