Snow cover is a critical factor controlling plant performance, such as survival, growth, and biomass, and vegetation cover in regions with seasonal snow (e.g., high-latitude and high-elevation regions), due to its influence on the timing and length of the growing season, insulation effect during winter, and biotic and abiotic environmental factors. Therefore, changes in snow cover driven by rising temperatures and shifting precipitation patterns are expected to alter plant performance and vegetation cover. Despite the rapid increase in research on this topic in recent decades, there is still a lack of studies that quantitatively elucidate how plant performance and vegetation cover respond to shifting snow cover across snowy regions. Additionally, no comprehensive study has yet quantitatively examined these responses across regions, ecosystems, and plant functional types. Here, we conducted a meta-analysis synthesizing data from 54 snow cover manipulation studies conducted in both the field and laboratory across snowy regions to detect how plants performance and vegetation cover respond to decreased or increased snow cover. Our results demonstrate that plant survival, aboveground biomass, and belowground biomass exhibited significant decreases in response to decreased snow cover, with rates of survival having the greatest decrease. In response to increased snow cover, plant survival, growth, biomass and vegetation cover tended to increase, except for plant belowground length growth and biomass, which showed significant decreases. Additionally, our quantitative analysis of plant responses to changes in snow cover across regions, ecosystems, and plant functional types revealed that cold regions with thin snow cover, tundra and forest ecosystems, and woody species are particularly vulnerable to snow cover reduction. Overall, this study demonstrates the strong controls that snow cover exerts on plant performance, providing insights into the dynamics of snow-covered ecosystems under changing winter climatic conditions.

Study region: The source area of the Yangtze River, a typical catchment in the cryosphere on the Tibet Plateau, was used to develop and validate a distributed hydrothermal coupling model. Study focus: Climate change has caused significant changes in hydrological processes in the cryosphere, and related research has become hot topic. The source area of the Yangtze River (SAYR) is a key catchment for studies of hydrological processes in the cryosphere, which contains widespread glacier, snow, and permafrost. However, the current hydrological modeling of the SAYR rarely depicts the process of glacier/snow and permafrost runoff from the perspective of coupled water and heat transfer, resulting in distortion of simulations of hydrological processes. Therefore, we developed a distributed hydrothermal coupling model, namely WEP-SAYR, based on the WEP-L (Water and energy transfer process in large river basins) model by introducing modules for glacier and snow melt and permafrost freezing and thawing. New hydrological insights for the region: In the WEP-SAYR model, the soil hydrothermal transfer equations were improved, and a freezing point equation for permafrost was introduced. In addition, the glacier and snow meltwater processes were described using the temperature index model. Compared to previously applied models, the WEP-SAYR portrays in more detail glacier/ snow melting, dynamic changes in permafrost water and heat coupling, and runoff dynamics, with physically meaningful and easily accessible model parameters. The model can describe the soil temperature and moisture changes in soil layers at different depths from 0 to 140 cm. Moreover, the model has a good accuracy in simulating the daily/monthly runoff and evaporation. The Nash-Sutcliffe efficiency exceeded 0.75, and the relative error was controlled within +/- 20 %. The results showed that the WEP-SAYR model balances the efficiency of hydrological simulation in large scale catchments and the accurate portrayal of the cryosphere elements, which provides a reference for hydrological analysis of other catchments in the cryosphere.

In recent decades, the Himalayas have seen increasing extreme precipitation events. Climate change has impacted the occurrence and distribution of extreme precipitation events across the Himalayas. Patterns of both western disturbances and the Indian summer monsoon are undergoing significant changes in nature due to climate change. However, the magnitude and intensity of flood in a stream are not always linearly dependent on the amount of precipitation. Other factors, such as topography, land use, soil characteristics, and antecedent hydrological conditions, play a pivotal role in modulating the response of a watershed to an extreme precipitation event. On July 07-11, 2023, several districts of Himachal Pradesh faced devastating floods resulting in loss of life, infrastructure, and environmental damage with significant economic consequences. Developing a resilient solution for managing such events and reducing damage requires an in-depth understanding of multiple causative factors of such extreme events. In this paper, we analyzed the meteorological and hydrological factors that caused the flooding situation in Himachal Pradesh during July 2023. Hydrometeorological data from several observation stations were analyzed along with reanalysis data from ERA5, SMAP-L4, and FLDAS-NOAH to understand the causative factors that lead to peak floods. The compounding of extremely heavy rainfall with near-saturation antecedent moisture content and snowmelt was found to be the leading factor in inflating and sustaining the flood peak.

