Snow Surface Research Articles

Dust storms from the Taklamakan Desert significantly darken snow surface on surrounding mountains

Abstract. The Taklamakan Desert (TD) is a major source of mineral dust emissions into the atmosphere. These dust particles have the ability to darken the surface of snow on the surrounding high mountains after deposition, significantly impacting the regional radiation balance. However, previous field measurements have been unable to capture the effects of severe dust storms accurately, and their representation on regional scales has been inadequate. In this study, we propose a modified remote-sensing approach that combines data from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite and simulations from the Snow, Ice, and Aerosol Radiative (SNICAR) model. This approach allows us to detect and analyze the substantial snow darkening resulting from dust storm deposition. We focus on three typical dust events originating from the Taklamakan Desert and observe significant snow darkening over an area of ∼ 2160, ∼ 610, and ∼ 640 km2 in the Tien Shan, Kunlun, and Qilian mountains, respectively. Our findings reveal that the impact of dust storms extends beyond the local high mountains, reaching mountains located approximately 1000 km away from the source. Furthermore, we observe that dust storms not only darken the snowpack during the spring but also in the summer and autumn seasons, leading to increased absorption of solar radiation. Specifically, the snow albedo reduction (radiative forcing) triggered by severe dust deposition is up to 0.028–0.079 (11–31.5 W m−2), 0.088–0.136 (31–49 W m−2), and 0.092–0.153 (22–38 W m−2) across the Tien Shan, Kunlun, and Qilian mountains, respectively. This further contributes to the aging of the snow, as evidenced by the growth of snow grain size. Comparatively, the impact of persistent but relatively slow dust deposition over several months during non-event periods is significantly lower than that of individual dust events. This highlights the necessity of giving more attention to the influence of extreme events on the regional radiation balance. This study provides a deeper understanding of how a single dust event can affect the extensive snowpack and demonstrates the potential of employing satellite remote sensing to monitor large-scale snow darkening.

Investigating Road Ice Formation Mechanisms Using Road Weather Information System (RWIS) Observations

Ice formation on roads leads to a higher incidence of accidents and increases winter de-icing/anti-icing costs. This study analyzed 3 years (2019–2021) of Road Weather Information System (RWIS) sub-hourly measurements collected by the Montana Department of Transportation (MDT) to understand the first-order factors of road ice formation and its mechanisms. First, road ice is formed only when the road pavement surface temperature is equal to or below the freezing point (i.e., 32 °F (i.e., 0 °C)), while the corresponding 2 m air temperature could be above 32 °F. Nevertheless, when the road pavement was below 32 °F ice often did not form on the roads. Therefore, one challenge is to know under what conditions road ice forms. Second, the pavement surface temperature is critical for road ice formation. The clear road (i.e., with no ice or snow) surface pavement temperature is generally warmer than the air temperature during both day and night. This feature is different from a natural land surface, where the land skin temperature is lower than the air temperature on cloud-free nights due to radiative cooling. Third, subsurface temperature, measured using a RWIS subsurface sensor below a road surface, did not vary as much as the pavement temperature and, thus, may not be a good index for road ice formation. Fourth, urban heat island effects lead to black ice formation more frequently than roads located in other regions. Fifth, evaporative cooling from the water surface near a road segment further reduces the outlying air temperature, a mechanism that increases heat loss for bridges or lake-side roads in addition to radiative cooling. Additionally, mechanical lifting via mountains and hills is also an efficient mechanism that makes the air condense and, consequently, form ice on the roads. Forecasting road ice formation is in high demand for road safety. These observed features may help to develop a road ice physical model consisting of functions of hyper-local weather conditions, local domain knowledge, the road texture, and geographical environment.

The genome of the Arctic snow-alga Limnomonas spitsbergensis (Chlamydomonadales).

