In this study, we used satellite observations to identify 10 typical dust-loading events over the Indian Himalayas. Next, the aerosol microphysical and optical properties during these identified dust storms are characterized using cotemporal in situ measurements over Mukteshwar, a representative site in Indian Himalayas. Relative to the background values, the mass of coarse particles (size range between 2.5 and 10 mu m) and the extinction coefficient were found to be enhanced by 400% (from 24 +/- 15 to 98 +/- 40 mu g/m3) and 175% (from 89 +/- 57 Mm-1 to 156 +/- 79 Mm-1), respectively, during these premonsoonal dust-loading events. Moreover, based on the air mass trajectory, these dust storms can be categorized into two categories: (a) mineral dust events (MDEs), which involve long-range transported dust plumes traversing through the lower troposphere to reach the Himalayas and (b) polluted dust events (PDEs), which involve short-range transported dust plumes originating from the arid western regions of the Indian subcontinent and traveling within the heavily polluted boundary layer of the Gangetic plains before reaching the Himalayas. Interestingly, compared to the background, the SSA and AAE decrease during PDEs but increase during MDEs. More importantly, we observe a twofold increase in black carbon concentrations and the aerosol absorption coefficient (relative to the background values) during the PDEs with negligible changes during MDEs. Consequently, the aerosol-induced snow albedo reduction (SAR) also doubles during MDEs and PDEs relative to background conditions. Thus, our findings provide robust observational evidence of substantial dust-induced snow and glacier melting over the Himalayas.

Permafrost degradation is a growing direct impact of climate change. Detecting permafrost shrinkage, in terms of extension, depth reduction and active layer shift is fundamental to capture the magnitude of trends and address actions and warnings. Temperature profiles in permafrost allow direct understanding of the status of the frozen ground layer and its evolution in time. The Sommeiller Pass permafrost monitoring station, at about 3000 m of elevation, is the key site of the regional network installed in 2009 during the European Project PermaNET in the Piedmont Alps (NW Italy). The station consists of three vertical boreholes with different characteristics, equipped with a total of 36 thermistors distributed in three different chains. The collected raw data shows a degradation of the permafrost base at approximately 60 m of depth since 2014, corresponding to about 0.03 degrees C/yr. In order to verify and better quantify this potential degradation, three on-site sensor calibration campaigns were carried out to understand the reliability of these measurements. By repeating calibrations in different years, two key results have been achieved: the profiles have been corrected for errors and the re-calibration allowed to distinguish the effective change of permafrost temperatures during the years, from possible drifts of the sensors, which can be of the same order of magnitude of the investigated thermal change. The warming of permafrost base at a depth of similar to 60 m has been confirmed, with a rate of (4.2 +/- 0.5)center dot 10(-2) degrees C/yr. This paper reports the implementation and installation of the on-site metrology laboratory, the dedicated calibration procedure adopted, the calibration results and the resulting adjusted data, profiles and their evolution with time. It is intended as a further contribution to the ongoing studies and definition of best practices, to improve data traceability and comparability, as prescribed by the World Meteorological Organization Global Cryosphere Watch programme.

The significant uncertainties of Black Carbon (BC) radiative forcing are becoming an obstacle to the evaluation of their impacts and mitigation measures. One of the crucial reasons for this uncertainty could be the poorly constrained BC vertical profile. The BC has a lifetime of a few days to weeks and there is a clear pointer that it can be vertically transported through convection besides the horizontal advection. The present study aims for the intercomparison between the BC mass concentrations obtained through the aircraft-based observations and that derived from the selected Copernicus Atmosphere Monitoring Service (CAMS) reanalysis data over the three different locations of India, which is one of the largest emitters of BC aerosols. The aircraft-based BC observations were conducted from 0.5 to 7 km altitudes using Aethalometer during CAIPEEX (Cloud Aerosol Interaction and Precipitation Enhancement Experiment) Phase I campaigns from June to September 2009. The output of the present study suggests the CAMS reanalysis data significantly underestimated BC mass throughout the vertical profile with an average mass normalized mean bias of greater than -70% at all three locations. Furthermore, the vertical radiative forcing and heating rates of BC were also calculated for both observation and reanalysis data. The output depicts the net forcing due to CAMS simulated BC in all the layers were 1-12 folds lower over all the study regions compared with observed BC aerosols. Likewise, the estimated mean biases in heating rate were in the range of -0.001 to -0.190 K day(-1) for all the vertical layers over the study locations. The possible reasons for these disparities could be poorly constrained emissions, especially aircraft emissions and/or their transformation schemes in aerosol modules. The present study emphasized that the validation of the vertical profile is also an essential factor for better constraints of the BC aerosols in climate models.

