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Documenting the rate, magnitude and causes of snow loss is essential to benchmark the pace of climate change and to manage the differential water security risks of snowpack declines 1 – 4 . So far, however, observational uncertainties in snow mass 5 , 6 have made the detection and attribution of human-forced snow losses elusive, undermining societal preparedness. Here we show that human-caused warming has caused declines in Northern Hemisphere-scale March snowpack over the 1981–2020 period. Using an ensemble of snowpack reconstructions, we identify robust snow trends in 82 out of 169 major Northern Hemisphere river basins, 31 of which we can confidently attribute to human influence. Most crucially, we show a generalizable and highly nonlinear temperature sensitivity of snowpack, in which snow becomes marginally more sensitive to one degree Celsius of warming as climatological winter temperatures exceed minus eight degrees Celsius. Such nonlinearity explains the lack of widespread snow loss so far and augurs much sharper declines and water security risks in the most populous basins. Together, our results emphasize that human-forced snow losses and their water consequences are attributable—even absent their clear detection in individual snow products—and will accelerate and homogenize with near-term warming, posing risks to water resources in the absence of substantial climate mitigation. Snowpack reconstructions for major river basins in the Northern Hemisphere reveal that the snowpack has declined in almost half of the basins, with roughly one-third of the declines attributable to human-induced warming.

Plants are expected to generate more global-scale runoff under increasing atmospheric carbon dioxide concentrations through their influence on surface resistance to evapotranspiration. Recent studies using Earth System Models from phase 5 of the Coupled Model Intercomparison Project ostensibly reaffirm this result, further suggesting that plants will ameliorate the dire reductions in water availability projected by other studies that use aridity metrics. Here we complicate this narrative by analysing the change in precipitation partitioning to plants, runoff and storage in multiple Earth system models under both high carbon dioxide concentrations and warming. We show that projected plant responses directly reduce future runoff across vast swaths of North America, Europe and Asia because bulk canopy water demands increase with additional vegetation growth and longer and warmer growing seasons. These runoff declines occur despite increased surface resistance to evapotranspiration and vegetation total water use efficiency, even in regions with increasing or unchanging precipitation. We demonstrate that constraining the large uncertainty in the multimodel ensemble with regional-scale observations of evapotranspiration partitioning strengthens these results. We conclude that terrestrial vegetation plays a large and unresolved role in shaping future regional freshwater availability, one that will not ubiquitously ameliorate future warming-driven surface drying.

Efforts to understand the influence of historical global warming on individual extreme climate events have increased over the past decade. However, despite substantial progress, events that are unprecedented in the local observational record remain a persistent challenge. Leveraging observations and a large climate model ensemble, we quantify uncertainty in the influence of global warming on the severity and probability of the historically hottest month, hottest day, driest year, and wettest 5-d period for different areas of the globe. We find that historical warming has increased the severity and probability of the hottest month and hottest day of the year at >80% of the available observational area. Our framework also suggests that the historical climate forcing has increased the probability of the driest year and wettest 5-d period at 57% and 41% of the observed area, respectively, although we note important caveats. For the most protracted hot and dry events, the strongest and most widespread contributions of anthropogenic climate forcing occur in the tropics, including increases in probability of at least a factor of 4 for the hottest month and at least a factor of 2 for the driest year. We also demonstrate the ability of our framework to systematically evaluate the role of dynamic and thermodynamic factors such as atmospheric circulation patterns and atmospheric water vapor, and find extremely high statistical confidence that anthropogenic forcing increased the probability of record-low Arctic sea ice extent.

