Glacial changes are crucial to regional water resources and ecosystems in the Sawir Mountains. However, glacial changes, including the mass balance and glacial meltwater of the Sawir Mountains, have sparsely been reported. Three model calibration strategies were constructed including a regression model based on albedo and in-situ mass balance of Muz Taw Glacier (A-Ms), regression model based on albedo and geodetic mass balance of valley, cirque, and hanging glaciers (A-Mr), and degree-day model (DDM) to obtain a reliable glacier mass balance in the Sawir Mountains and provide the latest understanding in the contribution of glacial meltwater runoff to regional water resources. The results indicated that the glacial albedo reduction was significant from 2000 to 2020 for the entire Sawir Mountains, with a rate of 0.015 (10a)- 1, and the spatial pattern was higher in the east compared to the west. Second, the three strategies all indicated that the glacier mass balance has been continuously negative during the past 20 periods, and the average annual glacier mass balance was -1.01 m w.e. Third, the average annual glacial meltwater runoff in the Sawir Mountains from 2000 to 2020 was 22 x 106 m3, and its

A comprehensive global investigation on the impact of reduction (changes) in aerosol emissions due to Coronavirus disease-2019 (COVID-19) lockdowns on aerosol single scattering albedo (SSA) utilizing satellite observations and model simulations is conducted for the first time. The absolute change in Ozone Monitoring Instrument (OMI) retrieved, and two highly-spatially resolved models (Modern-Era Retrospective Analysis for Research and Applications-2 (MERRA-2) and Copernicus Atmosphere Monitoring Service (CAMS)) simulated SSA is <4% (<0.04-0.05) globally during COVID (2020) compared to normal (2015-2019) period. Change in SSA during COVID is not significantly different from long-term and year-to-year variability in SSA. A small change in SSA indicates that significant reduction in anthropogenic aerosol emissions during COVID-19 induced lockdowns has a negligible effect in changing the net contribution of aerosol scattering and/or absorption to total aerosol extinction. The changes in species-wise aerosol optical depth (AOD) are examined in detail to explain the observed changes in SSA. Model simulations show that total AOD decreased during COVID-19 lockdowns, consistent with satellite observations. The respective contributions of sulfate and black carbon (BC) to total AOD increased, which resulted in a negligible change in SSA during the spring and summer seasons of COVID over South Asia. Europe and North America experience a small increase in SSA (<2%) during the summer season of COVID due to a decrease in BC contribution. The change in SSA (2%) is the same for a small change in BC AOD contribution (3%), and for a significant change in sulfate AOD contribution (20%) to total AOD. Since, BC SSA is 5-times lower (higher absorption) than that of sulfate SSA, the change in SSA remains the same. For a significant change in SSA to occur, the BC AOD contribution needs to be changed significantly (4-5 times) compared to other aerosol species. A sensitivity analysis reveals that change in aerosol radiative forcing during COVID is primarily dependent on change in AOD rather than SSA. These quantitative findings can be useful to devise more suitable future global and regional mitigation strategies aimed at regulating aerosol emissions to reduce environmental impacts, air pollution, and public health risks.

