Brown carbon (BrC) is the ubiquitous part of the atmospheric organic carbon. It absorbs solar lights and greatly impacts the Earth's radiative balance. This study examines the spectral characteristics of BrC and its radiative effect in the Dhaka South (DS) site and Dhaka North (DN) site from July 2023 to January 2024 with a high-volume particulate matter sampler on quartz filters. Spectral characteristics such as absorption coefficient (babe,), mass absorption efficiency (MAE), absorption angstrom exponent (AAE), and refractive index (Kabs-x) were determined by using a UV -visible spectrophotometer, and fluorescence emission spectra were analyzed in different pH by the fluorescent spectrophotometer. The concentrations of BrC and black carbon (BC) were determined by an aethalometer. The mean concentrations of BrC and BC in Dhaka city were 18.63 +/- 3.84 mu g 111-3 and 17.93 +/- 3.82 pg M-3, respectively. The AAE values lie in the range of 3.20-4.01 (DN) and 3.27-4.53 (DS), and the radiative forcing efficiency of BrC was obtained at 4.43 +/- 1.02 W g-1 in DN and 3.93 +/- 0.74 W g-1 in DS, indicating the presence of highly light-absorbing BrC in these locations. Average MAE and Kabs_k values were 1.55 +/- 0.45 m2g1 and 0.044 + 0.013, respectively, in DS, alternatively 1.84 +/- 0.59 m2g1 and 0.052 +/- 0.016 in DN. The fluorescence excitation-emission spectra confirmed the presence of a polyconjugate cyclic ring with multifunctional groups in the structure of BrC. Light absorption properties and fluorescence emission spectra were varied with the change of pH. As the pH increased (2-8), the AAE value decreased and MAEB,c_365 increased due to protonation or deprotonation. This study highlights that the BrC has a significant impact on the air quality as well as the Earth's radiative balance, emphasizing its strong light-absorbing properties and variability with environmental factors.

Ongoing climate warming and increased human activities have led to significant permafrost degradation on the Qinghai-Tibet Plateau (QTP). Mapping the distribution of active layer thickness (ALT) can provide essential information for understanding this degradation. Over the past decade, InSAR (Interferometric synthetic aperture radar) technology has been utilized to estimate ALT based on remotely-sensed surface deformation information. However, these methods are generally limited by their ability to accurate extract seasonal deformation and model subsurface water content of active layer. In this paper, an ALT inversion method considering both seasonal deformation from InSAR and smoothly multilayer soil moisture from ERA5 is proposed. Firstly, we introduce a ground seasonal deformation extraction model combining RobustSTL and InSAR, and the deformation extraction accuracy by considering the deformation characteristics of permafrost are evaluated, proving the effectiveness of RobustSTL in extracting seasonal deformation of permafrost. Then, using ERA5 soil moisture products, a smoothed multilayer soil moisture model for ALT inversion is established. Finally, integrating the seasonal deformation and multilayer soil moisture, the ALT can be estimated. The proposed model is applied to the Yellow River source region (YRSR) with Sentinel-1A images acquired from 2017 to 2021, and the ALT retrieval accuracy is validated with measured data. Experimental results show that the vertical deformation rate of the study area generally ranges from -30 mm/year to 20 mm/year, with seasonal deformation amplitude ranging from 2 mm to 30 mm. The RobustSTL method has the highest accuracy in extracting seasonal deformation of permafrost, with an RMSE (root mean square error) of 0.69 mm, and is capable of capturing the freeze-thaw characteristics of the active layer. The estimated ALT of the YRSR ranges from 49 cm to 450 cm, with an average value of 145 cm. Compared to the measured data, the proposed method has an average error of 37.5 cm, which represents a 21 % improvement in accuracy over existing methods.

