{
  "abstract": "Quantifying the financial risk posed by landfalling tropical cyclones requires statistical methods that extend beyond the limits of a short and non-stationary historical observational record. This paper explores techniques for improving site-specific loss estimation in tropicalcyclone catastrophe risk, an area of ongoing interest to insurance and reinsurance pricingand solvency capital management. We present an end-to-end probabilistic catastrophe riskmodel that captures extreme tail behavior by fitting a continuous Weibull intensity distribution to multi-era NOAA HURDAT2 meteorological data, simulating a 10,000-year stochasticevent set. This hazard catalog is evaluated against an Industry Exposure Database derivedfrom NOAA Digital Coast economic indices, representing a total insured asset value of$39.01 Billion across primary high-hazard coastal corridors. Physical damage is simulatedvia structural vulnerability functions parameterized as log-normal cumulative distributionfunctions, and liabilities are reshaped through vectorized financial policy layers, tracking individual properties rather than county-averaged zones. The resulting property-level resolution reveals loss concentration patterns within a single metro area that a regionally-averagedmodel cannot recover.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": null,
  "author_total": 1,
  "authors": [
    {
      "name": "Kunal J. Rathore"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/0ybbzrqsp45m8.bib",
  "cited_by": 0,
  "doi": "10.31223/x5dv48",
  "fulltext_url": null,
  "id": "0ybbzrqsp45m8",
  "issns": [],
  "landing_url": "https://eartharxiv.org/repository/view/15152/",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/legalcode",
  "metadata_licence": null,
  "native_subjects": [
    [
      "bepress",
      "Catastrophe"
    ],
    [
      "bepress",
      "Computational Engineering"
    ],
    [
      "bepress",
      "Earth Sciences"
    ],
    [
      "bepress",
      "Engineering"
    ],
    [
      "bepress",
      "Environmental Sciences"
    ],
    [
      "bepress",
      "Hazard"
    ],
    [
      "bepress",
      "Loss curve"
    ],
    [
      "bepress",
      "Physical Sciences and Mathematics"
    ],
    [
      "bepress",
      "Risk"
    ],
    [
      "openalex",
      "1902|Tropical and Extratropical Cyclones Research"
    ]
  ],
  "openalex": "W7214149087",
  "pdf_url": "https://eartharxiv.org/repository/object/15152/download/26516/",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-24",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/0ybbzrqsp45m8.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:36Z",
      "native_id": "15152",
      "source": "eartharxiv",
      "url": "https://eartharxiv.org/repository/view/15152/"
    }
  ],
  "subjects": [
    {
      "field": "earth",
      "origin": "bepress:Environmental Sciences",
      "subfield": "environmental-science"
    }
  ],
  "title": "A Probabilistic Framework for Site-Specific Tropical Cyclone Loss Quantification and Reinsurance Optimization",
  "title_text": "A Probabilistic Framework for Site-Specific Tropical Cyclone Loss Quantification and Reinsurance Optimization",
  "type": "preprint",
  "updated_at": "2026-10-30T12:17:36Z",
  "url": "https://research.draconitic.com/paper/0ybbzrqsp45m8",
  "venue": "EarthArXiv",
  "versions": []
}