We develop innovative RADAR sensors using Vector Network Analyzers (VNA), Software-Defined Radio (SDR), and System-on-Chip (SoC) technologies for high-resolution measurements in L-, C-, and Ku-bands, optimizing for cost-efficiency and performance.

RADAR sensors will be deployed at three diverse sites: FERM (Belgium), Brundage Reservoir (Idaho, USA), and Weissfluhjoch (Switzerland). They will capture sub-daily changes in soil, vegetation, and snow. In situ data collection will support the validation of key variables like soil moisture (SSM), vegetation optical depth (VOD), and snow water equivalent (SWE).

Using advanced Radiative Transfer Models (RTMs) and machine learning, we will simulate and retrieve Essential Climate Variables (ECVs). Data assimilation with models like GLEAM will enhance the estimation of non-observable variables, including root-zone soil moisture (RZSM) and evaporation (E).

The collected RADAR and in situ data will be processed validated using independent field measurements, ensuring accurate retrieval of ECVs and robust model performance.