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Glaciers distinct from the Greenland and Antarctic ice sheets cover an area of approximately 706,000 square kilometres globally(1), with an estimated total volume of 170,000 cubic kilometres, or 0.4 metres of potential sea-level-rise equivalent(2). Retreating and thinning glaciers are icons of climate change(3) and affect regional runoff(4) as well as global sea level(5,6). In past reports from the Intergovernmental Panel on Climate Change, estimates of changes in glacier mass were based on the multiplication of averaged or interpolated results from available observations of a few hundred glaciers by defined regional glacier areas(7-10). For data-scarce regions, these results had to be complemented with estimates based on satellite altimetry and gravimetry(11). These past approaches were challenged by the small number and heterogeneous spatiotemporal distribution of in situ measurement series and their often unknown ability to represent their respective mountain ranges, as well as by the spatial limitations of satellite altimetry (for which only point data are available) and gravimetry (with its coarse resolution). Here we use an extrapolation of glaciological and geodetic observations to show that glaciers contributed 27 +/- 22 millimetres to global mean sea-level rise from 1961 to 2016. Regional specific-mass-change rates for 2006-2016 range from -0.1 metres to -1.2 metres of water equivalent per year, resulting in a global sea-level contribution of 335 +/- 144 gigatonnes, or 0.92 +/- 0.39 millimetres, per year. Although statistical uncertainty ranges overlap, our conclusions suggest that glacier mass loss may be larger than previously reported(11.) The present glacier mass loss is equivalent to the sea-level contribution of the Greenland Ice Sheet(12), clearly exceeds the loss from the Antarctic Ice Sheet(13), and accounts for 25 to 30 per cent of the total observed sea-level rise(14). Present mass-loss rates indicate that glaciers could almost disappear in some mountain ranges in this century, while heavily glacierized regions will continue to contribute to sea-level rise beyond 2100.

Ongoing climate warming has been demonstrated to impact the cryosphere in the Indian Himalayas, with substantial consequences for the risk of disasters, human well-being, and terrestrial ecosystems. Here, we present evidence that the warming observed in recent decades has been accompanied by increased snow avalanche frequency in the Western Indian Himalayas. Using dendrogeomorphic techniques, we reconstruct the longest time series (150 y) of the occurrence and runout distances of snow avalanches that is currently available for the Himalayas. We apply a generalized linear autoregressive moving average model to demonstrate linkages between climate warming and the observed increase in the incidence of snow avalanches. Warming air temperatures in winter and early spring have indeed favored the wetting of snow and the formation of wet snow avalanches, which are now able to reach down to subalpine slopes, where they have high potential to cause damage. These findings contradict the intuitive notion that warming results in less snow, and thus lower avalanche activity, and have major implications for the Western Himalayan region, an area where human pressure is constantly increasing. Specifically, increasing traffic on a steadily expanding road network is calling for an immediate design of risk mitigation strategies and disaster risk policies to enhance climate change adaption in the wider study region.

In mountain territories, snow avalanches are a prevalent threat. Long-term risk management involves defining meaningful compromises between protection and overall sustainability of communities and their environment. Methods able to (i) consider all sources of losses, (ii) account for the high uncertainty levels that affect all components of the risk and (iii) cope for marked non-stationarities should be employed. Yet, on the basis of a literature review and an analysis of relations to Sustainable Development Goals (SDGs), it is established that snow avalanche risk assessment and mitigation remain dominated by approaches that can be summed up as deterministic, hazard oriented, stationary and not holistic enough. A more comprehensive paradigm relying on formal statistical modelling is then proposed and first ideas to put it to work are formulated. Application to different mountain environments and broader risk problems is discussed.

The release of carbon dioxide during oxidative weathering of sedimentary rocks acts as a positive feedback to warming, according to 2.5 years of CO2 flux measurements from the Draix-Bleone Critical Zone Observatory, France.Sedimentary rocks can release carbon dioxide (CO2) during the weathering of rock organic carbon and sulfide minerals. This sedimentary carbon could act as a feedback on Earth's climate over millennial to geological timescales, yet the environmental controls on the CO2 release from rocks are poorly constrained. Here, we directly measure CO2 flux from weathering of sedimentary rocks over 2.5 years at the Draix-Bleone Critical Zone Observatory, France. Total CO2 fluxes approached values reported for soil respiration, with radiocarbon analysis confirming the CO2 source from rock organic carbon and carbonate. The measured CO2 fluxes varied seasonally, with summer fluxes five times larger than winter fluxes, and were positively correlated with temperature. The CO2 release from rock organic carbon oxidation increased by a factor of 2.2 when temperature increased by 10 degrees C. This temperature sensitivity is similar to that of degradation of recent-plant-derived organic matter in soils. Our flux measurements identify sedimentary-rock weathering as a positive feedback to warming, which may have operated throughout Earth's history to force the surface carbon cycle.

