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arXiv · 2607.21954

Anomalous Diffusion of Tropical Cyclones Observed in Huge Ensembles of Hindcasts

Abstract

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 inferred for actual TCs from the fluctuations in their tracks from the shortest paths between the initiation and termination of each cyclone. We reproduce the same anomalous diffusion power laws connecting spatial position and time using HENS. In addition, we show that the variance in the position of a single TC across HENS since initiation follows a scaling law with time that, in some cases, corresponds to ballistic motion of the TC through the background atmospheric flow. This determination was enabled by the exceptional statistics determined from thousands of plausible yet counterfactual recreations of 34 individual TCs. HENS consists of 7424 15-day hindcasts initiated from observed atmospheric conditions each day from June 1, 2023 to August 31, 2023 using the ECMWF ERA5 meteorological reanalysis. The hindcasts were generated using NVIDIA's Spherical Fourier Neural Operator (SFNO) machine-learning-based weather and climate emulator. We identify tropical cyclones in HENS using a variant of the Tempest Extremes detection and tracking frameworks for TCs with adjustments to the disposable parameters to minimize the numbers of false positives and negatives relative to the International Best Track Archive for Climate Stewardship (IBTrACS) records for TCs observed in summer 2023. We conclude with the implications of our findings for the predictability of TC tracks and landfall locations on lead times of days to weeks.

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BibTeXRIS

Abdoul R. Zeba, William D. Collins, Ankur Mahesh, Boris Bonev, Karthik Kashinath, Thorsten Kurth, Michael S. Pritchard, Shashank Subramanian. 2026-07-24. Anomalous Diffusion of Tropical Cyclones Observed in Huge Ensembles of Hindcasts. https://arxiv.org/abs/2607.21954

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