Snow-algae are a diverse group of extremophilic microeukaryotes found on melting polar and alpine snowfields. They play an important role in the microbial ecology of the cryosphere, and their propagation on snow and ice surfaces may in part accelerate climate-induced melting of these systems. High quality snow-algae genomes are needed for studies on their unique physiology, adaptive mechanisms and genome evolution under multiple forms of stress, including cold temperatures and intense sunlight. Here we assembled and annotated the genome of Limnomonas spitsbergensis, a cryophilic biciliate green alga originally isolated from melting snow on Svalbard, in the Arctic. The L. spitsbergensis genome assembly is based primarily on the use of PacBio long reads and secondly Illumina short reads, with an assembly size of 260.248 Mb in 124 contigs. A combination of three alternative annotation strategies were used including protein homology, RNA-seq evidence and PacBio full length transcript isoforms. The best merged set of annotations identified 18,277 protein-coding genes, which were 95.2% complete based on BUSCO analysis. We also provide the annotated mitogenome, which is a relatively large 77.942 kb circular mapping sequence containing extensive repeats. The L. spitsbergensis genome will provide a new resource for research on snow-algae adaptation, behavior and natural selection in unique, low-temperature terrestrial environments that are under threat from climate change.

An inverse model to correct for the effects of post-depositional processing on ice-core nitrate and its isotopes: model framework and applications at Summit, Greenland, and Dome C, Antarctica

Abstract. Comprehensive evaluation of the effects of post-depositional processing is a prerequisite for appropriately interpreting ice-core records of nitrate concentration and isotopes. In this study, we developed an inverse model that uses archived snow/ice-core nitrate signals to reconstruct primary nitrate flux (i.e., the deposition flux of nitrate to surface snow that originates from long-range transport or stratospheric input) and its isotopes (δ15N and Δ17O). The model was then applied to two polar sites, Summit, Greenland, and Dome C, Antarctica, using measured snowpack nitrate concentration and isotope profiles in the top few meters. At Summit, the model successfully reproduced the observed atmospheric δ15N(NO3-) and Δ17O(NO3-) and their seasonality. The model was also able to reasonably reproduce the observed snowpack nitrate profiles at Dome C as well as the skin layer and atmospheric δ15N(NO3-) and Δ17O(NO3-) at the annual scale. The calculated Fpri at Summit was 6.9 × 10−6 kgN m2 a−1, and the calculated Δ17O(NO3-) of Fpri is consistent with atmospheric observations in the Northern Hemisphere. However, the calculated δ15N(NO3-) of Fpri displays an opposite seasonal pattern to atmospheric observations in the northern mid-latitudes, but it is consistent with observations in two Arctic coastal sites. The calculated Fpri at Dome C varies from 1.5 to 2.2 × 10−6 kgN m−2 a−1, with δ15N(NO3-) of Fpri varying from 6.2 ‰ to 29.3 ‰ and Δ17O(NO3-) of Fpri varying from 48.8 ‰ to 52.6 ‰. The calculated Fpri at Dome C is close to the previous estimated stratospheric denitrification flux in Antarctica, and the high δ15N(NO3-) and Δ17O(NO3-) of Fpri at Dome C also point towards the dominant role of stratospheric origin of primary nitrate to Dome C.

Spatial and temporal stable water isotope data from the upper snowpack at the EastGRIP camp site, NE Greenland, sampled in summer 2018

Abstract. Stable water isotopes stored in snow, firn and ice are used to reconstruct climatic parameters. The imprint of these parameters at the snow surface and their preservation in the upper snowpack are determined by a number of processes influencing the recording of the environmental signal. Here, we present a dataset of approximately 3800 snow samples analysed for their stable water isotope composition, which were obtained during the summer season next to the deep drilling site of the East Greenland Ice Core Project in northeast Greenland (75.635411° N, 36.000250° W). Sampling was carried out every third day between 14 May and 3 August 2018 along a 39 m long transect. Three depth intervals in the top 10 cm were sampled at 30 positions with a higher resolution closer to the surface (0–1 and 1–4 cm depth vs. 4–10 cm). The sample analysis was carried out at two renowned stable water isotope laboratories that produced isotope data with the overall highest uncertainty of 0.09 ‰ for δ18O and 0.8 ‰ for δD. This unique dataset shows the strongest δ18O variability closest to the surface, damped and delayed variations in the lowest layer, and a trend towards increasing homogeneity towards the end of the season, especially in the deepest layer. Additional information on the snow height and its temporal changes suggests a non-uniform spatial imprint of the seasonal climatic information in this area, potentially following the stratigraphic noise of the surface. The data can be used to study the relation between snow height (changes) and the imprint and preservation of the isotopic composition at a site with 10–14 cm w.e. yr−1 accumulation. The high-temporal-resolution sampling allows additional analyses on (post-)depositional processes, such as vapour–snow exchange. The data can be accessed at https://doi.org/10.1594/PANGAEA.956626 (Zuhr et al., 2023a).

