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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.

The simulation of snow water equivalent (SWE) remains difficult for regional climate models. Accurate SWE simulation depends on complex interacting climate processes such as the intensity and distribution of precipitation, rain-snow partitioning, and radiative fluxes. To identify the driving forces behind SWE difference between model and reanalysis datasets, and guide model improvement, we design a framework to quantitatively decompose the SWE difference contributed from precipitation distribution and magnitude, ablation, temperature and topography biases in regional climate models. We apply this framework within the California Sierra Nevada to four regional climate models from the North American Coordinated Regional Downscaling Experiment (NA-CORDEX) run at three spatial resolutions. Models generally predict less SWE compared to Landsat-Era Sierra Nevada Snow Reanalysis (SNSR) dataset. Unresolved topography associated with model resolution contribute to dry and warm biases in models. Refining resolution from 0.44° to 0.11° improves SWE simulation by 35%. To varying degrees across models, additional difference arises from spatial and elevational distribution of precipitation, cold biases revealed by topographic correction, uncertainties in the rain-snow partitioning threshold, and high ablation biases. This work reveals both positive and negative contributions to snow bias in climate models and provides guidance for future model development to enhance SWE simulation.

Thermokarst is the process whereby the thawing of ice-rich permafrost ground causes land subsidence, resulting in development of distinctive landforms. Accelerated thermokarst due to climate change will damage infrastructure, but also impact hydrology, ecology and biogeochemistry. Here, we present a circumpolar assessment of the distribution of thermokarst landscapes, defined as landscapes comprised of current thermokarst landforms and areas susceptible to future thermokarst development. At 3.6 × 10 6 km 2 , thermokarst landscapes are estimated to cover ∼20% of the northern permafrost region, with approximately equal contributions from three landscape types where characteristic wetland, lake and hillslope thermokarst landforms occur. We estimate that approximately half of the below-ground organic carbon within the study region is stored in thermokarst landscapes. Our results highlight the importance of explicitly considering thermokarst when assessing impacts of climate change, including future landscape greenhouse gas emissions, and provide a means for assessing such impacts at the circumpolar scale. In thermokarst landscapes, permafrost thaw causes land subsidence with impacts on hydrology, ecology and biogeochemistry. Here, Olefeldt et al . produce circumpolar maps of thermokarst distribution, identifying that they cover 20% of the northern permafrost region, but store half the below-ground organic carbon.

The land ice contribution to global mean sea level rise has not yet been predicted1 using ice sheet and glacier models for the latest set of socio-economic scenarios, nor using coordinated exploration of uncertainties arising from the various computer models involved. Two recent international projects generated a large suite of projections using multiple models2,3,4,5,6,7,8, but primarily used previous-generation scenarios9 and climate models10, and could not fully explore known uncertainties. Here we estimate probability distributions for these projections under the new scenarios11,12 using statistical emulation of the ice sheet and glacier models. We find that limiting global warming to 1.5 degrees Celsius would halve the land ice contribution to twenty-first-century sea level rise, relative to current emissions pledges. The median decreases from 25 to 13 centimetres sea level equivalent (SLE) by 2100, with glaciers responsible for half the sea level contribution. The projected Antarctic contribution does not show a clear response to the emissions scenario, owing to uncertainties in the competing processes of increasing ice loss and snowfall accumulation in a warming climate. However, under risk-averse (pessimistic) assumptions, Antarctic ice loss could be five times higher, increasing the median land ice contribution to 42 centimetres SLE under current policies and pledges, with the 95th percentile projection exceeding half a metre even under 1.5 degrees Celsius warming. This would severely limit the possibility of mitigating future coastal flooding. Given this large range (between 13 centimetres SLE using the main projections under 1.5 degrees Celsius warming and 42 centimetres SLE using risk-averse projections under current pledges), adaptation planning for twenty-first-century sea level rise must account for a factor-of-three uncertainty in the land ice contribution until climate policies and the Antarctic response are further constrained.

Lake ecosystems are jeopardized by the impacts of climate change on ice seasonality and water temperatures. Yet historical simulations have not been used to formally attribute changes in lake ice and temperature to anthropogenic drivers. In addition, future projections of these properties are limited to individual lakes or global simulations from single lake models. Here we uncover the human imprint on lakes worldwide using hindcasts and projections from five lake models. Reanalysed trends in lake temperature and ice cover in recent decades are extremely unlikely to be explained by pre-industrial climate variability alone. Ice-cover trends in reanalysis are consistent with lake model simulations under historical conditions, providing attribution of lake changes to anthropogenic climate change. Moreover, lake temperature, ice thickness and duration scale robustly with global mean air temperature across future climate scenarios (+0.9 °C °C air –1 , –0.033 m °C air –1 and –9.7 d °C air –1 , respectively). These impacts would profoundly alter the functioning of lake ecosystems and the services they provide. Anthropogenic climate change is impacting the temperature and ice cover of lakes across the globe, according to an attribution analysis based on hindcasts and projections from lake models.