We estimate snow albedo feedback effects of anthropogenic increases in global radiative forcing, which includes carbon dioxide, methane, nitrous oxide, CFC11, CFC12, black carbon, anthropogenic sulfur emissions, total solar irradiance, and local sulfur emissions by compiling annual observations (1972-2008) for radiative forcing, temperature, snow cover, sulfur emissions, and various teleconnections for 255 5 degrees x 5 degrees grid cells in the Northern Hemisphere. Panel DOLS estimates of the long-run relations indicate that the effect of radiative forcing on temperature increases with latitude (consistent with polar amplification), eliminating snow cover increases local temperature by about 2.8 degrees C, and a 1 degrees C temperature increase reduces snow cover by about 1%. These values create a snow albedo feedback (SAF) that amplifies the temperature increase of higher forcing by about 3.4% relative to its direct effect while an increase in sulfur emissions increases the temperature reduction by about 0.4% relative to its direct effect. The 3.4% SAF is smaller than values generated by process-based climate models and may be associated with the empirical estimates for snowmelt sensitivity Delta S-c/Delta T-s To narrow estimates for the SAF from climate models, we conclude with suggestions for a new experimental design that controls for the simultaneous relation between temperature and snow cover.

Observing the isotopic evolution of snow meltwater helps in understanding the process of snow melting but remains a challenge to acquire in the field. In this study, we monitored the melting of two snowpacks near Baishui Glacier No. 1, a typical temperate glacier on the southeastern Tibetan Plateau. We employed a physically based isotope model (PBIM) to calculate the isotopic composition of meltwater draining from natural snowpacks. The initial condition of the PBIM was revised to account for natural conditions, i.e., the initial delta O-18 stratigraphy of snow layers before melting. Simulations revealed that the initial heterogeneity of delta O-18 in snow layers as well as ice-liquid isotopic exchange were responsible for most variations of delta O-18 in snow meltwater, whereas new snow and wind drift could result in sudden changes of the isotopic composition of the meltwater. The fraction of ice involved in the isotopic exchange (f) was the most sensitive parameter for the model output. The initial delta O-18 in the snowpack is mirrored in meltwater in case of smallfand is smoothed with a large exchange fractionf. The other unknown parameter of the PBIM is the dimensionless rate constant of isotopic exchange, which depends on water percolation and initial snow depth. The successful application of the PBIM in the field might not only be useful for understanding snow melting process but might also provide the possibility of predicting the isotopic composition of snow meltwater and improve the accuracy of hydrograph separation.

Black carbon (BC) in snow plays an important role to accelerate snow melting. However, current studies mostly focused on BC concentrations, few on their size distributions in snow which affected BC's effect on albedo changes. Here we presented refractory BC (rBC) concentrations and size distributions in snow collected from Chinese Altai Mountains in Central Asia from November 2016 to April 2017. The results revealed that the average rBC concentrations were 5.77 and 2.82 ng g(-1) for the surface snow and sub-surface snow, which were relatively higher in the melting season (April) than that in winter (November-January). The mass median volume-equivalent diameter of rBC size in surface snow was approximately at 120-150 nm, which was typically smaller than that in the atmosphere (about 200 nm for urban atmosphere). However, there existed no specific mass median volume-equivalent diameter of BC size for sub-surface snow in winter. While during the melting season, the median mass size of rBC in sub-surface snow was similar to that in surface snow. Backward trajectories indicated that anthropogenic sourced BC dominated rBC in snow (70%-85%). This study will promote our understanding on BC size distributions in snow, and highlight the possible impact of BC size on climate effect.