Comparing FY-2F/CTA products to ground-based manual total cloud cover observations in Xinjiang under complex underlying surfaces and different weather conditions

Abstract. Clouds are an important parameter of artificial water augmentation, which is of substantial significance to judge the precipitation capacity. Xinjiang is an arid region in northwestern China, where weather stations are sparsely distributed, the types of underlying surface are complex, and the climate between the southern and northern region varies greatly. However, the retrieval of the total cloud cover (TCC) from satellite in arid areas is a challenging task. Based on the TCC data observed by ground observation stations (GOSs) from June 2015 to May 2016 considering the complex underlying surfaces and different weather conditions, the precision, consistency, and error between the cloud total amount from the FengYun-2F stationary satellite (FY-2F/CTA) and manually observed TCC are compared and evaluated in the Xinjiang region. The findings of this study are as follows: (1) the precision rate (PR) of FY-2F/CTA in the Xinjiang region is 75.6 %, which gradually decreases from north to south, demonstrating a high false rate (FR) and a low missing rate (MR). The consistency rate (CR) is 51.5 %, with little difference among three subregions of Xinjiang, all showing a high weak rate (WR) and low strong rate (SR), which means that the TCC values inverted from FY-2 satellite data are generally lower than those observed by GOSs, especially in southern Xinjiang. The bias is −20 %, and all the error indexes (EIs) including bias, MAE, and RMSE increase from central to the north and south of Xinjiang; that means the EIs are the lowest in Tianshan and the highest in southern Xinjiang. FY-2F/CTA exhibits higher PR and CR in the underlying surface of vegetation compared to non-vegetation; that is to say that FY-2F/CTA performs best in the underlying surfaces of forest and plowland, while their performance is relatively poorer in the underlying surface of snow and ice. (2) With rising temperature the PR and CR of FY-2F/CTA increase, while the EIs decrease. Under various temperature conditions, FY-2F/CTA has always exhibited high MR, low FR (on the contrary in January), high WR, and low SR. From low elevation to high elevation, the PR and CR of FY-2F/CTA decrease, but the PR increases significantly when the altitude is higher than 2000 m. (3) Dust reduces the CR of FY-2F/CTA and increases their WR and MR but has a relatively minor impact on the identification of cloud and non-cloud. (4) Under different cloud cover levels, the PR and EIs of FY-2F/CTA are directly proportional to the amount of TCC, while the CR is inversely proportional to it: that is, the CR is higher and the PR and EIs are lower under clear-sky and partly cloudy conditions, and the CR is lower and the PR and EIs are higher under cloudy and overcast conditions. This study assessed the FY-2F/CTA under various conditions in arid areas of Xinjiang, including complex underlying surface, various temperature and altitude, dust effects, and different cloud cover levels. Thus, the research finding could serve as a valuable reference for satellite-based retrieval and applications related to TCC in arid regions.

Experimental Study on Shear Strength of Roof–Snow Interfaces for Prediction of Roof Snow Sliding

The sliding of roof snow may result in surcharges of snow load on lower roofs or the injury of pedestrians on the ground. It is therefore of great significance to study the mechanism of roof snow sliding, such that prevention or control measures can be developed to manage the risk. Considering four commonly used roofing materials, glass, steel, membrane, and concrete, two types of experiments were carried out in this study to possibly reveal the influence of roofing materials on the shear strength of the roof–snow interface: one is the critical angle tests where the angle at which the snow starts to slide off from the roof is tested, and the other is the shearing tests which aim to test the shear strength of the roof–snow interfaces at specific temperatures. The results showed that the critical angle for roof snow sliding, as well as the shear strength of the roof–snow interface for the four considered roofing materials, show a U-shape trend with the increase in surface roughness and that the shear strength of the roof–snow surface ranges from 0.15 kPa to 2 kPa for the cases considered, while the strength reaches its maximum at certain temperatures near −5 °C for a specific roofing material and snow thickness. These findings could be a useful reference for future experimental or simulation studies on roof snow sliding.

