In recent years, increasing wildfire activity in the western United States has led to significant emissions of smoke aerosols, impacting the atmospheric energy balance through their absorption and scattering properties. Single scattering albedo (SSA) is a key parameter that governs these radiative effects, but accurately retrieving SSA from satellites remains challenging due to limitations in sensor resolution, low sensitivity of traditional remote sensing methods, and uncertainties in radiative transfer modeling, particularly from surface reflectance and aerosol characterization. Smoke optical properties evolve rapidly after emission, influenced by fuel type, combustion conditions, and chemical aging. Accurate SSA retrieval near the source thus requires high-temporal-resolution satellite observations. Critical Reflectance (CR) method provides this capability by identifying a unique reflectance value at which top-of-atmosphere (TOA) reflectance becomes insensitive to aerosol loading and primarily reflects aerosol absorption. SSA can be retrieved from this critical reflectance. This study presents a geostationary-based CR method using the Advanced Baseline Imager (ABI) on GOES-R satellites. The approach leverages ABI's high temporal (5-10 min) and spatial (3 km) resolution, consistent viewing geometry, and wide coverage. A tailored look-up table, based on an AOD-dependent smoke model for North America, links CR to SSA. Case studies show strong agreement with AERONET measurements, with retrieval differences mostly within 0.01-well below AERONET's +/- 0.03 uncertainty. The method captures temporal and spatial variations in smoke absorption and demonstrates robustness across daylight hours. This GEO-based CR approach offers an effective tool for high-resolution SSA retrieval, contributing to improved aerosol radiative forcing estimates and climate modeling.

Light-absorbing impurities (LAIs), such as mineral dust (MD), organic carbon (OC), and black carbon (BC), deposited in snow, can reduce snow albedo and accelerate snowmelt. The Ili Basin, influenced by its unique geography and westerly atmospheric circulation, is a critical region for LAI deposition. However, quantitative assessments on the impact of LAIs on snow in this region remain limited. This study investigated the spatial distribution of LAIs in snow and provided a quantitative evaluation of the effects of MD and BC on snow albedo, radiative forcing, and snowmelt duration through sampling analysis and model simulations. The results revealed that the Kunes River Basin in the eastern Ili Basin exhibited relatively high concentrations of MD. In contrast, the southwestern Tekes River Basin showed relatively high concentrations of OC and BC. Among the impurities, MD plays a dominant role in the reduction of snow albedo and has a greater effect on the absorption of solar radiation by snow than BC, while MD is the most important light-absorbing impurity responsible for the reduction in the number of snow-melting days in the Ili Basin. Under the combined influence of MD and BC, the snowmelt period in the Ili Basin was reduced by 2.19 +/- 1.43 to 7.31 +/- 4.76 days. This study provides an initial understanding of the characteristics of LAIs in snow and their effects on snowmelt within the Ili Basin, offering essential basic data for future research on the influence of LAIs on snowmelt runoff and hydrological processes in this region.

Black carbon (BC) affects the Arctic climate via aerosol-radiation-cloud interaction and snow/ice albedo feedback. Fires have become a substantial source of the Arctic BC in recent years, while the radiative effects of BC in the Arctic due to the recent extreme fires remain unclear. In this study, the atmospheric and snow radiative forcing of BC in the Arctic due to the extreme fires in summer 2019 were investigated based on numerical simulations, and the effects on meteorological variables and snow albedo were explored. Biomass burning BC in summer 2019 caused negative radiative forcing at the bottom of the atmosphere in Greenland and the central Arctic Ocean, and it caused positive radiative forcing in Europe, central Siberia, and northern Canada, with values that can reach 9 W/m2 and 18 W/m2, respectively. The radiative forcing was spatially heterogeneous, which was mainly induced by the dominant role of semi-direct and indirect radiative effects of BC related to cloud changes. The air temperature in the higher troposphere increased in the central Arctic Ocean and Greenland, and the near-surface air temperature increased in Europe, central Siberia, and northern Canada. The responses of wind field and relative humidity were mainly linked with the air temperature changes, and the cyclone activity anomaly can be observed in the central Arctic. Biomass burning BC caused positive snow radiative forcing in Greenland of 0.4-1.4 W/m2, and the maximum snow albedo reduction was about 0.005. Overall, this study highlights the importance of BC from fires on the Arctic climate.

