Precise rainfall data, of high temporal frequency greatly helps advance an understanding of its impact on crops, soil infiltration and groundwater recharge. Free, publicly available, long-term rainfall data in India is generally only available at monthly intervals. While this is sufficient for understanding long term seasonal rainfall trends it is insufficient for deeper analysis.
Hourly rainfall data could help model much more accurately how much of rainwater in a watershed infiltrates into the ground. This indirectly could be used to estimate drinking water security, since much of India depends on groundwater for domestic use. Hourly data also helps ascertain the extent of flooding accurately in the event of heavy rainfall events. Daily rainfall data helps capture the phenomenon of dry spells, which can adversely impact crops in areas where supplementary irrigation isn't available, as it is in much of India.
This project explores openly available high frequency, high resolution, remotely sensed, rainfall datasets made available by the Tropical Rainfall Monitoring Mission (TRMM), the Global Precipitation Measurement (GPM) and modeled CHIRPS precipitation data. We evaluate these datasets to understand the accuracy of each and their possible use cases. As a first step, we have made available the CHIRPS Daily rainfall dataset for exploration. The first goal would be to compare this dataset with Indian Meteorological Department's data for better understanding. See related blogposts below for more