Drought is a complex and multivariate phenomenon influenced by diverse physical and biological processes. Such complexity precludes simplistic explanations of cause and effect, making investigations of climate change and drought a challenging task. Here, we review important recent advances in our understanding of drought dynamics, drawing from studies of paleoclimate, the historical record, and model simulations of the past and future. Paleoclimate studies of drought variability over the last two millennia have progressed considerably through the development of new reconstructions and analyses combining reconstructions with process-based models. This work has generated new evidence for tropical Pacific forcing of megadroughts in Southwest North America, provided additional constraints for interpreting climate change projections in poorly characterized regions like East Africa, and demonstrated the exceptional magnitude of many modern era droughts. Development of high resolution proxy networks has lagged in many regions (e.g., South America, Africa), however, and quantitative comparisons between the paleoclimate record, models, and observations remain challenging. Fingerprints of anthropogenic climate change consistent with long-term warming projections have been identified for droughts in California, the Pacific Northwest, Western North America, and the Mediterranean. In other regions (e.g., Southwest North America, Australia, Africa), however, the degree to which climate change has affected recent droughts is more uncertain. While climate change-forced declines in precipitation have been detected for the Mediterranean, in most regions, the climate change signal has manifested through warmer temperatures that have increased evaporative losses and reduced snowfall and snowpack levels, amplifying deficits in soil moisture and runoff despite uncertain precipitation changes. Over the next century, projections indicate that warming will increase drought risk and severity across much of the subtropics and mid-latitudes in both hemispheres, a consequence of regional precipitation declines and widespread warming. For many regions, however, the magnitude, robustness, and even direction of climate change-forced trends in drought depends on how drought is defined, with often large differences across indicators of precipitation, soil moisture, runoff, and vegetation health. Increasing confidence in climate change projections of drought and the associated impacts will likely depend on resolving uncertainties in processes that are currently poorly constrained (e.g., land-atmosphere interactions, terrestrial vegetation) and improved consideration of the role for human policies and management in ameliorating and adapting to changes in drought risk.

Recent studies have found that terrestrial dryness indices like the Palmer Drought Severity Index (PDSI), Standardized Precipitation Evapotranspiration Index (SPEI), and Aridity Index calculated from future climate model projections are mostly negative, implying a drying land surface with warming. Yet, the same models' future runoff and bulk soil moisture projections instead show regional signals of varying sign, and their vegetation projections show widespread greening, suggesting that the dryness indices could overstate climate change's direct impacts. Most modeling studies have attributed this gap to the indices' omission of CO2-driven stomatal closure. However, here we show that the index-impact gap is still wide even in future-like model experiments that switch off CO2 effects on plants. In these simulations, mean PDSI, Aridity Index, and SPEI still decline broadly with strong warming, while mean runoff, bulk soil moisture, and vegetation still respond more equivocally. This implies that CO2-plant effects are not the dominant or sole reason for the simulated index-impact gap. We discuss several alternative mechanisms that may explain it.

Plants influence extreme heat events by regulating land-atmosphere water and energy exchanges. The contribution of plants to changes in future heat extremes will depend on the responses of vegetation growth and physiology to the direct and indirect effects of elevated CO2. Here we use a suite of earth system models to disentangle the radiative versus vegetation effects of elevated CO2 on heat wave characteristics. Vegetation responses to a quadrupling of CO2 increase summer heat wave occurrence by 20 days or more-30-50% of the radiative response alone-across tropical and mid-to-high latitude forests. These increases are caused by CO2 physiological forcing, which diminishes transpiration and its associated cooling effect, and reduces clouds and precipitation. In contrast to recent suggestions, our results indicate CO2-driven vegetation changes enhance future heat wave frequency and intensity in most vegetated regions despite transpiration-driven soil moisture savings and increases in aboveground biomass from CO2 fertilization.

