Search Results (26)

Over the past decades, the cryosphere has changed significantly in High Mountain Asia (HMA), leading to multiple natural hazards such as rock–ice avalanches, glacier collapse, debris flows, landslides, and glacial lake outburst floods (GLOFs). Monitoring cryosphere change and evaluating its hydrological effects are essential for studying climate change, the hydrological cycle, water resource management, and natural disaster mitigation and prevention. However, knowledge gaps, data uncertainties, and other substantial challenges limit comprehensive research in climate–cryosphere–hydrology–hazard systems. To address this, we provide an up-to-date, comprehensive, multidisciplinary review of remote sensing techniques in cryosphere studies, demonstrating primary methodologies for delineating glaciers and measuring geodetic glacier mass balance change, glacier thickness, glacier motion or ice velocity, snow extent and water equivalent, frozen ground or frozen soil, lake ice, and glacier-related hazards. The principal results and data achievements are summarized, including URL links for available products and related data platforms. We then describe the main challenges for cryosphere monitoring using satellite-based datasets. Among these challenges, the most significant limitations in accurate data inversion from remotely sensed data are attributed to the high uncertainties and inconsistent estimations due to rough terrain, the various techniques employed, data variability across the same regions (e.g., glacier mass balance change, snow depth retrieval, and the active layer thickness of frozen ground), and poor-quality optical images due to cloudy weather. The paucity of ground observations and validations with few long-term, continuous datasets also limits the utilization of satellite-based cryosphere studies and large-scale hydrological models. Lastly, we address potential breakthroughs in future studies, i.e., (1) outlining debris-covered glacier margins explicitly involving glacier areas in rough mountain shadows, (2) developing highly accurate snow depth retrieval methods by establishing a microwave emission model of snowpack in mountainous regions, (3) advancing techniques for subsurface complex freeze–thaw process observations from space, (4) filling knowledge gaps on scattering mechanisms varying with surface features (e.g., lake ice thickness and varying snow features on lake ice), and (5) improving and cross-verifying the data retrieval accuracy by combining different remote sensing techniques and physical models using machine learning methods and assimilation of multiple high-temporal-resolution datasets from multiple platforms. This comprehensive, multidisciplinary review highlights cryospheric studies incorporating spaceborne observations and hydrological models from diversified techniques/methodologies (e.g., multi-spectral optical data with thermal bands, SAR, InSAR, passive microwave, and altimetry), providing a valuable reference for what scientists have achieved in cryosphere change research and its hydrological effects on the Third Pole. Full article

In this work, we develop a software suite for studies of atmosphere–underlying SNOW-spaceborne optical receiver light TRANsmission calculations (SNOWTRAN) with applications for the solution of forward and inverse radiative transfer problems in polar regions. Assuming that the aerosol load is extremely low, the proposed theory does not require the numerical procedures for the solution of the radiative transfer equation and is based on analytical equations for the spectral nadir reflectance and simple approximations for the local optical properties of atmosphere and snow. The developed model is validated using EnMAP and PRISMA spaceborne imaging spectroscopy data close to the Concordia research station in Antarctica. A new, fast technique for the determination of the snow grain size and assessment of the snowpack vertical inhomogeneity is then proposed and further demonstrated on EnMAP imagery over the Aviator Glacier and in the vicinity of the Concordia research station in Antarctica. The results revealed a large increase in precipitable water vapor at the Concordia research station in February 2023 that was linked to a warming event and a four times larger grain size at Aviator Glacier compared with Dome C. Full article

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 Ruíz (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 × 10⁻³ µg·m⁻²·year⁻¹ and 6.58 × 10⁻³ µg·m⁻²·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. Full article

