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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. Using systematic satellite observations of land surface temperature and soil moisture during soil dry-downs, the spatially-explicit global distribution of the critical soil moisture threshold of plant water stress and its drivers is uncovered. [ABSTRACT FROM AUTHOR]

The monitoring of soil moisture and sea surface salinity over the Earth has been profoundly enhanced during the last thirteen years due to a new generation of satellite sensors. L-band radiometry is currently the only technology providing direct measurements of soil moisture, insensitive to surface roughness and distribution of elements in the soil, and the only technology the only technology for measuring that allows us to measure sea surface salinity from space. The Soil Moisture and Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP) satellite missions resolve global and local variability with a spatial resolution of approximately 43 km, a swath width close to 1000 km, and a sampling time, for each mission, of at least twice every 3 days. These resolutions and samplings can be increased by either merging data from the two sensors, and with complementary information gathered from other passive or active sensors, or with in situ information at higher spatial resolution. Numerous scientific studies based on the use of this new type of measurement have led to a better understanding and constraint of the processes governing the variability of the water cycle, ocean circulation and the Earth's climate. The continuity of measurements, and the increased spatial and radiometric resolution is critical for fulfilling scientific needs. Future L-band radiometry missions currently being planned in Europe (the Copernicus Imaging Microwave Radiometer), and in China (the Ocean Salinity mission) should provide better constraints on auxiliary parameters by combining multiple frequencies, but they will not have improved spatial resolution beyond SMOS and SMAP. The temporal continuity with SMOS and SMAP will likely not be ensured. In parallel, new concepts are being developed to increase spatial resolution of both land and ocean parameters. [ABSTRACT FROM AUTHOR]

Despite the mounting attention being paid to vegetation growth and their driving forces for water-limited ecosystems, the relative contributions of atmospheric and soil moisture dryness stress on vegetation growth are an ongoing debate. Here we comprehensively compare the impacts of high vapor pressure deficit (VPD) and low soil water content (SWC) on vegetation growth in Eurasian drylands during 1982–2014. The analysis indicates a gradual decoupling between atmospheric dryness and soil dryness over this period, as the former has expanded faster than the latter. Moreover, the VPD–SWC relation and VPD–greenness relation are both non-linear, while the SWC–greenness relation is near-linear. The loosened coupling between VPD and SWC, the non-linear correlations among VPD–SWC-greenness and the expanded area extent in which SWC acts as the dominant stress factor all provide compelling evidence that SWC is a more influential stressor than VPD on vegetation growth in Eurasian drylands. In addition, a set of 11 Earth system models projected a continuously growing constraint of SWC stress on vegetation growth towards 2100. Our results are vital to dryland ecosystems management and drought mitigation in Eurasia. [ABSTRACT FROM AUTHOR]

Environmental change is a consequence of many interrelated factors. How vegetation responds to natural and human activity still needs to be well established, quantified and understood. Recent satellite missions providing hydrologic and ecological indicators enable better monitoring of Earth system changes, yet there is no automatic way to address this issue directly from observations. Here, we develop an observation-based methodology to capture evidence of changes in global terrestrial ecosystems and attribute these changes to natural or anthropogenic activity. We use the longest time record of global microwave L-band soil moisture and vegetation optical depth as satellite data and build spatially explicit maps of change in soil and vegetation water content and biomass reflecting large ecosystem changes during the last decade, 2010–20. Regions of prominent trends (from $-8\%$ to 9% per year) are observed, especially in humid and semi-arid climates. We further combine such trends with land cover change maps, vegetation greenness and precipitation variability to assess their relationship with major documented ecosystem changes. Several regions emerge from our results. They cluster changes according to human activity drivers, including deforestation (Amazon, Central Africa) and wildfires (East Australia), artificial reforestation (South-East China), abandonment of farm fields (Central Russia) and climate shifts related to changes in precipitation variability (East Africa, North America and Central Argentina). Using the high sensitivity of soil and vegetation water content to ecosystem changes, microwave satellite observations enable us to quantify and attribute global vegetation responses to climate or anthropogenic activities as a direct measure of environmental changes and the mechanisms driving them. This work identifies and quantifies the main large ecosystem changes during 2010-2020. Regions with prominent joint SM and VOD trends stand out, and can be semantically attributed to climate or anthropogenic activities, from reforestation and deforestation to irrigation changes and wildfires. [ABSTRACT FROM AUTHOR]

