A 10,000-Year Global Stochastic Tropical Cyclone Catalog with Wind-Dependent Track Transitions (WHITS)
arXiv:2605.20494v1 Announce Type: new Abstract: Reliable assessment of tropical cyclone (TC) risk is limited by the brevity and spatial sparsity of the historical record, particularly for the rare, high-intensity landfalls that dominate insured loss. We present WHITS (Wind-focused Hurricane Interactive Track Simulator), a non-parametric semi-Markov track generator that extends the HITS framework of Nakamura et al. (2015) in three ways: transitions between historical track segments are conditioned on local wind speed in addition to position, age, and forward vector; the kernel selection on the
The increasing frequency and intensity of extreme weather events necessitate more accurate and long-range predictive models for risk assessment.
This AI model significantly improves tropical cyclone risk assessment by generating extensive, high-fidelity storm catalogs, which is crucial for infrastructure planning, insurance, and disaster preparedness.
The ability to generate 10,000-year stochastic tropical cyclone catalogs with wind-dependent track transitions vastly enhances the resolution and reliability of long-term climate risk modeling.
- · Reinsurance companies
- · Coastal urban planners
- · Climate risk modelers
- · Infrastructure developers
- · Entities relying on outdated climate risk assessments
- · Regions unprepared for increased storm activity
Improved catastrophic risk models will lead to more accurate insurance premiums and better-informed development decisions in hurricane-prone zones.
Enhanced foresight into extreme weather patterns could drive significant investment in climate adaptation technologies and resilient infrastructure.
The long-term economic stability of coastal regions might improve due to proactive risk mitigation, potentially influencing migration patterns and capital allocation.
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Read at arXiv cs.LG