The snowpack evolution during the melt season on an Arctic glacier is assessed using ground-based oblique-view cameras, spaceborne imaging and spaceborne RADAR. The repeated and systematic Synthetic Aperture RADAR (SAR) imaging by the European Space Agency’s Sentinel-1 spaceborne RADARs allows for all-weather, all-illumination condition monitoring of the snow-covered fraction of the glacier and hence assessing its water production potential. A comparison of the RADAR reflectivity with optical and multispectral imaging highlights the difference between the observed quantities—water content in the former, albedo in the latter—and the complementarity for understanding the snow melt processes. This work highlights the temporal inertia between the visible spring melting of the snowpack and the snow metamorphism. It was found that the snowpack exhibits that approximately 30 days before it starts to fade. Full article

Climate change and climate variability drive rapid glacier melt and snowpack loss, extreme precipitation and temperature events, and alteration of water availability in the Himalayas. There is increasing observational evidence of climate change impacts on water resource availability and agricultural productivity in the central Himalayan region. Here, we assess the farmers’ perception of climate change and its impacts on agriculture in western Nepal. We interviewed 554 households and conducted eight focus group discussions to collect farmers’ perceptions of temperature and rainfall characteristics, water availability, onset and duration of different seasons, and the impacts of such changes on their lives and livelihoods. Our results indicate that the farmers’ perceptions of rising annual and summer temperatures are consistent with observations. Perception, however, contradicts observed trends in winter temperature, as well as annual, monsoon, and winter precipitation. In addition, farmers are increasingly facing incidences of extreme events, including rainfall, floods, landslides, and droughts. These hazards often impact agricultural production, reducing household income and exacerbating the economic impacts on subsistence farmers. Integrated assessment of farmers’ perceptions and hydrometeorological observations is crucial to improving climate change impact assessment and informing the design of mitigation and adaptation strategies. Full article

Changes in water resources within basins can significantly impact ecosystems, agriculture, and biodiversity, among others. Basins in northern Canada have a cold climate, and the recent changes in climate can have a profound impact on water resources in these basins. Therefore, it is crucial to study long term trends in water flow as well as their influential factors, such as temperature and precipitation. This study focused on analyzing long term trends in water flow across the Athabasca River Basin (ARB) and Peace River Basin (PRB). Long term trends in temperature and precipitation within these basins were also studied. Water flow data from 18 hydrometric stations provided by Water Survey of Canada were analyzed using the Mann-Kendall test and Sen’s slope. In addition, hybrid climate data provided by Alberta Environment and Parks at approximately 10 km spatial resolution were analyzed for the ARB and its surrounding regions during 1950–2019. Trend analysis was performed on the water flow data on monthly, seasonal, and annual scales, and the results were cross-checked with trends in temperature and precipitation and land use and land cover data. The overall temperature across the basins has been increasing since 1950, while precipitation showed an insignificant decrease during this period. Winter water flow in the upper ARB has been slowly and steadily increasing since 1956 because of the rising temperatures and the subsequent slow melting of snowpacks/glaciers. The warm season flows in the middle and lower subregions declined up to 1981, then started to show an increasing trend. The middle and lower ARB exhibited a rapid increase in warm-season water flow since 2015. A similar trend change was also observed in the PRB. The gradual increase in water flow observed in the recent decades may continue by the mid-century, which is beneficial for agriculture, forestry, fishery, and industry. However, climate and land cover changes may alter the trend of water flow in the future; therefore, it is important to have a proper management plan for water usage in the next decades. Full article

A majority of the annual precipitation in many mountains falls as snow, and obtaining accurate estimates of the amount of water stored within the snowpack is important for water supply forecasting. Mountain topography can produce complex patterns of snow distribution, accumulation, and ablation, yet the interaction of topography and meteorological patterns tends to generate similar inter-annual snow depth distribution patterns. Here, we question whether snow depth patterns at or near peak accumulation are repeatable for a 10-year time frame and whether years with limited snow depth measurement can still be used to accurately represent snow depth and mean snow depth. We used snow depth measurements from the West Glacier Lake watershed, Wyoming, USA, to investigate the distribution of snow depth. West Glacier Lake is a small (0.61 km²) windswept (mean of 8 m/s) watershed that ranges between 3277 m and 3493 m. Three interpolation methods were compared: (1) a binary regression tree, (2) multiple linear regression, and (3) generalized additive models. Generalized additive models using topographic parameters with measured snow depth presented the best estimates of the snow depth distribution and the basin mean amounts. The snow depth patterns near peak accumulation were found to be consistent inter-annually with an average annual correlation coefficient (r²) of 0.83, and scalable based on a winter season accumulation index (r² = 0.75) based on the correlation between mean snow depth measurements to Brooklyn Lake snow telemetry (SNOTEL) snow depth data. Full article

