An anomalous warm weather event in the Antarctic McMurdo Dry Valleys on 18 March 2022 created an opportunity to characterize soil biota communities most sensitive to freeze-thaw stress. This event caused unseasonal melt within Taylor Valley, activating stream water and microbial mats around Canada Stream. Liquid water availability in this polar desert is a driver of soil biota distribution and activity. Because climate change impacts hydrological regimes, we aimed to determine the effect on soil communities. We sampled soils identified from this event that experienced thaw, nearby hyper-arid areas, and wetted areas that did not experience thaw to compare soil bacterial and invertebrate communities. Areas that exhibited evidence of freeze-thaw supported the highest live and dead nematode counts and were composed of soil taxa from hyper-arid landscapes and wetted areas. They received water inputs from snowpacks, hyporheic water, or glacial melt, contributing to community differences associated with organic matter and salinity gradients. Inundated soils had higher organic matter and lower conductivity (p < .02) and hosted the most diverse microbial and invertebrate communities on average. Our findings suggest that as liquid water becomes more available under predicted climate change, soil communities adapted to the hyper-arid landscape will shift toward diverse, wetted soil communities.

Vast deserts and sandy lands in the mid-latitudes cover an area of 17.64 x 106 km2, with 6.98 x 106 km2 experiencing seasonal frozen soil (SFG). Freeze-thaw cycles of SFG significantly influence local surface processes in deserts, impacting meteorological disasters such as infrastructure failures and sandstorms. This study investigates the freeze-thaw dynamics of SFG in crescent dunes from three deserts in northern China: the Tengger Desert, Mu Us Sandy Land, and Ulan Buh Desert, over the period from 2019 to 2024.Freezing occurs from November to January, followed by thawing from January to March. The thawing rate (2.72 cm/day) was 1.8 times higher than the freezing rate (1.48 cm/day). The maximum seasonal freezing depth (MSFD) exceeded 0.80 mat all dune slopes, with depths surpassing 1.10 mat the leeward slope and lower slope positions. Soil moisture content, ranging from 1 % to 1.6 %, is critical for freezing, and this threshold varies depending on the dune's mechanical composition. The hardness of frozen desert soil is primarily controlled by moisture, along with temperature and particle size.Temperature initiates freezing, while moisture and particle size control the resulting hardness.These findings shed light on the seasonal freeze-thaw processes in desert soils and have practical implications for agricultural management, engineering design, and environmental hazard mitigation in arid regions.

作为东北多年冻土典型区，在气候变化和人类活动的共同影响下，大兴安岭山区多年冻土广泛快速退化，并导致了冻融灾害的频发。为系统地掌握该区工程冻融灾害分布及冻土退化情况，我们采用ERT、浅层测温（0～2 m）和无人机航测等方法于2023年8—9月开展了大兴安岭多年冻土区冻融灾害调查。结果表明，沥青路面下融沉长度和融沉量最大且以路基融沉（包含路基倾斜和波浪路面）为主；混凝土路面以长大深纵裂为主，而林区铁路和中俄原油管道（China-Russia crude oil pipelines, CRCOPs）以管基和施工运营作业带（right-of-way，或ROW）融沉和热喀斯特为主。冻融灾害地理分异特征明显：融沉灾害多发现于地势平坦且冻土保存条件较好的位置，融沉灾害的年平均地温与坡度呈正相关关系，且破坏长度与坡度为负相关关系。阳坡的融沉灾害平均破坏长度大于阴坡破坏长度。低纬度的融沉灾害平均破坏长度大于高纬度破坏长度。年平均地温较低的草甸土和森林土的融沉灾害的平均破坏长度大于年平均地温较高的暗棕壤的融沉灾害的破坏长度。冻融灾害对交通工程设施地基基础的安全运营造成了威胁：CRCOPs Ⅰ和Ⅱ线（漠河—...

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.

Predicting the impacts of climate change on aquatic ecosystems in the Subarctic is challenging due to the presence of permafrost and the wide range of geomorphologic conditions found across this heterogeneous landscape. To accurately predict how fish and wildlife will be impacted by climate change, it is critical to identify the habitat requirements of important prey such as macroinvertebrates. To better understand spatial heterogeneity in macroinvertebrate populations and identify key habitat requirements, we compared taxonomic richness, relative abundance, and density of macroinvertebrate populations in seven different lake basin types, spanning a large latitudinal and elevational gradient of subarctic Alaska. We used nonparametric statistics and NMDS to relate macroinvertebrate community metrics to landscape characteristics such as sedimentary deposit type, permafrost extent, geomorphology, and lake basin type, as well as chemical conditions within the lakes. Macroinvertebrate richness was highest in areas with continuous permafrost, largely driven by richness in dipterans. Lake water chemistry influenced taxa richness, relative abundance, and densities of both macroinvertebrates and microcrustaceans. Invertebrate densities were greatest in regions (parks) with higher nutrient concentrations and specific conductance, with higher relative abundance of dipterans in older landscape terrains (Yedoma) while a higher relative abundance of microcrustaceans was found in landscapes with little peat accumulation (sand dunes). As climate-driven permafrost thaw continues across the subarctic, shifts in pH, specific conductance, and calcium are likely to occur due to changes in active layer thickness and surface and groundwater flow paths that drive nutrient and solute delivery. Changes in invertebrate relative abundance and density are most likely to occur in ETOC and Diptera, two of the most ecologically important invertebrate groups found in subarctic lakes.

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.