The light absorption enhancement (E-abs) of black carbon (BC) coated with non-BC materials is crucial in the assessment of radiative forcing, yet its evolution during photochemical aging of plumes from biomass burning, the globe's largest source of BC, remains poorly understood. In this study, plumes from open burning of corn straw were introduced into a smog chamber to explore the evolution of E-abs during photochemical aging. The light absorption of BC was measured with and without coating materials by using a thermodenuder, while the size distributions of aerosols and composition of BC coating materials were also monitored. E-abs was found to increase initially, and then decrease with an overall downward trend. The lensing effect dominated in E-abs at 520 nm, with an estimated contribution percentages of 47.5%-94.5%, which is far greater than light absorption of coated brown carbon (BrC). The effects of thickening and chemical composition changes of the coating materials on E-abs were evaluated through comparing measured E-abs with that calculated by the Mie theory. After OH exposure of 1 x 10(10) molecules cm(-3) s, the thickening of coating materials led to an E-abs increase by 3.2% +/- 1.6%, while the chemical composition changes or photobleaching induced an E-abs decrease by 4.7% +/- 0.6%. Simple forcing estimates indicate that coated BC aerosols exhibit warming effects that were reduced after aging. The oxidation of light-absorbing CxHy compounds, such as polycyclic aromatic hydrocarbons (PAHs), to CxHyO and CxHyO>1 compounds in coating materials may be responsible for the photobleaching of coated BrC. Plain Language Summary Understanding how black carbon (BC) coated with non-BC materials affects light absorption is crucial for assessing its impact on the Earth's climate. However, there is limited knowledge about how this process changes when BC, particularly from biomass burning, is exposed to light. Biomass burning is a significant global source of BC. This study investigated the changes in light absorption of BC from burning corn straw as it aged in a controlled environment. We measured the light absorption of BC with and without its coating materials. Our results showed that the main cause of increased light absorption was the lensing effect of the coating materials, which was more significant than the light absorption by the coating materials themselves. We also discovered that as the coating materials thickened, BC absorbed more light. However, changes in the chemical composition of the coating materials led to a decrease in total absorption. These findings suggest that while coated BC initially has a warming effect on the climate, this effect diminished as the BC ages. The decrease is likely due to the breakdown of light-absorbing compounds in the coating materials, such as polycyclic aromatic hydrocarbons (PAHs).

Global warming in tandem with surface albedo reduction caused by black carbon (BC) deposition on glaciers accelerated glacier melting; however, their respective contributions remain unclear. Glaciers in the Qilian Mountains are crucial for the development of oases in the Hexi Corridor; however, their area has decreased by more than 20% over the past half-century. Thus, this study developed a dynamic deposition model for light-absorbing particles (LAPs), coupled with a surface energy and mass balance model. We comprehensively assessed the effects of BC and warming on the melting of a typical glacier in the Qilian Mountains based on the coupled model. BC on the glacier surface caused 13.1% of annual glacier-wide melting, of which directly deposited atmospheric BC reduced the surface albedo by 0.02 and accounted for 9.1% of glacier melting. The air temperature during 2000-2010 has increased by 1.5 degrees C relative to that during the 1950s, accounting for 51.9% of current glacier melting. Meanwhile, BC emission have increased by 4.6 times compared to those of the early Industrial Revolution recorded in an ice core, accounting conservatively for 6.3% of current glacier melting. Mitigating BC emissions has a limited influence on current glacier melting; however, in the long-term, mitigation should exert a noteworthy impact on glacier melting through the self-purification of glaciers.

A critical comprehension of the impact of snow cover on urban bidirectional reflectance is pivotal for precise assessments of energy budgets, radiative forcing, and urban climate change. This study develops a numerical model that employs the Monte Carlo ray-tracing technique and a snow anisotropic reflectance model (ART) to simulate spectral albedo and bidirectional reflectance, accounting for urban structure and snow anisotropy. Validation using three flat surfaces and MODIS data (snow-free, fresh snow, and melting snow scenarios) revealed minimal errors: the maximum domain-averaged BRDF bias was 0.01% for flat surfaces, and the overall model-MODIS deviation was less than 0.05. The model's performance confirmed its accuracy in reproducing the reflectance spectrum. A thorough investigation of key factors affecting bidirectional reflectance in snow-covered urban canyons ensued, with snow coverage found to be the dominant influence. Urban coverage, building height, and soot pollutant concentration significantly impact visible and infrared reflectance, while snow grain size has the greatest effect on shortwave infrared. The bidirectional reflectance at backward scattering angles (0.5-0.6) at 645 nm is lower than forward scattering (around 0.8) in the principal plane as snow grain size increases. These findings contribute to a deeper understanding of snow-covered urban canyons' reflectance characteristics and facilitate the quantification of radiation interactions, cloud-snow discrimination, and satellite-based retrieval of aerosol and snow parameters.

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.

