Future North Atlantic tropical cyclone intensities in thermodynamically modified historical environments

Lalo, Nicholas; Xu, Wenwei; Yao, Lili; Sun, Ning; Balaguru, Karthik; Rice, Julian; Thurber, Travis; Yang, Zhaoqing; Deb, Minthun; Judi, David

doi:10.57931/2588708

Title: Future North Atlantic tropical cyclone intensities in thermodynamically modified historical environments

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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.

Authors:

Lalo, Nicholas; Xu, Wenwei; Yao, Lili; Sun, Ning; Balaguru, Karthik; Rice, Julian; Thurber, Travis; Yang, Zhaoqing; Deb, Minthun; Judi, David

Pacific Northwest National Laboratory

Publication Date:: Wed Sep 17 00:00:00 EDT 2025

DOE Contract Number:: AC05-76RL01830

Research Org.:: Pacific Northwest National Lab (United States)

Sponsoring Org.:: USDOE Office of Science (SC), Biological and Environmental Research (BER)

Subject:: Climate Change; Machine Learning; TGW; Tropical Cyclones

OSTI Identifier:: 2588708

DOI:: https://doi.org/10.57931/2588708

Citation Formats


                    Lalo, Nicholas, Xu, Wenwei, Yao, Lili, Sun, Ning, Balaguru, Karthik, Rice, Julian, Thurber, Travis, Yang, Zhaoqing, Deb, Minthun, and Judi, David. Future North Atlantic tropical cyclone intensities in thermodynamically modified historical environments.  United States: N. p., 2025. 
        Web.  doi:10.57931/2588708.

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                    Lalo, Nicholas, Xu, Wenwei, Yao, Lili, Sun, Ning, Balaguru, Karthik, Rice, Julian, Thurber, Travis, Yang, Zhaoqing, Deb, Minthun, & Judi, David. Future North Atlantic tropical cyclone intensities in thermodynamically modified historical environments.  United States.  doi:https://doi.org/10.57931/2588708

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                    Lalo, Nicholas, Xu, Wenwei, Yao, Lili, Sun, Ning, Balaguru, Karthik, Rice, Julian, Thurber, Travis, Yang, Zhaoqing, Deb, Minthun, and Judi, David. 2025.  
"Future North Atlantic tropical cyclone intensities in thermodynamically modified historical environments".  United States.  doi:https://doi.org/10.57931/2588708.  https://www.osti.gov/servlets/purl/2588708. Pub date:Wed Sep 17 00:00:00 EDT 2025

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@article{osti_2588708,

  title        = {Future North Atlantic tropical cyclone intensities in thermodynamically modified historical environments},

  author       = {Lalo, Nicholas and Xu, Wenwei and Yao, Lili and Sun, Ning and Balaguru, Karthik and Rice, Julian and Thurber, Travis and Yang, Zhaoqing and Deb, Minthun and Judi, David},

  abstractNote = {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.},

  doi          = {10.57931/2588708},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {Wed Sep 17 00:00:00 EDT 2025},

  month        = {Wed Sep 17 00:00:00 EDT 2025}

}

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DOI: https://doi.org/10.57931/2588708

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