Snow is highly sensitive to atmospheric warming. However, because of the lack of sufficiently long snow avalanche time series and statistical techniques capable of accounting for the numerous biases inherent to sparse and incomplete avalanche records, the evolution of process activity in a warming climate remains little known. Filling this gap requires innovative approaches that put avalanche activity into a long-term context. Here, we combine extensive historical records and Bayesian techniques to construct a 240-y chronicle of snow avalanching in the Vosges Mountains (France). We show evidence that the transition from the late Little Ice Age to the early twentieth century (i.e., 1850 to 1920 CE) was not only characterized by local winter warming in the order of +1.35 °C but that this warming also resulted in a more than sevenfold reduction in yearly avalanche numbers, a severe shrinkage of avalanche size, and shorter avalanche seasons as well as in a reduction of the extent of avalanche-prone terrain. Using a substantial corpus of snow and climate proxy sources, we explain this abrupt shift with increasingly scarcer snow conditions with the low-to-medium elevations of the Vosges Mountains (600 to 1,200 m above sea level [a.s.l.]). As a result, avalanches migrated upslope, with only a relict activity persisting at the highest elevations (release areas >1,200 m a.s.l.). This abrupt, unambiguous response of snow avalanche activity to warming provides valuable information to anticipate likely changes in avalanche behavior in higher mountain environments under ongoing and future warming.

Ski tourism is a major sector of mountain regions economy, which is under the threat of long-term climate change. Snow management, and in particular grooming and artificial snowmaking, has become a routine component of ski resort operations, holding potential for counteracting the detrimental effect of natural snow decline. However, conventional snowmaking can only operate under specific meteorological conditions. Whether snowmaking is a relevant adaptation measure under future climate change is a widely debated issue in mountainous regions, with major implications on the supply side of this tourism industry. This often lacks comprehensive scientific studies for informing public and private decisions in this sector. Here we show how climate change influences the operating conditions of one of the main ski tourism markets worldwide, the French Alps. Our study addresses snow reliability in 129 ski resorts in the French Alps in the 21st century, using a dedicated snowpack model explicitly accounting for grooming and snowmaking driven by a large ensemble of adjusted and downscaled regional climate projections, and using a geospatial model of ski resorts organization. A 45% snowmaking fractional coverage, representative of the infrastructures in the early 2020s, is projected to improve snow reliability over grooming-only snow conditions, both during the reference period 1986-2005 and below 2 degrees C global warming since pre-industrial. Beyond 3 degrees C of global warming, with 45% snowmaking coverage, snow conditions would become frequently unreliable and induce higher water requirements.

Bedload transport modelling in rivers takes into account the size and density of pebbles to estimate particle mobility, but does not formally consider particle shape. To address this issue and to compare the relative roles of the density and shape of particles, we performed original sediment transport experiments in an annular flume using molded artificial pebbles equipped with a radio frequency identification tracking system. The particles were designed with four distinct shapes and four different densities while having the same volume, and their speeds and distances traveled under constant hydraulic conditions were analyzed. The results show that particle shape has more influence than particle density on the resting time between particle displacement and the mean traveling distance. For all densities investigated, the particle shape systematically induced differences in travel distance that were strongly correlated (R-2 = 0.94) with the Sneed and Folks shape index. Such shape influences, although often mentioned, are here quantified for the first time, demonstrating why and how they can be included in bedload transport models.

