Glaciers playa vital role in providing water resources for drinking, agriculture, and hydro-electricity in many mountainous regions. As global warming progresses, accurately reconstructing long-term glacier mass changes and comprehending their intricate dynamic relationships with environmental variables are imperative for sustaining livelihoods in these regions. This paper presents the use of eXplainable Machine Learning (XML) models with GRACE and GRACE-FO data to reconstruct long-term monthly glacier mass changes in the Upper Yukon Watershed (UYW), Canada. We utilized the H2O-AutoML regression tools to identify the best performing Machine Learning (ML) model for filling missing data and predicting glacier mass changes from hydroclimatic data. The most accurate predictive model in this study, the Gradient Boosting Machine, coupled with explanatory methods based on SHapley Additive eXplanation (SHAP) and Local Interpretable Model-Agnostic Explanations (LIME) analyses, led to automated XML models. The XML unveiled and ranked key predictors of glacier mass changes in the UYW, indicating a decrease since 2014. Analysis showed decreases in snow water equivalent, soil moisture storage, and albedo, along with increases in rainfall flux and air temperature were the main drivers of glacier mass loss. A probabilistic analysis hinging on these drivers suggested that the influence of the key hydrological features is more critical than the key meteorological features. Examination of climatic oscillations showed that high positive anomalies in sea surface temperature are correlated with rapid depletion in glacier mass and soil moisture, as identified by XML. Integrating H2OAutoML with SHAP and LIME not only achieved high prediction accuracy but also enhanced the explainability of the underlying hydroclimatic processes of glacier mass change reconstruction from GRACE and GRACE-FO data in the UYW. This automated XML framework is applicable globally, contingent upon sufficient high-quality data for model training and validation.

To address data scarcity on long-term glacial discharge and inadequacies in simulating and predicting hydrological processes in the Tien Shan, this study analysed the observed discharge at multiple timescales over 1980s-2017 and projected changes within a representative glacierized high-mountain region: eastern Tien Shan, Central Asia. Hydrological processes were simulated to predict changes under four future scenarios (SSP1, SSP2, SSP3, and SSP5) using a classical hydrological model coupled with a glacier dynamics module. Discharge rates at annual, monthly (June, July, August) and daily timescales were obtained from two hydrological gauges: Urumqi Glacier No.1 hydrological station (UGH) and Zongkong station (ZK). Overall, annual and summer discharge increased significantly ( p < 0.05) at both stations over the study period. Their intra-annual variations mainly resulted from differences in their recharge mechanisms. The simulations show that a tipping point in annual discharge at UGH may occur between 2018 and 2024 under the four SSPs scenarios. Glacial discharge is predicted to cease earlier at ZK than at UGH. This relates to glacier type and size, suggesting basins with heavily developed small glaciers will reach peak discharge sooner, resulting in an earlier freshwater supply challenge. These findings serve as a reference for research into glacial runoff in Central Asia and provide a decision-making basis for planning local water-resource projects.

To understand the characteristics of particulate matter (PM) and other air pollutants in Xinjiang, a region with one of the largest sand-shifting deserts in the world and significant natural dust emissions, the concentrations of six air pollutants monitored in 16 cities were analyzed for the period January 2013-June 2019. The annual mean PM2.5, PM10, SO2, NO2, CO, and O-3 concentrations ranged from 51.44 to 59.54 mu g m(-3), 128.43-155.28 mu g m(-3), 10.99-17.99 mu g m(-3), 26.27-31.71 mu g m(-3), 1.04-1.32 mg m(-3), and 55.27-65.26 mu g m(-3), respectively. The highest PM concentrations were recorded in cities surrounding the Taklimakan Desert during the spring season and caused by higher amounts of wind-blown dust from the desert. Coarse PM (PM10-2.5) was predominant, particularly during the spring and summer seasons. The highest PM2.5/PM10 ratio was recorded in most cities during the winter months, indicating the influence of anthropogenic emissions in winters. The annual mean PM2.5 (PM10) concentrations in the study area exceeded the annual mean guidelines recommended by the World Health Organization (WHO) by a factor of ca. similar to 5-6 (similar to 7-8). Very high ambient PM concentrations were recorded during March 19-22, 2019, that gradually influenced the air quality across four different cities, with daily mean PM2.5 (PM10) concentrations similar to 8-54 (similar to 26-115) times higher than the WHO guidelines for daily mean concentrations, and the daily mean coarse PM concentration reaching 4.4 mg m(-3). Such high PM2.5 and concentrations pose a significant risk to public health. These findings call for the formulation of various policies and action plans, including controlling the land degradation and desertification and reducing the concentrations of PM and other air pollutants in the region. (C) 2020 Elsevier Ltd. All rights reserved.