Sublimation of Snow

Abstract Snow is a vital part of water resources, and sublimation may remove 10% to 90% of snowfall from the system. To improve our understanding of the physics that govern sublimation rates, as well as how those rates might change with the climate, we deployed an array of four towers with over 100 instruments from NCAR’s Integrated Surface Flux System from November 2022 to June 2023 in the East River Watershed, Colorado, in conjunction with the U.S. Department of Energy’s Surface Atmosphere Integrated Field Laboratory (SAIL) and the National Oceanic and Atmospheric Administration (NOAA)’s Study of Precipitation, the Lower Atmosphere and Surface for Hydrometeorology (SPLASH) campaigns. Mass balance observations, snow pits, particle flux sensors, and terrestrial lidar scans of the evolving snowfield demonstrated how blowing snow influences sublimation rates, which we quantified with latent heat fluxes measured by eddy covariance systems at heights 1 to 20 m above the snow surface. Detailed temperature profiles at finer resolutions highlighted the role of the stable boundary layer. Four-stream radiometers indicated the important role of changing albedo in the energy balance and its relationship to water vapor losses. Collectively, these observations span scales from seconds to seasons, from boundary layer turbulence to valley-circulation to mesoscale meteorology. We describe the field campaign, highlights in the observations, and outreach and education products we are creating to facilitate cross-disciplinary dialogue and convey relevant findings to those seeking to better understand Colorado River snow and streamflow.

Location Dictates Snow Aerodynamic Roughness

We conducted an experiment comparing wind speeds and aerodynamic roughness length (z0) values over three snow surface conditions, including a flat smooth surface, a wavy smooth surface, and a wavy surface with fresh snow added, using the wind simulation tunnel at the Shinjo Cryospheric Laboratory in Shinjo, Japan. The results indicate that the measurement location impacts the computed z0 values up to a certain measurement height. When we created small (4 cm high) snow bedforms as waves with a 50 cm period, the computed z0 values varied by up to 35% based on the horizontal sampling location over the wave (furrow versus trough). These computed z0 values for the smooth snow waves were not significantly different than those for the smooth flat snow surface. Fresh snow was then blown over the snow waves. Here, for three of four horizontal sampling locations, the computed z0 values were significantly different over the fresh snow-covered waves as compared to those over the smooth snow waves. Since meteorological stations are usually established over flat land surfaces, a smooth snow surface texture may seem to be an appropriate assumption when calculating z0, but the snowpack surface can vary substantially in space and time. Therefore, the nature of the snow surface geometry should be considered variable when estimating a z0 value, especially for modeling purposes.

Foraging efficiency of two alpine bird species in central Japan

ABSTRACT Capsule The foraging efficiency of Alpine Accentors Prunella collaris and Japanese Accentors P. rubida is highest on the snow surface in the alpine zone, where they forage for fallen arthropods. Aims To compare the foraging efficiency of two bird species across alpine habitats, including the snow surface, and discuss the impact of changes in snow cover on their foraging behaviour. Methods The foraging efficiency of two alpine bird species, recorded as the number of pecks per unit time, was compared in the alpine zone of Mount Norikura in central Japan, among four habitat types: snow surface, Japanese Stone Pine scrub, alpine tundra and scree. Results In total, respective 45 and 32 foraging sequences of Alpine Accentors and Japanese Accentors were recorded. For both species, foraging efficiency was markedly higher on the snow surface than in other habitats. Conclusion Alpine bird species exhibit high foraging efficiency on the snow surface in the alpine zone, assuming that prey sizes are similar across habitats. With the decreasing amount of remaining snowpack in the alpine zone, due to the general trend of climate change, bird species will likely have a shorter period to efficiently utilize these foraging habitats in the future.