Multi-source precipitation products (MSPs) are critical for hydrologic modeling, but their spatial and temporal heterogeneity and uncertainty present challenges to simulation accuracy that need to be addressed urgently. This study assessed the impact of different precipitation data sources on hydrologic modeling in an arid basin. There were seven precipitation products and meteorological station interpolated data that were used to drive the hydrological model, and we evaluated their performance by fusing the six precipitation products through the dynamic bayesian averaging algorithm. Ultimately, the runoff simulation uncertainty was quantified based on the DREAM algorithm, and the information transfer entropy was used to quantify the differences in hydrologic simulation processes driven by different precipitation data. The results showed that CMFD and ERA5 weights were higher, and the DBMA fused precipitation annual mean value was about 309.83 mm with good simulation accuracy (RMSE of 1.46 and R-2 of 0.75). The simulation was satisfactory (NSE >0.80) after parameter calibration and data assimilation for all driving data, with CHIRPS and TRMM performed better in the common mode, and HRLT and CMFD performed excellently in the glacier mode. The DREAM algorithm indicated less uncertainty for DBMA, CHIRPS and HRLT data. The entropy of information transfer revealed that precipitation occupied a significant position in information transfer, especially affecting evapotranspiration and surface soil moisture. CMFD and TPS CMADS were highest in snow water equivalent information entropy, and CHIRPS and TPS CMADS were highest in evapotranspiration information entropy. CDR, CHIRPS, ERA5-Land and IDW STATION had the highest snow water equivalent information entropy, DBMA and CMORPH had the highest runoff information entropy, CHIRPS and TRMM had the highest soil moisture information entropy, whereas ERA5, HRLT, and TPS CMADS had the highest evapotranspiration information entropy in glacial mode. This study reveals significant differences between different precipitation data sources in hydrological modeling of arid basin, which is an important reference for future water resources management and climate change adaptation strategies.

Arctic permafrost soils contain a vast reservoir of soil organic carbon (SOC) vulnerable to increasing mobilization and decomposition from polar warming and permafrost thaw. How these SOC stocks are responding to global warming is uncertain, partly due to a lack of information on the distribution and status of SOC over vast Arctic landscapes. Soil moisture and organic matter vary substantially over the short vertical distance of the permafrost active layer. The hydrological properties of this seasonally thawed soil layer provide insights for understanding the dielectric behavior of water inside the soil matrix, which is key for developing more effective physics-based radar remote sensing retrieval algorithms for large-scale mapping of SOC. This study provides a coupled hydrologic-electromagnetic framework to model the frequency-dependent dielectric behavior of active layer organic soil. For the first time, we present joint measurement and modeling of the water matric potential, dielectric permittivity, and basic physical properties of 66 soil samples collected across the Alaskan Arctic tundra. The matric potential measurement allows for estimating the soil water retention curve, which helps determine the relaxation time through the Eyring equation. The estimated relaxation time of water molecules in soil is then used in the Debye model to predict the water dielectric behavior in soil. A multi-phase dielectric mixing model is applied to incorporate the contribution of various soil components. The resulting organic soil dielectric model accepts saturation water fraction, organic matter content, mineral texture, temperature, and microwave frequency as inputs to calculate the effective soil dielectric characteristic. The developed dielectric model was validated against lab-measured dielectric data for all soil samples and exhibited robust accuracy. We further validated the dielectric model against field-measured dielectric profiles acquired from five sites on the Alaskan North Slope. Model behavior was also compared against other existing dielectric models, and an indepth discussion on their validity and limitations in permafrost soils is given. The resulting organic soil dielectric model was then integrated with a multi-layer electromagnetic scattering forward model to simulate radar backscatter under a range of soil profile conditions and model parameters. The results indicate that low frequency (P-,L-band) polarimetric synthetic aperture radars (SARs) have the potential to map water and carbon characteristics in permafrost active layer soils using physics-based radar retrieval algorithms.