Documenting and predicting the loss of seasonal snow is vital but complex owing to regional heterogeneity in the response of snow to warming. Such heterogeneity arises because the marginal loss of snow per degree of warming depends strongly on mean winter temperatures: Regions warmer than −8°C experience steep, accelerating snow declines, while colder regions show little change. This robust, generalizable pattern emerges across snow measures, spatial scales, regions, and data sets, but lacks a clear physical explanation. Here, using in situ and gridded observations of Northern Hemisphere snow and temperature, we reveal a simple yet potent driver: how the mean and variability of the daily wintertime temperature distribution influences the number of winter days below freezing. As average wintertime temperatures warm toward freezing, days below 0°C—critical to snow accumulation and persistence—decrease nonlinearly. The loss of each cold day is in turn associated with a linear reduction in snowfall, snowpack persistence, and snow cover duration, explaining the rapid snow declines for regions with mean winter temperatures approaching—but still below—freezing. We further show that this relationship entails a sharp escalation in the likelihood of extremely low‐snow winters, or snow droughts, during warm winters, even in regions with average temperatures several degrees below 0°C. Our findings resolve a key puzzle in the nonlinear temperature sensitivity of snow, offering a framework for seasonal‐scale snow resource monitoring and forecasting and for interpreting future projections of seasonal snow with warming.

Runoff from snowmelt is regarded as a vital water source for people and ecosystems throughout the Northern Hemisphere (NH). Numerous studies point to the threat global warming poses to the timing and magnitude of snow accumulation and melt. But analyses focused on snow supply do not show where changes to snowmelt runoff are likely to present the most pressing adaptation challenges, given sub-annual patterns of human water consumption and water availability from rainfall. We identify the NH basins where present spring and summer snowmelt has the greatest potential to supply the human water demand that would otherwise be unmet by instantaneous rainfall runoff. Using a multi-model ensemble of climate change projections, we find that these basins-which together have a present population of ∼2 billion people-are exposed to a 67% risk of decreased snow supply this coming century. Further, in the multi-model mean, 68 basins (with a present population of >300 million people) transition from having sufficient rainfall runoff to meet all present human water demand to having insufficient rainfall runoff. However, internal climate variability creates irreducible uncertainty in the projected future trends in snow resource potential, with about 90% of snow-sensitive basins showing potential for either increases or decreases over the near-term decades. Our results emphasize the importance of snow for fulfilling human water demand in many NH basins, and highlight the need to account for the full range of internal climate variability in developing robust climate risk management decisions.

Increasingly, climate change impact assessments rely directly on climate models. Assessments of future water security depend in part on how the land model components in climate models partition precipitation into evapotranspiration and runoff, and on the sensitivity of this partitioning to climate. Runoff sensitivities are not well constrained, with CMIP5 models displaying a large spread for the present day, which projects onto change under warming, creating uncertainty. Here we show that constraining CMIP5 model runoff sensitivities with observed estimates could reduce uncertainty in runoff projection over the western United States by up to 50%. We urge caution in the direct use of climate model runoff for applications and encourage model development to use regional-scale hydrological sensitivity metrics to improve projections for water security assessments.

Climate models project significant twenty-first-century declines in water availability over the American West from anthropogenic warming. However, the physical mechanisms underpinning this response are poorly characterized, as are the uncertainties from vegetation’s modulation of evaporative losses. To understand the drivers and uncertainties of future hydroclimate in the American West, a 35-member single model ensemble is used to examine the response of summer soil moisture and runoff to anthropogenic forcing. Widespread dry season soil moisture declines occur across the region despite increases in total water-year precipitation and ubiquitous increases in plant water-use efficiency. These modeled soil moisture declines are initially forced by significant snowpack losses that directly diminish summer soil water, even in regions where water-year precipitation increases. When snowpack priming is coupled with a warming- and CO₂-induced shift in phenology and increased primary production, widespread increases in leaf area further reduces summer soil moisture and runoff by outpacing decreased stomatal conductance from high CO₂. The net effects lead to the cooccurrence of both a “greener” and “drier” future across the western United States. Because simulated vegetation exerts a large influence on predicted changes in water availability in the American West, these findings highlight the importance of reducing the substantial uncertainties in the ecological processes increasingly incorporated into numerical Earth system models.