The deposition of light absorbing impurities (LAIs) (e.g., black carbon (BC), organic carbon (OC), mineral dust (MD)) on snow is an important attribution to accelerate snowmelt across the northern Xinjiang, China. At present, there is still a lack of understanding of the LAIs concentration, elution and enrichment process in snow cover over Xinjiang. Based on these, continuously sampling during two years carried out to investigate the concentrations, impacts and potential sources of LAIs in snow at Kuwei Station in the southern Altai Mountains. The average concentrations of BC, OC and MD in the surface snow were 2787 +/- 2334 ng g(-1), 6130 +/- 6127 ng g(-1), and 70.03 +/- 62.59 mu g g(-1), respectively, which dramatically increased along with snowmelt intensified, reflecting a significant enrichment process of LAIs at the snow surface. Besides, high LAIs concentrations also found in the subsurface and melting layers of the snowpit, reflecting the elution and redistribution of LAIs. With the simulation of the SNow ICe Aerosol Radiative model, BC was the main dominant factor in reducing snow albedo and radiative forcing (RF), its impact was more remarkable in the snowmelt period. The average contribution rates of BC, MD and BC + MD to snow albedo reduction increased by 20.0 +/- 1.9%, 13.0 +/- 0.2%, and 20.5 +/- 2.3% in spring compared with that in winter; meanwhile, the corresponding average RFs increased by 15.8 +/- 3.4 W m(-2), 4.7 +/- 0.3 W m(-2) and 16.4 +/- 3.2 W m(-2), respectively. Changes in the number of snowmelt days caused by BC and MD decreased by 3.0 +/- 0.4 d to 8.3 +/- 1.3 d. It indicated that surface enrichment of LAIs during snow melting might accelerate snowmelt further. Weather Research and Forecasting Chemistry model showed that the resident emission was the main potential source of BC and OC in snow. This implied that the mitigation of intensive snowmelt needs to mainly reduce resident emission of LAIs in the future. (C) 2020 Elsevier Ltd. All rights reserved.

Optimizing the functions and services provided by the mountain cryosphere will maximize its benefits and minimize the negative impacts experienced by the populations that live and work in the cryosphere-fed regions. The high sensitivity of the mountain cryosphere to climate change highlights the importance of evaluating cryospheric changes and any cascading effects if we are to achieve regional sustainable development goals (SDGs). The southern Altai Mountains (SAM), which are located in the arid to semi-arid region of central Asia, are vulnerable to ecological and environmental changes as well as to developing economic activities in northern Xinjiang, China. Furthermore, cryospheric melting in the SAM serves as a major water resource for northeastern Kazakhstan. Here, we systematically investigate historical cryospheric changes and possible trends in the SAM and also discover the opportunities and challenges on regional water resources management arising from these changes. The warming climate and increased solid precipitation have led to inconsistent trends in the mountain cryosphere. For example, mountain glaciers, seasonally frozen ground (SFG), and river ice have followed significant shrinkage trends as evidenced by the accelerated glacier melt, shallowed freezing depth of SFG, and thinned river ice with shorter durations, respectively. In contrast, snow accumulation has increased during the cold season, but the duration of snow cover has remained stable because of the earlier onset of spring melting. The consequently earlier melt has changed the timing of surface runoff and water availability. Greater interannual fluctuations in snow cover have led to more frequent transitions between snow cover hazards (snowstorm and snowmelt flooding) and snow droughts, which pose challenges to hydropower, agriculture, aquatic life, the tail-end lake environment, fisheries, and transboundary water resource management. Increasing the reservoir capacity to regulate interannual water availability and decrease the risk associated with hydrological hazards related to extreme snowmelt may be an important supplement to the regulation and supply of cryospheric functions in a warmer climate.

The deposition of light absorbing impurities (LAIs) (e.g., black carbon (BC), organic carbon (OC), mineral dust (MD)) on snow is an important attribution to accelerate snowmelt across the northern Xinjiang, China. At present, there is still a lack of understanding of the LAIs concentration, elution and enrichment process in snow cover over Xinjiang. Based on these, continuously sampling during two years carried out to investigate the concentrations, impacts and potential sources of LAIs in snow at Kuwei Station in the southern Altai Mountains. The average concentrations of BC, OC and MD in the surface snow were 2787 +/- 2334 ng g(-1), 6130 +/- 6127 ng g(-1), and 70.03 +/- 62.59 mu g g(-1), respectively, which dramatically increased along with snowmelt intensified, reflecting a significant enrichment process of LAIs at the snow surface. Besides, high LAIs concentrations also found in the subsurface and melting layers of the snowpit, reflecting the elution and redistribution of LAIs. With the simulation of the SNow ICe Aerosol Radiative model, BC was the main dominant factor in reducing snow albedo and radiative forcing (RF), its impact was more remarkable in the snowmelt period. The average contribution rates of BC, MD and BC + MD to snow albedo reduction increased by 20.0 +/- 1.9%, 13.0 +/- 0.2%, and 20.5 +/- 2.3% in spring compared with that in winter; meanwhile, the corresponding average RFs increased by 15.8 +/- 3.4 W m(-2), 4.7 +/- 0.3 W m(-2) and 16.4 +/- 3.2 W m(-2), respectively. Changes in the number of snowmelt days caused by BC and MD decreased by 3.0 +/- 0.4 d to 8.3 +/- 1.3 d. It indicated that surface enrichment of LAIs during snow melting might accelerate snowmelt further. Weather Research and Forecasting Chemistry model showed that the resident emission was the main potential source of BC and OC in snow. This implied that the mitigation of intensive snowmelt needs to mainly reduce resident emission of LAIs in the future. (C) 2020 Elsevier Ltd. All rights reserved.