Third Pole natural cascade alpine lakes (NCALs) are exceptionally sensitive to climate change, yet the underlying cryosphere-hydrological processes and associated societal impacts are largely unknown. Here, with a state-of-the-art cryosphere-hydrology-lake-dam model, we quantified the notable high-mountain Hoh-Xil NCALs basin (including Lakes Zonag, Kusai, Hedin Noel, and Yanhu, from upstream to downstream) formed by the Lake Zonag outburst in September 2011. We demonstrate that long-term increased precipitation and accelerated ice and snow melting as well as short-term heavy precipitation and earthquake events were responsible for the Lake Zonag outburst; while the permafrost degradation only had a marginal impact on the lake inflows but was crucial to lakeshore stability. The quadrupling of the Lake Yanhu area since 2012 was due to the tripling of inflows (from 0.25 to 0.76 km(3)/year for 1999 to 2010 and 2012 to 2018, respectively). Prediction of the NCALs changes suggests a high risk of the downstream Qinghai-Tibet Railway, necessitating timely adaptions/mitigations.

Season snow cover plays an important role in vegetation growth in alpine regions. In this study, we analyzed the spatial and temporal variations in seasonal snow cover and the start of the growing season (SOS) of alpine grasslands and preliminarily studied the mechanism by which snow cover affects SOS changes by modifying the soil temperature (ST) and soil moisture (SM) in spring. The results showed that significant interannual trends in the SOS, snow end date (SED), snow cover days (SCD), ST, and SM existed over the Tibetan Plateau (TP) in China from 2000 to 2020. The SOS advanced by 2.0 d/10 a over the TP over this period. Moreover, the SOS showed advancing trends in the eastern and central parts of the TP and a delayed trend in the west. The SED and SCD exhibited an advancing trend and a decreasing trend in high-elevation areas, respectively, and the opposite trends in low-elevation areas. The ST showed a decreasing trend in low-elevation areas and an increasing trend in high-elevation areas. The SM tended to increase in most areas. The effects of the seasonal snow cover on the ST and SM indirectly influenced the SOS of alpine grasslands. The delayed SEDs and more SCD observed herein could provide increasingly wet soil conditions optimal for the advancement of the SOS, while less snow and shorter snow seasons could delay the SOS of alpine grasslands on the TP.

Recent increases in surface temperature and snow melt acceleration in the Himalayan region are influenced by many factors. Here we investigate the influence of absorbing aerosols, including black carbon and dust, on surface temperature and snow melt in western, central, and eastern parts of the India-Nepal Himalayan region (INHR). We compare 40-y simulations (1971-2010) one with all evolving forcing agents representative of a present-day aerosol scenario, compared to a low aerosol forcing scenario. The difference between these scenarios shows a significant increase in surface air temperature, with higher warming in parts of Western and Central Himalaya (-0.2-2 degrees C) in the months of April and May. Higher absorbing aerosol (BC and dust abundance) both at the surface and in the atmospheric column, in the present-day aerosol simulations, led to increases in atmospheric radiative forcing and surface shortwave heating rate forcing (SWHRF), compared to the low aerosol forcing case. Therefore, the absorbing aerosols cause anomalous atmospheric heat energy transfer to land due to high surface SWHRF and changes in surface energy flux, leading to snow melt. The present model version did not parameterize snow albedo feedback, which would increase the magnitudes of the changes simulated here. (C) 2021 Elsevier B.V. All rights reserved.

Cold seasons in Arctic ecosystems are increasingly important to the annual carbon balance of these vulnerable ecosystems. Arctic winters are largely harsh and inaccessible leading historic data gaps during that time. Until recently, cold seasons have been assumed to have negligible impacts on the annual carbon balance but as data coverage increases and the Arctic warms, the cold season has been shown to account for over half of annual methane (CH4) emissions and can offset summer photosynthetic carbon dioxide (CO2) uptake. Freeze-thaw cycle dynamics play a critical role in controlling cold season CO(2)and CH(4)loss, but the relationship has not been extensively studied. Here, we analyze freeze-thaw processes through in situ CO(2)and CH(4)fluxes in conjunction with soil cores for physical structure and porewater samples for redox biogeochemistry. We find a movement of water toward freezing fronts in soil cores, leaving air spaces in soils, which allows for rapid infiltration of oxygen-rich snow melt in spring as shown by oxidized iron in porewater. The snow melt period coincides with rising ecosystem respiration and can offset up to 41% of the summer CO(2)uptake. Our study highlights this important seasonal process and shows spring greenhouse gas emissions are largely due to production from respiration instead of only bursts of stored gases. Further warming is projected to result in increases of snowpack and deeper thaws, which could increase this ecosystem respiration dominate snow melt period causing larger greenhouse gas losses during spring.