A number of global surface soil moisture (SM) datasets have been retrieved from the L-band frequency Soil Moisture Active Passive (SMAP) and the Soil Moisture and Ocean Salinity (SMOS) missions to study the terrestrial water, energy, and carbon cycles. This paper presents the performance of the recently developed 9 km global SMAP product (hereafter SMAP-INRAE-BORDEAUX, SMAP-IB9). The product retrieves SM from the 9 km SMAP radiometric products using the forward model (L-MEB, L-band Microwave Emission of the Biosphere) of SMOS INRA-CESBIO (SMOS-IC) and SMOS L2 algorithms. We inter-compared SMAP-IB9 with two other products with a similar grid resolution (similar to 10 km): the SMAP Enhanced Level-3 SM dataset (SMAP-E) and the enhanced global dataset for the land component of the fifth generation of European reanalysis (ERA5-Land) with the main objective of assessing the discrepancy in accuracy between remotely sensed and model SM datasets. We found that ERA5-Land and SMAP-IB9 SM had the overall highest correlations (R = 0.62(+/- 0.15) for ERA5-Land vs. 0.60 (+/- 0.17) for SMAP-IB9 and 0.50(+/- 0.15) for SMAP-E) by comparing with the International Soil Moisture Network (ISMN) in-situ measurements from 22 networks. ERA5-Land showed better performances in the forest areas where SMAP-IB9 and SMAP-E still showed high potential in detecting the time variations of the observed SM, particularly in terms of median correlation values (0.62(+/- 0.18) for SMAP-IB9 vs. 0.66(+/- 0.16) for ERA5-and). The discrepancy in R between satellite and model SM products that were reported in some past studies has decreased to statistically insignificant levels over time. For instance, in the non-forest areas, we found that the latest versions of the SMAP SM products (SMAP-E and SMAP-IB9) had relatively comparable performances with ERA5-Land with regard to median ubRMSE (0.07(+/- 0.02) m(3)/m(3) for both SMAP-E and ERA5-Land) and R (0.59 (+/- 0.16) for SMAP-IB9 vs. 0.61(+/- 0.15) for ERA5-Land), respectively.

The Tibetan Plateau (TP) is distributed with large areas of permafrost, which have received increasing attention as the climate warms. Accurately modeling the extent of permafrost and permafrost changes is now an important challenge for climate change research and climate modeling in this region. Uncertainty in land use and land cover (LULC), which is important information characterizing surface conditions, directly affects the accuracy of the simulation of permafrost changes in land surface models. In order to investigate the effect of LULC uncertainty on permafrost simulation, we conducted simulation experiments on the TP using the Community Land Model, version 5 (CLM5) with five high-resolution LULC products in this study. Firstly, we evaluated the simulation results using shallow soil temperature data and deep borehole data at several sites. The results show that the model performs well in simulating shallow soil temperatures and deep soil temperature profiles. The effect of different land use products on the shallow soil temperature and deep soil temperature contours is not obvious due to the small differences in land use products at these sites. Although there is little difference in the simulating results of different land use products when compared to the permafrost distribution map, the differences are noticeable for the simulation of the active layer. Land cover had a greater impact on soil temperature simulations in regions with greater land use inconsistency, such as at the junction of bare soil and grassland in the northwestern part of the TP, as well as in the southeast region with complex topography. The main way in which this effect occurs is that land cover affects the net surface radiation, which in turn causes differences in soil temperature simulations. In addition, we discuss other factors affecting permafrost simulation results and point out that increasing the model plant function types as well as carefully selecting LULC products is one of the most important ways to improve the simulation performance of land-surface models in permafrost regions.

