Surface albedo (SA) is crucial for understanding land surface processes and climate simulation. This study analyzed SA changes and its influencing factors in Central Asia from 2001 to 2020, with projections 2025 to 2100. Factors analyzed included snow cover fraction, fractional vegetation cover, soil moisture, average state climate indices (temperature and precipitation), and extreme climate indices (heatwave indices and extreme precipitation indices). Pearson correlation coefficient, geographical convergent cross mapping, and geographical detector were used to quantify the correlation, causal relationship strength, and impact degree between SA and the influencing factors. To address multicollinearity, ridge regression (RR), geographically weighted ridge regression (GWRR), and piecewise structural equation modeling (pSEM) were combined to construct RR-pSEM and GWRR-pSEM models. Results indicated that SA in Central Asia increased from 2001 to 2010 and decreased from 2011 to 2020, with a projected future decline. There is a strong correlation and significant causality between SA and each factor. Snow cover fraction was identified as the most critical factor influencing SA. Average temperature and precipitation had a greater impact on SA than extreme climate indices, with a 1 degrees C temperature increase corresponding to a 0.004 decrease in SA. This study enhances understanding of SA changes under climate change, and provides a methodological framework for analyzing complex systems with multicollinearity. The proposed models offer valuable tools for studying interrelated factors in Earth system science.

This study uses a new dataset on gauge locations and catchments to assess the impact of 21st-century climate change on the hydrology of 221 high-mountain catchments in Central Asia. A steady-state stochastic soil moisture water balance model was employed to project changes in runoff and evaporation for 2011-2040, 2041-2070, and 2071-2100, compared to the baseline period of 1979-2011. Baseline climate data were sourced from CHELSA V21 climatology, providing daily temperature and precipitation for each subcatchment. Future projections used bias-corrected outputs from four General Circulation Models under four pathways/scenarios (SSP1 RCP 2.6, SSP2 RCP 4.5, SSP3 RCP 7.0, SSP5 RCP 8.5). Global datasets informed soil parameter distribution, and glacier ablation data were integrated to refine discharge modeling and validated against long-term catchment discharge data. The atmospheric models predict an increase in median precipitation between 5.5% to 10.1% and a rise in median temperatures by 1.9 degrees C to 5.6 degrees C by the end of the 21st century, depending on the scenario and relative to the baseline. Hydrological model projections for this period indicate increases in actual evaporation between 7.3% to 17.4% and changes in discharge between + 1.1% to -2.7% for the SSP1 RCP 2.6 and SSP5 RCP 8.5 scenarios, respectively. Under the most extreme climate scenario (SSP5-8.5), discharge increases of 3.8% and 5.0% are anticipated during the first and second future periods, followed by a decrease of -2.7% in the third period. Significant glacier wastage is expected in lower-lying runoff zones, with overall discharge reductions in parts of the Tien Shan, including the Naryn catchment. Conversely, high-elevation areas in the Gissar-Alay and Pamir mountains are projected to experience discharge increases, driven by enhanced glacier ablation and delayed peak water, among other things. Shifts in precipitation patterns suggest more extreme but less frequent events, potentially altering the hydroclimate risk landscape in the region. Our findings highlight varied hydrological responses to climate change throughout high-mountain Central Asia. These insights inform strategies for effective and sustainable water management at the national and transboundary levels and help guide local stakeholders.

Aerosol optical properties, including absorption and scattering coefficients (B-abs, and B-scat), extinction coefficient (B-ext), single scattering albedo (SSA), and so forth, are critical metrics to estimate the radiative balance of the atmosphere. However, their ground measurements are sparsely distributed in the world, where Central Asia is void in these measurements. We had been performing the measurements of AOPs and BC with a photoacoustic extinctiometer (PAX) in Jimunai, a border town of China neighboring Kazakhstan, Central Asia, from Aug 2016 to Apr 2019. This three-year study first reported statistically significant trends of B-abs, B-scat, B-ext, SSA, and derived concentrations of BC (Mann-Kendall trend test, p-value 0.05) in the Central-Asian area. B-abs and B-scat show increasing trends and SSA was decreasing determined by the greater increasing pace of B-abs than B-scat. Seasonal and diurnal variations of the AOPs were associated with climate shift and residents' commute activity, respectively. The difference in the magnitudes and trends of AOPs between the measurements and satellites' observations advise that more care should be invested when choosing remote-sensing data to represent the AOPs at a specific site. The increasing trend of derived BC concentrations is reflected in the deposition record of BC in a snowpit of the nearby Muz Taw glacier. We suppose that the dramatically increasing BC particles emitted from Jimunai are significant factors triggering the melting of the adjacent mountain glaciers. The outflow of dust from the neighboring Gurbantiinggiit Desert could occasionally invade into Jimunai and deteriorate the local air quality, as evidenced by a probable dust event captured by the PAX on Feb 15, 2018. Finally, we outlook the future perspectives of measurements in Jimunai as a long-standing station.

