Streamflow seasonality in a snow-dwindling world.

Climate warming induces shifts from snow to rain in cold regions1, altering snowpack dynamics with consequent impacts on streamflow that raise challenges to many aspects of ecosystem services2-4. A straightforward conceptual model states that as the fraction of precipitation falling as snow (snowfall fraction) declines, less solid water is stored over the winter and both snowmelt and streamflow shift earlier in season. Yet the responses of streamflow patterns to shifts in snowfall fraction remain uncertain5-9. Here we show that as snowfall fraction declines, the timing of the centre of streamflow mass may be advanced or delayed. Our results, based on analysis of 1950-2020 streamflow measurements across 3,049 snow-affected catchments over the Northern Hemisphere, show that mean snowfall fraction modulates the seasonal response to reductions in snowfall fraction. Specifically, temporal changes in streamflow timing with declining snowfall fraction reveal a gradient from earlier streamflow in snow-rich catchments to delayed streamflow in less snowy catchments. Furthermore, interannual variability of streamflow timing and seasonal variation increase as snowfall fraction decreases across both space and time. Our findings revise the 'less snow equals earlier streamflow' heuristic and instead point towards a complex evolution of seasonal streamflow regimes in a snow-dwindling world.

2023 summer warmth unparalleled over the past 2,000 years.

Including an exceptionally warm Northern Hemisphere summer1,2, 2023 has been reported as the hottest year on record3-5. However, contextualizing recent anthropogenic warming against past natural variability is challenging because the sparse meteorological records from the nineteenth century tend to overestimate temperatures6. Here we combine observed and reconstructed June-August surface air temperatures to show that 2023 was the warmest Northern Hemisphere extra-tropical summer over the past 2,000 years exceeding the 95% confidence range of natural climate variability by more than 0.5 °C. Comparison of the 2023 June-August warming against the coldest reconstructed summer in CE 536 shows a maximum range of pre-Anthropocene-to-2023 temperatures of 3.93 °C. Although 2023 is consistent with a greenhouse-gases-induced warming trend7 that is amplified by an unfolding El Niño event8, this extreme emphasizes the urgency to implement international agreements for carbon emission reduction.

Climate velocities and species tracking in global mountain regions.

Mountain ranges contain high concentrations of endemic species and are indispensable refugia for lowland species that are facing anthropogenic climate change1,2. Forecasting biodiversity redistribution hinges on assessing whether species can track shifting isotherms as the climate warms3,4. However, a global analysis of the velocities of isotherm shifts along elevation gradients is hindered by the scarcity of weather stations in mountainous regions5. Here we address this issue by mapping the lapse rate of temperature (LRT) across mountain regions globally, both by using satellite data (SLRT) and by using the laws of thermodynamics to account for water vapour6 (that is, the moist adiabatic lapse rate (MALRT)). By dividing the rate of surface warming from 1971 to 2020 by either the SLRT or the MALRT, we provide maps of vertical isotherm shift velocities. We identify 17 mountain regions with exceptionally high vertical isotherm shift velocities (greater than 11.67 m per year for the SLRT; greater than 8.25 m per year for the MALRT), predominantly in dry areas but also in wet regions with shallow lapse rates; for example, northern Sumatra, the Brazilian highlands and southern Africa. By linking these velocities to the velocities of species range shifts, we report instances of close tracking in mountains with lower climate velocities. However, many species lag behind, suggesting that range shift dynamics would persist even if we managed to curb climate-change trajectories. Our findings are key for devising global conservation strategies, particularly in the 17 high-velocity mountain regions that we have identified.

Critical transitions in the Amazon forest system.

The possibility that the Amazon forest system could soon reach a tipping point, inducing large-scale collapse, has raised global concern1-3. For 65 million years, Amazonian forests remained relatively resilient to climatic variability. Now, the region is increasingly exposed to unprecedented stress from warming temperatures, extreme droughts, deforestation and fires, even in central and remote parts of the system1. Long existing feedbacks between the forest and environmental conditions are being replaced by novel feedbacks that modify ecosystem resilience, increasing the risk of critical transition. Here we analyse existing evidence for five major drivers of water stress on Amazonian forests, as well as potential critical thresholds of those drivers that, if crossed, could trigger local, regional or even biome-wide forest collapse. By combining spatial information on various disturbances, we estimate that by 2050, 10% to 47% of Amazonian forests will be exposed to compounding disturbances that may trigger unexpected ecosystem transitions and potentially exacerbate regional climate change. Using examples of disturbed forests across the Amazon, we identify the three most plausible ecosystem trajectories, involving different feedbacks and environmental conditions. We discuss how the inherent complexity of the Amazon adds uncertainty about future dynamics, but also reveals opportunities for action. Keeping the Amazon forest resilient in the Anthropocene will depend on a combination of local efforts to end deforestation and degradation and to expand restoration, with global efforts to stop greenhouse gas emissions.

Evidence of human influence on Northern Hemisphere snow loss.

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 declines1-4. So far, however, observational uncertainties in snow mass5,6 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.