Humidity is a basic and crucial meteorological indicator commonly measured in several forms, including specific humidity, relative humidity, and absolute humidity. These different forms can be inter-derived based on the saturation vapor pressure (SVP). In past decades, dozens of formulae have been developed to calculate the SVP with respect to, and in equilibrium with, liquid water and solid ice surfaces, but many prior studies use a single function for all temperature ranges, without considering the distinction between over the liquid water and ice surfaces. These different approaches can result in humidity estimates that may impact our understanding of surface-subsurface thermal-hydrological dynamics in cold regions. In this study, we compared the relative humidity (RH) downloaded and calculated from four data sources in Alaska based on five commonly used SVP formulas. These RHs, along with other meteorological indicators, were then used to drive physics-rich land surface models at a permafrost-affected site. We found that higher values of RH (up to 40 %) were obtained if the SVP was calculated with the over-ice formulation when air temperatures were below freezing, which could lead to a 30 % maximum difference in snow depths. The choice of whether to separately calculate the SVP over an ice surface in winter also produced a significant range (up to 0.2 m) in simulated annual maximum thaw depths. The sensitivity of seasonal thaw depth to the formulation of SVP increases with the rainfall rate and the height of above-ground ponded water, while it diminishes with warmer air temperatures. These results show that RH variations based on the calculation of SVP with or without over-ice calculation meaningfully impact physicallybased predictions of snow depth, sublimation, soil temperature, and active layer thickness. Under particular conditions, when severe flooding (inundation) and cool air temperatures are present, care should be taken to evaluate how humidity data is estimated for land surface and earth system modeling

Permafrost and ground freezing/thawing processes are physically and eco-climatologically important factors in the terrestrial cryosphere. The model reproducibility of frozen ground affects the certainty and reliability of simulated eco-climate conditions in cold regions as well as on a global scale. This study evaluated the variations and their attributes in the model performance developed and employed in the recent decade regarding the subsurface thermal state using outputs from Japanese and international model intercomparison projects and reanalysis data. The simulated surface and subsurface physical states were compared at four Arctic sites under different frozen ground conditions (Fairbanks, Kevo, Tiksi, and Yakutsk). The results showed that despite large variations in the modeled permafrost temperature, all the models, including the reanalysis data, successfully reproduced the permafrost conditions for the continuous permafrost sites. In contrast, some models failed to reproduce the presence of permafrost for the sites in the discontinuous to isolated permafrost zones. Evaluations of near-surface ground temperature variability revealed that the overall wellness of the simulated ground thermal states relied on winter reproducibility. The importance of snowpack metamorphosis for adequate thermal insulation was confirmed and demonstrated. The results at the coastal tundra site imply the importance of snow cover redistribution and wind crust formation owing to strong winds, the lack of which resulted in overestimations of thermal insulation and overcooled near-surface ground by most models.

The detailed physical processes involved in slowing glacier ablation by material cover remain poorly understood so far. In the present study, using the snow cover model SNOWPACK, the effect of geotextile cover on the energy and mass balance at the tongue of the Urumqi Glacier No. 1 (Chinese Tien Shan) was simulated between July 12, 2022 and August 31, 2022. The mass changes and the energy fluxes with and without material cover were compared. The results indicated that the geotextile covering reduced glacier ablation by approximately 68% compared to the ablation in the uncovered regions. The high solar reflectivity of the geotextile reduced the net short-wave radiation energy available for the melt by 45%. Thermal insulation of the geotextile reduced the sensible heat flux by 15%. In addition, the wet geotextile exerted a cooling effect through long-wave radiation and negative latent heat flux. This cooling effect reduced the energy available for ablation by 20%. Consequently, only 37% of the energy was used for melting compared to that used in the uncovered regions (67%). Sensitivity experiments revealed that the geotextile cover used at a thickness range of 0.045-0.090 m reduced the ice loss by approximately 68%-72%, and a further increase in the thickness of the geotextile cover led to little improvements. A higher temperature and greater wind speed increased glacier ablation, although their effects were small. When the precipitation was set to zero, it led to a significantly increased melt. Overall, the geotextile effectively protected the glacier tongue from rapid melting, and the observed results have provided inspiration for developing an effective and sustainable approach to protect the glaciers using geotextile cover.