Soil parameters form the foundation of hydrogeological research and are crucial for studying engineering construction and maintenance, climate change, and ecological environment effects in cold regions. However, the soil properties in the permafrost region of the Qinghai-Tibet Plateau (QTP) remain unclear. Hence, in this study, soil temperature (Ts), volumetric specific heat capacity (C), thermal conductivity (K), thermal diffusivity (D), soil water content (SWC), electric conductivity (EC), vertical (Kv) and horizontal (Kh) saturated hydraulic conductivity, bulk density (rho b), and soil texture near the Qinghai-Tibet Railway were measured, and their effects on the freeze-thaw process were evaluated. The results revealed a predominantly sandy loam soil texture, with Kh and Kv showing strong spatial variability, while the other parameters presented moderate spatial variability. Thermokarst lake had a limited influence on D, C, K, and rho b but significantly reduced Kh and Kv. Groundwater affected SWC, Ts, and EC. The model results showed that all parameters indicated small sensitivities to the maximum thawing depth (MTD), with MTD positively responding to all parameters except for Kv and porosity (rho p). Except for Kh and Kv, all parameters showed high sensitivities to the time from starting to complete freezing (TSCF). TSCF responded positively to C, rho p, and density (rho d) and negatively to K and Kh. This study expanded the quantification of soil properties in the QTP, which can help improve the accuracy of cryohydrogeologic models, thus guiding the construction and maintenance of infrastructure engineering.

Uncertainty plays a key role in hydrological modeling and forecasting, which can have tremendous environmental, economic, and social impacts. Therefore, it is crucial to comprehend the nature of this uncertainty and identify its scope and effects in a way that enhances hydrological modeling and forecasting. During recent decades, hydrological researchers investigated several approaches for reducing inherent uncertainty considering the limitations of sensor measurement, calibration, parameter setting, model conceptualization, and validation. Nevertheless, the scope and diversity of applications and methodologies, sometimes brought from other disciplines, call for an extensive review of the state-of-the-art in this field in a way that promotes a holistic view of the proposed concepts and provides textbook-like guidelines to hydrology researchers and the community. This paper contributes to this goal where a systematic review of the last decade's research (2010 onward) is carried out. It aims to synthesize the theories and tools for uncertainty reduction in surface hydrological forecasting, providing insights into the limitations of the current state-of-the-art and laying down foundations for future research. A special focus on remote sensing and multi-criteria-based approaches has been considered. In addition, the paper reviews the current state of uncertainty ontology in hydrological studies and provides new categorizations of the reviewed techniques. Finally, a set of freely accessible remotely sensed data and tools useful for uncertainty handling and hydrological forecasting are reviewed and pointed out.

From the beginning of May 2023 to the end of August 2023, the Northern Hemisphere experienced significant wildfire activity with the most widespread fires occurring in Canada. Forest fires in Canada destroyed more than 15.6 million hectares of forests. These wildfires worsened air quality across the region and other parts of the world. The smoke reached southern Europe by the end of June 2023. To better understand the consequences of such forest fires far from the site of origin, aerosol optical, microphysical and radiative properties were analyzed during this event for southern Europe using data from the Visible Infrared Imaging Radiometer Suite (VIIRS), TROPOspheric Monitoring Instrument (TROPOMI), and Aerosol Robotic Network (AERONET). TROPOMI aerosol index (AI) and the carbon monoxide (CO) product confirm that the smoke originated directly from these forest fires. AERONET data from the El Arenosillo site in southern Spain showed maximum aerosol optical depth (AOD) values on June 27 reached 2.36. Data on Angstrom Exponent (AE), aerosol volume size distribution (VSD), single scattering albedo (SSA), fine mode fraction (FMF), volume particle concentration, effective radius (R Eff ), absorption AOD (AAOD), extinction AE (EAE) and absorption AE (AAE) showed that fine-mode particles with carbonaceous aerosols contribution predominated in the atmosphere above the El Arenosillo site. Direct aerosol radiative forcing (DARF) at the top (DARF TOA ) and bottom of atmosphere (DARF BOA ) were-103.1 and-198.93 Wm-2 , respectively. The atmospheric aerosol radiative forcing (DARF ATM ) was found to be 95.83 Wm-2 and with a heating rate 2.69 K day-1 , which indicates the resulting warming of the atmosphere.

Aerosols affect Earth's climate both directly and indirectly, which is the largest uncertainty in the assessment of radiative forcings affecting anthropogenic climate change. The standard Aerosol Robotic Network (AERONET) aerosol products have been widely used for more than 30 years. Currently, there is strong community interest in the possibility of determining aerosol composition directly from remote sensing observations. This work presents the results of applying such a recently developed approach by Li et al. to extended datasets of the directional sky radiances and spectral aerosol optical depth (AOD) measured by AERONET for the retrievals of aerosol components. First, the validation of aerosol optical properties retrieved by this component approach with AERONET standard products shows good agreement. Then, spatiotemporal variations of the obtained aerosol component concentration are characterized globally, especially the absorbing aerosol species (black carbon, brown carbon, and iron oxides) and scattering aerosol species (organic carbon, quartz, and inorganic salts). Finally, we compared the black carbon (BC) and dust column concentration retrievals to the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), products in several regions of interest (Amazon zone, Desert, and Taklamakan Desert) for new insights on the quantitative assessment of MERRA-2 aerosol composition products (R = 0.60-0.85 for BC; R = 0.75-0.90 for dust). The new value-added and long-term aerosol composition product globally is available online (https://doi.org/10.6084/ m9.figshare.25415239.v1), which provides important measurements for the improvement and optimization of aerosol modeling to enhance estimation of the aerosol radiative forcing. SIGNIFICANCE STATEMENT: In the assessment of climate change, the uncertainty associated with aerosol radiative forcing is the largest one. The purpose of this study is to provide a new value-added and long-term aerosol composition (including absorbing and scattering aerosol species) inversion dataset derived from Aerosol Robotic Network (AERONET) measurements for characterizing their spatiotemporal variations at global scale. We find some new insights on the quantitative assessment of black carbon and dust column concentration products in the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2). Our results and aerosol composition inversion dataset will provide robust support for the overall improvement and optimization of aerosol modeling to better understand the aerosol radiative forcing.

