SM2RAIN

SM2RAIN estimates rainfall from soil moisture time series to validate soil moisture products, including the Climate Change Initiative (CCI) soil moisture dataset, and support hydrological research.

Key Features:

• Rainfall Estimation: Derives rainfall from soil moisture time series using the SM2RAIN algorithm.
• Soil Moisture Validation: Uses rainfall-derived signals to validate the Climate Change Initiative (CCI) soil moisture product.
• Remote Sensing Integration: Leverages remote sensing techniques to estimate hydrological variables such as rainfall and soil moisture.
• Python® Implementation: Implemented in Python® with specific classes and methods for algorithm execution and data processing.
• Big Data Handling: Processes large volumes of satellite-derived data for regional and global-scale analyses.
• Case Study Application: Applies the SM2RAIN algorithm to the CCI soil moisture product as an example application.

Scientific Applications:

• Soil Moisture Product Validation: Validation of satellite-derived soil moisture products using rainfall estimates.
• Hydrological Research: Investigation of hydrological variables and water-cycle dynamics from remotely sensed observations.
• Natural Hazard Assessment: Support for natural hazard assessment and mitigation through improved soil moisture and rainfall information.
• Data‑sparse Region Studies: Estimation of rainfall and soil moisture in regions with limited ground-based instrumentation.

Methodology:

Implements the SM2RAIN algorithm using Python® classes and methods, applying remote-sensing-based rainfall estimation to the Climate Change Initiative (CCI) soil moisture product and processing large volumes of satellite-derived data.