This project explored the integrated use of satellite, ground observations and hydrological distributed models to support water resources assessment and monitoring in High Mountain Asia (HMA). Hydrological data products were generated taking advantage of the synergies of European and Chinese data assets and space-borne observation systems. Energy-budget-based glacier mass balance and hydrological models driven by satellite observations were developed. These models can be applied to describe glacier-melt contribution to river flow. Satellite hydrological data products were used for forcing, calibration, validation and data assimilation in distributed river basin models. A pilot study was carried out on the Red River basin. Multiple hydrological data products were generated using the data collected by Chinese satellites. A new Evapo-Transpiration (ET) dataset from 2000 to 2018 was generated, including plant transpiration, soil evaporation, rainfall interception loss, snow/ice sublimation and open water evaporation. Higher resolution data were used to characterize glaciers and their response to environmental forcing. These studies focused on the Parlung Zangbo Basin, where glacier facies were mapped with GaoFeng (GF), Sentinal-2/Multi-Spectral Imager (S2/MSI) and Landsat8/Operational Land Imager (L8/OLI) data. The geodetic mass balance was estimated between 2000 and 2017 with Zi-Yuan (ZY)-3 Stereo Images and the SRTM DEM. Surface velocity was studied with Landsat5/Thematic Mapper (L5/TM), L8/OLI and S2/MSI data over the period 2013–2019. An updated method was developed to improve the retrieval of glacier albedo by correcting glacier reflectance for anisotropy, and a new dataset on glacier albedo was generated for the period 2001–2020. A detailed glacier energy and mass balance model was developed with the support of field experiments at the Parlung No. 4 Glacier and the 24 K Glacier, both in the Tibetan Plateau. Besides meteorological measurements, the field experiments included glaciological and hydrological measurements. The energy balance model was formulated in terms of enthalpy for easier treatment of water phase transitions. The model was applied to assess the spatial variability in glacier melt. In the Parlung No. 4 Glacier, the accumulated glacier melt was between 1.5 and 2.5 m w.e. in the accumulation zone and between 4.5 and 6.0 m w.e. in the ablation zone, reaching 6.5 m w.e. at the terminus. The seasonality in the glacier mass balance was observed by combining intensive field campaigns with continuous automatic observations. The linkage of the glacier and snowpack mass balance with water resources in a river basin was analyzed in the Chiese (Italy) and Heihe (China) basins by developing and applying integrated hydrological models using satellite retrievals in multiple ways. The model FEST-WEB was calibrated using retrievals of Land Surface Temperature (LST) to map soil hydrological properties. A watershed model was developed by coupling ecohydrological and socioeconomic systems. Integrated modeling is supported by an updated and parallelized data assimilation system. The latter exploits retrievals of brightness temperature (Advanced Microwave Scanning Radiometer, AMSR), LST (Moderate Resolution Imaging Spectroradiometer, MODIS), precipitation (Tropical Rainfall Measuring Mission (TRMM) and FengYun (FY)-2D) and in-situ measurements. In the case study on the Red River Basin, a new algorithm has been applied to disaggregate the SMOS (Soil Moisture and Ocean Salinity) soil moisture retrievals by making use of the correlation between evaporative fraction and soil moisture. Full article

