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Abstract During extensive periods without rain, known as dry-downs, decreasing soil moisture (SM) induces plant water stress at the point when it limits evapotranspiration, defining a critical SM threshold (θcrit). Better quantification of θcrit is needed for improving future projections of climate and water resources, food production, and ecosystem vulnerability. Here, we combine systematic satellite observations of the diurnal amplitude of land surface temperature (dLST) and SM during dry-downs, corroborated by in-situ data from flux towers, to generate the observation-based global map of θcrit. We find an average global θcrit of 0.19 m3/m3, varying from 0.12 m3/m3 in arid ecosystems to 0.26 m3/m3 in humid ecosystems. θcrit simulated by Earth System Models is overestimated in dry areas and underestimated in wet areas. The global observed pattern of θcrit reflects plant adaptation to soil available water and atmospheric demand. Using explainable machine learning, we show that aridity index, leaf area and soil texture are the most influential drivers. Moreover, we show that the annual fraction of days with water stress, when SM stays below θcrit, has increased in the past four decades. Our results have important implications for understanding the inception of water stress in models and identifying SM tipping points.

Abstract Dryland ecosystems cover 40% of our planet's land surface, support billions of people, and are responding rapidly to climate and land use change. These expansive systems also dominate core aspects of Earth's climate, storing and exchanging vast amounts of water, carbon, and energy with the atmosphere. Despite their indispensable ecosystem services and high vulnerability to change, drylands are one of the least understood ecosystem types, partly due to challenges studying their heterogeneous landscapes and misconceptions that drylands are unproductive “wastelands.” Consequently, inadequate understanding of dryland processes has resulted in poor model representation and forecasting capacity, hindering decision making for these at‐risk ecosystems. NASA satellite resources are increasingly available at the higher resolutions needed to enhance understanding of drylands' heterogeneous spatiotemporal dynamics. NASA's Terrestrial Ecology Program solicited proposals for scoping a multi‐year field campaign, of which Adaptation and Response in Drylands (ARID) was one of two scoping studies selected. A primary goal of the scoping study is to gather input from the scientific and data end‐user communities on dryland research gaps and data user needs. Here, we provide an overview of the ARID team's community engagement and how it has guided development of our framework. This includes an ARID kickoff meeting with over 300 participants held in October 2023 at the University of Arizona to gather input from data end‐users and scientists. We also summarize insights gained from hundreds of follow‐up activities, including from a tribal‐engagement focused workshop in New Mexico, conference town halls, intensive roundtables, and international engagements.

Abstract Vegetation optical depth (VOD) satellite microwave retrievals provide significant insights into vegetation water content and responses to hydroclimatic changes. While VOD variations are commonly linked to dry biomass and live fuel moisture content (LFMC), the impact of canopy temperature (Tc) remains overlooked in large‐scale studies. Here, we investigated the impact of Tc on L‐band (1.4 GHz) and X‐band (10.7 GHz) VOD at diurnal and seasonal timescales. Synthetic benchmark VOD was created using realistic fields of Tc, LFMC, and biomass in an electromagnetic model. Perturbation experiments revealed that Tc strongly affects diurnal VOD variations at both L‐band and X‐band. Seasonally, while biomass emerges as the largest contributor to VOD variations in 70% (at X‐band) and 90% (at L‐band) of our study region, Tc and LFMC still play substantial roles. The findings stress the importance of refining retrieval algorithms to distinguish Tc, LFMC, and biomass effects for future VOD applications in ecohydrology.

Abstract Satellite‐retrieved vegetation optical depth (VOD) has provided extensive insights into global plant function (such as, carbon stocks, water stress, crop yields) because of VOD's ability to monitor plant water stress and biomass at near daily temporal frequency under all‐weather conditions. However, arguably, the greatest challenge with broadly applying VOD is its lack of validation partly because of VOD's simultaneous sensitivity to plant water status and biomass changes, as well as intensive methods required to measure these properties in‐situ. Here, inspired by the recent Yao et al. (2024), https://doi.org/10.1029/2023GL107121 article, I argue that VOD estimated from global navigation satellite systems (GNSS) and land surface models with plant hydraulic schemes are two emerging methods that show promise for more widely validating satellite‐based VOD. I encourage wider adoption of these approaches to validate and further advance satellite‐based VOD research.