In Arctic soils, warming accelerates decomposition of organic matter and increases emission of greenhouse gases (GHGs), contributing to a positive feedback to climate change. Although microorganisms play a key role in the processes between decomposition of organic matter and GHGs emission, the effects of warming on temporal responses of microbial activity are still elusive. In this study, treatments of warming and precipitation were conducted from 2012 to 2018 in Cambridge Bay, Canada. Soils of organic and mineral layers were collected monthly from June to September in 2018 and analyzed for extracellular enzyme activities and bacterial community structures. The activity of hydrolases was the highest in June and decreased thereafter over summer in both organic and mineral layers. Bacterial community structures changed gradually over summer, and the responses were distinct depending on soil layers and environmental factors; water content and soil temperature affected the shift of bacterial community structures in both layers, whereas bacterial abundance, dissolved organic carbon, and inorganic nitrogen did so in the organic layer only. The activity of hydrolases and bacterial community structures did not differ significantly among treatments but among months. Our results demonstrate that temporal variations may control extracellular enzyme activities and microbial community structure rather than the small effect of warming over a long period in high Arctic soil. Although the effects of the treatments on microbial activity were minor, our study provides insight that microbial activity may increase due to an increase in carbon availability, if the growing season is prolonged in the Arctic.

Precipitation and snow/ice melt water are the primary water sources in inland river basins in arid areas, and these are sensitive to global climate change. A dataset of snow cover in the upstream region of the Shule River catchment was established using MOD10A2 data from 2000 to 2019, and the spatiotemporal variations in the snow cover and its meteorological, runoff, and topographic impacts were analyzed. The results show that the spatial distribution of the snow cover is highly uneven owing to altitude differences. The snow cover in spring and autumn is mainly concentrated along the edges of the region, whereas that in winter and summer is mainly distributed in the south. Notable differences in snow accumulation and melting are observed at different altitudes, and the annual variation in the snow cover extent shows bimodal characteristics. The correlation between the snow cover extent and runoff is most significant in April. The snow cover effectively replenishes the runoff at higher altitudes (3300-4900 m), but this contribution weakens with increasing altitude (>4900 m). The regions with a high snow cover frequency are mostly concentrated at high altitudes. Regions with slopes of 45 degrees. The snow cover frequency and slope aspect show symmetrical changes.

Knowledge of the spatiotemporal dynamics of the soil temperature in cold environment is key to understanding the effects of climate change on land-atmosphere feedback and ecosystem functions. Here, we quantify the recent thermal status and trends in shallow ground using the most up-to-date data set of over 457 sites in Russia. The data set consists of in situ soil temperatures at multiple depths (0.8, 1.6, and 3.2 m) collected from 1975 to 2016. For the region as a whole, significant soil warming occurred over the period. The mean annual soil temperature at depths of 0.8, 1.6, and 3.2 m increased at the same level, at ca 0.30-0.31 degrees C/decade, whereas the increase in maximum soil temperature ranged from 0.40 degrees C/decade at 0.8 m to 0.31 degrees C/decade at 3.2 m. Unlike the maximum soil temperature, the increases in minimum soil temperature did not vary (ca 0.25 degrees C/decade) with depth. Due to the overall greater increase in maximum soil temperature than minimum soil temperature, the intra-annual variability of soil temperature increased over the decades. Moreover, the soil temperature increased faster in the continuous permafrost area than in the discontinuous permafrost and seasonal frost areas at shallow depths (0.8 and 1.6 m depth), and increased slower at the deeper level (3.2 m). The warming rate of the maximum soil temperature at the shallower depths was less than that at the deeper level over the discontinuous permafrost area but greater over the seasonal frost area. However, the opposite was found regarding the increase in minimum soil temperature. Correlative analyses suggest that the trends in mean and extreme soil temperatures positively relate to the trends in snow cover thickness and duration, which results in the muted response of intra-annual variability of the soil temperature as snow cover changes. This study provides a comprehensive view of the decadal evolutions of the shallow soil temperatures over Russia, revealing that the temporal trends in annual mean and extreme soil temperatures vary with depth and permafrost distribution.