The present work proposes to improve estimates of snowpack and snowmelt and their assessment in the steep Himalayan ranges at the sub-catchment scale. Temporal variability of streamflow and the associated distribution of accumulated snow in catchments with glacier presence in the Himalayas illustrates how changes in snowpack and snowmelt can affect the water supply for local water management. The primary objective of this study is to assess the role of elevation, temperature lapse rate (TLR), and precipitation lapse rate (PLR) in the computation of snowpack (or snowfall) and snowmelt in sub-catchments of the Satluj River basin. Modeling of snowpack and snowmelt was constructed using the Soil Water Assessment Tool (SWAT) in both historical (1991–2008) and near-time scenarios (2011–2030) by implementing real-time hydrometeorological, snow-hydrological parameters, and Global Circulation Model (GCM) datasets. The modeled snowmelt-induced streamflow showed a good agreement with the observed streamflow (~60%), calibrated and validated at three gauges. A Sequential Uncertainty Parameter Fitting (SUFI2) method (SUFI2) resulted that the curve number (CN2) was found to be significantly sensitive during calibration. The snowmelt hydrological parameters such as snowmelt factor maximum (SMFMX) and snow coverage (SNO50COV) significantly affected objective functions, such as R2 and NSE, during the model optimization. For the validation of snowpack and snowmelt, the results have been contrasted with previous studies and found comparable. The computed snowpack and snowmelt were found highly variable over the Himalayan sub-catchments, as also reported by previous researchers. The magnitude of snowpack change consistently decreases across all the sub-catchments of the Satluj river catchment (varying between 4% and 42%). The highest percentage of changes in the snowpack was observed over high-elevation sub-catchments. Full article

The global climate shift currently underway has significant impacts on both the quality and quantity of snow precipitation. This directly influences the spatial variability of the snowpack as well as cumulative snow height. Contemporary glacier retreat reorganizes periglacial morphology: while the glacier area decreases, the moraine area increases. The latter is becoming a new water storage potential that is almost as important as the glacier itself, but with considerably more complex topography. Hence, this work fills one of the missing variables of the hydrological budget equation of an arctic glacier basin by providing an estimate of the snow water equivalent (SWE) of the moraine contribution. Such a result is achieved by investigating Structure from Motion (SfM) image processing that is applied to pictures collected from an Unmanned Aerial Vehicle (UAV) as a method for producing snow depth maps over the proglacial moraine area. Several UAV campaigns were carried out on a small glacial basin in Spitsbergen (Arctic): the measurements were made at the maximum snow accumulation season (late April), while the reference topography maps were acquired at the end of the hydrological year (late September) when the moraine is mostly free of snow. The snow depth is determined from Digital Surface Model (DSM) subtraction. Utilizing dedicated and natural ground control points for relative positioning of the DSMs, the relative DSM georeferencing with sub-meter accuracy removes the main source of uncertainty when assessing snow depth. For areas where snow is deposited on bare rock surfaces, the correlation between avalanche probe in-situ snow depth measurements and DSM differences is excellent. Differences in ice covered areas between the two measurement techniques are attributed to the different quantities measured: while the former only measures snow accumulation, the latter includes all of the ice accumulation during winter through which the probe cannot penetrate, in addition to the snow cover. When such inconsistencies are observed, icing thicknesses are the source of the discrepancy that is observed between avalanche probe snow cover depth measurements and differences of DSMs. Full article

Seasonal snow and glaciers in arid mountain regions are essential in sustaining human populations, economic activity, and ecosystems, especially in their role as reservoirs. However, they are threatened by global atmospheric changes, in particular by variations in air temperature and their effects on precipitation phase, snow dynamics and mass balance. In arid environments, small variations in snow mass and energy balance can produce large changes in the amount of available water. This paper provides insights into the impact of global warming on the mass balance of the seasonal snowpack in the mountainous Copiapó river basin in northern Chile. A dataset from an experimental station was combined with reanalysis data to run a physically based snow model at site and catchment scales. The basin received an average annual precipitation of approximately 130 mm from 2001 to 2016, with sublimation losses higher than 70% of the snowpack. Blowing snow sublimation presented an orographic gradient resultant from the decreasing air temperature and windy environment in higher elevations. Under warmer climates, the snowpack will remain insensitive in high elevations (>4000 m a.s.l.), but liquid precipitation will increase at lower heights. Full article

