This study evaluates the ability of the Model for Prediction Across Scales - Atmosphere (MPAS version 8.1.0) to reproduce an unprecedented extreme precipitation event that occurred along the coast of the state of São Paulo (SP), in southeastern Brazil, on February 18-19, 2023. A set of sensitivity experiments was conducted using global variable-resolution (VR) meshes (60–3, 60–10 and 46–12 km) and a regional 3-km mesh. The 60-3 km experiments examine the influence of lead time, microphysical parameterizations, physics suites, and modeling framework (regional vs. global VR). Model simulations were evaluated against precipitation data from the CEMADEN rain gauge network and radar estimates from FCTH. Results show that simulation skill is highly sensitive to model configuration. While the 60–3 km global VR mesh with the CP physics suite simulates precipitation associated with orographic lifting along the Serra do Mar Mountain, the best overall performance is obtained with coarser 60-10 km global VR mesh using MR physics suite. This configuration provides improved representation of atmospheric moisture transport and PBL processes. The regional 3 km experiment simulates precipitation intensity close to the observed maximum (675 mm/day vs 683 mm/day), although the rainfall core is displaced. These findings highlight the challenges of predicting highly localized extreme rainfall over coastal complex terrain and provide guidance for the application of MPAS in forecasting high-impact precipitation events in southeastern Brazil. • This is the first study to use the MPAS model to simulate an unprecedented extreme precipitation event over the São Paulo coast in southeastern Brazil. • Experiments with low resolution (10 km) global variable-resolution meshes over the study area outperformed those with high resolution (3 km). • Physical parameterizations associated with the representation of atmospheric moist and PBL processes play a critical role in the reproduction of precipitation. • Regional MPAS with 3 km resolution and no convective parameterization reproduced the precipitation intensity observed during the event.

Iran's long history of climate-related crises, primarily driven by droughts, has been intensified by ongoing climate change, placing forest ecosystems under increasing hydroclimatic stress. In recent decades, prolonged droughts combined with elevated atmospheric moisture deficits have reduced ecosystem resilience and increased vulnerability to degradation. To better understand long-term drought dynamics and their ecological impacts, we developed two 200-year chronologies (1821-2020) of tree-ring width (TRW) and stable oxygen isotope variations (δ1⁸O) from Juniperus polycarpos in the Hezar Masjed Mountains, northeastern Iran. The δ1⁸O record served as a proxy for atmospheric moisture conditions and was used to reconstruct growing-season (March-September) vapor pressure deficit (VPD). When combined with TRW in a multiple regression framework, this dual-parameter approach enabled reconstruction of the Standardized Precipitation-Evapotranspiration Index (SPEI07), representing cumulative growing-season hydroclimatic conditions related to soil moisture availability. This allows the differentiation of atmospheric and soil drought impacts on tree growth over two centuries. By classifying drought years into VPD-only, SPEI-only, and combined drought events, we found that drought conditions associated with reduced soil moisture availability (SPEI) exerted the strongest constraint on radial growth. Tree growth declined most strongly during severe SPEI droughts, followed by severe combined drought (COMB-D) years, whereas atmospheric drought alone (VPD-D) had a weaker and more transient effect. Growth typically recovered within two years following drought events. Analysis of long-term drought classifications (1821-2020) revealed a shift towards more intense droughts in recent decades, particularly in the frequency of severe VPD and combined drought years. Our findings highlight that tree growth in semi-arid mountain ecosystems is primarily limited by soil moisture availability, with atmospheric drought acting as an additional stressor when coinciding with soil moisture deficits. This study demonstrates the value of combining multiple tree-ring proxies to disentangle drought mechanisms and improve understanding of forest responses to climate change.

City-scale cooling and thermal comfort: A dual-index comparison of heat mitigation strategy effectiveness across geographically-diverse cities.

