Land surface albedo (LSA) directly affects the radiation balance and the surface heat budget. LSA is a key variable for local and global climate research. The complexity of LSA variations and the driving factors highlight the importance of continuous spatial and temporal monitoring. Snow, vegetation and soil are the main underlying surface factors affecting LSA dynamics. In this study, we combined Global Land Surface Satellite (GLASS) products and ERA5 reanalysis products to analyze the spatiotemporal variation and drivers of annual mean blue-sky albedo for stable land cover types in the middle-high latitudes of the Northern Hemisphere (30~90 degrees N) from 1982 to 2015. Snow cover (SC) exhibited a decreasing trend in 99.59% of all pixels (23.73% significant), with a rate of -0.0813. Soil moisture (SM) exhibited a decreasing trend in 85.66% of all pixels (22.27% significant), with a rate of -0.0002. The leaf area index (LAI) exhibited a greening trend in 74.38% of all pixels (25.23% significant), with a rate of 0.0014. Blue-sky albedo exhibited a decreasing trend in 98.97% of all pixels (65.12% significant), with a rate of -0.0008 (OLS slope). Approximately 98.16% of all pixels (57.01% significant) exhibited a positive correlation between blue-sky albedo and SC. Approximately 47.78% and 67.38% of all pixels (17.13% and 25.3% significant, respectively) exhibited a negative correlation between blue-sky albedo and SM and LAI, respectively. Approximately 10.31%, 20.81% and 68.88% of the pixel blue-sky albedo reduction was mainly controlled by SC, SM and LAI, respectively. The decrease in blue-sky albedo north of 40 degrees N was mainly caused by the decrease in SC. The decrease in blue-sky albedo south of 40 degrees N was mainly caused by SM reduction and vegetation greening. The decrease in blue-sky albedo in the western Tibetan Plateau was caused by vegetation greening, SM increase and SC reduction. The results have important scientific significance for the study of surface processes and global climate change.

Land surface albedo plays a crucial role in the land surface energy budget and climate. This paper identified the spatiotemporal variations of surface albedo on the Tibetan Plateau (TP) from 1982 to 2015, and quantified the relationships between the spatial and temporal patterns of the albedo and associated influencing factors (snow cover, vegetation, and soil moisture) on the seasonal and interannual basis using satellite products and reanalysis data. It was determined that the albedo presented a distinct spatial variability, with high values in mountainous areas and low values on the southeastern TP. Spatially, average albedo exhibited a positive correlation with snow cover and negative correlations with vegetation and soil moisture. Average albedo over the whole TP had a clear seasonal cycle with a peak in winter and a minimum value in summer, which is dictated by seasonal changes in snow and vegetation covers. Annual average albedo exhibited a weakly downward trend, which was mainly contributed by a significant decrease in summer, pointing to the important role in vegetation dynamics for temporal change of the albedo. On the regional basis, interannual variation of albedo was more responsive to snow cover over the snow-and vegetation-coexisting area than the snow-covered area, and to changes in Normalized Difference Vegetation Index (NDVI) over the vegetation-covered area than the snow-and vegetation-coexisting area; albedo had a weakly negative correlation with soil moisture over bare soil. Furthermore, our results indicated that snow cover was the dominant factor for albedo change on mountainous areas, and vegetation change predominated the variation of albedo on the eastern, southern, and northwestern TP. Specifically, variations in snow cover contributed more than those of vegetation to the interannual albedo variation over the Three Rivers Headwater Region. These results would be beneficial for better understanding the climate and eco-environment changes over the TP. (c) 2021 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http:// creativecommons.org/licenses/by/4.0/).

