Articles | Volume 13, issue 8
https://doi.org/10.5194/tc-13-2149-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-13-2149-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Suitability analysis of ski areas in China: an integrated study based on natural and socioeconomic conditions
Jie Deng
Heihe Remote Sensing Experimental Research Station, Key Laboratory of Remote Sensing of Gansu Province, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, 730000, China
Center for Excellence in Tibetan Plateau Earth Sciences, Chinese
Academy of Sciences, Beijing, 100101, China
University of Chinese Academy of Sciences, Beijing, 100049, China
Heihe Remote Sensing Experimental Research Station, Key Laboratory of Remote Sensing of Gansu Province, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, 730000, China
Center for Excellence in Tibetan Plateau Earth Sciences, Chinese
Academy of Sciences, Beijing, 100101, China
Cunde Xiao
State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing, 100000, China
Shijin Wang
State Key Laboratory of Cryospheric Science, Northwest Institute of
Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, 730000,
China
Liyun Dai
Heihe Remote Sensing Experimental Research Station, Key Laboratory of Remote Sensing of Gansu Province, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, 730000, China
Akynbekkyzy Meerzhan
Heihe Remote Sensing Experimental Research Station, Key Laboratory of Remote Sensing of Gansu Province, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, 730000, China
University of Chinese Academy of Sciences, Beijing, 100049, China
Jiangsu Center of Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, 210000, China
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Related subject area
Discipline: Snow | Subject: Remote Sensing
Evaluating snow depth retrievals from Sentinel-1 volume scattering over NASA SnowEx sites
Improved snow property retrievals by solving for topography in the inversion of at-sensor radiance measurements
Simulation of Arctic snow microwave emission in surface-sensitive atmosphere channels
Retrieval of snow and soil properties for forward radiative transfer modeling of airborne Ku-band SAR to estimate snow water equivalent: the Trail Valley Creek 2018/19 snow experiment
Evaluating L-band InSAR snow water equivalent retrievals with repeat ground-penetrating radar and terrestrial lidar surveys in northern Colorado
Reanalyzing the spatial representativeness of snow depth at automated monitoring stations using airborne lidar data
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Mapping surface hoar from near-infrared texture in a laboratory
Thermal infrared shadow-hiding in GOES-R ABI imagery: snow and forest temperature observations from the SnowEx 2020 Grand Mesa field campaign
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Temporal stability of a new 40-year daily AVHRR Land Surface Temperature dataset for the Pan-Arctic region
Snow water equivalent retrieved from X- and dual Ku-band scatterometer measurements at Sodankylä using the Markov Chain Monte Carlo method
Bayesian physical–statistical retrieval of snow water equivalent and snow depth from X- and Ku-band synthetic aperture radar – demonstration using airborne SnowSAr in SnowEx'17
Snow water equivalent retrieval over Idaho – Part 1: Using Sentinel-1 repeat-pass interferometry
Passive microwave remote-sensing-based high-resolution snow depth mapping for Western Himalayan zones using multifactor modeling approach
Retrieval of snow water equivalent from dual-frequency radar measurements: using time series to overcome the need for accurate a priori information
Snow accumulation, albedo and melt patterns following road construction on permafrost, Inuvik–Tuktoyaktuk Highway, Canada
Measuring the spatiotemporal variability in snow depth in subarctic environments using UASs – Part 1: Measurements, processing, and accuracy assessment
Measuring the spatiotemporal variability in snow depth in subarctic environments using UASs – Part 2: Snow processes and snow–canopy interactions
Evaluating Snow Microwave Radiative Transfer (SMRT) model emissivities with 89 to 243 GHz observations of Arctic tundra snow
Evaluating the utility of active microwave observations as a snow mission concept using observing system simulation experiments
Evaluation of snow depth retrievals from ICESat-2 using airborne laser-scanning data
How do tradeoffs in satellite spatial and temporal resolution impact snow water equivalent reconstruction?