In this study, we investigated the aerosol radiative forcing (ARF) using ground-based measurements of PM2.5 and black carbon aerosols at a semi-arid, rain shadow location, Solapur in peninsular India. It is observed that aerosols caused a net cooling effect at top of the atmosphere (TOP) indicating that the aerosols reflect more solar radiation back to space than they absorb. At the surface, the aerosols caused a net cooling effect indicating more presence of scattering type aerosols. The resulting ARF of the aerosols was found to be ranging from +38 Wm-2 in monsoon to +53 Wm-2 in pre-monsoon indicating trapping of energy which resulted in a warming of the atmosphere. However, BC -only forcing indicated a significant warming effect at TOP as well as in the atmosphere which showed the potential of the absorbing carbonaceous aerosols. Overall, BC was responsible for 44% and 32% of the composite ARF, even though it formed only 7% and 2% of composite aerosol in the dry and wet periods, respectively. The warming impact of BC aerosols was also manifested in terms of their contribution to aerosol radiative forcing efficiency (ARFE) which was about four times more for BC-only than that for composite aerosols. More atmospheric heating rates were observed during dry periods for composite and BC-only aerosols than during wet period. These findings have important implications for aerosol-cloud-precipitation studies as well as the atmospheric thermodynamics and hydrological cycle over this semi-arid region where the total aerosol load is not significant and rainfall amount is scarce.

Poverty and income inequality are problems faced by many countries including China. Since the implementation of Targeted Poverty Alleviation (TPA), absolute poverty has been eradicated, meanwhile, Chinese rural residents' income and inequality have experienced unprecedented new dynamics, but still, very few studies have focused on them. Hence, we attempt to examine the new trends in Chinese farmers' income inequality and to understand its causes during this period. We observe that China's urban-rural income ratio has been shrinking and the urban-rural inequality has been decreasing from 2014 to 2021. The reduction in the Theil index indicates a decrease in the regional inequality of farmers' income as well, and the decline in inter-regional inequality among eight economic zones contributes about 80% to increased equality. These new trends are caused by the fact that, with the TPA, the incomes of rural residents especially that in destitute areas, grew faster than that of urban residents and farmers in prosperous areas. The higher share of non-agricultural industry and agricultural mechanization level have significant positive impact on regional equality of farmers' income, while urban-rural dual structure has significant negative inhibitory effects. The lowest farmers' income and the highest inequality in the Northwest, and the slowest growth in the Northeast deserve more attention in rural Revitalization. From these findings, we propose four policy implications that would be applied to improve Chinese farmers' income equality, govern relative poverty, and achieve common prosperity in the post-poverty era.

Global warming leads to the melting of permafrost, affects changes in soil microbial community structures and related functions, and contributes to the soil carbon cycle in permafrost areas. Located at the southern edge of Eurasia's permafrost region, the Greater Khingan Mountains are very sensitive to climate change. Therefore, by analyzing the bacterial community structure, diversity characteristics, and driving factors of soil profiles (active surface layer, active deep layer, transition layer, and permafrost layer) in this discontinuous permafrost region, this research provides support for the study of the carbon cycling process in permafrost regions. The results show that the microbial diversity (Shannon index (4.81)) was the highest at 0-20 cm, and the Shannon index of the surface soil of the active layer was significantly higher than that of the other soil layers. Acidobacteria and Proteobacteria were the dominant bacteria in the active layer soil of the permafrost area, and Chloroflexi, Actinobacteria, and Firmicutes were the dominant bacteria in the permafrost layer. Chloroflexi made the greatest contribution to the bacterial community in the permafrost soil, and Bacteroidota made the greatest contribution to the bacterial community in the active surface soil. The structure, richness, and diversity of the soil bacterial community significantly differed between the active layer and the permafrost layer. The number of bacterial species was the highest in the active layer surface soil and the active layer bottom soil. The difference in the structure of the bacterial community in the permafrost soil was mainly caused by changes in electrical conductivity and soil-water content, while that in the active layer soil was mainly affected by pH and soil nutrient indices. Soil temperature, NO3--N, and pH had significant effects on the structure of the bacterial community. The active layer and permafrost soils were susceptible to environmental information processing and genetic information processing. Infectious disease: the number of bacterial species was significantly higher in the surface and permafrost layers than in the other layers of the soil. In conclusion, changes in the microbial community structure in soil profiles in discontinuous permafrost areas sensitive to climate change are the key to soil carbon cycle research.