Abstract Classical theories for axisymmetric, nearly inviscid Hadley circulations typically neglect processes such as vertical momentum advection to obtain analytical solutions. Using simple 1.5- and 2-layer axisymmetric inviscid models, we clarify the relative significance of these processes, with particular focus on seasonally varying dry Hadley cells. We show that vertical momentum advection strongly modifies the strength, extent, and seasonal response of the circulation. Including nonzero surface zonal winds in a two-layer model only produces a negligible weakening of the solstitial circulation. Building on these results, we introduce a semianalytical theory for the meridional structure of dry, nearly inviscid Hadley cells that explicitly incorporates vertical momentum advection. This theory accurately explains the strength and extent of seasonally varying Hadley circulations simulated in axisymmetric GCMs. Importantly, the theory shows that axisymmetric Hadley circulations do not undergo the rapid nonlinear strengthening with seasonality predicted by earlier models. Meridional variations in gross stability observed in the simulations can, in principle, lead to deviations from the theory. We explain the cause of these variations and show that their impact is limited: While the mass transport streamfunction is very sensitive to these variations, the heat transport profile, along with the meridional profiles of zonal wind and temperature, remains relatively invariant due to angular momentum constraints. Finally, we assess the influence of vertical momentum diffusion on the axisymmetric GCM simulations and discuss implications for eddying and moist atmospheres, as well as for regime transitions of the Hadley circulation and connections to monsoons.

Abstract The Great Plains low-level jet (GPLLJ) is a major mechanism of atmospheric moisture transport, contributing to warm-season precipitation in the central United States. We have found enhanced GPLLJ activity associated with subseasonal dry soil moisture anomalies over the southern Great Plains. We hypothesize that subseasonal dry soil moisture anomalies modulate GPLLJ intensity through warmer near-surface temperatures, deepening of the planetary boundary layer, and stronger geostrophic and ageostrophic winds, leading to nocturnal supergeostrophic winds through enhanced buoyancy and the Blackadar inertial oscillation. To test our hypothesis and separate the time scales embedded in GPLLJ variability, we use daily fifth generation ECMWF atmospheric reanalysis (ERA5) variables (e.g., soil moisture, geopotential height, virtual potential temperature) as time series inputs to multivariate singular spectrum analysis (MSSA). MSSA decomposes the set of variables into different time scales of covariability. The temporal empirical orthogonal functions (T-EOFs) are then used to reconstruct the original wind speed time series with variability from representative time scales (i.e., synoptic, planetary, subseasonal). Our findings show that reconstructing the GPLLJ without the subseasonal variability, which is strongly correlated with soil moisture, leads to underestimated wind speeds during dry periods and overestimated wind speeds during wet periods. These findings quantitatively demonstrate how the land surface plays an important role in modulating GPLLJ intensity which can have major implications for improving subseasonal predictability of GPLLJ activity and subsequent extreme precipitation. Significance Statement The central United States is one of the world’s most productive regions in terms of agriculture and renewable aeolian energy. In this region, the Great Plains low-level jet (GPLLJ) is the main mechanism of atmospheric transport of momentum, energy, moisture, and scalars. Our work uses temporal decomposition to highlight the subseasonal signal embedded within the GPLLJ variability associated with soil moisture.

Tin-based metal-oxide resist (Sn-MOR) is a promising candidate material for next-generation photolithography, yet its shelf and in-process stability are significantly undermined by reactions with ambient moisture. While an in-depth computational study is required to understand the reaction mechanism and provide design rules balancing moisture stability and photospeed, the long time scale of degradation reactions hampers ab initio calculations. In this work, we introduce a two-phase active learning (2P-AL) framework, which couples deep potential molecular dynamics with well-tempered metadynamics (WT-MetaD) to capture the rare-event reaction dynamics of solvated Sn-MOR molecules in aqueous solution. The first phase focuses on exploration to broaden structural diversity under a fixed simulation budget, and the subsequent phase focuses on convergence to systematically improve force field fidelity and ultimately achieve ab initio-level accuracy. WT-MetaD simulations with this model successfully constructed the free energy landscape of moisture-induced degradation of Sn-MOR molecules and uncovered a plausible pathway by which ambient moisture can promote degradation in Sn-MORs, offering molecular-level insight into their stability challenges. In parallel, the proposed 2P-AL framework offers an adaptable and efficient approach to investigate reaction dynamics in solution-phase reactive systems, yielding direct molecular insight into moisture-induced degradation in disordered Sn-MOR materials.