Objective Xinjiang, recognized as a crucial coal resource area and strategic reserve in China, possesses abundant coal resources. The Zhundong coalfield, a large-scale open-pit mining area within this region, significantly contributes to increased concentrations of light-absorbing aerosols due to its coal production activities and associated industrial processes. These activities also produce substantial amounts of black carbon (BC), which, through atmospheric transport, mixes with snow and ice, influencing glacier ablation in the Tianshan Mountains. While previous studies on the Zhundong coalfield have predominantly concentrated on the ecological pollution resulting from mining activities, they have overlooked the implications for climate and radiative forcing in the area. In this context, it is crucial to employ satellite remote sensing technology to analyze and assess the optical properties and radiative forcing effects of light-absorbing aerosols in the Zhundong coalfield region. Such an approach is significant for understanding the regional environmental and climatic impacts associated with the development of open-pit coal resources in the arid regions of western China. Methods We investigate the temporal and spatial characteristics of aerosol optical depth (AOD) in the Zhundong coalfield by utilizing MODIS aerosol product (MOD04_L2) data spanning from 2005 to 2020. To simulate aerosol particle size information, a Mie scattering model is employed under the core-shell assumption. An uncertainty interval of 0.03 is selected to estimate the possible range of particle sizes within each grid, constrained by maximum and minimum values. The inter of these constraints is then used to calculate the optical parameters for various particle size combinations. Additionally, the influence of sand and dust aerosols is considered by setting the single scattering albedo (SSA) range for these aerosols between 0.93 and 0.96. The simulated extinction coefficient (sigma(ext)) is used as a threshold value; any portion smaller than this threshold is excluded to quantify the concentration of local BC columns. Finally, the radiative forcing effect of light-absorbing aerosols in the Zhundong coalfield over the past decade is evaluated using the SBDART radiative transfer model. Results and Discussions The AOD in the Zhundong coalfield exhibited pronounced spatial heterogeneity from 2005 to 2020, with high AOD values predominantly concentrated in the mining area and its surrounding regions (Fig. 2). Seasonal variations reveal the highest concentrations in spring and winter, followed by fall, with the lowest levels observed in summer. During spring and winter, AOD values generally exceed 0.15, except in certain desert areas. Interannual fluctuations in AOD are frequent, marked by significant turning points in 2010, 2012, and 2017 (Fig. 3), which indicates that coal production, energy restructuring, and capacity reduction policies have a significant effect on air quality in mining regions. The inter-monthly variation displays a distinct U pattern (Fig. 3), with AOD peaking at 0.27 in February, which highlights the substantial influence of anthropogenic activities on regional air quality. Dusty weather in spring emerges as a dominant factor. Overall, the temporal variation in AOD in the Zhundong coalfield reflects the combined effects of natural factors and human activities. In the Wucaiwan and Dajing mining areas, the range of BC number density is (1?3)x10(18) grid(-1) (Fig. 6). In 2012, against the backdrop of China's coal economic performance, open-pit mining was less affected by the decline in production growth due to its larger production capacity and lower costs, influenced by mining methods, climatic conditions, and economic activities. In contrast, shaft mining is more heavily affected by safety risks and environmental constraints, which may lead to production limitations, especially under strengthened policy and regulatory measures. As a result, there are greater fluctuations in BC number density in the Dajing mining area (Fig. 6). The range of BC number density is 20?40 kg/grid, with seasonal variations largely consistent, although peak months differed. This suggests that BC mass concentration is closely related to particle aging and size (Fig. 7). Radiative forcing values at the top of the atmosphere, at the surface, and within the atmosphere showed varying degrees of decrease between 2011 and 2017, followed by a gradual increase. This suggests that reducing emissions of light-absorbing aerosols from mining sites can effectively lower regional radiative forcing values in the context of reduced coal production (Fig. 10). Radiative forcing values are higher in March and April during spring, when BC is aged and mixed with other aerosol components through mutual encapsulation, which results in more complex microphysical-chemical properties. This process enhances the absorption capacity of BC for both short- and long-wave radiations (Fig. 10). Conclusions We analyze the overall change in AOD in the Zhundong coalfield from 2005 to 2020 using the MODIS aerosol dataset. By integrating a meter scattering model to simulate optical parameters under various particle size combinations and constraining these simulations with single scattering albedo (SSA) observations from MODIS, this approach allows us to determine the eligible particle size information and optical parameters, enabling the calculation of BC mass concentration within the atmospheric column of the Zhundong coalfield. Subsequently, the area's radiative forcing is estimated using the SBDART radiative transfer model. The findings reveal several key insights. 1) The changes in AOD are closely linked to policy implementation and economic activities within the coal mining area. Interannual variations indicate that AOD peaked in 2012 and subsequently declined, which suggests that policies and economic activities significantly affect AOD levels. Seasonally, AOD is higher in spring and winter and lower in summer. The unique topographic and meteorological conditions facilitate the transport of BC from the mining area to other regions, which highlights the combined effects of seasonal meteorological conditions and human activities. 2) The column concentration of light-absorbing aerosols in the coal mine area is affected by both anthropogenic activities and meteorological conditions, particularly during sandy and dusty weather. A comparison of column concentrations between the Wucaiwan and Dajing mines shows that open-pit mining adapts more effectively in 2012, given the context of China's coal economic operations, whereas shaft mining may face greater challenges. 3) By examining the changes in AOD and light-absorbing aerosols, it is evident that reducing emissions of light-absorbing aerosols from coal mining areas can effectively decrease regional radiative forcing values in the short term. Inter-monthly variations reveal that atmospheric radiative forcing trends differ from those at the surface and the top of the atmosphere, with the latter two being closely related to the optical properties of light-absorbing aerosols. In spring, the frequent occurrence of sand and dust facilitates the mixing of BC with other substances, forming light-absorbing aerosols with a core-shell structure. This significantly enhances the light-absorbing capacity of BC, thereby increasing radiative forcing.