The impact of aerosols, especially the absorbing aerosols, in the Himalayan region is important for climate. We closely examine ground-based high-quality observations of aerosol characteristics including radiative forcing from several locations in the Indo-Gangetic Plain (IGP), the Himalayan foothills and the Tibetan Plateau, relatively poorly studied regions with several sensitive ecosystems of global importance, as well as highly vulnerable large populations. This paper presents a state-of-the-art treatment of the warming that arises from these particles, using a combination of new measurements and modeling techniques. This is a first-time analysis of its kind, including ground-based observations, satellite data, and model simulations, which reveals that the aerosol radiative forcing efficiency (ARFE) in the atmosphere is clearly high over the IGP and the Himalayan foothills (80-135 Wm(-2) per unit aerosol optical depth (AOD)), with values being greater at higher elevations. AOD is >0.30 and single scattering albedo (SSA) is similar to 0.90 throughout the year over this region. The mean ARFE is 2-4 times higher here than over other polluted sites in South and East Asia, owing to higher AOD and aerosol absorption (i.e., lower SSA). Further, the observed annual mean aerosol induced atmospheric heating rates (0.5-0.8 Kelvin/day), which are significantly higher than previously reported values for the region, imply that the aerosols alone could account for >50 % of the total warming (aerosols + greenhouse gases) of the lower atmosphere and surface over this region. We demonstrate that the current state-of-the-art models used in climate assessments significantly underestimate aerosol-induced heating, efficiency and warming over the Hindu Kush - Himalaya - Tibetan Plateau (HKHTP) region, indicating a need for a more realistic representation of aerosol properties, especially of black carbon and other aerosols. The significant, regionally coherent aerosol induced warming that we observe in the high altitudes of the region, is a significant factor contributing to increasingair temperature, observed accelerated retreat of the glaciers, and changes in the hydrological cycle and precipitation patterns over this region. Thus, aerosols are heating up the Himalayan climate, and will remain a key factor driving climate change over the region.

Boreal ecosystems account for 29% of the world's total forested area and contain more carbon than any other terrestrial biome. Over the past 60 years, Alaska has warmed twice as rapidly as the contiguous U.S. and wildfire activity has increased, including the number of fires, area burned, and frequency of large wildfire seasons. These recent and rapid changes in climate and wildfire have implications for future vegetation composition, structure, and biomass in interior Alaska, given that the vegetation is highly dependent on active layer thickness, soil moisture, organic layer depth, and plant-available nutrients. Here we developed a new succession extension (DGS) of the LANDIS-II forest landscape model which integrates a vegetation dynamics model (NECN) with a soil carbon model (DAMM-McNiP), a hydrologic model (SHAW), and a deep soil profile permafrost model (GIPL) in a spatially-explicit framework. DGS Succession uses the algorithms in the NECN Succession extension of LANDIS-II to simulate growth, mortality and reproduction of vegetation but has three major improvements. First, the simple bucket model in NECN was replaced with a physically-based model (SHAW) that simulates energy and water fluxes (e.g. snow depth, evapotranspiration, soil moisture) at multiple levels in the canopy and soil. Second, the active, slow, and passive soil pools in NECN were replaced by seven soil pools that are measurable in the field, with carbon and nitrogen dynamics dictated by DAMM-McNiP. Finally, soil temperature and soil moisture are simulated only at one depth in NECN, but in DGS, soil temperature (and hence permafrost dynamics) are simulated at as many as 50 user-defined depths down to 4 m with SHAW and 75 m with GIPL. During the initial calibration phase, DGS was applied at three inventory sites at the Bonanza Creek Long Term Ecological Research area in Interior Alaska where climate forcings, species biomass, soil temperature, and/or soil moisture were available. For the landscape-scale simulations, DGS was run with the SCRPPLE fire extension of LANDIS-II under two scenarios of climate using a similar to 400,000 ha landscape that included the inventory sites. Across all three sites, DGS generally captured the variation in soil moisture and temperature across depths, seasons, and years reasonably well, though there were some discrepancies at each site. DGS had better agreement with field measurements of soil moisture and temperature than its predecessor NECN which produced unrealistically low soil moisture and unrealistically high seasonal fluctuations in soil temperature. At the landscape scale, ignitions, area burned, and soil temperature increased under climate change, as expected, while soil moisture was relatively unchanged across climate scenarios. Biomass tended to decline under climate change, which differs from other modeling studies in this region but is consistent with the browning trends observed from remote sensing data. Simulating climate, vegetation succession, hydrology, permafrost, carbon and nutrient cycling, and wildfire in an integrated, spatially-explicit framework like LANDIS-II will allow us to disentangle the drivers and ecosystem responses in this rapidly changing ecosystem, as well as other forested systems with complex hydrologic, biochemical, cryospheric, and vegetation feedbacks.