455 citations · 711 across the 25 of their papers we have counts for
4 papers · 1 filter
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…
Surface temperature extremes produced by huge machine learning hindcasts of summer 2023
Mark Risser, Ankur Mahesh, William D. Collins +6
The summer of 2023 brought record-breaking heat extremes across the globe. In this work, we investigate how much worse these extremes might have become, given identical large-scale…
On Neural Scaling Laws for Weather Emulation through Continual Training
Shashank Subramanian, Alexander Kiefer, Arnur Nigmetov +3
Neural scaling laws, which in some domains can predict the performance of large neural networks as a function of model, data, and compute scale, are the cornerstone of building fou…
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…