Abstract Moisture transport is a key driver of mass and energy transfer in the climate system, and its role is increasingly amplified under global warming as enhanced atmospheric moisture alters source–sink dynamics. Yet, the mechanisms by which the atmospheric hydrological cycle controls summer precipitation in the densely populated and disaster-prone monsoon region of China (MRC) remain poorly understood. Here, we apply the Lagrangian model FLEXPART to quantify changes in the atmospheric water cycle associated with MRC summer precipitation from 1979 to 2020. Evaporation from MRC contributes ~35% of summer rainfall on average due to dense air parcel convergence, strong uptake, and relatively low transport loss. Long-term trends indicate a strengthening of the summer water cycle, with total precipitation increasing at a rate of 2.5% per decade, and the moisture originating from MRC accounting for ~71% of this increase. This intensification is closely caused by increased atmospheric moisture uptake of air parcels during transport, which is associated with both higher air parcel density and intensified surface evaporation. The higher parcel density over the northern MRC and Northeast Asia is tied to an anomalous anticyclonic circulation over Northeast Asia that favors southward transport, partially compensating for the weakened oceanic moisture influx from the south. Intensified surface evaporation over the MRC is linked to vegetation-controlled evapotranspiration. These findings highlight the importance of integrating moisture transport dynamics and land–surface interactions to understand regional hydrological variability under a warming climate.

The high reactivity of isocyanate groups not only makes them excellent precursors for polyurethanes and polyureas, but it also leads to their degradation through reactions with atmospheric moisture. Conventionally, blocking reagents containing alcohol or amine groups have been used to protect isocyanate groups. However, such covalent protection approaches often require harsh deprotection conditions. Herein, we report a non-covalent supramolecular strategy that provides both high protection efficiency and facile deprotection of isocyanate compounds. In this approach, the isocyanate groups are encapsulated within crystalline pillar[n]arene macrocycles. Owing to the highly hydrophobic nature of the pillar[n]arene crystals, the isocyanate guests are effectively protected from water in the crystalline state: the isocyanate groups are active even after the crystalline complexes are exposed to water vapour or directly immersed in water. Furthermore, although the host-guest complex is stabilized in the crystalline state, simple dissolution in an appropriate reaction solvent simultaneously triggers deprotection, enabling subsequent polyurethane synthesis.

ABSTRACT Precipitation influenced by altered cloud characteristics is primarily due to anthropogenic climate change. This study investigates Northern (NR) and Southern (SR) regions of India, to delineate Monsoonal heterogeneity through cloud properties using satellite data (2002-2024), statistical and machine learning models. Cloud parameters show rising trend. Rate of rise differs substantially for cloud liquid water path (CLW) during 2013–2022, with a relatively low rate in NR (0.62 ± 0.20 g/m2/decade) and significantly larger (1.58 ± 0.29 ) in SR indicating complex interactions between topography and atmospheric dynamics modulating cloud characteristics. Changes in cloud effective radius (CER) and cloud optical thickness (COT) across the latitudes could be due to spatial gradients in anthropogenic aerosol loading and associated meteorological influences in NR. Cloud clustering in NR has shown distinct structures (silhouette score ≈0.39), with one of clusters exhibiting high CER, COT and CLW, implying presence of active convective regimes and persistent congestus clouds. SR showed less distinct clustering, marking consistent transition towards higher values from 2002–2012 to 2013–2024. This distinction may be due to enhanced convective intensity driven by changes in atmospheric moisture and large-scale dynamics. This study advances comprehension of regional variation of monsoon dynamics impacted by climate change.

