SM2RAIN-Climate: monthly global long-term rainfall dataset
A global monthly rainfall dataset derived from satellite soil moisture observations using the SM2RAIN algorithm, providing an independent alternative to traditional precipitation products.
doi.org
At a glance
- Region
- Global
- Coverage
- Global
- Access
- Free
- Category
- Research
- Last updated
- 2023
What's inside
- Precipitation
- Soil Moisture
- Remote Sensing
Terms explained
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: Precipitation
- 02
Model input
Drive hydrological, crop and urban drainage models.
- 03
Irrigation scheduling
Decide when and how much to irrigate.
Because it has: Soil Moisture
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
Field-scale ET
Estimate crop water use per field by combining satellite and weather with ML.
Machine access and documentation
Data paper
SM2RAIN-Climate: monthly global long-term rainfall dataset
Scientific Data 2023
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