This article investigates the snow albedo changes in Colombian tropical glaciers, namely, Sierra Nevada de Santa Marta (SNSM), Sierra Nevada del Cocuy (NSC), Nevado del Ruiz (NDR), Nevado Santa Isabel (NDS), Nevado del Tolima (NDT), and Nevado del Huila (NDH). They are associated with the possible mineral dust deposition from the Sahara Desert during the June and July months using snow albedo (SA), snow cover (SC), and land surface temperature (LST) from the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard NASA's Terra and Aqua satellites. And mineral dust (MD) from The Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), both of them during 2000-2020. Results show the largest snow albedo reductions were observed at 39.39%, 32.1%, and 30.58% in SNC, SNSM, and NDR, respectively. Meanwhile, a multiple correlation showed that the glaciers where MD contributed the most to SA behavior were 35.4%, 24%, and 21.4% in NDS, NDC, and NDR. Results also display an increasing trend of dust deposition on Colombian tropical glaciers between 2.81 x 10-3 & mu;g & BULL;m-2 & BULL;year-1 and 6.58 x 10-3 & mu;g & BULL;m-2 & BULL;year-1. The results may help recognize the influence of Saharan dust on reducing snow albedo in tropical glaciers in Colombia. The findings from this study also have the potential to be utilized as input for both regional and global climate models. This could enhance our comprehension of how tropical glaciers are impacted by climate change.

In the context of climate change, the variation of seasonal frozen soil affects the eco-hydrological process in a water tower, which has been widely noted by scientists worldwide. However, the latitudinal characteristics of the temporal and spatial variation of seasonal freezing depth and their response to changing climatic factors need to be strengthened. Therefore, Changbai Mountain, a typical high-latitude water tower, was chosen to analyze the change in temporal and spatial variation of freezing depth and the influence of climatic factors by the modified Mann-Kendll trend test and Generalized Additive Model (GAM) methods. Results showed that the higher the latitude, the greater the freezing depth, the longer the freeze-thaw cycles, the earlier the freeze onset and the later the thaw onset. However, the frozen soil had a clear degradation trend during the period 1960-2018. There was also a significantly latitudinal characteristic. The higher the latitude, the greater the degradation of frozen soil. The downward trend was the largest with-0.35 cm/yr in the high latitude, followed by-0.24 cm/year in the middle-high latitude and the smallest with-0.10 cm/yr in the low latitude. In addition, due to climate change, the period of freeze-thaw cycles has been shortened, the freeze onset was delayed, and thaw onset has been advanced. According to the response of monthly average freezing depth (MAFD) to climatic factors, there is a strong correlation between MAFD and climatic factors in different months. When the soil started to freeze and thaw, temperature was the main factor influencing the change in freezing depth (p < 0.05). It is interesting to note that the air temperature contributed more strongly to the change in MAFD than surface temperature. When the frozen soil was in stable freezing period (from December to March of the following year), the snow cover gradually became the main influencing factor. Snow depth and snow pressure had the greatest contribution to the degradation of frozen soil. The higher the latitude, the longer the duration of influence of snow on frozen soil (explained difference = 20-61%). In addition, wind speed was also an important influencing factor on the change of MAFD in each month. Especially during the thaw period in April and May, wind speed was the most important influencing factor in the high latitude region. This study would be beneficial for the protection of the ecohydrological cycle in cold region and would provide a basis for the study of seasonal frozen soil.

The vast majority of surface water resources in the semi-arid western United States start as winter snowpack. Solar radiation is a primary driver of snowmelt, making snowpack water resources especially sensitive to even small increases in concentrations of light absorbing particles such as mineral dust and combustion-related black carbon (BC). Here we show, using fresh snow measurements and snowpack modeling at 51 widely distributed sites in the Rocky Mountain region, that BC dominated impurity-driven radiative forcing in 2018. BC contributed three times more radiative forcing on average than dust, and up to 17 times more at individual locations. Evaluation of 2015-2018 archived samples from most of the same sites yielded similar results. These findings, together with long-term observations of atmospheric concentrations and model studies, indicate that BC rather than dust has dominated radiative forcing by light absorbing impurities on snow for decades, indicating that mitigation strategies to reduce radiative forcing on headwater snow-water resources would need to focus on reducing winter and spring BC emissions.

Depositions of light-absorbing particles (LAPs), such as black carbon (BC) and dust, on the snow surface modulate the snow albedo; therefore, they are considered key factors of snow-atmosphere interaction in the present-day climate system. However, their detailed roles have not yet been fully elucidated, mainly due to the lack of in-situ measurements. Here, we develop a new model chain NHM-Chem-SMAP, which is composed of a detailed regional meteorology-chemistry model and a multilayered physical snowpack model, and evaluate it using LAPs concentrations data measured at Sapporo, Japan during the 2011-2012 winter. NHM-Chem-SMAP successfully reproduces the in-situ measured seasonal variations in the mass concentrations of BC and dust in the surface snowpack. Furthermore, we find that LAPs from domestic and foreign sources played a role in shortening the snow cover duration by 5 and 10 days, respectively, compared to the completely pure snow condition.