Absorption of collimated incident radiation in a semitransparent strongly scattering medium: Computational analysis and explanation of red algae blooming in snow

The study of directional radiation absorption in weakly absorbing and strongly scattering media is of interest for a variety of important applications, including laser hyperthermia of human tumors in a therapeutic window of transparency, determination of the optical and thermal properties of highly porous ceramics, and calculations of the deep solar heating of snow cover in polar regions and mountains. In such problems, multiple scattering of radiation can lead to a non-monotonic variation of the absorbed radiation power with distance from the illuminated surface of the medium and to the appearance of the absorption maximum at some depth below the surface. This effect has a known physical explanation and can be predicted using the suggested analytical solution based on the transport approximation for the scattering phase function and the two-flux approximation for the diffuse component of the radiation intensity. The range of illumination angles at which the absorption maximum inside an optically thick medium is observed is determined. The position and magnitude of this maximum are also obtained. In the present work, the verification of this approximate solution using reference numerical calculations is carried out for the first time. It is shown that the simple analytical model is acceptable for regular calculations. Computational results for pure snow illuminated by the Sun showed that red light gives the strongest absorption maximum at a small distance from the snow surface. This is a basis of the presented physical explanation for the intense photosynthesis of red microalgae responsible for the well-known ``snow blood'' phenomenon.

Understanding snow saltation parameterizations: lessons from theory, experiments and numerical simulations

Abstract. Drifting and blowing snow are important features in polar and high mountain regions. They control the surface mass balance in windy conditions and influence sublimation of snow and ice surfaces. Despite their importance, model representations in weather and climate assessments have high uncertainties because the associated physical processes are complex and highly variable in space and time. This contribution investigates the saltation system, which is the lower boundary condition for drifting and blowing snow models. Using a combination of (previous) measurements and new physics-based modeling with large-eddy simulation (LES), we show that the prevailing parameterizations that describe the saltation system in atmospheric models are based on contradictory assumptions: while some scaling laws are typical of a saltation system dominated by aerodynamic entrainment, others represent a saltation system controlled by splash. We show that both regimes can exist, depending on the friction velocity. Contrary to sand saltation, aerodynamic entrainment of surface particles is not negligible. It is important at low wind speeds, leading to a saltation height and near-surface particle velocity which increase with the friction velocity. In a splash-dominated saltation regime at higher friction velocities, the saltation height and near-surface particle velocity become invariant with the friction velocity and closer to what is observed with sand. These findings are accompanied by a detailed description of the theoretical, experimental and numerical arguments behind snow saltation parameterizations. This work offers a comprehensive understanding of the snow saltation system and its scaling laws, useful for both modelers and experimentalists.

Observations of cyanogen bromide (BrCN) in the global troposphere and their relation to polar surface O3 destruction

Abstract. Bromine activation (the production of Br in an elevated oxidation state) promotes ozone destruction and mercury removal in the global troposphere and commonly occurs in both springtime polar boundary layers, often accompanied by nearly complete ozone destruction. The chemistry and budget of active bromine compounds (e.g., Br2, BrCl, BrO, HOBr) reflect the cycling of Br and affect its environmental impact. Cyanogen bromide (BrCN) has recently been measured by iodide ion high-resolution time-of-flight mass spectrometry (I− CIMS), and trifluoro methoxide ion time-of-flight mass spectrometry (CF3O− CIMS) during the NASA Atmospheric Tomography Mission second, third, and fourth deployments (NASA ATom), and could be a previously unquantified participant in active Br chemistry. BrCN mixing ratios ranged from below the detection limit (1.5 pptv) up to as high as 36 pptv (10 s average) and enhancements were almost exclusively confined to the polar boundary layers in the Arctic winter and in both polar regions during spring and fall. The coincidence of BrCN with active Br chemistry (often observable BrO, BrCl and O3 loss) and high CHBr3/CH2Br2 ratios imply that much of the observed BrCN is from atmospheric Br chemistry rather than a biogenic source. Likely BrCN formation pathways involve the heterogeneous reactions of active Br (Br2, HOBr) with reduced nitrogen compounds, for example hydrogen cyanide (HCN/CN−), on snow, ice, or particle surfaces. Competitive reaction calculations of HOBr reactions with Cl−/Br− and HCN/CN− in solution, as well as box model calculations with bromine chemistry, confirm the viability of this formation channel and show a distinct pH dependence, with BrCN formation favored at higher pH values. Gas-phase loss processes of BrCN due to reaction with radical species are likely quite slow and photolysis is known to be relatively slow (BrCN lifetime of ∼ 4 months in midlatitude summer). These features, and the lack of BrCN enhancements above the polar boundary layer, imply that surface reactions must be the major loss processes. The fate of BrCN determines whether BrCN production fuels or terminates bromine activation. BrCN reactions with other halogens (Br−, HOCl, HOBr) may perpetuate the active Br cycle; however, preliminary laboratory experiments showed that BrCN did not react with aqueous bromide ion (< 0.1 %) to reform Br2. Liquid-phase reactions of BrCN are more likely to convert Br to bromide (Br−) or form a C–Br bonded organic species, as these are the known condensed-phase reactions of BrCN and would therefore constitute a loss of atmospheric active Br. Thus, further study of the chemistry of BrCN will be important for diagnosing polar Br cycling.