Over the past decades, large variations of precipitation were observed in Africa, which often led to dramatic consequences for local society and economy. To avoid such disasters in the future, it is crucial to better anticipate the expected changes, especially in the current context of climate change and population growth. To this date, however, projections of precipitation over Africa are still associated with very large uncertainties. To better understand how this uncertainty can be reduced, this study uses an advanced Bayesian analysis of variance (ANOVA) method to characterize, for the first time in the regional climate projections of CORDEX-AFRICA, the different sources of uncertainty associated with the projections of precipitation over Africa.By 2090, the ensemble mean precipitation is projected to increase over the Horn of Africa from September to May and over the eastern Sahel and Guinea Coast from June to November. It is projected to decrease over the northern coast and southern Africa all year long, over western Sahel from March to August, and over the Sahel and Guinea Coast from March to May. Most of these projections however are not robust, i.e., the magnitude of change is smaller than the associated uncertainty. Over time, the relative contribution of internal variability (excluding interannual variability) to total uncertainty is moderate and quickly falls below 10%. By 2090, it is found that over the Horn of Africa, northern coast, southern Africa, and Sahel, most of the uncertainty results from a large dispersion across the driving Global Climate Models (in particular MIROC, CSIRO, CCCma, and IPSL), whereas over the tropics and parts of eastern Africa, most of the uncertainty results from a large dispersion across Regional Climate Models (in particular CLMcom).

To mitigate climate change and improve food security, it is essential to understand how fertilizer strategies impact the dynamics of soil organic carbon and its fractions. The soil organic carbon (SOC), light fraction organic carbon (LFOC), and particulate organic carbon (POC) were investigated every five years in a corn (Zea mays L.) cropping system with chemical fertilization and manuring over twenty-four years (1992–2016) in a semiarid area of northern China. There were four treatments with chemical fertilizer (i.e., N1P1, N2P2, N3P3, N4P4), three treatments with chemical fertilizer plus manure (i.e., N2P1M1, N3P2M3, N4P2M2), and one treatment with manure alone (i.e., M6), and an unfertilized treatment (control). The carbon sequestration rate (CSR) and efficiency (CSE) of SOC, POC, and LFOC were identified. The results revealed that the fertilization treatments (N2P2, N3P3, N2P1M1, N3P2M3, N4P2M2, and M6) promoted SOC sequestration, with a sequestration rate of 0.19~1.29 Mg ha−1 y−1. The excess application of chemical fertilizer caused a reduction in POC, whereas the application of NP, NPM or manure resulted in greater POC sequestration in soil, with a carbon sequestration rate of 0.04~0.24 Mg ha−1 y−1. The LFOC stocks were 1.43~2.24 Mg ha−1 under the NP treatments, 2.47~6.68 Mg ha−1 under the NPM treatments and 8.12 Mg ha−1 under the M treatment; these stocks were all higher than that of the control treatment. Different fertilization strategies affected the pools of SOC with different sequestration rates. We found the carbon sequestration rates of SOC and LFOC were logarithmically correlated with the annual carbon input. When the annual C input is approximately 1.39 Mg ha−1 y−1, the SOC level will be maintained; when the annual C input is higher than 0.8 Mg ha−1 y−1, the LFOC level increases. This study describes the relationship between carbon inputs and the SOC(LFOC) sequestration rates under continuous fertilization in arid cropland. The results further evidence that the long-term fertilization of NPM and M increases the potential for SOC sequestration and quantifies the amount of exogenous carbon input required for soil organic matter enhancement.

The failure of a weak snow layer buried below cohesive slab layers is a necessary, but insufficient, condition for the release of a dry-snow slab avalanche. The size of the crack in the weak layer must also exceed a critical length to propagate across a slope. In contrast to pioneering shear-based approaches, recent developments account for weak layer collapse and allow for better explaining typical observations of remote triggering from low-angle terrain. However, these new models predict a critical length for crack propagation that is almost independent of slope angle, a rather surprising and counterintuitive result. Based on discrete element simulations we propose a new analytical expression for the critical crack length. This new model reconciles past approaches by considering for the first time the complex interplay between slab elasticity and the mechanical behavior of the weak layer including its structural collapse. The crack begins to propagate when the stress induced by slab loading and deformation at the crack tip exceeds the limit given by the failure envelope of the weak layer. The model can reproduce crack propagation on low-angle terrain and the decrease in critical length with increasing slope angle as modeled in numerical experiments. The good agreement of our new model with extensive field data and the ease of implementation in the snow cover model SNOWPACK opens a promising prospect for improving avalanche forecasting.