Earth System Models (ESMs) are essential tools for understanding and predicting global change, but they cannot explicitly resolve hillslope‐scale terrain structures that fundamentally organize water, energy, and biogeochemical stores and fluxes at subgrid scales. Here we bring together hydrologists, Critical Zone scientists, and ESM developers, to explore how hillslope structures may modulate ESM grid‐level water, energy, and biogeochemical fluxes. In contrast to the one‐dimensional (1‐D), 2‐ to 3‐m deep, and free‐draining soil hydrology in most ESM land models, we hypothesize that 3‐D, lateral ridge‐to‐valley flow through shallow and deep paths and insolation contrasts between sunny and shady slopes are the top two globally quantifiable organizers of water and energy (and vegetation) within an ESM grid cell. We hypothesize that these two processes are likely to impact ESM predictions where (and when) water and/or energy are limiting. We further hypothesize that, if implemented in ESM land models, these processes will increase simulated continental water storage and residence time, buffering terrestrial ecosystems against seasonal and interannual droughts. We explore efficient ways to capture these mechanisms in ESMs and identify critical knowledge gaps preventing us from scaling up hillslope to global processes. One such gap is our extremely limited knowledge of the subsurface, where water is stored (supporting vegetation) and released to stream baseflow (supporting aquatic ecosystems). We conclude with a set of organizing hypotheses and a call for global syntheses activities and model experiments to assess the impact of hillslope hydrology on global change predictions.

The ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) was launched to the International Space Station on 29 June 2018 by the National Aeronautics and Space Administration (NASA). The primary science focus of ECOSTRESS is centered on evapotranspiration (ET), which is produced as Level‐3 (L3) latent heat flux (LE) data products. These data are generated from the Level‐2 land surface temperature and emissivity product (L2_LSTE), in conjunction with ancillary surface and atmospheric data. Here, we provide the first validation (Stage 1, preliminary) of the global ECOSTRESS clear‐sky ET product (L3_ET_PT‐JPL, Version 6.0) against LE measurements at 82 eddy covariance sites around the world. Overall, the ECOSTRESS ET product performs well against the site measurements (clear‐sky instantaneous/time of overpass: r² = 0.88; overall bias = 8%; normalized root‐mean‐square error, RMSE = 6%). ET uncertainty was generally consistent across climate zones, biome types, and times of day (ECOSTRESS samples the diurnal cycle), though temperate sites are overrepresented. The 70‐m‐high spatial resolution of ECOSTRESS improved correlations by 85%, and RMSE by 62%, relative to 1‐km pixels. This paper serves as a reference for the ECOSTRESS L3 ET accuracy and Stage 1 validation status for subsequent science that follows using these data.

Core Ideas: Satellites, particularly at L‐band frequency, can globally map near‐surface soil moisture. Near‐surface moisture is extended to the root zone using models and data assimilation. Validation uses core monitoring sites, monitoring networks, field campaigns, and multi‐satellite comparisons. Efforts are underway to associate soil moisture variability dynamics with land surface attributes. This is an update to the special section “Remote Sensing for Vadose Zone Hydrology—A Synthesis from the Vantage Point” [Vadose Zone Journal 12(3)]. Satellites (e.g., Soil Moisture Active Passive [SMAP] and Soil Moisture and Ocean Salinity [SMOS]) using passive microwave techniques, in particular at L‐band frequency, have shown good promise for global mapping of near‐surface (0–5‐cm) soil moisture at a spatial resolution of 25 to 40 km and temporal resolution of 2 to 3 d. C‐ and X‐band soil moisture records date back to 1978, making available an invaluable data set for long‐term climate research. Near‐surface soil moisture is further extended to the root zone (top 1 m) using process‐based models and data assimilation schemes. Validation of remotely sensed soil moisture products has been ongoing using core monitoring sites, sparse monitoring networks, intensive field campaigns, as well as multi‐satellite comparison studies. To transfer empirical observations across space and time scales and to develop improved retrieval algorithms at various resolutions, several efforts are underway to associate soil moisture variability dynamics with land surface attributes in various energy‐ and water‐rich environments. We describe the most recent scientific and technological advances in soil moisture remote sensing. We anticipate that remotely sensed soil moisture will find many applications in vadose zone hydrology in the coming decades.