Precipitation and Soil Moisture Variation over the Tibetan Plateau to the Anomaly of Indian Summer Monsoon from 1979 to 2019

The Indian Summer Monsoon (ISM) can profoundly influence the summer precipitation patterns of the Tibetan Plateau (TP) and indirectly affect the TP’s soil humidity. This study investigates the responses of TP’s precipitation and soil moisture to the ISM in the monsoon season (June to September, JJAS) from 1979 to 2019. Precipitation in the TP and the ISM intensity generally exhibit a positive correlation in the west and a negative correlation in the east. The response of TP soil moisture to the ISM generally aligns with precipitation patterns, albeit with noted inconsistencies in certain TP regions. A region exhibiting these inconsistencies (30°–32°N, 80°–90°E) is selected as the study area, hereafter referred to as IRR. In periods of strong ISM, precipitation in IRR increases, yet soil moisture decreases. Conversely, in years with a weak ISM, the pattern is reversed. During strong ISM years, the rainfall increase in IRR is modest, and the soil remains drier compared to other TP regions. Under the combined effects of a marginal increase in precipitation and relatively rapid evaporation, soil moisture in the IRR decreased during years of strong ISM. During weak ISM years, the surface temperature in the IRR is higher compared to strong ISM years, potentially accelerating the melting of surface permafrost and snow in this region. Additionally, glacier meltwater, resulting from warmer temperatures in the northwest edge of the TP, may also result in the humidification of the soil in the IRR.

Impacts of physical parameterization scheme of snow and soil properties over the Tibetan Plateau on the simulation of summer rainfall in China

AbstractAccurate representation of soil and snow state variables in the land surface model is crucial for good simulation results. In order to investigate the potential impacts of the overestimated snow cover over the Tibetan Plateau (TP) on precipitation over China, we designed comparative experiments over TP with and without updated soil texture data, soil hydrological parameters, and the fresh snow density scheme to address this issue with the Weather Research and Forecasting Model (WRF). The results show that snow cover fraction (SCF) and surface albedo in winter on the TP were overestimated in the WRF control experiment (CTL), with albedo bias exceeding 0.4 in the western TP. The SCF in the WRF improved experiment (WRFIM) is about 8% lower than that of the CTL, and the bias is decreased to 0.2–0.3 in the interior of the TP. The thermal and dynamic effects of the TP in winter have a significant impact on the weather and climate of East Asia during summer. Thus, the simulated summer rainfall bias is significantly reduced by WRFIM in North China, and the mid-lower reaches of the Yangtze River, along with the spatial correlation coefficient between the observed-based and WRF-simulated rainfall increased from 0.76 in CTL to 0.88 in WRFIM. The WRFIM-simulated reductions in snow cover and albedo cause a decrease in upward shortwave radiation and eventually increase net surface radiation. The horizontal temperature gradient of the atmosphere is increased in the WRFIM compared to the CTL, and the increased temperature in the lower and middle layers accommodates more water vapor, which is not conducive to precipitation formation. Correspondingly, the Western Pacific Subtropical High at 500 hPa in the middle troposphere weakened. The low-level anticyclonic circulation at 850 hPa also weakened to the east, affecting water vapor transport in eastern China. It leads to a decrease in the water vapor transported northward by southeasterly from the western Pacific Ocean and a decrease in the water vapor flux reaching North China. This work indicates that accurate characterization of soil properties and snow cover on the TP is crucial for improving the simulation bias of summer rainfall in China.

