Do Not Use the ICAT Hurricane Loss “Dataset”: An Opportunity for Course Correction in Climate Science

Abstract A fatally flawed time series of U.S. hurricane losses assembled by an insurance company almost a decade ago has found its way into analyses published in the peer-reviewed literature. The flawed time series is based on undocumented modifications to a research-quality dataset that I and my colleagues published almost two decades ago. The uncritical use of the time series has led to erroneous conclusions published in the peer-reviewed literature which then were repeated in important climate science assessments. This paper explains the origin of the flawed dataset and demonstrates its many biases. The errors are so obvious and consequential that papers published in the peer-reviewed literature that rely on the flawed dataset should be retracted. While mistakes happen in science, what matters more is what we in the community do when mistakes are discovered.

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Publication Details

Journal
Journal of Applied Meteorology and Climatology
Published
2025-04-01
DOI
https://doi.org/10.1175/jamc-d-24-0222.1
Primary Topic
Meteorological Phenomena and Simulations
Type
article
Field-Weighted Citation Impact
0.00
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article

Do Not Use the ICAT Hurricane Loss “Dataset”: An Opportunity for Course Correction in Climate Science

Roger A. Pielke
Journal of Applied Meteorology and Climatology
Meteorological Phenomena and Simulations
article

Do Not Use the ICAT Hurricane Loss “Dataset”: An Opportunity for Course Correction in Climate Science

Roger A. Pielke
article en

Abstract

Abstract A fatally flawed time series of U.S. hurricane losses assembled by an insurance company almost a decade ago has found its way into analyses published in the peer-reviewed literature. The flawed time series is based on undocumented modifications to a research-quality dataset that I and my colleagues published almost two decades ago. The uncritical use of the time series has led to erroneous conclusions published in the peer-reviewed literature which then were repeated in important climate science assessments. This paper explains the origin of the flawed dataset and demonstrates its many biases. The errors are so obvious and consequential that papers published in the peer-reviewed literature that rely on the flawed dataset should be retracted. While mistakes happen in science, what matters more is what we in the community do when mistakes are discovered.

Journal of Applied Meteorology and ClimatologyVol. 64(4)
University of Colorado Boulder (US)
Openalex Percentile: Top 87%
Meteorological Phenomena and Simulations
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