The subtropical wetlands of the Doon Valley function as significant net sources of greenhouse gases (GHGs), with methane (CH₄) dominating the radiative forcing (∼62% of CO₂-equivalent emissions) despite lower molar fluxes than carbon dioxide (CO₂). High-resolution field measurements reveal that CH₄ emissions are primarily controlled by anaerobic conditions, sustained soil moisture, elevated temperatures, and low dissolved oxygen, whereas CO₂ fluxes exhibit greater temporal variability and respond strongly to thermal regimes and ionic strength. A key biogeoclimatic insight is the seasonal decoupling of soil moisture and atmospheric water vapor (H2O), where summer drying coincides with peak humidity driven by energy-limited evapotranspiration. Pronounced spatial heterogeneity in gas fluxes further suggests that land-use context and modified hydrological pathways may interact with climatic drivers to influence wetland carbon dynamics. The wetland complex (221.39ha) emits approximately 0.0195 Mt CO₂-eq annually, underscoring its disproportionate role in regional GHG budgets. These findings reveal strong coupling among hydrological saturation, thermal regimes, redox conditions, and atmospheric moisture in regulating GHG emissions. The study underscores the high climate sensitivity of monsoon-dependent wetlands and highlights the need for targeted hydrological restoration and continuous monitoring to mitigate future amplification of emissions under warming scenarios.

Climatic characteristics, particularly temperature and ambient humidity, significantly affect the qualitative and quantitative indicators of flax production and fibre formation. Conventional technologies for obtaining flax fibre are based on natural dew retting, the efficiency of which depends on atmospheric moisture. The decrease in air humidity during summer periods due to climate change complicates the biological processes involved in the transformation of flax stems into retted straw. A separate harvesting technology involving low cutting of stems and their placement into windrows has been proposed to utilize productive soil moisture during retting and to accelerate seed harvesting. During field laying, windrows change their geometric parameters, become denser, and increase adhesion both between stems and with the soil surface, which requires periodic lifting and loosening. This paper presents the results of field experimental studies conducted using a developed experimental picker to determine rational structural and technological parameters based on a four-factor experimental design. Changes in windrow geometry and their interaction with the working elements of the picker were analysed. Optimal parameters of the picker for flax retting preparation were established. The study is aimed at developing a new technical solution for flax harvesting.

We report a scalable, moisture-powered in-planta sensor platform for the continuous monitoring of plant hydration and growth. The system integrates two components: a leaf-mounted tattoo sensor for estimating vapor pressure deficit (VPD) and a kirigami-inspired strain sensor for tracking radial stem growth. Uniquely, the tattoo sensor serves a dual function: measuring temperature and humidity beneath the leaf surface while simultaneously harvesting power from ambient moisture via a vanadium pentoxide (V2O5) nanosheet membrane. This moist-electric-generator (MEG) configuration enables energy-autonomous operation, delivering a power density of 0.1114 μW/cm2. The V2O5-based sensor exhibits high sensitivity to humidity (4.2 mV/% RH) and temperature (1.02%/°C), enabling accurate VPD estimation for over 10 days until leaf senescence. The eutectogel-based kirigami strain sensor, wrapped around the stem, offers a gauge factor of 1.5 and immunity to unrelated mechanical disturbances, allowing for continuous growth tracking for more than 20 days. Both sensors are fabricated via cleanroom-free, roll-to-roll compatible methods, underscoring their potential for large-scale agricultural deployment to monitor abiotic stress and improve crop management.

Rattans of the genus Korthalsia are ecologically and economically important non-timber forest resources in Southeast Asia, yet their conservation is limited by knowledge of species-specific distribution patterns and environmental constraints. We modeled the potential distributions of four Korthalsia species (K. flagellaris, K. laciniosa, K. rigida, and K. scortechinii) using species distribution models (SDMs). Models were fitted in R using the sdm package, and ensemble maps were generated by combining predictions from Random Forest (RF), Generalized Linear Models (GLMs), Generalized Additive Models (GAM), and GLMnet. The top predictors influencing habitat distribution included soil physical structure, atmospheric moisture demand, and canopy light availability. The dominance of these factors reflects three distinct and non-interchangeable environmental axes that regulate belowground moisture dynamics, atmospheric constraints on gas exchange, and the energetic requirements for recruitment. All four species ensemble models significantly outperformed the null model, and spatial block cross-validation (k = 5, 200 km blocks) indicated a marginal drop in area under the curve (AUC) values, confirming a predictive signal under geographically independent evaluation. Ensemble suitability maps identified Peninsular Malaysia, Borneo, and Sumatra as centers of predicted habitat. Core habitat was estimated to be less than 0.6% of total suitable area for all species, ranging from 980 km2 (K. scortechinii) to 19,256 km2 (K. rigida), with anthropogenic modification exceeding 50% in the core habitat in K. flagellaris and K. rigida. These results provide the first species-specific baseline for these Korthalsia across Southeast Asia, supporting more targeted conservation and restoration planning under varying habitat constraints.

