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Arid and semi-arid regions of the world are particularly vulnerable to greenhouse gas–driven hydroclimate change. Climate models are our primary tool for projecting the future hydroclimate that society in these regions must adapt to, but here, we present a concerning discrepancy between observed and model-based historical hydroclimate trends. Over the arid/semi-arid regions of the world, the predominant signal in all model simulations is an increase in atmospheric water vapor, on average, over the last four decades, in association with the increased water vapor–holding capacity of a warmer atmosphere. In observations, this increase in atmospheric water vapor has not happened, suggesting that the availability of moisture to satisfy the increased atmospheric demand is lower in reality than in models in arid/semi-arid regions. This discrepancy is most clear in locations that are arid/semi-arid year round, but it is also apparent in more humid regions during the most arid months of the year. It indicates a major gap in our understanding and modeling capabilities which could have severe implications for hydroclimate projections, including fire hazard, moving forward. 

Abstract Terrestrial processes influence the atmosphere by controlling land‐to‐atmosphere fluxes of energy, water, and carbon. Prior research has demonstrated that parameter uncertainty drives uncertainty in land surface fluxes. However, the influence of land process uncertainty on the climate system remains underexplored. Here, we quantify how assumptions about land processes impact climate using a perturbed parameter ensemble for 18 land parameters in the Community Earth System Model version 2 under preindustrial conditions. We find that an observationally‐informed range of land parameters generate biogeophysical feedbacks that significantly influence the mean climate state, largely by modifying evapotranspiration. Global mean land surface temperature ranges by 2.2°C across our ensemble (σ = 0.5°C) and precipitation changes were significant and spatially variable. Our analysis demonstrates that the impacts of land parameter uncertainty on surface fluxes propagate to the entire Earth system, and provides insights into where and how land process uncertainty influences climate. 

Climate change projections consistently demonstrate that warming temperatures and dwindling seasonal snowpack will elicit cascading effects on ecosystem function and water resource availability. Despite this consensus, little is known about potential changes in the variability of ecohydrological conditions, which is also required to inform climate change adaptation and mitigation strategies. Considering potential changes in ecohydrological variability is critical to evaluating the emergence of trends, assessing the likelihood of extreme events such as floods and droughts, and identifying when tipping points may be reached that fundamentally alter ecohydrological function. Using a single-model Large Ensemble with sophisticated terrestrial ecosystem representation, we characterize projected changes in the mean state and variability of ecohydrological processes in historically snow-dominated regions of the Northern Hemisphere. Widespread snowpack reductions, earlier snowmelt timing, longer growing seasons, drier soils, and increased fire risk are projected for this century under a high-emissions scenario. In addition to these changes in the mean state, increased variability in winter snowmelt will increase growing-season water deficits and increase the stochasticity of runoff. Thus, with warming, declining snowpack loses its dependable buffering capacity so that runoff quantity and timing more closely reflect the episodic characteristics of precipitation. This results in a declining predictability of annual runoff from maximum snow water equivalent, which has critical implications for ecosystem stress and water resource management. Our results suggest that there is a strong likelihood of pervasive alterations to ecohydrological function that may be expected with climate change. 

Abstract The Arctic hydrological system is an interconnected system that is experiencing rapid change. It is comprised of permafrost, snow, glacier, frozen soils, and inland river systems. In this study, we aim to lower the barrier of using complex land models in regional applications by developing a generalizable optimization methodology and workflow for the Community Terrestrial Systems Model (CTSM), to move them toward a more Actionable Science paradigm. Further end‐user engagement is required to make science such as this “fully actionable.” We applied CTSM across Alaska and the Yukon River Basin at 4‐km spatial resolution. We highlighted several potentially useful high‐resolution CTSM configuration changes. Additionally, we performed a multi‐objective optimization using snow and river flow metrics within an adaptive surrogate‐based model optimization scheme. Four representative river basins across our study domain were selected for optimization based on observed streamflow and snow water equivalent observations at 10 SNOTEL sites. Fourteen sensitive parameters were identified for optimization with half of them not directly related to hydrology or snow processes. Across fifteen out‐of‐sample river basins, 13 had improved flow simulations after optimization and the mean Kling‐Gupta Efficiency of daily flow increased from 0.43 to 0.63 in a 30‐year evaluation. In addition, we adapted the Shapley Decomposition to disentangle each parameter's contribution to streamflow performance changes, with the seven non‐hydrological parameters providing a non‐negligible contribution to performance gains. The snow simulation had limited improvement, likely because snow simulation is influenced more by meteorological forcing than model parameter choices. 