The impact of high latitude climate warming on Arctic snow cover and its insulating properties has key implications for the surface and soil energy balance. Few studies have investigated specific trends in Arctic snowpack properties because there is a lack of long-term in situ observations and current detailed snow models fail to represent the main traits of Arctic snowpacks. This results in high uncertainty in modeling snow feedbacks on ground thermal regime due to induced changes in snow insulation. To better simulate Arctic snow structure and snow thermal properties, we implemented new parameterizations of several snow physical processes-including the effect of Arctic low vegetation and wind on snowpack-in the Crocus detailed snowpack model. Significant improvements compared to standard Crocus snow simulations and ERA-Interim (ERAi) reanalysis snow outputs were observed for a large set of in-situ snow data over Siberia and North America. Arctic Crocus simulations produced improved Arctic snow density profiles over the initial Crocus version, leading to a soil surface temperature bias of -0.5 K with RMSE of 2.5 K. We performed Crocus simulations over the past 39 years (1979-2018) for circumpolar taiga (open forest) and pan-Arctic areas at a resolution of 0.5 degrees, driven by ERAi meteorological data. Snowpack properties over that period feature significant increase in spring snow bulk density (mainly in May and June), a downward trend in snow cover duration and an upward trend in wet snow (mainly in spring and fall). The pan-Arctic maximum snow water equivalent shows a decrease of -0.33 cm dec(-1). With the ERAi air temperature trend of +0.84 K dec(-1) featuring Arctic winter warming, these snow property changes have led to an upward trend in soil surface temperature (Tss) at a rate of +0.41 K dec(-1) in winter. We show that the implemented snowpack property changes increased the Tss trend by 36% compared to the standard simulation. Winter induced changes in Tss led to a significant increase of 16% (+4 cm dec(-1)) in the estimated active layer thickness (ALT) over the past 39 years. An increase in ALT could have a significant impact on permafrost evolution, Arctic erosion and hydrology.

Black carbon (BC), dust, and organic carbon (OC) aerosols, when deposited onto the surface of glaciers, can absorb light and decrease the snow albedo. These impurities in snow are referred to as ILAIs (i.e., insoluble light absorbing impurities). Atmospheric chemical models have been extensively used to simulate the transport and deposition of atmospheric aerosols in glacierized areas. However, systematic investigations of ILAIs in snowpack of glaciers on the Tibetan Plateau (TP) are rare. In this study, observations of ILAIs in snow and simulations of ILAIs of atmospheric aerosol at surface over four glaciers on the TP have been analyzed. Strong correlation between BC and dust was found in surface aged-snow, and their correlation significantly varied with snowpit depth. BC and OC concentrations in snowpit tended to decrease with depth. Significant differences of ILAI concentrations among depth intervals reflect their diverse hydrophilicities, physiochemical properties and postdepositional processes in snowpit, offering important observational constraints on the related processes. Monthly variation of atmospheric ILAIs at surface over glaciers is characterized by distinct spatial heterogeneity. The statistical results show higher ILAI concentrations in the summer of 2015 than 2014, which is in qualitative agreement with CALIPSO observations, likely reflecting the effects of inter-annual variation of summer monsoon on snow ILAI loadings. Optical attenuation (ATN) of BC is gradually decreased with depth of snowpit, whereas the trend of mass absorption cross- (MAC) of BC throughout the profile of snowpit is opposite to that of ATN. The scanning electron microscopy (SEM) imaging demonstrates that calcium and silicon rich particles dominate over biological, quartz and flying ash particles in the cryoconite, providing additional constraints on the sources of dust-in-snow and can facilitate better understanding of the physicochemical properties and climatic effects of particles in the glacial cryoconite.

The populations, species, and communities in high elevation mountainous regions at or above tree line are being impacted by the changing climate. Mountain systems have been recognized as both resilient and extremely threatened by climate change, requiring a more nuanced understanding of potential trajectories of the biotic communities. For high elevation systems in particular, we need to consider how the interactions among climate drivers and topography currently structure the diversity, species composition, and life-history strategies of these communities. Further, predicting biotic responses to changing climate requires knowledge of intra- and inter-specific climate associations within the context of topographically heterogenous landscapes. Changes in temperature, snow, and rain characteristics at regional scales are amplified or attenuated by slope, aspect, and wind patterns occurring at local scales that are often under a hectare or even a meter in extent. Community assemblages are structured by the soil moisture and growing season duration at these local sites, and directional climate change has the potential to alter these two drivers together, independently, or in opposition to one another due to local, intervening variables. Changes threaten species whose water and growing season duration requirements are locally extirpated or species who may be outcompeted by nearby faster-growing, warmer/drier adapted species. However, barring non-analogue climate conditions, species may also be able to more easily track required resource regimes in topographically heterogenous landscapes. New species arrivals composed of competitors, predators and pathogens can further mediate the direct impacts of the changing climate. Plants are moving uphill, demonstrating primary succession with the emergence of new habitats from snow and rock, but these shifts are constrained over the short term by soil limitations and microbes and ultimately by the lack of colonizable terrestrial surfaces. Meanwhile, both subalpine herbaceous and woody species pose threats to more cold-adapted species. Overall, the multiple interacting direct and indirect effects of the changing climate on high elevation systems may lead to multiple potential trajectories for these systems.