Near-surface atmospheric moisture is a key component of the climate and environment systems, exerting significant influences on both nature and human beings. However, existing moisture data are often limited by sparse observations and low spatial/temporal resolution, which restricts their applicability at fine scales, particularly in populated and urbanized regions with strong moisture variability, such as the North China Plain (NCP). Here, we construct a high-resolution (daily and 1 km) near-surface atmospheric moisture index collection comprising six different indicators over the NCP during 2003-2020 (HiMIC-NCP). HiMIC-NCP is generated by the Light Gradient Boosting Machine(LightGBM) algorithm by integrating meteorological observations and multiple covariates, including 2-meter air temperature, land surface temperature, water vapor, topography, and population density. The dataset exhibits a high accuracy with R² values ranging from 0.879 to 0.988, and mean absolute error and root mean square error remaining within reasonable ranges. The dataset also exhibits high consistency with ground observations across spatial and temporal regimes, demonstrating its robustness and reliability, and thereby provides a high-quality foundation for fine-scale climate change assessment, agricultural management, and public health studies.

Abstract As a vital atmospheric component, water vapor influences climate change and drives numerous weather‐related processes. The Global Positioning System (GPS) provides a valuable tool for investigating Precipitable Water Vapor (PWV). This study reanalyzed the raw GPS data from 2000 to 2020 at 25 stations over China to generate a consistent and reliable GPS PWV data set. To obtain homogenized GPS PWV time series, potential artificial shifts in the mean caused by changes in instruments and environmental conditions were identified and corrected based on GPS station log files and comparisons with numerical weather prediction reanalysis PWV from the ECMWF Reanalysis v5 (ERA5) and satellite PWV observations from the Moderate Resolution Imaging Spectrometer (MODIS). A comprehensive assessment of the spatiotemporal variability of PWV is performed using this homogenized GPS data set, while using the ERA5 and the MODIS PWV products for comparison. We first found that both ERA5 and MODIS are slightly wetter than GPS PWV, and ERA5 agrees better with GPS PWV than MODIS does. The annual PWV trends are generally significantly positive across China, and exhibit a west‐to‐east gradient in increasing PWV. The homogenized GPS PWV shows a wetting in eastern and central China during summer and a drying or no trend in winter over central and northern China. The relationships among PWV, specific humidity, and precipitation with temperature more closely follow the scale of the Clausius‐Clapeyron expectation in monsoon‐dominated regions than in the plateau region. This study provides new insights into China's atmospheric moisture dynamics in a changing climate.

Harvesting renewable energy from ambient moisture into sustainable electricity represents a promising route to address global energy and climate challenges. However, the moisture energy utilization is low in existing moisture-electric generators (MEGs) technologies. Here, we report a carrier-type-engineered graphene oxide (GO)-based MEG that not only generates electricity from moisture but also drives clean hydrogen production via electrochemical water splitting. The optimized device delivers a steady voltage output of 0.90V and an ultra-high current density of 0.25 mA∙cm-2 at 80% relative humidity, maintaining excellent stability for two weeks. Importantly, we first reveal that the proton-electron recombination during MEG discharge produces abundant neutral hydrogen atoms absorbed on the carbon nanotube substrate, which subsequently act as highly active species for the hydrogen evolution reaction (HER), achieving a remarkably low overpotential of ∼20mV. The present work marks the first demonstration of hydrogen generation directly coupled with MEG discharge via cascade utilization of intermediate neutral hydrogen molecules. Furthermore, the device can be rejuvenated through a recycling treatment, enabling cyclic operation. This study not only advances the fundamental understanding of charge transfer and proton dynamics in MEGs but also introduces a new paradigm for coupling ambient-energy harvesting with sustainable hydrogen production.