Alpine blooming of “snow fleas”: the importance of snow for Alpine springtails (Hexapoda: Collembola) ecology and biodiversity

Springtails can occur in large populations on the snow surface. This peculiar habitat hosts specialized winter-active springtails living in colonies and using this seasonal habitat for feeding, effective dispersal and migration. Snow-active species have never been studied in Southern European Alps: the aim of this work is to study snow-active springtails of Adamello-Brenta Nature Park (“PNAB”; Italy), a peripheral mountain range of relevant biogeographic interest using integrative taxonomy. Springtail “bloomings” were sampled for 17 months by an environmental assistant of the park. Nine assemblages of springtails were found when temperatures were higher than 0 °C; eight were monospecific, with a total of five species found. The snow-active springtail fauna found includes both common Central-Northern European nival species like Desoria hiemalis (first record for Italy, although genetically differentiated from Northern Alps populations), Ceratophysella sigillata (known in Italy mainly from caves) and three species likely new to science (Hypogastrura cf. kelmendica sp1, Hypogastrura cf. kelmendica sp2, H. cf. peloponnesica, all belonging to the Hypogastrura socialisgroup). Snow is an important ephemeral habitat for springtails, for the biodiversity hosted and for its importance as an ecological corridor. We could hypothesize that snow, especially in peripheral mountain chains, acts as a fragmentary ephemeral habitat for those cold-adapted springtails. This could constitute a relevant aspect to take into consideration for conservation biology, especially in the context of the ongoing climate change. On the other hand, the Alpine chain probably acts as an ecological barrier for nival species, since isolated species and populations were found in PNAB.Graphical

Spatio-temporal patterns and trends in MODIS-retrieved radiative forcing by snow impurities over the Western US from 2001 to 2022

The seasonal mountain snowpack of the Western US (WUS) is a key water resource to millions of people and an important component of the regional climate system. Impurities at the snow surface can affect snowmelt timing and rate through snow radiative forcing (RF), resulting in earlier streamflow, snow disappearance, and less water availability in dry months. Predicting the locations, timing, and intensity of impurities is challenging, and little is known concerning whether snow RF has changed over recent decades. Here we analyzed the relative magnitude and spatio-temporal variability of snow RF across the WUS at three spatial scales (pixel, watershed, regional) using remotely sensed RF from spatially and temporally complete (STC) MODIS data sets (STC-MODIS Snow Covered Area and Grain Size/MODIS Dust Radiative Forcing on Snow) from 2001 to 2022. To quantify snow RF impacts, we calculated a pixel-integrated metric over each snowmelt season (1st March–30th June) in all 22 years. We tested for long-term trend significance with the Mann–Kendall test and trend magnitude with Theil–Sen’s slope. Mean snow RF was highest in the Upper Colorado region, but notable in less-studied regions, including the Great Basin and Pacific Northwest. Watersheds with high snow RF also tended to have high spatial and temporal variability in RF, and these tended to be near arid regions. Snow RF trends were largely absent; only a small percent of mountain ecoregions (0.03%–8%) had significant trends, and these were typically decreasing trends. All mountain ecoregions exhibited a net decline in snow RF. While the spatial extent of significant RF trends was minimal, we found declining trends most frequently in the Sierra Nevada, North Cascades, and Canadian Rockies, and increasing trends in the Idaho Batholith. This study establishes a two-decade chronology of snow impurities in the WUS, helping inform where and when RF impacts on snowmelt may need to be considered in hydrologic models and regional hydroclimate studies.