Surface soil moisture (SSM) is an important variable in drought monitoring, floods predicting, weather forecasting, etc. and plays a critical role in water and heat exchanges between land and atmosphere. SSM products from L-band observations, such as the Soil Moisture Active Passive (SMAP) Mission, have proven to be optimal global estimations. Although X-band has a lower sensitivity to soil moisture than that of L-band, Chinese FengYun-3 series satellites (FY-3A/B/C/D) have provided sustainable and daily multiple SSM products from X-band since 2008. This research developed a new global SSM product (NNsm-FY) from FY-3B MWRI from 2010 to 2019, transferred high accuracy of SMAP L-band to FY-3B X-band. The NNsm-FY shows good agreement with in-situ observations and SMAP product and has a higher accuracy than that of official FY-3B product. With this new dataset, Chinese FY-3 satellites may play a larger role and provide opportunities of sustainable and longer-term soil moisture data record for hydrological study. [ABSTRACT FROM AUTHOR]

Climate change is altering precipitation regimes globally, with expectations of intensified precipitation patterns (for example, larger but fewer rainfall events) and more frequent and extreme drought. Both aspects of precipitation change can impact ecosystem function individually, but it is more likely that they will occur in combination. In a central US mesic grassland, we imposed an extreme 2-year drought (growing season precipitation reduced by 66%) on plots with a long-term (16-year) history of exposure to either ambient or intensified precipitation patterns (average threefold increase in event size and threefold decrease in event number during the growing season). While this intensified pattern did not alter total precipitation amount, it generally led to ecosystem responses consistent with a drier environment (for example, reduced soil moisture, aboveground net primary production (ANPP), and soil CO2 flux, but little evidence for altered root biomass). Surprisingly, this history of intensified precipitation patterns did not affect the response of ANPP to the subsequent extreme drought. In contrast, previous exposure to intensified precipitation patterns reduced root production and muted soil CO2 flux responses to rainfall events during drought. Reduced root production in plots experiencing compounded precipitation extremes was driven not by the dominant C4 grass species, Andropogon gerardii, but collectively by the subdominant species in the plant community. Overall, our results reveal that compound changes in precipitation patterns and amount affected this grassland in ways that were less apparent (that is, belowground) than responses to either change individually and significantly reduced ecosystem carbon uptake. [ABSTRACT FROM AUTHOR]

Both low soil water content (SWC) and high atmospheric dryness (vapor pressure deficit, VPD) can negatively affect terrestrial gross primary production (GPP). The sensitivity of GPP to soil versus atmospheric dryness is difficult to disentangle, however, because of their covariation. Using global eddy-covariance observations, here we show that a decrease in SWC is not universally associated with GPP reduction. GPP increases in response to decreasing SWC when SWC is high and decreases only when SWC is below a threshold. By contrast, the sensitivity of GPP to an increase of VPD is always negative across the full SWC range. We further find canopy conductance decreases with increasing VPD (irrespective of SWC), and with decreasing SWC on drier soils. Maximum photosynthetic assimilation rate has negative sensitivity to VPD, and a positive sensitivity to decreasing SWC when SWC is high. Earth System Models underestimate the negative effect of VPD and the positive effect of SWC on GPP such that they should underestimate the GPP reduction due to increasing VPD in future climates. Using global flux tower observations, the authors show that atmospheric dryness always reduces photosynthesis, whereas soil dryness can increase photosynthesis if soil water stores are sufficient. [ABSTRACT FROM AUTHOR]

The land surface influences the atmospheric boundary layer (ABL) through its impacts on the partitioning of available energy into evaporation and warming. Previous research on understanding this complex link focused mainly on site-scale flux observations, gridded satellite observations, climate modeling, and machine-learning experiments. Observational evidence of land surface conditions, among which soil moisture, impacting ABL properties at intermediate landscape scales is lacking. Here, we use a combination of global weather balloon soundings, satellite-observed soil moisture, and a coupled land-atmosphere model to infer the soil moisture impact on the ABL. The inferred relationship between soil moisture and surface flux partitioning reflects distinctive energy- and water-limited regimes, even at the landscape scale. We find significantly different behavior between those two regimes, associating dry conditions with on average warmer (≈3 K), higher (≈400 m) and drier (≈1 kPa) afternoon ABLs than wet conditions. This evidence of land–atmosphere coupling from globally distributed atmospheric measurements highlights the need for an accurate representation of land–atmosphere coupling into climate models and their climate change projections. [ABSTRACT FROM AUTHOR]