Moisture-electric generators (MEGs) offer a promising route for clean energy harvesting. However, most existing MEGs suffer from low current densities due to limited ion concentration and migration rates, while often lack of capability for direct integration of wearable systems. Here, a moisture-electric yarn (MEY) featuring high current density and continuous power generation is designed. An ion pump strategy is introduced to facilitate the establishment of ion concentration gradients and enhance ion migration rates, enhancing electrical output. The MEY continuously generates ∼1V and a high current density of 5.7mAcm-3 at 25 °C and 60% RH, outperforming most reported MEGs. A scalable continuous fabrication process enables single-batch production of hundreds of meters of yarn. Owing to its yarn structure, the output current increases with length, reaching 4.3mA for a 1m yarn (∼0.1g). Harvesting atmospheric and body moisture, a 2m MEY can sustainably power LED strips. This lightweight and sewable yarn provides a safe and eco-friendly auxiliary power source for wearable electronics and real-time positioning applications.

Here, we report the first examples of enantioselective geminal olefin disulfonoxylation reactions. Our reaction protocol is operationally simple and involves stirring the olefin substrate with an enantiopure hypervalent iodine reagent in the presence of 2 equiv of a sulfonic acid in dichloromethane. No special precautions to exclude air or ambient moisture are necessary. We have conducted a thorough investigation of the substrate scope with respect to both the olefin substrate and the sulfonic acid partner. The reaction scales well, and the scalemic products serve as versatile chirons.

ABSTRACT Lignocellulosic fibres can be used to produce cost-effective and environmentally friendly composites. Water-absorption properties of natural fibres and their low wettability with polymers limit their use in composite manufacturing for structural, automotive, and other industrial applications. Natural fibres, such as coir, exhibit high strain-to-fracture and toughness due to their porous architecture. However, this increases moisture absorption and retention, which impacts their mechanical properties. This study reports the influence of water absorption on tensile behaviour of coconut fibre and its interface adhesion with polylactic acid (PLA). The moisture absorption characteristics of untreated and alkaline-treated coconut fibre were analysed using water soaking as an accelerated condition for atmospheric moisture absorption at different durations. Alkaline-treated fibre exhibited a 28% higher tensile strength and a 33% improved elastic modulus compared to untreated fibres. The interfacial adhesion of alkaline-treated and water-soaked fibres with PLA was assessed using a fibre pull-out test. The alkaline-treated fibres showed 48% higher interface strength compared to untreated fibres, whereas after water absorption, the interface weakened and the bond strength reduced by 33% and 14% for untreated and alkaline-treated fibres, respectively. This study provides critical insights into the moisture-dependent mechanical performance and interfacial behaviour of coir fibre/PLA composites under humid service conditions.

As the global climate has warmed anthropogenically over the past decades, the atmosphere across most of the globe has experienced significant moistening, except for a "moistening hole" (MH) -like change over the Western U.S. This regional anomaly since 1980 is at odds with the forced response of climate models to global warming in this region. Here, through analysis of a wide array of observations and water-tagging enabled simulations, we find that atmospheric forcing originating from the North Pacific contributes to the MH. A barotropic high-pressure circulation trend over the North Pacific, driven by observed sea surface temperature cooling in the tropical Eastern Pacific, enhances atmospheric sinking over the Western U.S. through equatorward cold air advection. This intensified atmospheric descent suppresses precipitation and weakens land-sourced evaporation, which are critical for replenishing atmospheric moisture in the region. We suggest that focusing on low-frequency changes of atmospheric vertical motion may offer insights into assessing and projecting climate stress and drought risks posed by long-term atmospheric moisture deficits in arid regions.