Terrestrial evaporation (E) plays a crucial role in the water, energy, and carbon cycles and modulates climate change through multiple feedback mechanisms. While process-based models estimate E using satellite-derived drivers, they typically operate at daily or lower temporal resolutions. Key components of E, such as transpiration and interception loss, exhibit strong diurnal variability, especially under water stress and during or shortly after precipitation events. Therefore, capturing the sub-daily variability of these variables is essential for improved process understanding and E monitoring at fine temporal resolutions. Sub-Daily microwave observations offer the potential to resolve these short-term processes while providing all-sky retrievals. The Sub-daily Land Atmosphere INTEractions (SLAINTE) mission, proposed as part of European Space Agency's New Earth Observation Mission Ideas, aims to provide sub-daily Synthetic Aperture Radar (SAR) observations of surface soil moisture (SSM), vegetation optical depth (VOD), and wet/dry canopy state (WDCS). These observations are expected to enhance the estimation of E beyond current capabilities. This study explores the added value of such observations through observing system simulation experiments conducted at four European eddy-covariance forest sites, constraining a sub-daily version of the Global Land Evaporation Amsterdam Model (GLEAM) with synthetic sub-daily microwave observations. Three experiments assess the impact of: 1) sub-daily SSM on bare soil evaporation and transpiration; 2) sub-daily VOD on transpiration; and 3) sub-daily WDCS on interception loss. Results demonstrate that prospective sub-daily microwave data can substantially improve E estimates and its components, showing average relative improvements in terms of Δ RMSE of up to 25% for interception loss when assimilating sub-daily WDCS, and up to 33% for transpiration when using sub-daily VOD. Our results highlight the need for satellite missions that provide sub-daily microwave data to better understand forest responses to environmental stress.

Current satellite-based active microwave observations lack the temporal resolution needed to accurately capture rapid Earth system dynamics such as soil–plant–atmosphere interactions, rainfall interception, snowfall and rain-on-snow events. Ground-based radar systems can resolve these processes but typically rely on high-end VNAs, limiting their affordability and deployment scale. This work presents a low-cost SFCW radar system built around a compact, SDR-based VNA with an enhanced RF front end supported by remote-access firmware and a cloud-based back end with automatic backup. Calibration experiments and preliminary measurements demonstrate that the system achieves stable performance and is capable of capturing high-temporal-resolution microwave signatures relevant for climate monitoring.