Om Dhakal contributed an article to the periodic newsletter of the Young Engineering Geologists (YEG) community, focusing on an innovative method to enhance rainfall intensity data in regions lacking high-frequency measurements. His work is particularly relevant to rural and mountainous areas of Nepal—his home country—where weather stations often provide only daily rainfall totals, limiting accurate flood and landslide risk assessments.

This novel technique bridges that gap by using NASA’s high-resolution satellite rainfall data—specifically from the GPM-IMERG system, which estimates rainfall every 30 minutes globally.

The challenge is that satellite data often don’t match ground-based measurements. To fix this, the method scales the satellite’s sub-daily rainfall estimates so their daily total aligns perfectly with what’s measured on the ground. This is done using a statistical tool called the Johnson SB distribution, which reshapes the satellite data to reflect realistic hourly patterns while preserving the total daily rainfall.

In a test case from central Nepal, satellite data overestimated a heavy rain event by more than 80%. After applying the adjustment, the corrected hourly rainfall sequence closely matched the true daily total, providing a far more accurate picture of when and how the rain fell. This type of enhanced data is vital for predicting landslides, planning drainage systems, and understanding how climate change is affecting local rainfall patterns.

Read the full news article here.