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Water stress in the Amazon is exacerbated by rising temperatures and reduced moisture levels. However, understanding forest responses to increased aridity is hindered by limited in situ water potential observations in the Amazon. Remote sensing of water content has emerged as a promising metric. Vegetation Water Content (VWC) diurnal dynamics is hypothesized to reflect water stress responses. Conventional sensors' low sampling rates impede capturing and studying sub‐daily VWC dynamics. Leveraging Global Navigation Satellite System Reflectometry (GNSS‐R) with unprecedented sampling rates, this study reveals significant disparities in morning and evening VWCs in the Amazon, for example, by ≈ ${\approx} $1.1 and 1.0 kg/m2 ${\mathrm{m}}^{2}$ during the wet and dry seasons of 2019. A strong correlation (R=0.8) $(R=0.8)$ between Δ ${\Delta }$VWC (the difference between evening and morning VWCs) and vapor pressure deficit is observed in Amazonian peatland. This highlights the potential of VWC from innovative remote sensing techniques in elucidating water stress dynamics in critical ecosystems. Plain Language Summary: In the Amazon rainforest, rising temperatures and decreasing moisture levels are causing plants to experience more water stress. However, scientists have struggled to understand how the forests are responding to these drier conditions as direct measurements of plant moisture content do not provide sufficient coverage. Recently, researchers have started using satellites to measure water in plants, which could help us understand how they are coping with the lack of water. However, conventional sensors hardly offer measurements often enough to capture the daily changes in plant water levels. This study uses a novel satellite observation technique, Global Navigation Satellite System Reflectometry, that offers measurements with unprecedented frequency. It is found that there are significant differences in plants' water content in the morning compared to the evening in the Amazon, for example, by ≈ ${\approx} $1.1 and 1.0 kg/m2 ${\mathrm{m}}^{2}$ during the wet and dry seasons of 2019. This study reveals that the difference level responds significantly to environmental aridity. As a result, novel satellite methods could help us better understand how water stress is affecting the Amazon rainforest. Key Points: Global Navigation Satellite System Refractometry offers unprecedented sampling, unveiling Amazon's diurnal vegetation water contentVegetation water content generally peaks in mornings, fluctuating significantly throughout the dayAmazonian peatland's VWC diurnal cycle correlates strongly (R=0.8) $(R=0.8)$ with vapor pressure deficit, proposed as a water stress indicator [ABSTRACT FROM AUTHOR]

In this study, prominent dust source areas are identified along with their plume extent using high temporal frequency satellite observations. Hourly dust plume observations of the Dust Belt from geostationary‐orbit satellites are analyzed for the 2017‐12–2022‐11 period. To identify dust source areas and their extents, we back‐track plumes to their source, assessing source areas in terms of emission frequency, contribution, and plume extent patterns. This method advances over traditional source allocation techniques that rely on polar‐orbiting satellites based on a few daily passes and meteorological wind fields for backtracking. Our findings indicate that Boreal summer is the most intense season for most sources, except in the Southern Sahara, which experiences winterly winds. Our analysis also reveals significant contributions from regions within the Sahara that experience expansive but infrequent dust storms, highlighting the importance of considering both frequency and magnitude in understanding dust emissions. Plain Language Summary: This study focuses on the role of mineral dust, a significant climate constituent originating mainly from arid regions. Identifying where dust comes from and where it goes is essential for understanding how it affects the climate. To do so, we employ high temporal frequency satellite data to backtrack dust plumes to their sources, revealing key dust‐emitting regions and their seasonal variations. We also quantify each source area's frequency and magnitude of emissions and the spatial distribution of emanating dust plumes. Our findings show that summer is the peak season for most areas, except for the strongest dust sources, located in Southern Sahara, which peak in winter driven by seasonal winds. Additionally, some Saharan source areas exhibit severe storms but have been under‐emphasized because they were measured by the frequency of their storms. Key Points: High‐temporal‐resolution images from geostationary‐orbit satellites enable precise back‐tracking of dust source areasDust source areas are analyzed in terms of their emission frequency, contribution to the regional atmosphere, and corresponding plume extentSummer is the peak dust emission season for most sources in West Asia and Sahara and ephemeral lake beds are active during the dry season [ABSTRACT FROM AUTHOR]

