Lalo et al. (2025) Future North Atlantic tropical cyclone intensities in modified historical environments

Identification

• Journal: Scientific Data
• Year: 2025
• Date: 2025-12-05
• Authors: Nicholas Lalo, Wenwei Xu, Lili Yao, Ning Sun, Karthik Balaguru, Julian Rice, Serena Lipari, Travis Thurber, Zhaoqing Yang, Mithun Deb, David Judi
• DOI: 10.1038/s41597-025-06186-z

Research Groups

Pacific Northwest National Laboratory, Richland, WA, USA

Short Summary

This study investigates future North Atlantic tropical cyclone (TC) intensities under various climate change scenarios by applying warming signals to 618 historical TC events using a deep-learning intensity model, revealing regional shifts in intensity despite conservative overall projections. An interactive dashboard is also provided to explore the simulated data.

Objective

• To assess potential shifts in North Atlantic tropical cyclone intensity within evolving climate scenarios by rerunning historical storm events with fixed tracks and initial conditions under projected warming signals.

Study Configuration

• Spatial Scale: North Atlantic Basin, including the Gulf of Mexico, U.S. East Coast, and Caribbean Sea.
• Temporal Scale: Historical (1979-2018), Near-future (2019-2058), and Far-future (2059-2098).

Methodology and Data

• Models used:
  • Risk Analysis Framework for Tropical Cyclones (RAFT)'s deep-learning intensity model (Multi-Layer Perceptron - MLP).
  • Eight General Circulation Models (GCMs) from CMIP6 for deriving warming signals.
  • tcpyPI Python package for Maximum Potential Intensity (VMPI) calculations.
• Data sources:
  • International Best Track Archive for Climate Stewardship (IBTrACS) dataset (observed TC tracks and initial intensities).
  • Statistical Hurricane Intensity Prediction Scheme (SHIPS) dataset (environmental inputs for TC intensity prediction).
  • ERA5 reanalysis data (environmental inputs).
  • Coupled Model Intercomparison Project Phase 6 (CMIP6) climate scenarios (SSP585 and SSP245) for future warming signals.

Main Results

• The study simulates 618 historical TC events (1979-2018) and reruns them under eight CMIP6-derived future warming scenarios, holding storm tracks and initial conditions constant.
• For SSP245 and SSP585 near-future scenarios, marginal increases in both 75th- and 99th-percentile instantaneous and lifetime maximum wind speeds are observed.
• The SSP585 far-future scenario shows a modest decrease in overall instantaneous and lifetime maximum wind speeds.
• Landfall intensities show slight decreases in median values across all future scenarios, with minimal changes in extreme landfall events.
• Rapid intensification and weakening events show minimal changes, except for fewer occurrences in the SSP585 far-future scenarios.
• Regionally, ensemble-mean intensity declines in the central Gulf of Mexico, while the U.S. East Coast shows slight intensity increases.
• The Caribbean Sea exhibits a pronounced drop in simulated wind speeds (approximately 5.1 to 7.7 meters per second) under SSP585 far-future cold and hot models.
• The RAFT model successfully simulates stronger storms (up to Category 4) but tends to underestimate the peak intensities of Category 5 storms.

Contributions

• Provides a dataset of 618 historical and future simulated TCs across the North Atlantic Basin using RAFT's deep learning intensity model, offering insights into potential intensification patterns under a range of warming scenarios.
• Develops an interactive web-based dashboard for users to explore individual storm simulations and scenario-modified environmental drivers, facilitating broader access and engagement with the data.
• Complements existing dynamical downscaling approaches (e.g., WRF-TGW) by more effectively simulating major TCs (Category 3 and 4) across the full North Atlantic Basin, addressing geographical and intensity limitations of other models.

Funding

• U.S. Department of Energy (DOE), Office of Science, Office of Biological and Environmental Research, as part of the Integrated Coastal Modeling (ICoM) project.
• National Energy Research Scientific Computing Center (NERSC), a U.S. Department of Energy Office of Science User Facility (Contract No. DE-AC02-05CH11231, NERSC award BER-ERCAP0024320).
• Pacific Northwest National Laboratory (operated for DOE by Battelle Memorial Institute under contract DE-AC05-76RL01830).

Citation

@article{Lalo2025Future,
  author = {Lalo, Nicholas and Xu, Wenwei and Yao, Lili and Sun, Ning and Balaguru, Karthik and Rice, Julian and Lipari, Serena and Thurber, Travis and Yang, Zhaoqing and Deb, Mithun and Judi, David},
  title = {Future North Atlantic tropical cyclone intensities in modified historical environments},
  journal = {Scientific Data},
  year = {2025},
  doi = {10.1038/s41597-025-06186-z},
  url = {https://doi.org/10.1038/s41597-025-06186-z}
}