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February 16, 2026Scientific Data2 citationsOpen Access

Global Intensity-Duration-Frequency curves based on observed sub-daily rainfall (GSDR-IDF)

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AGAmy C. GreenSGSelma B. GuerreiroHFHayley J. Fowler

Key Points

  • The research aims to develop a global dataset of intensity-duration-frequency curves from sub-daily rainfall data.
  • Developed GSDR-IDF, a global dataset using over 24,000 quality-controlled sub-daily rain gauge records.
  • Applied robust extreme value analysis methods for multiple return levels and durations.
  • Combined return levels to create intensity-duration-frequency curves for each rain gauge.
  • Provided a globally accessible and reproducible resource for hydrological modelling and flood-risk assessment.
  • Enabled enhanced climate resilience planning across various disciplines.

Abstract

Abstract Short-duration extreme rainfall events can cause flash flooding and infrastructure failures, yet resources to assess these remain limited, particularly at the global scale. Heterogeneous data availability, inconsistent quality control, and methodological differences hinder the development of comparable intensity-duration-frequency (IDF) estimates. To address this gap, we present GSDR-IDF, a global dataset of intensity-duration-frequency curves derived from the largest quality-controlled sub-daily rain gauge dataset: the Global Sub-Daily Rainfall dataset (GSDR), comprising +24,000 hourly rain gauge records for all major climate regions. We apply robust extreme value analysis methods, including single-gauge and regional frequency approaches, to estimate return levels for 1-, 3-, 6- and 24-hour durations and for 10-, 30-, and 100-year return levels. These are then combined to give IDF curves for each rain gauge, providing an openly accessible, traceable, and reproducible resource for hydrological modelling, engineering design, flood-risk assessment and climate-resilience planning. This dataset represents a step change in accessibility and precision for global IDF estimation and enables a wide range of cross-disciplinary applications.

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Cite This Study

Green et al. (2026) studied this question.

synapsesocial.com/papers/6992652ceb1f82dc367a0f0ahttps://doi.org/10.1038/s41597-026-06858-4
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