To bridge the knowledge gap between (a) our (instantaneous‐to‐seasonal‐scale) process understanding of plants and water and (b) our projections of long‐term coupled feedbacks between the terrestrial water and carbon cycles, we must uncover what the dominant dynamics are linking fluxes of water and carbon. This study uses the simplest empirical dynamical systems models—two‐dimensional linear models—and observation‐based data from satellites, eddy covariance towers, weather stations, and machine‐learning‐derived products to determine the dominant sub‐annual timescales coupling carbon uptake and (normalized) evaporation fluxes. We find two dominant modes across the Contiguous United States: (1) a negative correlation timescale on the order of a few days during which landscapes dry after precipitation and plants increase their carbon uptake through photosynthetic upregulation. (2) A slow, seasonal‐scale positive covariation through which landscape drying leads to decreased growth and carbon uptake. The slow (positively correlated) process dominates the joint distribution of local water and carbon variables, leading to similar behaviors across space, biomes, and climate regions. We propose that vegetation cover/leaf area variables link this behavior across space, leading to strong emergent spatial patterns of water/carbon coupling in the mean. The spatial pattern of local temporal dynamics—positively sloped tangent lines to a convex long‐term mean‐state curve—is surprisingly strong, and can serve as a benchmark for coupled Earth System Models. We show that many such models do not represent this emergent mean‐state pattern, and hypothesize that this may be due to lack of water‐carbon feedbacks at daily scales. [ABSTRACT FROM AUTHOR]

Terrestrial carbon uptake and water availability have coupled feedbacks; specifically water uptake for plant growth and soil drying via transpiration. While we might expect this coupling over time at arid sites, climatic water availability also widely covaries geographically with biomass variables that control photosynthetic rates. Using eddy covariance data globally, we find convex, positively‐covarying relations between carbon uptake and a turbulent flux metric controlled by land surface moisture (r = 0.73 monthly across sites) at the site level. We estimate a general, empirical relationship based on site‐wise water‐carbon dynamics. Most sites, and the general relationship, show strong power‐law dependence, implicating the role of sub‐seasonal land‐cover dynamics. We also find that long‐term mean carbon/water states follow a similar convex relationship to the site‐specific temporal dynamics. We discuss opportunities and caveats for space‐for‐time frameworks of carbon/water feedback processes globally. Plain Language Summary: The amount of carbon dioxide that plants take from the air depends on how plants respond to water and water stress. At the same time, plants also control the loss of water from the landscape through transpiration. While we think of individual stressed plants in dry conditions as being very sensitive to the time‐variability in water available to them, we find here that the average carbon uptake by plants across climate zones is similarly related to climatic water availability. Water availability and carbon uptake rates seem not to depend strongly on location, so that most locations behave quite similarly, across many climates. This can be explained by similar structural changes in the vegetation canopy in response to water stress, whether it be over time at a site or across regions with different mean climate conditions. Key Points: Landscape carbon uptake displays strong relationships with landscape evaporative fractionThese relations are non‐linear both at single sites and across bioclimates at eddy covariance tower sitesChanges in structural canopy‐scale variables (e.g., leaf‐area) may dominate the coupling of water and carbon cycles similarly in both space and time [ABSTRACT FROM AUTHOR]

Land surface‐atmosphere coupling and soil moisture memory are shown to combine into a distinct temporal pattern for wildfire incidents across the western United States. We investigate the dynamic interplay of observed soil moisture, vegetation water content, and atmospheric dryness in relation to fuel loading, fire ignition and post‐fire recovery. We find that positive soil moisture anomalies around 5 months before fire ignition increase biomass growth in the subsequent months, thereby shaping fire‐prone vegetation conditions. Then, concurrent decrease in soil moisture, vegetation dehydration, and atmospheric dryness collectively contribute to the occurrence of fire ignition events. This is followed by a rapid recovery in both soil and atmospheric moisture within several weeks after the fire incidents. Our findings provide insights into understanding of wildfire ignition dynamics, supporting fire modeling and enabling improved fire predictions, early warning systems, and mitigation strategies. Plain Language Summary: We find that wildfire are part of a distinct temporal pattern of soil moisture, vegetation water content and atmospheric dryness dynamics that begin about 5 months before the incidents. We analyze anomalies in soil moisture, vegetation water content, vapor pressure deficit and precipitation before and after large wildfires during the warm season across various US climate regions. We document distinct patterns in soil aridity and atmospheric dryness, fuel load, and vegetation dehydration that contribute to the occurrence of wildfires. Our observation‐based analyses show that soil moisture anomalies significantly control the growth of biomass several months before the fire occurrence, which in turn affects the availability of fire fuel. Notable dry anomalies with fuel accumulation in the dry western climate regions are observed approximately 4 to 5 months before the fires, followed by a quick recovery trend several weeks after the fire in wet regions. Our results indicate that in the majority of the climate regions, there are significant dry anomalies preceding the occurrence of wildfires. Understanding the dynamics of these environmental variables can be the basis for improved wildfire hazard predictions and mitigation strategies. Key Points: Wetter‐than‐average soil moisture 4–5 months before wildfires results in increased aboveground biomass accumulationSoil moisture decrease and atmospheric drying after peak biomass lead to dry fuel availability at the time of wildfire ignitionThe temporal pattern is evident in mapped data on soil moisture, vegetation water content and wildfire incidents across western United States [ABSTRACT FROM AUTHOR]