December 5, 2025Open Access

Future North Atlantic tropical cyclone intensities in modified historical environments

Key Points

Tropical cyclone intensity correlates strongly with climate conditions, indicating projected increases in severity.
Analysis of 618 historical tropical cyclone events was performed using a deep-learning intensity model.
A fixed-constraint approach was utilized to maintain storm tracks while evaluating future intensities.
These findings highlight the need for adaptive disaster planning frameworks as climate conditions evolve.

Abstract

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.

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