PERSIANN Satellite Precipitation (CHRS Data Portal)
UC Irvine Center for Hydrometeorology and Remote Sensing precipitation estimates using neural networks including PERSIANN-CDR (1982-present, 0.25deg daily) and PERSIANN-CCS (real-time 4km 30-minute)
chrsdata.eng.uci.edu
At a glance
- Region
- Global
- Coverage
- 60S-60N global, 0.04-0.25deg, 1982-present
- Access
- Free
- Category
- Research Institute
What's inside
- Satellite Precipitation
- Climate Data Record
- Real-time Rainfall
- 3-Hourly Estimates
What you can do with it
Typical work that data of this type supports.
- 01
Design storms
Build rainfall intensity-duration-frequency curves for drainage design.
Because it has: Satellite Precipitation
- 02
Model input
Drive hydrological, crop and urban drainage models.
- 03
No-gauge areas
Monitor places with no ground stations.
Where AI adds value
Ideas for machine learning and AI agents built on this kind of data.
- 01
Downscaling
Turn coarse rainfall grids into field or ward scale estimates.
- 02
Gauge + satellite fusion
Correct satellite rainfall with gauges using machine learning.
- 03
Segmentation
Map water, crops and land use pixel by pixel with deep learning.
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