An Hourly Dataset of Moisture Budget Components Over the Indian Subcontinent (1940-2024)

Area of Science:

• Atmospheric Science
• Climate Science
• Data Science

Background:

• Understanding atmospheric moisture transport is crucial for climate studies.
• High-resolution datasets are needed for detailed analysis of regional climate phenomena.
• Existing reanalysis data may not fully capture moisture budget dynamics.

Purpose of the Study:

• To construct and present a comprehensive, high-resolution gridded dataset of atmospheric moisture budget components over the Indian subcontinent.
• To provide a reliable resource for analyzing moisture processes and supporting climate research in the region.

Main Methods:

• Utilized ERA5 reanalysis data from 1940-2024 for the Indian subcontinent and surrounding oceans.
• Calculated seven column-integrated moisture budget components using central finite difference methods and vertical integration.
• Validated the dataset against ERA5 single-level outputs for physical consistency.

Main Results:

• Developed ERA5moistIN, a dataset with 0.25-degree spatial and hourly temporal resolution.
• The dataset includes key moisture budget terms like storage change, advection, and convergence.
• Validation confirmed the dataset's physical consistency and reliability.

Conclusions:

• ERA5moistIN provides a valuable, high-resolution resource for atmospheric moisture studies.
• The dataset is suitable for monsoon analysis, extreme event attribution, and model evaluation.
• The diagnostic framework is adaptable to other datasets and regions.