The Tibetan Plateau (TP) has experienced accelerated warming in recent decades, especially in winter. However, a comprehensive quantitative study of its long-term warming processes during daytime and nighttime is lacking. This study quantifies the different processes driving the acceleration of winter daytime and nighttime warming over the TP during 1961-2022 using surface energy budget analysis. The results show that the surface warming over the TP is mainly controlled by two processes: (a) a decrease in snow cover leading to a decrease in albedo and an increase in net downward shortwave radiation (snow-albedo feedback), and (b) a warming in tropospheric temperature (850 - 200 hPa) leading to an increase in downward longwave radiation (air warming-longwave radiation effect). The latter has a greater impact on the spatial distribution of warming than the former, and both factors jointly influence the elevation dependent warming pattern. Snow-albedo feedback is the primary factor in daytime warming over the monsoon region, contributing to about 59% of the simulated warming trend. In contrast, nighttime warming over the monsoon region and daytime/nighttime warming in the westerly region are primarily caused by the air warming-longwave radiation effect, contributing up to 67% of the simulated warming trend. The trend in the near-surface temperature mirrors that of the surface temperature, and the same process can explain changes in both. However, there are some differences: an increase in sensible heat flux is driven by a rise in the ground-atmosphere temperature difference. The increase in latent heat flux is associated with enhanced evaporation due to increased soil temperature and is also controlled by soil moisture. Both of these processes regulate the temperature difference between ground and near-surface atmosphere.

This study shows the impact of black carbon (BC) aerosol atmospheric rivers (AAR) on the Antarctic Sea ice retreat. We detect that a higher number of BC AARs arrived in the Antarctic region due to increased anthropogenic wildfire activities in 2019 in the Amazon compared to 2018. Our analyses suggest that the BC AARs led to a reduction in the sea ice albedo, increased the amount of sunlight absorbed at the surface, and a significant reduction of sea ice over the Weddell, Ross Sea (Ross), and Indian Ocean (IO) regions in 2019. The Weddell region experienced the largest amount of sea ice retreat (similar to 33,000 km(2)) during the presence of BC AARs as compared to similar to 13,000 km(2) during non-BC days. We used a suite of data science techniques, including random forest, elastic net regression, matrix profile, canonical correlations, and causal discovery analyses, to discover the effects and validate them. Random forest, elastic net regression, and causal discovery analyses show that the shortwave upward radiative flux or the reflected sunlight, temperature, and longwave upward energy from the earth are the most important features that affect sea ice extent. Canonical correlation analysis confirms that aerosol optical depth is negatively correlated with albedo, positively correlated with shortwave energy absorbed at the surface, and negatively correlated with Sea Ice Extent. The relationship is stronger in 2019 than in 2018. This study also employs the matrix profile and convolution operation of the Convolution Neural Network (CNN) to detect anomalous events in sea ice loss. These methods show that a higher amount of anomalous melting events were detected over the Weddell and Ross regions. Impact Statement Sea ice protects ice sheets, which are melting at a very high rate to raise the sea level. In addition to global warming, this study is indicative that black carbon aerosols transported from anthropogenic wildfire events, such as from the Amazon, darken the snow, reduce their reflectance, increase the absorption of solar energy incident on the surface, and exacerbate the sea ice retreat. Thus, this study points out that anthropogenic wildfire impacts far away from a region can have a severe impact on sea ice and ice sheets over the Antarctic which has a sea level rise potential of 60 m. Our study shows that only over the Weddell region, sea ice retreat was 20,000 km(2) higher during the presence of BC transport events than other days in 2019.