To better understand the ecological and hydrological responses to climatic and cryospheric changes, the spatiotemporal variations in the active layer thickness (ALT) need to be scrupulously studied. Based on more than 230 sites from the circumpolar active layer monitoring network, the spatiotemporal characteristics of the ALT across the northern hemisphere during 1990-2015 were investigated. Results indicate that the ALT exhibits substantial spatial variations across the northern hemisphere, ranging from approximately 30 cm in the arctic and subarctic regions to greater than 10 m in the mountainous permafrost regions at mid-latitudes. Regional averages of ALT are 48 cm in Alaska, 93 cm in Canada, 164 cm in the Nordic countries (including Greenland and Svalbard) and Switzerland, 330 cm in Mongolia, 476 cm in Kazakhstan, and 230 cm on the Qinghai-Tibetan Plateau (QTP), respectively. In Russia, the regional averages of ALT in European North, West Siberia, Central Siberia, Northeast Siberia, Chukotka, and Kamchatka are 110, 92, 69, 61, 53 and 60 cm, respectively. Increasing trends of ALT were not uniformly present in the observational records. Significant changes in the ALT were observed at 73 sites, approximately 43.2 % of the investigated 169 sites that are available for statistical analysis. Less than 25 % Alaskan sites and approximately 33 % Canadian sites showed significant increase in the ALT. On the QTP, almost all the sites showed significant ALT increases. Insignificant increase and even decrease in the ALT were observed in some parts of the northern hemisphere, e.g., Mongolia, parts of Alaska and Canada. The air and ground temperatures, vegetation, substrate, microreliefs, and soil moisture in particular, play decisive roles in the spatiotemporal variations in the ALT, but the relationships among each other are complicated and await further studies.

Observations on black carbon (BC) aerosols over an urban site (Pune) and a rural, high altitude site (Sinhagad) during summer and winter seasons over the period of 2009-2013 are reported. Apart from the temporal variation of BC over both the sites, its mass fraction to total suspended particulates (TSP) is studied. Finally, using the chemical composition of TSP and BC in the OPAC model, season-wise optical properties of aerosols are obtained which are further used in the SBDART model to derive the aerosol radiative forcing (ARF) at surface and top of the atmosphere and thereby the atmospheric forcing and heating rates in each season over both the sites. BC mass concentration and its mass fraction to TSP (Mf BC) were higher at Pune than at Sinhagad, indicating impact of more anthropogenic sources. At both the sites winter season witnessed higher BC concentrations than summer as well as higher Mf BC which is due to the prevailing favorable meteorological conditions in winter. Diurnal variation of BC showed different patterns at Pune and Sinhagad in terms of strength and occurrence of high and low values that could be attributed to varying local boundary layer conditions and source activities at both the sites. Negative ARF indicated cooling at top of the atmosphere and at surface leading to warming of the atmosphere at both the sites. However, surface cooling and atmospheric warming was more dominant at Pune leading to higher atmospheric heating rates, underlining the impact of absorbing BC aerosols which were about three times more at Pune than Sinhagad. (C) 2015 Elsevier Ltd. All rights reserved.

The warming of Arctic region has recently gained worldwide attention due to its projected impacts on global climate system. The effect of anthropogenic black carbon (BC) aerosol on snow is of enduring interest due to its role in aerosol radiative forcing and further consequences for Arctic and global climate change. Using an A ethalometer, measurements of BC aerosols were continuously carried out over the Indian Arctic Station, Himadri during the Arctic Summer (23 July to 19 August) of 2012. Monthly mean BC mass concentration during July and August was found to be 0.093 +/- 0.046 and 0.069 +/- 0.050 mu g/m(3), respectively. BC mass concentration showed maximum loading during 0800-1600 LT. Transport from distant sources (as observed from air mass back trajectories) apart from some local anthropogenic activities (emissions from shipping and power plant) could be the possible sources for observed BC concentration at Himadri. Using the OPAC and SBDART models, optical properties and aerosol radiative forcing (ARF) in the spectral range 0.2 to 4 mu m for composite aerosol and without-BC aerosol at the top of the atmosphere, surface and atmosphere were computed. The presence of BC resulted in positive radiative forcing in the atmosphere leading to warming effect (+2.1 W/m(2)) whereas cooling was observed at the top of the atmosphere (-0.4 W/m(2)) and at surface (-2.5 W/m(2)). BC formed about 57% of atmospheric ARF. (C) 2015 Elsevier B.V. All rights reserved.