Land Data Assimilation: Harmonizing Theory and Data in Land Surface Process Studies

AbstractData assimilation plays a dual role in advancing the “scientific” understanding and serving as an “engineering tool” for the Earth system sciences. Land data assimilation (LDA) has evolved into a distinct discipline within geophysics, facilitating the harmonization of theory and data and allowing land models and observations to complement and constrain each other. Over recent decades, substantial progress has been made in the theory, methodology, and application of LDA, necessitating a holistic and in‐depth exploration of its full spectrum. Here, we present a thorough review elucidating the theoretical and methodological developments in LDA and its distinctive features. This encompasses breakthroughs in addressing strong nonlinearities in land surface processes, exploring the potential of machine learning approaches in data assimilation, quantifying uncertainties arising from multiscale spatial correlation, and simultaneously estimating model states and parameters. LDA has proven successful in enhancing the understanding and prediction of various land surface processes (including soil moisture, snow, evapotranspiration, streamflow, groundwater, irrigation and land surface temperature), particularly within the realms of water and energy cycles. This review outlines the development of global, regional, and catchment‐scale LDA systems and software platforms, proposing grand challenges of generating land reanalysis and advancing coupled land‒atmosphere DA. We lastly highlight the opportunities to expand the applications of LDA from pure geophysical systems to coupled natural and human systems by ingesting a deluge of Earth observation and social sensing data. The paper synthesizes current LDA knowledge and provides a steppingstone for its future development, particularly in promoting dual driven theory‐data land processes studies.

Impact of Land Surface Snow Processes on the Arctic Stable Boundary Layer

Abstract The impact of land surface snow processes on the Arctic stable boundary layer (ASBL) is investigated using the Navy’s Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS) to reduce the cold bias caused by decoupling between the land surface and atmosphere. The Noah land surface model (LSM) with improved snow processes is examined using COAMPS forecast forcing in the one-dimensional mode for one month. The new snow physics shows that the snow properties, roughness length, and sensible heat flux are modified as expected to compensate for the old LSM deficiency. These new snow processes are incorporated into the COAMPS Noah LSM, and the 48-h forecasts using both old and new Noah LSMs are performed for January 2021 with an every-6-h data assimilation update cycle. Standard verifications of the 48-h forecasts have used all available observational datasets and the snow depth from the Land Information System (LIS) analyses. The statistics have shown reduced monthly mean cold biases ∼1°C by the new snow physics. The weaker strength of surface inversion and stronger turbulence kinetic energy (TKE) from the new snow physics provides a higher boundary layer due to significantly stronger eddy mixing. The simulations have also shown the insignificant impact of different lateral boundary conditions obtained from the global forecasts or analyses on the results of the new snow physics. This study highlights the importance of the revised snow physics in Noah LSM for reducing the decoupling problem, improving the forecasts, and studying ASBL physics over the Arctic region.

Soot-on-snow experiment: artificial deposition of light-absorbing particles onto snow surfaces in 2018

The absorption of shortwave irradiance in snow depends on the physical properties of snow (e.g., snow grain size and shape, liquid water content, etc.) and light-absorbing particles (LAP). Originating from natural and anthropogenic sources, LAP has been reported to accelerate snowmelt significantly in different regions globally. Yet, our process-level understanding of LAP after deposition onto snow remains rather limited. Here we investigate the impacts of artificial deposition of different LAP onto snow surfaces in an outdoor environment of northern Finland. Following LAP dry deposition into a custom-made tent standing on top of the snowpack, the albedo was followed along with the properties of snow in snow pit measurements throughout the spring season. The results showed that the albedo decay at the end of the season for the different spots were linked to the initial amount and type of LAP that were deposited onto the snowpack. Measured snow temperature profiles from LAP doped snow versus natural reference snow illustrated that the LAP affected snow had higher temperatures in the subsurface snow layers. Collected snow samples analyzed for size distribution of soot particles revealed no apparent agglomeration of soot particles during thaw-freezing events taking place during the experiment. Despite the relatively large perturbation of the experimentally deposited LAP, their impact on the season length was only up to 3 days. Additional experiments are, nevertheless, needed to better constrain the effects of LAP on snow albedo, melt rate, and other associated processes.