The global climate is becoming warmer and wetter, and the physical properties of saline soil are easily affected by the external climate changes, which can lead to complex water-heat-salt-mechanics (WHSM) coupling effect within the soil. However, in the context of climate change, the current research on the surface energy balance process and laws of water and salt migration in saline soil are not well understood. Moreover, testing systems for studying the impact of external meteorological factors on the properties of saline soil are lacking. Therefore, this study developed a testing system that can simulate the environmental coupling effect of the WHSM in saline soil against a background of climate change. Based on meteorological data from the Hexi District in the seasonal permafrost region of China, the testing system was used to clarify the characteristics of surface energy and WHSM coupling changes in sulfate saline soil in Hexi District during the transition of the four seasons throughout the year. In addition, the reliability of the testing system was also verified using testing data. The results showed that the surface albedo of sulfate saline soil in the Hexi region was the highest in winter, with the highest exceeding 0.4. Owing to changes in the external environment, the heat flux in the sulfate saline soil in spring, summer, and early autumn was positive, while the heat flux in late autumn and winter was mainly negative. During the transition of the four seasons throughout the year in the Hexi region, the trends of soil temperature, volumetric water content, and conductivity were similar, first increasing and then decreasing. As the soil depth increased, the influence of external environmental factors on soil temperature, volumetric water content, and conductivity gradually weakened, and the hysteresis effect became more pronounced. Moreover, owing to the influence of external environmental temperature, salt expansion in the positive temperature stage accounts for approximately five times the salt-frost heave deformation in the negative temperature stage, indicating that the deformation of sulfate saline soil in the Hexi region is mainly caused by salt expansion. Therefore, to reduce the impact of external climate change on engineering buildings and agriculture in salted seasonal permafrost regions, appropriate measures and management methods should be adopted to minimize salt expansion and soil salinization.

Evapotranspiration (ET) is a critical component of the soil-plant-atmosphere continuum, significantly influencing the water and energy balance of ecosystems. However, existing studies on ET have primarily focused on the growing season or specific years, with limited long-term analyses spanning decades. This study aims to analyse the components of ET within the alpine ecosystem of the Heihe River Basin, specifically investigating the dynamics of vegetation transpiration (T) and soil evaporation (Ev). Utilizing the SPAC model and integrating meteorological observations and eddy covariance data from 2013 to 2022, we investigate the impact of solar radiation and vegetation dynamics on ET and its partitioning (T/ET). The agreement between measured and simulated energy fluxes (net radiation and latent energy flux) and soil temperature underscores the validity of the model's performance. Additionally, a comparison employing the underlying water use efficiency method reveals consistent T/ET values during the growing season, further confirming the model's accuracy. Results indicate that the annual average T/ET during the 10-year study period is 0.41 +/- 0.03, close to the global average but lower than in warmer, humid regions. Seasonal analysis reveals a significant increase in T/ET during the growing season (April to October), particularly in May and June, coinciding with the thawing of permafrost and increased soil moisture. In addition, the study finds that the leaf area index and canopy stomatal conductance exhibit a logarithmic relationship with T/ET, whereas soil temperature and downward longwave radiation show an exponential relationship with T/ET. This study highlights the importance of understanding the stomatal conductance dynamics and their controls of transpiration process within alpine ecosystems. By providing key insights into the hydrological processes of these environments, it offers guidance for adapting to climate change impacts.

Refractory black carbon (rBC) is a primary aerosol species, produced through incomplete combustion, that absorbs sunlight and contributes to positive radiative forcing. The overall climate effect of rBC depends on its spatial distribution and atmospheric lifetime, both of which are impacted by the efficiency with which rBC is transported or removed by convective systems. These processes are poorly constrained by observations. It is especially interesting to investigate rBC transport efficiency through the Asian Summer Monsoon (ASM) since this meteorological pattern delivers vast quantities of boundary layer air from Asia, where rBC emissions are high to the upper troposphere/lower stratosphere (UT/LS) where the lifetime of rBC is expected to be long. Here, we present in situ observations of rBC made during the Asian Summer Monsoon Chemistry and Climate Impact Project of summer, 2022. We use observed relationships between rBC and CO in ASM outflow to show that rBC is removed nearly completely (>98%) from uplifted air and that rBC concentrations in ASM outflow are statistically indistinguishable from the UT/LS background. We compare observed rBC and CO concentrations to those expected based on two chemical transport models and find that the models reproduce CO to within a factor of 2 at all altitudes whereas rBC is overpredicted by a factor of 20-100 at altitudes associated with ASM outflow. We find that the rBC particles in recently convected air have thinner coatings than those found in the UTLS background, suggesting transport of a small number of rBC particles that are negligible for concentration.

