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

Area of Science:

• Hydrology and Climate Science
• Extreme Weather Event Analysis
• Geospatial Data Science

Background:

• Extreme rainfall events pose significant risks, including flash flooding and infrastructure damage.
• Global-scale assessment of these events is hindered by data limitations and methodological inconsistencies.
• Intensity-Duration-Frequency (IDF) curves are crucial for understanding rainfall extremes but lack global comparability.

Purpose of the Study:

• To develop a comprehensive, global dataset of Intensity-Duration-Frequency (IDF) curves.
• To address the limitations in data availability, quality control, and methodological differences in existing IDF estimates.
• To provide an open, traceable, and reproducible resource for various scientific and engineering applications.

Main Methods:

• Utilized the Global Sub-Daily Rainfall dataset (GSDR), comprising over 24,000 hourly rain gauge records.
• Applied robust extreme value analysis, including single-gauge and regional frequency approaches.
• Estimated return levels for multiple durations (1-24 hours) and return periods (10-100 years) to construct IDF curves.

Main Results:

• Generated GSDR-IDF, a global dataset of IDF curves for each rain gauge.
• The dataset covers all major climate regions, offering unprecedented global coverage and precision.
• Provides estimates for various return levels crucial for risk assessment.

Conclusions:

• The GSDR-IDF dataset represents a significant advancement in global IDF estimation accessibility and accuracy.
• Enables enhanced hydrological modeling, engineering design, and flood-risk assessment.
• Facilitates cross-disciplinary applications in climate resilience and disaster preparedness planning.