Over the past two decades the primary driver of mass loss from the West Antarctic Ice Sheet (WAIS) has been warm ocean water underneath coastal ice shelves, not a warmer atmosphere. Yet, surface melt occurs sporadically over low-lying areas of the WAIS and is not fully understood. Here we report on an episode of extensive and prolonged surface melting observed in the Ross Sea sector of the WAIS in January 2016. A comprehensive cloud and radiation experiment at the WAIS ice divide, downwind of the melt region, provided detailed insight into the physical processes at play during the event. The unusual extent and duration of the melting are linked to strong and sustained advection of warm marine air toward the area, likely favoured by the concurrent strong El Niño event. The increase in the number of extreme El Niño events projected for the twenty-first century could expose the WAIS to more frequent major melt events. Sporadic surface melt over the West Antarctic Ice Sheet is not fully understood. Here, the authors report on an extensive melting episode in the Ross Ice Shelf area in 2016 and use comprehensive in situ observations and model simulations to highlight the role of the strong El Niño event.

The compound nature of large wildfires in combination with complex physical and biophysical processes affecting variations in hydroclimate and fuel conditions makes it difficult to directly connect wildfire changes over fire-prone regions like the western United States (U.S.) with anthropogenic climate change. Here we show that increasing large wildfires during autumn over the western U.S. are fueled by more fire-favorable weather associated with declines in Arctic sea ice during preceding months on both interannual and interdecadal time scales. Our analysis (based on observations, climate model sensitivity experiments, and a multi-model ensemble of climate simulations) demonstrates and explains the Arctic-driven teleconnection through regional circulation changes with the poleward-shifted polar jet stream and enhanced fire-favorable surface weather conditions. The fire weather changes driven by declining Arctic sea ice during the past four decades are of similar magnitude to other leading modes of climate variability such as the El Niño-Southern Oscillation that also influence fire weather in the western U.S. The western United States have seen an increase in wildfire activity in recent decades, the causes of which are not well understood. Here, the authors show that Arctic sea ice decline contributed to this increase through its influence on regional circulation which enhanced fire-favourable weather conditions.

Warming thaws permafrost, releasing carbon that can cause more warming. Radiocarbon, soil carbon, and remote sensing data suggest that 0.2–2.5 Pg of carbon has been emitted from permafrost as CO 2 and CH 4 around Arctic lakes since the 1950s. Permafrost thaw exposes previously frozen soil organic matter to microbial decomposition. This process generates methane and carbon dioxide, and thereby fuels a positive feedback process that leads to further warming and thaw 1 . Despite widespread permafrost degradation during the past ∼40 years 2 , 3 , 4 , the degree to which permafrost thaw may be contributing to a feedback between warming and thaw in recent decades is not well understood. Radiocarbon evidence of modern emissions of ancient permafrost carbon is also sparse 5 . Here we combine radiocarbon dating of lake bubble trace-gas methane (113 measurements) and soil organic carbon (289 measurements) for lakes in Alaska, Canada, Sweden and Siberia with numerical modelling of thaw and remote sensing of thermokarst shore expansion. Methane emissions from thermokarst areas of lakes that have expanded over the past 60 years were directly proportional to the mass of soil carbon inputs to the lakes from the erosion of thawing permafrost. Radiocarbon dating indicates that methane age from lakes is nearly identical to the age of permafrost soil carbon thawing around them. Based on this evidence of landscape-scale permafrost carbon feedback, we estimate that 0.2 to 2.5 Pg permafrost carbon was released as methane and carbon dioxide in thermokarst expansion zones of pan-Arctic lakes during the past 60 years.

The Arctic warms nearly four times faster than the global average, and aerosols play an increasingly important role in Arctic climate change. In the Arctic, sea salt is a major aerosol component in terms of mass concentration during winter and spring. However, the mechanisms of sea salt aerosol production remain unclear. Sea salt aerosols are typically thought to be relatively large in size but low in number concentration, implying that their influence on cloud condensation nuclei population and cloud properties is generally minor. Here we present observational evidence of abundant sea salt aerosol production from blowing snow in the central Arctic. Blowing snow was observed more than 20% of the time from November to April. The sublimation of blowing snow generates high concentrations of fine-mode sea salt aerosol (diameter below 300 nm), enhancing cloud condensation nuclei concentrations up to tenfold above background levels. Using a global chemical transport model, we estimate that from November to April north of 70° N, sea salt aerosol produced from blowing snow accounts for about 27.6% of the total particle number, and the sea salt aerosol increases the longwave emissivity of clouds, leading to a calculated surface warming of +2.30 W m−2 under cloudy sky conditions.Fine sea salt aerosols produced by blowing snow in the Arctic impact cloud properties and warm the surface, according to observations from the MOSAiC expedition.

Despite the importance of high-latitude surface energy budgets (SEBs) for land-climate interactions in the rapidly changing Arctic, uncertainties in their prediction persist. Here, we harmonize SEB observations across a network of vegetated and glaciated sites at circumpolar scale (1994–2021). Our variance-partitioning analysis identifies vegetation type as an important predictor for SEB-components during Arctic summer (June-August), compared to other SEB-drivers including climate, latitude and permafrost characteristics. Differences among vegetation types can be of similar magnitude as between vegetation and glacier surfaces and are especially high for summer sensible and latent heat fluxes. The timing of SEB-flux summer-regimes (when daily mean values exceed 0 Wm −2 ) relative to snow-free and -onset dates varies substantially depending on vegetation type, implying vegetation controls on snow-cover and SEB-flux seasonality. Our results indicate complex shifts in surface energy fluxes with land-cover transitions and a lengthening summer season, and highlight the potential for improving future Earth system models via a refined representation of Arctic vegetation types. An international team of researchers finds high potential for improving climate projections by a more comprehensive treatment of largely ignored Arctic vegetation types, underscoring the importance of Arctic energy exchange measuring stations.