To elucidate the molecular composition and sources of organic aerosols in Central Asia, carbonaceous compounds, major ions, and 15 organic molecular tracers of total suspended particulates (TSP) were analyzed from September 2018 to August 2019 in Dushanbe, Tajikistan. Extremely high TSP concentrations (annual mean +/- std: 211 +/- 131 mu gm(-3)) were observed, particularly during summer (seasonal mean +/- std: 333 +/- 183 mu g m(- 3)). Organic carbon (OC: 11.9 +/- 7.0 mu gm(-3)) and elemental carbon (EC: 5.1 +/- 2.2 mu gm(-3)) exhibited distinct seasonal variations from TSP, with the highest values occurring in winter. A high concentration of Ca2+ was observed (11.9 +/- 9.2 mu g m(-3)), accounting for 50.8% of the total ions and reflecting the considerable influence of dust on aerosols. Among the measured organic molecular tracers, levoglucosan was the predominant compound (632 +/- 770 ng m(-3)), and its concentration correlated significantly with OC and EC during the study period. These findings highlight biomass burning (BB) as an important contributor to the particulate air pollution in Dushanbe. High ratios of levoglucosan to mannosan, and syringic acid to vanillic acid suggest that mixed hardwood and herbaceous plants were the main burning materials in the area, with softwood being a minor one. According to the diagnostic tracer ratio, OC derived from BB constituted a large fraction of the primary OC (POC) in ambient aerosols, accounting for an annual mean of nearly 30% and reaching 63% in winter. The annual contribution of fungal spores to POC was 10%, with a maximum of 16% in spring. Measurements of plant debris, accounting for 3% of POC, divulged that these have the same variation as fungal spores.

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.

Study RegionThe Naryn River Basin, KyrgyzstanStudy FocusWe investigate the impacts of climate change in the basin based on two families of General Circulation Models (GCMs) using the hydrological model SWAT. The forcing datasets are the widely used ISIMIP2 (I2) and the newly derived ISIMIP3 (I3) data which refer to the 5th and 6th stage of the Coupled Model Intercomparison Project (CMIP). Due to notable differences in the forcing we evaluate their impacts on various hydrological components of the basin, such as discharge, evapotranspiration (ETA) and soil moisture (SM). Besides, a partial correlation (PC) analysis is used to assess the meteorological controls of the basin with special emphasize on the SM-ETA coupling. New Hydrological Insights for the RegionAgreement in the basin's projections is found, such as discharge shifts towards an earlier peak flow of one month, significant SM reductions and ETA increases. I3 temperature projections exceed their previous estimates and show an increase in precipitation, which differs from I2. However, the mitigating effects do not lead to an improvement in the region's susceptibility to soil moisture deficits. The PC study reveals enhanced water-limited conditions expressed as positive SM-ETA feedback under I2 and I3, albeit slightly weaker under I3.

This paper presents the results of the study on columnar aerosol optical and physical properties and radiative effects directly observed over Dushanbe, the capital city of Tajikistan, a NASA AERONET site (equipped with a CIMEL sunphotometer) in Central Asia. The average aerosol optical depth (AOD) and Angstrom exponent (AE) during the observation period from July 2010 to April 2018 were found to be 0.28 +/- 0.20 and 0.82 +/- 0.40, respectively. The highest seasonal AOD (0.32 +/- 0.24), accompanied by the lowest average AE (0.61 +/- 0.25) and fine-mode fraction in AOD (0.39), was observed during summer due to the influence of coarse particles like dust from arid regions. Fine particles were found in significant amounts during winter. The 'mixed aerosol' was identified as the dominant aerosol type with presence of 'dust aerosol' during summer and autumn seasons. Aerosol properties like volume size distribution, single scattering albedo, asymmetry parameter and refractive index suggested the influence of coarse particles (during summer and autumn). Most of the air masses reaching this site transported local and regional emissions, including from beyond Central Asia, explaining the presence of various aerosol types in Dushanbe's atmosphere. The seasonal aerosol radiative forcing efficiency (ARFE) in the atmosphere was found high (>100 Wm(-2)) and consistent throughout the year. Consequently, this resulted in similar seasonally coherent high atmospheric solar heating rate (HR) of 1.5 K day(-1) during summer-autumn-winter, and ca. 0.9 K day(-1) during spring season. High ARFE and HR values indicate that atmospheric aerosols could exert significant implications to regional air quality, climate and cryosphere over the central Asian region and downwind Tianshan and Himalaya-Tibetan Plateau mountain regions with sensitive ecosystems. (C) 2020 Elsevier Ltd. All rights reserved.

