Assessing the potential of future sub-daily microwave observations for estimating evaporation

Evaporation (E) plays a key role in the terrestrial water, energy, and carbon cycles, and modulates climate change through multiple feedback mechanisms. Its accurate monitoring is thus crucial for water management, meteorological forecasts, and agriculture. However, traditional in situ measurements of E are limited in terms of availability and spatial coverage. As an alternative, global monitoring of E using satellite remote sensing, while indirect, holds the potential to fill this need. Today, different models exist that yield E estimates by combining observable satellite-based drivers of this flux, but typically work at daily or oven monthly time scales. As natural evaporation processes occur at sub-daily resolution, there is a need to estimate evaporation at finer temporal scales to capture the diurnal variability of this flux and to monitor water stress impacts on transpiration. Likewise, interception loss shows high intra-day variability, mainly concentrated during precipitation events and shortly after. Moreover, the moisture redistribution within the soil–plant–atmosphere continuum as a consequence of transpiration is highly non-linear and has a strong daily cycle.

Sub-daily microwave data could inform about these short-term processes, and as such improve process understanding and monitoring of E and its different components, while providing all-skies retrievals. The Sub-daily Land Atmosphere INTEractions (SLAINTE) mission, a mission idea submitted in response to ESA’s 12^th call for Earth Explorers, will aim to provide sub-daily SAR observations of soil moisture, vegetation optical depth (VOD) and wet/dry canopy state, enabling a more accurate estimation of E and the potential to advance E science beyond its current boundaries.

This study investigates the potential value of future SLAINTE observations for improving the estimation of E at four eddy covariance sites. In this regard, Observing System Simulation Experiments (OSSEs) are assembled. In total, three experiments using synthetic microwave observations are implemented, focusing on the role of (1) sub-daily soil moisture in improving bare soil evaporation and transpiration estimates, (2) sub-daily VOD in improving transpiration estimates, and (3) sub-daily microwave observations that inform about the wetness state of the canopy, to address the uncertainties related to rainfall interception loss. The Global Land Evaporation Amsterdam Model (GLEAM; Miralles et al., 2011) is used for the simulations. GLEAM is a state-of-the-art E model that estimates the different E components (mainly transpiration, soil evaporation, and interception loss) using satellite data, including microwave observations of surface soil moisture and VOD. The model is here adapted to work at sub-daily resolution. The results of the OSSEs illustrate that prospective sub-daily microwave data would lead to improvements in the estimation of evaporation and its separate components, even if based on current-generation evaporation models, and highlight the need for missions like SLAINTE to better comprehend the flow of water in ecosystems.