Abstract While remote sensing has provided extensive insights into the global terrestrial water, carbon, and energy cycles, space‐based retrievals remain limited in observing the belowground influence of the full soil moisture (SM) profile on ecosystem function. We show that this gap can be addressed when coupling 70 m resolution ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station retrievals of land surface temperature (LST) with in‐situ SM profile measurements. These data sets together reveal that ecosystem water use decreases with depth with 93% of sites showing significant LST coupling with SM shallower than 20 cm while 34% of sites have interactions with SM deeper than 50 cm. Furthermore, the median depth of peak ecosystem water use is estimated to be 10 cm, though forests have more common peak interactions with deeper soil layers (50–100 cm) in 37% of cases. High spatial resolution remote sensing coupled with field‐level data can thus elucidate the role of belowground processes on land surface behavior.

Satellite-based soil moisture products allow direct monitoring of agricultural drought, especially in regions with sparse ground-based observations. In this study, a soil moisture drought index only based on satellite soil moisture is developed and adopted to assess drought in Mainland Southeast Asia (MSA). We report here on an exceptionally severe Mainland Southeast Asia drought in 2016, which is believed to be strongly linked to the 2015–2016 super El Niño strongly. The event began in February 2016 and lasted until May 2016, with more than 50% of the study areas suffering from moderate drought or worse at peak period. We assess the evolution of agricultural droughts (defined as prolonged deficit in soil moisture) by placing it in the context of the forcing meteorological drought (prolonged deficit in precipitation). The drought assessment using satellite soil moisture is temporally consistent with precipitation-based metrics, but allows for better mapping of the spatial and temporal patterns of how a precipitation deficit may or may not lead to a soil moisture deficit. The specific advantages of a remote-sensing approach—wide-coverage without need for spatially-dense, ground-based climatological records, and sensitivity to otherwise unmeasured irrigation inputs—suggest further opportunity for drought monitoring in ungauged regions, particularly in agricultural contexts.

Soil moisture impacts the biosphere–atmosphere exchange of CO2 and CH4 and plays an important role in the terrestrial carbon cycle. A better representation of soil moisture would improve coupled carbon–water dynamics in terrestrial ecosystem models and could potentially improve model estimates of large-scale carbon fluxes and climate feedbacks. Here, we investigate using soil moisture observations from the Soil Moisture Active Passive (SMAP) satellite mission to inform simulated carbon fluxes in the global terrestrial ecosystem model LPJ-wsl. Results suggest that the direct insertion of SMAP reduces the bias in simulated soil moisture at in situ measurement sites by 40%, with a greater improvement at temperate sites. A wavelet analysis between the model and measurements from 26 FLUXNET sites suggests that the assimilated run modestly reduces the bias of simulated carbon fluxes for boreal and subtropical sites at 1–2-month time scales. At regional scales, SMAP soil moisture can improve the estimated responses of CO2 and CH4 fluxes to extreme events such as the 2018 European drought and the 2019 rainfall event in the Sudd (Southern Sudan) wetlands. The simulated improvements to land–surface carbon fluxes using the direct insertion of SMAP are shown across a variety of timescales, which suggests the potential of SMAP soil moisture in improving the model representation of carbon–water coupling.

When organic peat soils are sufficiently dry, they become flammable. In Southeast Asian peatlands, widespread deforestation and associated drainage create dry conditions that, when coupled with El Niño-driven drought, result in catastrophic fire events that release large amounts of carbon and deadly smoke to the atmosphere. While the effects of anthropogenic degradation on peat moisture and fire risk have been extensively demonstrated, climate change impacts to peat flammability are poorly understood. These impacts are likely to be mediated primarily through changes in soil moisture. Here, we used neural networks (trained on data from the NASA Soil Moisture Active Passive satellite) to model soil moisture as a function of climate, degradation, and location. The neural networks were forced with regional climate model projections for 1985–2005 and 2040–2060 climate under RCP8.5 forcing to predict changes in soil moisture. We find that reduced precipitation and increased evaporative demand will lead to median soil moisture decreases about half as strong as those observed during recent El Niño droughts in 2015 and 2019. Based on previous studies, such reductions may be expected to accelerate peat carbon emissions. Our results also suggest that soil moisture in degraded areas with less tree cover may be more sensitive to climate change than in other land use types, motivating urgent peatland restoration. Climate change may play an important role in future soil moisture regimes and by extension, future peat fire in Southeast Asian peatlands.