Related Experiment Video
Updated: Jul 12, 2025
08:20
In Situ Soil Moisture Sensors in Undisturbed Soils
Published on: November 18, 2022
6.3K
SM2RAIN-Climate, a monthly global long-term rainfall dataset for climatological studies
Hamidreza Mosaffa1, Paolo Filippucci2, Christian Massari2
1Research Institute for Geo-Hydrological Protection, National Research Council, Perugia, Italy. h.mosaffa@irpi.cnr.it.
Scientific Data
|November 1, 2023
Summary
A new global rainfall dataset, SM2RAIN-Climate, estimates precipitation from satellite soil moisture. This independent product shows robust performance, exceeding 0.8 correlation with existing datasets, aiding climate and water resource studies.
Area of Science:
- Climatology
- Hydrology
- Remote Sensing
Background:
- Long-term rainfall data is vital for climate studies, water management, agriculture, and hydrology.
- Satellite soil moisture observations offer a unique source for independent rainfall estimation.
- Previous SM2RAIN (Soil Moisture to Rain) products demonstrated global potential.
Purpose of the Study:
- Introduce the SM2RAIN-Climate dataset, a novel global monthly rainfall product.
- Utilize the European Space Agency (ESA) Climate Change Initiative (CCI) soil moisture v06.1 data.
- Provide a 24-year (1998-2021) global rainfall record at 1-degree resolution.
Main Methods:
- Derive rainfall estimates using the SM2RAIN algorithm applied to ESA CCI soil moisture data.
- Generate a global monthly rainfall product at 1-degree spatial resolution.
- Assess SM2RAIN-Climate performance against established state-of-the-art rainfall products.
Main Results:
- SM2RAIN-Climate demonstrates robust performance across most global regions.
- Correlation coefficients between SM2RAIN-Climate and other products consistently exceed 0.8.
- The dataset shows potential as an independent product for capturing global rainfall trends.
Conclusions:
- SM2RAIN-Climate offers a reliable and accurate long-term global rainfall dataset.
- Its independence from other satellite rainfall products enhances its value for validation and trend analysis.
- The product supports climatological studies and applications in water resource management and agriculture.
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