Exploring the use of multi-source high-resolution satellite data for snow water equivalent reconstruction over mountainous catchments
Estimating snow accumulation and ablation with L-band interferometric synthetic aperture radar (InSAR)
Snowmelt characterization from optical and synthetic-aperture radar observations in the La Joie Basin, British Columbia
Topographic and vegetation controls of the spatial distribution of snow depth in agro-forested environments by UAV lidar
Temporal stability of long-term satellite and reanalysis products to monitor snow cover trends
Towards long-term records of rain-on-snow events across the Arctic from satellite data
Implementing spatially and temporally varying snow densities into the GlobSnow snow water equivalent retrieval
Evaluation of E3SM land model snow simulations over the western United States
Landsat, MODIS, and VIIRS snow cover mapping algorithm performance as validated by airborne lidar datasets
Snow stratigraphy observations from Operation IceBridge surveys in Alaska using S and C band airborne ultra-wideband FMCW (frequency-modulated continuous wave) radar
Brief communication: A continuous formulation of microwave scattering from fresh snow to bubbly ice from first principles
Review article: Global monitoring of snow water equivalent using high-frequency radar remote sensing
Automated avalanche mapping from SPOT 6/7 satellite imagery with deep learning: results, evaluation, potential and limitations
Potential of X-band polarimetric synthetic aperture radar co-polar phase difference for arctic snow depth estimation
Snow water equivalent change mapping from slope-correlated synthetic aperture radar interferometry (InSAR) phase variations
Sentinel-1 time series for mapping snow cover depletion and timing of snowmelt in Arctic periglacial environments: case study from Zackenberg and Kobbefjord, Greenland
Sentinel-1 snow depth retrieval at sub-kilometer resolution over the European Alps
Characterizing tundra snow sub-pixel variability to improve brightness temperature estimation in satellite SWE retrievals
Mapping liquid water content in snow at the millimeter scale: an intercomparison of mixed-phase optical property models using hyperspectral imaging and in situ measurements
Brief communication: Evaluation of the snow cover detection in the Copernicus High Resolution Snow & Ice Monitoring Service
Evaluation of snow extent time series derived from Advanced Very High Resolution Radiometer global area coverage data (1982–2018) in the Hindu Kush Himalayas
Deriving Arctic 2 m air temperatures over snow and ice from satellite surface temperature measurements
Impact of dynamic snow density on GlobSnow snow water equivalent retrieval accuracy
The retrieval of snow properties from SLSTR Sentinel-3 – Part 1: Method description and sensitivity study
The retrieval of snow properties from SLSTR Sentinel-3 – Part 2: Results and validation
Tree canopy and snow depth relationships at fine scales with terrestrial laser scanning
Snow depth mapping with unpiloted aerial system lidar observations: a case study in Durham, New Hampshire, United States
Zachary Hoppinen, Ross T. Palomaki, George Brencher, Devon Dunmire, Eric Gagliano, Adrian Marziliano, Jack Tarricone, and Hans-Peter Marshall
The Cryosphere, 18, 5407–5430, https://doi.org/10.5194/tc-18-5407-2024, https://doi.org/10.5194/tc-18-5407-2024, 2024
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This study uses radar imagery from the Sentinel-1 satellite to derive snow depth from increases in the returning energy. These retrieved depths are then compared to nine lidar-derived snow depths across the western United State to assess the ability of this technique to be used to monitor global snow distributions. We also qualitatively compare the changes in underlying Sentinel-1 amplitudes against both the total lidar snow depths and nine automated snow monitoring stations.
Brenton A. Wilder, Joachim Meyer, Josh Enterkine, and Nancy F. Glenn
The Cryosphere, 18, 5015–5029, https://doi.org/10.5194/tc-18-5015-2024, https://doi.org/10.5194/tc-18-5015-2024, 2024
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Remotely sensed properties of snow are dependent on accurate terrain information, which for a lot of the cryosphere and seasonal snow zones is often insufficient in accuracy. However, as we show in this paper, we can bypass this issue by optimally solving for the terrain by utilizing the raw radiance data returned to the sensor. This method performed well when compared to validation datasets and has the potential to be used across a variety of different snow climates.
Melody Sandells, Nick Rutter, Kirsty Wivell, Richard Essery, Stuart Fox, Chawn Harlow, Ghislain Picard, Alexandre Roy, Alain Royer, and Peter Toose
The Cryosphere, 18, 3971–3990, https://doi.org/10.5194/tc-18-3971-2024, https://doi.org/10.5194/tc-18-3971-2024, 2024
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Satellite microwave observations are used for weather forecasting. In Arctic regions this is complicated by natural emission from snow. By simulating airborne observations from in situ measurements of snow, this study shows how snow properties affect the signal within the atmosphere. Fresh snowfall between flights changed airborne measurements. Good knowledge of snow layering and structure can be used to account for the effects of snow and could unlock these data to improve forecasts.
Benoit Montpetit, Joshua King, Julien Meloche, Chris Derksen, Paul Siqueira, J. Max Adam, Peter Toose, Mike Brady, Anna Wendleder, Vincent Vionnet, and Nicolas R. Leroux
The Cryosphere, 18, 3857–3874, https://doi.org/10.5194/tc-18-3857-2024, https://doi.org/10.5194/tc-18-3857-2024, 2024
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This paper validates the use of free open-source models to link distributed snow measurements to radar measurements in the Canadian Arctic. Using multiple radar sensors, we can decouple the soil from the snow contribution. We then retrieve the "microwave snow grain size" to characterize the interaction between the snow mass and the radar signal. This work supports future satellite mission development to retrieve snow mass information such as the future Canadian Terrestrial Snow Mass Mission.