Linking snow cover frequency (SCF) and atmospheric circulation is vital for comprehension of hemispheric-scale change mechanisms and for accurate forecasting. This study combined MODIS imagery with meteorological observations to investigate the variation of annual SCFs in the Qilian Mountains. Results indicated that more than 80% of annual SCF is distributed at high elevations and mostly on northern slopes, and that SCF is greater in the west than in the east. Abrupt change in the increase in annual SCF was not detected; however, significant (0.05 confidence level) variation with quasi-3-year and quasi-5-year periods indicated potential connection with monsoons. Topographically, SCF increased at high elevations and decreased in valleys. Moreover, SCF increased significantly with a rise in slope below 23 degrees and then decreased between 23 degrees and 45 degrees, and it decreased with a change in aspect from 70 degrees to 200 degrees and then increased from 200 degrees to 310 degrees. Annual SCF variation in the Qilian Mountains is dominated by precipitation rather than by temperature. In the years with high SCFs, southeasterly winds associated with an anticyclone over southeastern China and southwesterly winds associated with the cyclone over the Iranian Plateau brought warm moisture across northwestern China, favoring snowfall in the Qilian Mountains. Meanwhile, cold moisture outbreaks from the Arctic into the mid-latitudes are conducive to maintaining snow cover. However, in the years with low SCFs, the cold air might be difficultly transporting out of the Arctic region due to the strengthening polar vortex. Moreover, the water vapor was less than that of the mean state and divergence over the Qilian Mountains, which difficultly conduced snowfall over the Qilian Mountains.

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.

Melt-albedo feedback on glaciers is recognized as important processes for understanding glacier behavior and its sensitivity to climate change. This study selected the Muz Taw Glacier in the Altai Mountains to investigate the spatiotemporal variations in albedo and their linkages with mass balance, which will improve our knowledge of the recent acceleration of regional glacier shrinkage. Based on the Landsat-derived albedo, the spatial distribution of ablation-period albedo was characterized by a general increase with elevation, and significant east-west differences at the same elevation. The gap-filling MODIS values captured a nonsignificant negative trend of mean ablation-period albedo since 2000, with a total decrease of approximately 4.2%. From May to September, glacier-wide albedo exhibited pronounced V-shaped seasonal variability. A significant decrease in annual minimum albedo was found from 2000 to 2021, with the rate of approximately -0.30% yr(-1) at the 99% confidence level. The bivariate relationship demonstrated that the change of ablation-period albedo explained 82% of the annual mass-balance variability. We applied the albedo method to estimate annual mass balance over the period 2000-2015. Combined with observed values, the average mass balance was -0.82 +/- 0.32 m w.e. yr(-1) between 2000 and 2020, with accelerated mass loss.

Quantitative understanding of controls on thaw layer thickness (TLT) dynamics in the Arctic peninsula is essential for predictive understanding of permafrost degradation feedbacks to global warming and hydro biochemical processes. This study jointly interprets electrical resistivity tomography (ERT) measurements and hydro-thermal numerical simulation results to assess spatiotemporal variations of TLT and to determine its controlling factors in Barrow, Alaska. Time-lapse ERT measurements along a 35-m transect were autonomously collected from 2013 to 2015 and inverted to obtain soil electrical resistivity. Based on several probe-based UT measurements and co-located soil electrical resistivity, we estimated the electrical resistivity thresholds associated with the boundary between the thaw layer and permafrost using a grid search optimization algorithm. Then, we used the obtained thresholds to derive the UT from all soil electrical resistivity images. The spatiotemporal analysis of the ERT-derived TLT shows that the TLT at high-centered polygons (HCPs) is smaller than that at low-centered polygons (LCPs), and that both thawing and freezing occur earlier at the HCPs compared to the LCPs. In order to provide a physical explanation for dynamics in the thaw layer, we performed 1-D hydro thermal simulations using the community land model (CLM). Simulation results showed that air temperature and precipitation jointly govern the temporal variations of UT, while the topsoil organic content (SOC) and polygon morphology are responsible for its spatial variations. When the topsoil SOC and its thickness increase, TLT decreases. Meanwhile, at LCPs, a thicker snow layer and saturated soil contribute to a thicker TLT and extend the time needed for TLT to freeze and thaw. This research highlights the importance of combination of measurements and numerical modeling to improve our understanding spatiotemporal variations and key controls of TLT in cold regions.

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.