Future North Atlantic tropical cyclone intensities in modified historical environments

Tropical cyclones (TCs) have ranked as the deadliest and most financially crippling natural disasters in the United States. It is imperative to assess potential shifts in TC intensity within the paradigm of an evolving climate. In this study we apply a fixed-constraint storyline approach that holds storm tracks and initial conditions constant to probe future TC intensity in the North Atlantic Basin. First, we simulate 618 historical TC events using the Risk Analysis Framework for Tropical Cyclones (RAFT)'s deep-learning intensity model. Next, we apply warming signals derived from eight CMIP6 climate scenarios and rerun each event to explore how intensities respond across scenarios. Finally, we develop an interactive dashboard that allows users to explore individual storm simulations and the scenario-modified environmental drivers. Together, this dataset and tool provide a clear, illustrative way to investigate how TC intensity responds to changes in air-sea state.

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Publication Details

Journal
Scientific Data
Published
2025-12-05
DOI
https://doi.org/10.1038/s41597-025-06186-z
Primary Topic
Tropical and Extratropical Cyclones Research
Type
article
Field-Weighted Citation Impact
0.00

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article

Future North Atlantic tropical cyclone intensities in modified historical environments

Nicholas Lalo, Wenwei Xu, Mithun Deb, Lili Yao et al.
Scientific Data
Tropical and Extratropical Cyclones Research
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Future North Atlantic tropical cyclone intensities in modified historical environments

Nicholas Lalo, Wenwei Xu, Mithun Deb, Lili Yao, Karthik Balaguru, Travis Thurber, David Judi, Julian Rice, Ning Sun, Serena Lipari, Zhaoqing Yang
article en

Abstract

Tropical cyclones (TCs) have ranked as the deadliest and most financially crippling natural disasters in the United States. It is imperative to assess potential shifts in TC intensity within the paradigm of an evolving climate. In this study we apply a fixed-constraint storyline approach that holds storm tracks and initial conditions constant to probe future TC intensity in the North Atlantic Basin. First, we simulate 618 historical TC events using the Risk Analysis Framework for Tropical Cyclones (RAFT)'s deep-learning intensity model. Next, we apply warming signals derived from eight CMIP6 climate scenarios and rerun each event to explore how intensities respond across scenarios. Finally, we develop an interactive dashboard that allows users to explore individual storm simulations and the scenario-modified environmental drivers. Together, this dataset and tool provide a clear, illustrative way to investigate how TC intensity responds to changes in air-sea state.

Scientific DataVol. 12(1)
Pacific Northwest National Laboratory (US)
U.S. Department of Energy, Battelle, National Energy Research Scientific Computing Center, Office of Science, Biological and Environmental Research, Lawrence Berkeley National Laboratory, Pacific Northwest National Laboratory
Openalex Percentile: Top 57%
Tropical and Extratropical Cyclones Research
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