Randall Bonnell, Daniel McGrath, Jack Tarricone, Hans-Peter Marshall, Ella Bump, Caroline Duncan, Stephanie Kampf, Yunling Lou, Alex Olsen-Mikitowicz, Megan Sears, Keith Williams, Lucas Zeller, and Yang Zheng
The Cryosphere, 18, 3765–3785, https://doi.org/10.5194/tc-18-3765-2024, https://doi.org/10.5194/tc-18-3765-2024, 2024
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Snow provides water for billions of people, but the amount of snow is difficult to detect remotely. During the 2020 and 2021 winters, a radar was flown over mountains in Colorado, USA, to measure the amount of snow on the ground, while our team collected ground observations to test the radar technique’s capabilities. The technique yielded accurate measurements of the snowpack that had good correlation with ground measurements, making it a promising application for the upcoming NISAR satellite.
Jordan N. Herbert, Mark S. Raleigh, and Eric E. Small
The Cryosphere, 18, 3495–3512, https://doi.org/10.5194/tc-18-3495-2024, https://doi.org/10.5194/tc-18-3495-2024, 2024
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Automated stations measure snow properties at a single point but are frequently used to validate data that represent much larger areas. We use lidar snow depth data to see how often the mean snow depth surrounding a snow station is within 10 cm of the snow station depth at different scales. We found snow stations overrepresent the area-mean snow depth in ~ 50 % of cases, but the direction of bias at a site is temporally consistent, suggesting a site could be calibrated to the surrounding area.
Isis Brangers, Hans-Peter Marshall, Gabrielle De Lannoy, Devon Dunmire, Christian Mätzler, and Hans Lievens
The Cryosphere, 18, 3177–3193, https://doi.org/10.5194/tc-18-3177-2024, https://doi.org/10.5194/tc-18-3177-2024, 2024
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To better understand the interactions between C-band radar waves and snow, a tower-based experiment was set up in the Idaho Rocky Mountains. The reflections were collected in the time domain to measure the backscatter profile from the various snowpack and ground surface layers. The results demonstrate that C-band radar is sensitive to seasonal patterns in snow accumulation but that changes in microstructure, stratigraphy and snow wetness may complicate satellite-based snow depth retrievals.
James Dillon, Christopher Donahue, Evan Schehrer, Karl Birkeland, and Kevin Hammonds
The Cryosphere, 18, 2557–2582, https://doi.org/10.5194/tc-18-2557-2024, https://doi.org/10.5194/tc-18-2557-2024, 2024
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Surface hoar crystals are snow grains that form when vapor deposits on a snow surface. They create a weak layer in the snowpack that can cause large avalanches to occur. Thus, determining when and where surface hoar forms is a lifesaving matter. Here, we developed a means of mapping surface hoar using remote-sensing technologies. We found that surface hoar displayed heightened texture, hence the variability of brightness. Using this, we created surface hoar maps with an accuracy upwards of 95 %.
Steven J. Pestana, C. Chris Chickadel, and Jessica D. Lundquist
The Cryosphere, 18, 2257–2276, https://doi.org/10.5194/tc-18-2257-2024, https://doi.org/10.5194/tc-18-2257-2024, 2024
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We compared infrared images taken by GOES-R satellites of an area with snow and forests against surface temperature measurements taken on the ground, from an aircraft, and by another satellite. We found that GOES-R measured warmer temperatures than the other measurements, especially in areas with more forest and when the Sun was behind the satellite. From this work, we learned that the position of the Sun and surface features such as trees that can cast shadows impact GOES-R infrared images.
Jiahui Xu, Yao Tang, Linxin Dong, Shujie Wang, Bailang Yu, Jianping Wu, Zhaojun Zheng, and Yan Huang
The Cryosphere, 18, 1817–1834, https://doi.org/10.5194/tc-18-1817-2024, https://doi.org/10.5194/tc-18-1817-2024, 2024
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Understanding snow phenology (SP) and its possible feedback are important. We reveal spatiotemporal heterogeneous SP on the Tibetan Plateau (TP) and the mediating effects from meteorological, topographic, and environmental factors on it. The direct effects of meteorology on SP are much greater than the indirect effects. Topography indirectly effects SP, while vegetation directly effects SP. This study contributes to understanding past global warming and predicting future trends on the TP.