Abstract CTEA (N,N‐bis[2‐(carboxylmethyl)thioethyl]amine) is a mixed donor ligand that has been incorporated into multiple fluorescent sensors such as NiSensor‐1 that was reported to be selective for Ni²⁺. Other metal ions such as Zn²⁺do not produce an emission response in aqueous solution. To investigate the coordination chemistry and selectivity of this receptor, we prepared NiCast, a photocage containing the CTEA receptor. Cast photocages undergo a photoreaction that decreases electron density on a metal‐bound aniline nitrogen atom, which shifts the binding equilibrium toward unbound metal ion. The unique selectivity of CTEA was examined by measuring the binding affinity of NiCast and the CTEA receptor for Ni²⁺, Zn²⁺, Cd²⁺and Cu²⁺under different conditions. In aqueous solution, Ni²⁺binds more strongly to the aniline nitrogen atom than Cd²⁺; however, in CH₃CN, the change in affinity virtually disappears. The crystal structure of [Cu(CTEA)], which exhibits a Jahn–Teller–distorted square pyramidal structure, was also analyzed to gain more insight into the underlying coordination chemistry. These studies suggest that the fluorescence selectivity of NiSensor‐1 in aqueous solution is due to a stronger interaction between the aniline nitrogen atom and Ni²⁺compared to other divalent metal ions except Cu²⁺. 

Abstract. The continental tropics play a leading role in the terrestrial energy,water, and carbon cycles. Land–atmosphere interactions are integral in theregulation of these fluxes across multiple spatial and temporal scales overtropical continents. We review here some of the important characteristics oftropical continental climates and how land–atmosphere interactions regulatethem. Along with a wide range of climates, the tropics manifest a diversearray of land–atmosphere interactions. Broadly speaking, in tropicalrainforest climates, light and energy are typically more limiting thanprecipitation and water supply for photosynthesis and evapotranspiration (ET),whereas in savanna and semi-arid climates, water is the critical regulatorof surface fluxes and land–atmosphere interactions. We discuss the impact ofthe land surface, how it affects shallow and deep clouds, and how theseclouds in turn can feed back to the surface by modulating surface radiationand precipitation. Some results from recent research suggest that shallowclouds may be especially critical to land–atmosphere interactions. On theother hand, the impact of land-surface conditions on deep convection appearsto occur over larger, nonlocal scales and may be a more relevantland–atmosphere feedback mechanism in transitional dry-to-wet regions andclimate regimes. 

Abstract Classifying the diverse ways that plants respond to hydrologic stress into generalizable ‘water‐use strategies’ has long been an eco‐physiological research goal. While many schemes for describing water‐use strategies have proven to be quite useful, they are also associated with uncertainties regarding their theoretical basis and their connection to plant carbon and water relations. In this review, we discuss the factors that shape plant water stress responses and assess the approaches used to classify a plant's water‐use strategy, paying particular attention to the popular but controversial concept of a continuum from isohydry to anisohydry.A generalizable and predictive framework for assessing plant water‐use strategies has been historically elusive, yet recent advances in plant physiology and hydraulics provide the field with a way past these obstacles. Specifically, we promote the idea that many metrics that quantify water‐use strategies are highly dynamic and emergent from the interaction between plant traits and environmental conditions, and that this complexity has historically hindered the development of a generalizable water‐use strategy framework.This idea is explored using a plant hydraulics model to identify: (a) distinct temporal phases in plant hydraulic regulation during drought that underpin dynamic water‐use responses, and (b) how variation in both traits and environmental forcings can significantly alter common metrics used to characterize plant water‐use strategies. This modelling exercise can bridge the divide between various conceptualizations of water‐use strategies and provide targeted hypotheses to advance the understanding and quantification of plant water status regulation across spatial and temporal scales.Finally, we describe research frontiers that are necessary to improve the predictive capacity of the plant water‐use strategy concept, including further investigation into the below‐ground determinants of plant water relations, targeted data collection efforts and the potential to scale these concepts from individuals to whole regions. A freePlain Language Summarycan be found within the Supporting Information of this article.