Glacial responses to climate change exhibit considerable heterogeneity. Although global glaciers are generally thinning and retreat, glaciers in the Karakoram region are distinct in their surging or advancing, exhibiting nearly zero or positive mass balance-a phenomenon known as the Karakoram Anomaly. This anomaly has sparked significant scientific interest, prompting extensive research into glacier anomalies. However, the dynamics of the Karakoram anomaly, particularly its evolution and persistence, remain insufficiently explored. In this study, we employed Landsat reflectance data and Moderate Resolution Imaging Spectroradiometer (MODIS) MCD43A3 albedo products to developed high-resolution albedo retrieval models using two machine learning (ML) regressions--random forest regression (RFR) and back-propagation neural network regression (BPNNR). The optimal BPNNR model (Pearson correlation coefficient [r] = 0.77-0.97, unbiased root mean squared error [ubRMSE] = 0.056-0.077, RMSE = 0.055-0.168, Bias = -0.149 similar to -0.001) was implemented on the Google Earth Engine cloud-based platform to estimate summer albedo at a 30-m resolution for the Karakoram region from 1990 to 2021. Validation against in-situ albedo measurements on three glaciers (Batura, Mulungutti and Yala Glacier) demonstrated that the model achieved an average ubRMSE of 0.069 (p < 0.001), with RMSE and ubRMSE improvements of 0.027 compared to MODIS albedo products. The high-resolution data was then used to identify firn/snow extents using a 0.37 threshold, facilitating the extraction of long-term firn-line altitudes (FLA) to indicate the glacier dynamics. Our findings revealed that a consistent decline in summer albedo across the Karakoram over the past three decades, signifying a darkening of glacier surfaces that increased solar radiation absorption and intensified melting. The reduction in albedo showed spatial heterogeneity, with slower reductions in the western and central Karakoram (-0.0005-0.0005 yr(-1)) compared to the eastern Karakoram (-0.006 similar to -0.01 yr(-1)). Notably, surge- or advance-type glaciers, avalanche-fed glaciers and debris-covered glaciers exhibited slower albedo reduction rates, which decreased further with increasing glacier size. Additionally, albedo reduction accelerated with altitude, peaking near the equilibrium-line altitude. Fluctuations in the albedo-derived FLAs suggest a transition in the dynamics of Karakoram glaciers from anomalous behavior to retreat. Most glaciers exhibited anomalous behavior from 1995 to 2010, peaking in 2003, but they have shown signs of retreat since the 2010s, marking the end of the Karakoram anomaly. These insights deepen our understanding of the Karakoram anomaly and provide a theoretical basis for assessing the effect of glacier anomaly to retreat dynamics on the water resources and adaptation strategies for the Indus and Tarim Rivers.

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.

Tibetan Plateau (TP) is known as the Third Pole of the Earth. Any changes in land surface processes on the TP can have an unneglectable impact on regional and global climate. With the warming and wetting climate, the land surface of the TP saw a darkening trend featured by decreasing surface albedo over the past decades, primarily due to the melting of glaciers, snow, and greening vegetation. Recent studies have investigated the effects of the TP land surface darkening on the field of climate, but these assessments only address one aspect of the feedback loop. How do these darkening-induced climate changes affect the frozen ground and ecosystems on the TP? In this study, we investigated the impact of TP land surface darkening on regional frozen ground and ecosystems using the state-of-the-art land surface model ORCHIDEE-MICT. Our model results show that darkening-induced climate changes on the TP will lead to a reduction in the area of regional frozen ground by 1.1x104 +/- 0.019x104 km2, a deepening of the regional permafrost active layer by 0.06 +/- 0.0004 m, and a decrease in the maximum freezing depth of regional seasonal frozen ground by 0.06 +/- 0.0016 m compared to the scenario without TP land surface darkening. Furthermore, the darkening-induced climate change on the TP will result in an increase in the regional leaf area index and an enhancement in the regional gross primary productivity, ultimately leading to an increase in regional terrestrial carbon stock by 0.81 +/- 0.001 PgC. This study addresses the remaining piece of the puzzle in the feedback loop of TP land surface darkening, and improves our understanding of interactions across multiple spheres on the TP. The exacerbated regional permafrost degradation and increasing regional terrestrial carbon stock induced by TP land surface darkening should be considered in the development of national ecological security barrier.

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