Precipitation comes in various phases, including rainfall, snowfall, sleet, and hail. Shifts of precipitation phases, as well as changes in precipitation amount, intensity, and frequency, have significant impacts on regional climate, hydrology, ecology, and the energy balance of the land-atmosphere system. Over the past century, certain progress has been achieved in aspects such as the observation, discrimination, transformation, and impact of precipitation phases. Mainly including: since the 1980s, studies on the observation, formation mechanism, and prediction of precipitation phases have gradually received greater attention and reached a certain scale. The estimation of different precipitation phases using new detection theories and methods has become a research focus. A variety of discrimination methods or schemes, such as the potential thickness threshold method of the air layer, the temperature threshold method of the characteristic layer, and the near-surface air temperature threshold method, have emerged one after another. Meanwhile, comparative studies on the discrimination accuracy and applicability assessment of multiple methods or schemes have also been carried out simultaneously. In recent years, the shift of precipitation from solid to liquid (SPSL) in the mid-to-high latitudes of the Northern Hemisphere has become more pronounced due to global warming and human activities. It leads to an increase in rain-on-snow (ROS) events and avalanche disasters, affecting the speed, intensity, and duration of spring snow-melting, accelerating sea ice and glacier melting, releasing carbon from permafrost, altering soil moisture, productivity, and phenological characteristics of ecosystems, and thereby affecting their structures, processes, qualities, and service functions. Although some progress has been made in the study of precipitation phases, there remains considerable research potential in terms of completeness of basic data, reliability of discrimination schemes, and the mechanistic understanding of the interaction between SPSL and other elements or systems. The study on shifts of precipitation phases and their impacts will play an increasingly important role in assessing the impacts of global climate change, water cycle processes, water resources management, snow and ice processes, snow and ice-related disasters, carbon emissions from permafrost, and ecosystem safety.

Glaciers provide multiple ecosystem services (ES) to human society. Due to the continued global warming, the valuation of glacier ES is of urgent importance because this knowledge can support the protection of glaciers. However, a systematic valuation of glacier ES is still lacking, particularly from the perspective of ES contributors. In this study, we introduce the concept of emergy to establish a methodological framework for accounting glacier ES values, and take the Tibetan Plateau (TP) as a case study to comprehensively evaluate the spatiotemporal characteristics of glacier ES during the early 21st century. The results show that the total glacier ES values on the TP increased from 2.36E+24 sej/yr in the 2000s to 2.40E+24 sej/yr in the 2010s, with an overall growth rate of 1.6%. The values of the various services in the 2010s are ranked in descending order: climate regulation (1.59E+24 sej/yr, 66.1%), runoff regulation (4.40E+23 sej/yr, 18.4%), hydropower generation (1.88E+23 sej/ yr, 7.8%). Significantly higher glacier ES values were recorded in the marginal TP than in the endorheic area. With the exception of climate regulation and carbon sequestration, all other service values increased during the study period, partially cultural services, which have experienced rapid growth in tandem with social development. The results of this study will help establish the methodological basis for the assessment of regional and global glacier ES, as well as a scientific basis for the regional protection of glacier resources.

Understanding the dynamics of soil respiration (Rs) in response to freeze-thaw cycles is crucial due to permafrost degradation on the Qinghai-Tibet Plateau (QTP). We conducted continuous in situ observations of Rs using an Li-8150 automated soil CO2 flux system, categorizing the freeze-thaw cycle into four stages: completely thawed (CT), autumn freeze-thaw (AFT), completely frozen (CF), and spring freeze-thaw (SFT). Our results revealed distinct differences in Rs magnitudes, diurnal patterns, and controlling factors across these stages, attributed to varying thermal regimes. The mean Rs values were as follows: 2.51 (1.10) mu mol center dot m(-2)center dot s(-1) (CT), 0.37 (0.04) mu mol center dot m(-2)center dot s(-1) (AFT), 0.19 (0.06) mu mol center dot m(-2)center dot s(-1) (CF), and 0.68 (0.19) mu mol center dot m(-2)center dot s(-1) (SFT). Cumulatively, the Rs contributions to annual totals were 89.32% (CT), 0.79% (AFT), 5.01% (CF), and 4.88% (SFT). Notably, the temperature sensitivity (Q10) value during SFT was 2.79 times greater than that in CT (4.63), underscoring the significance of CO2 emissions during spring warming. Soil temperature was the primary driver of Rs in the CT stage, while soil moisture at 5 cm depth and solar radiation significantly influenced Rs during SFT. Our findings suggest that global warming will alter seasonal Rs patterns as freeze-thaw phases evolve, emphasizing the need to monitor CO2 emissions from alpine meadow ecosystems during spring.