The COupled Snowpack and Ice surface energy and mass balance model in PYthon (COSIPY) was employed to investigate the relationship between the variability and sensitivity of the mass balance record of the Halji glacier, in the Himalayas, north-western Nepal, over a 40 year period since October 1981 to atmospheric drivers. COSIPY was forced with the atmospheric reanalysis dataset ERA5-Land that has been statistically downscaled to the location of an automatic weather station at the Halji glacier. Glacier mass balance simulations with air temperature and precipitation perturbations were executed and teleconnections investigated. For the mass-balance years 1982 to 2019, a mean annual glacier-wide climatic mass balance of −0.48 meters water equivalent per year (m w.e. a⁻¹) with large interannual variability (standard deviation 0.71 m w.e. a⁻¹) was simulated. This variability is dominated by temperature and precipitation patterns. The Halji glacier is mostly sensitive to summer temperature and monsoon-related precipitation perturbations, which is reflected in a strong correlation with albedo. According to the simulations, the climate sensitivity with respect to either positive or negative air temperature and precipitation changes is nonlinear: A mean temperature increase (decrease) of 1 K would result in a change of the glacier-wide climatic mass balance of −1.43 m w.e. a⁻¹ (0.99 m w.e. a⁻¹) while a precipitation increase (decrease) of 10% would cause a change of 0.45m w.e. a⁻¹ (−0.59 m w.e. a⁻¹). Out of 22 circulation and monsoon indexes, only the Webster and Yang Monsoon index and Polar/Eurasia index provide significant correlations with the glacier-wide climatic mass balance. Based on the strong dependency of the climatic mass balance from summer season conditions, we conclude that the snow–albedo feedback in summer is crucial for the Halji glacier. This finding is also reflected in the correlation of albedo with the Webster and Yang Monsoon index. Full article

The Antarctic Peninsula (AP) region has been one of the regions on Earth with strongest warming since 1950. However, the northwest of the AP showed a cooling from 2000 to 2015, which had local consequences with an increase in snow accumulation and a deceleration in the loss of mass from glaciers. In this paper, we studied the effects of increased snow accumulation in the permafrost thermal regime in two boreholes (PG1 and PG2) in Livingston Island, South Shetlands Archipelago, from 2009 to 2015. The two boreholes located c. 300 m apart but at similar elevation showed different snow accumulation, with PG2 becoming completely covered with snow all year long, while the other remained mostly snow free during the summer. The analysis of the thermal regimes and of the estimated soil surface energy exchange during the study period showed the effects of snow insulation in reducing the active layer thickness. These effects were especially relevant in PG2, which transitioned from a subaerial to a subnival regime. There, permafrost aggraded from below, with the active layer completely disappearing and the efficiency of thermal insulation by the snowpack prevailing in the thermal regime. This situation may be used as an analogue for the transition from a periglacial to a subglacial environment in longer periods of cooling in the paleoenvironmental record. Full article

In this study, snow samples collected from nine snowpacks from Mt. Yulong are measured to examine the monthly and annual isotopic variation. The results indicate that the late autumn and winter snow sampled in 2008/2009 show a similar high–low–high δ¹⁸O variation. In spring, the high–low–high curve still exists in the lower layers (<1.5 m), while relatively high values are witnessed in the upper layers (>1.5 m). Isotopic homogenization, smoothing the vertical variation of δ¹⁸O in snow, is observed in June and July when snow melting occurs. Samples collected in April of 2009, 2012 and 2017 show significant differences, suggesting annual changes of isotope contents in snow. This study suggests that the isotope contents in the snow profile can reflect meteorological information. At the monthly scale, we can distinguish the information on snow accumulation and melting by determining the monthly variation of vertical isotope contents in snow. At the annual scale, we can analyze the annual difference of corresponding meteorological factors. Collectively, observing the stable isotopes in snow could provide evidence for climate change, particularly when climatic data are lacking or are challenging to obtain in cold glacierized regions. Full article