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.

The location of Central Asia, almost at the center of the global dust belt region, makes it susceptible for dust events. The studies on atmospheric impact of dust over the region are very limited despite the large area occupied by the region and its proximity to the mountain regions (Tianshan, Hindu Kush-Karakoram-Himalayas, and Tibetan Plateau). In this study, we analyse and explain the modification in aerosols' physical, optical and radiative properties during various levels of aerosol loading observed over Central Asia utilizing the data collected during 2010-2018 at the AERONET station in Dushanbe, Tajikistan. Aerosol episodes were classified as strong anthropogenic, strong dust and extreme dust. The mean aerosol optical depth (AOD) during these three types of events was observed a factor of similar to 3, 3.5 and 6.6, respectively, higher than the mean AOD for the period 2010-2018. The corresponding mean fine-mode fraction was 0.94, 0.20 and 0.16, respectively, clearly indicating the dominance of fine-mode anthropogenic aerosol during the first type of events, whereas coarse-mode dust aerosol dominated during the other two types of events. This was corroborated by the relationships among various aerosol parameters (AOD vs. AE, and EAE vs. AAE, SSA and RRI). The mean aerosol radiative forcing (ARF) at the top of the atmosphere (ARF(TOA)), the bottom of the atmosphere (ARF(BOA)), and in the atmosphere (ARF(ATM)) were -35 +/- 7, -73 +/- 16, and 38 +/- 17 Wm(2) during strong anthropogenic events, -48 +/- 12, -85 +/- 24, and 37 +/- 15 Wm(2) during strong dust event, and -68 +/- 19, -117 +/- 38, and 49 +/- 21 Wm(2) during extreme dust events. Increase in aerosol loading enhanced the aerosol-induced atmospheric heating rate to 0.5-1.6 K day(-1) (strong anthropogenic events), 0.4-1.9 K day(-1) (strong dust events) and 0.8-2.7 K day(-1) (extreme dust events). The source regions of air masses to Dushanbe during the onset of such events are also identified. Our study contributes to the understanding of dust and anthropogenic aerosols, in particular the extreme events and their disproportionally high radiative impacts over Central Asia. (C) 2021 China University of Geosciences (Beijing) and Peking University. Production and hosting by Elsevier B.V.

The location of Central Asia, almost at the center of the global dust belt region, makes it susceptible for dust events. The studies on atmospheric impact of dust over the region are very limited despite the large area occupied by the region and its proximity to the mountain regions (Tianshan, Hindu Kush-Karakoram-Himalayas, and Tibetan Plateau). In this study, we analyse and explain the modification in aerosols' physical, optical and radiative properties during various levels of aerosol loading observed over Central Asia utilizing the data collected during 2010-2018 at the AERONET station in Dushanbe, Tajikistan. Aerosol episodes were classified as strong anthropogenic, strong dust and extreme dust. The mean aerosol optical depth (AOD) during these three types of events was observed a factor of similar to 3, 3.5 and 6.6, respectively, higher than the mean AOD for the period 2010-2018. The corresponding mean fine-mode fraction was 0.94, 0.20 and 0.16, respectively, clearly indicating the dominance of fine-mode anthropogenic aerosol during the first type of events, whereas coarse-mode dust aerosol dominated during the other two types of events. This was corroborated by the relationships among various aerosol parameters (AOD vs. AE, and EAE vs. AAE, SSA and RRI). The mean aerosol radiative forcing (ARF) at the top of the atmosphere (ARF(TOA)), the bottom of the atmosphere (ARF(BOA)), and in the atmosphere (ARF(ATM)) were -35 +/- 7, -73 +/- 16, and 38 +/- 17 Wm(2) during strong anthropogenic events, -48 +/- 12, -85 +/- 24, and 37 +/- 15 Wm(2) during strong dust event, and -68 +/- 19, -117 +/- 38, and 49 +/- 21 Wm(2) during extreme dust events. Increase in aerosol loading enhanced the aerosol-induced atmospheric heating rate to 0.5-1.6 K day(-1) (strong anthropogenic events), 0.4-1.9 K day(-1) (strong dust events) and 0.8-2.7 K day(-1) (extreme dust events). The source regions of air masses to Dushanbe during the onset of such events are also identified. Our study contributes to the understanding of dust and anthropogenic aerosols, in particular the extreme events and their disproportionally high radiative impacts over Central Asia. (C) 2021 China University of Geosciences (Beijing) and Peking University. Production and hosting by Elsevier B.V.