Sonia Dupuis, Frank-Michael Göttsche, and Stefan Wunderle
EGUsphere, https://doi.org/10.5194/egusphere-2024-857, https://doi.org/10.5194/egusphere-2024-857, 2024
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The Arctic experienced pronounced warming throughout the last decades. This warming threatens ecosystems, vegetation dynamics, snow cover duration, and permafrost. Traditional monitoring methods like stations and climate models lack the detail needed. Land surface temperature (LST) data derived from satellites offers high spatial and temporal coverage, perfect for studying changes in the Arctic. In particular, LST information from AVHRR provides a 40-year record, valuable for analyzing trends.
Jinmei Pan, Michael Durand, Juha Lemmetyinen, Desheng Liu, and Jiancheng Shi
The Cryosphere, 18, 1561–1578, https://doi.org/10.5194/tc-18-1561-2024, https://doi.org/10.5194/tc-18-1561-2024, 2024
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We developed an algorithm to estimate snow mass using X- and dual Ku-band radar, and tested it in a ground-based experiment. The algorithm, the Bayesian-based Algorithm for SWE Estimation (BASE) using active microwaves, achieved an RMSE of 30 mm for snow water equivalent. These results demonstrate the potential of radar, a highly promising sensor, to map snow mass at high spatial resolution.
Siddharth Singh, Michael Durand, Edward Kim, and Ana P. Barros
The Cryosphere, 18, 747–773, https://doi.org/10.5194/tc-18-747-2024, https://doi.org/10.5194/tc-18-747-2024, 2024
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Seasonal snowfall accumulation plays a critical role in climate. The water stored in it is measured by the snow water equivalent (SWE), the amount of water released after completely melting. We demonstrate a Bayesian physical–statistical framework to estimate SWE from airborne X- and Ku-band synthetic aperture radar backscatter measurements constrained by physical snow hydrology and radar models. We explored spatial resolutions and vertical structures that agree well with ground observations.
Shadi Oveisgharan, Robert Zinke, Zachary Hoppinen, and Hans Peter Marshall
The Cryosphere, 18, 559–574, https://doi.org/10.5194/tc-18-559-2024, https://doi.org/10.5194/tc-18-559-2024, 2024
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The seasonal snowpack provides water resources to billions of people worldwide. Large-scale mapping of snow water equivalent (SWE) with high resolution is critical for many scientific and economics fields. In this work we used the radar remote sensing interferometric synthetic aperture radar (InSAR) to estimate the SWE change between 2 d. The error in the estimated SWE change is less than 2 cm for in situ stations. Additionally, the retrieved SWE using InSAR is correlated with lidar snow depth.
Dhiraj Kumar Singh, Srinivasarao Tanniru, Kamal Kant Singh, Harendra Singh Negi, and RAAJ Ramsankaran
The Cryosphere, 18, 451–474, https://doi.org/10.5194/tc-18-451-2024, https://doi.org/10.5194/tc-18-451-2024, 2024
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In situ techniques for snow depth (SD) measurement are not adequate to represent the spatiotemporal variability in SD in the Western Himalayan region. Therefore, this study focuses on the high-resolution mapping of daily snow depth in the Indian Western Himalayan region using passive microwave remote-sensing-based algorithms. Overall, the proposed multifactor SD models demonstrated substantial improvement compared to the operational products. However, there is a scope for further improvement.
Michael Durand, Joel T. Johnson, Jack Dechow, Leung Tsang, Firoz Borah, and Edward J. Kim
The Cryosphere, 18, 139–152, https://doi.org/10.5194/tc-18-139-2024, https://doi.org/10.5194/tc-18-139-2024, 2024
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Seasonal snow accumulates each winter, storing water to release later in the year and modulating both water and energy cycles, but the amount of seasonal snow is one of the most poorly measured components of the global water cycle. Satellite concepts to monitor snow accumulation have been proposed but not selected. This paper shows that snow accumulation can be measured using radar, and that (contrary to previous studies) does not require highly accurate information about snow microstructure.
Jennika Hammar, Inge Grünberg, Steven V. Kokelj, Jurjen van der Sluijs, and Julia Boike
The Cryosphere, 17, 5357–5372, https://doi.org/10.5194/tc-17-5357-2023, https://doi.org/10.5194/tc-17-5357-2023, 2023
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Roads on permafrost have significant environmental effects. This study assessed the Inuvik to Tuktoyaktuk Highway (ITH) in Canada and its impact on snow accumulation, albedo and snowmelt timing. Our findings revealed that snow accumulation increased by up to 36 m from the road, 12-day earlier snowmelt within 100 m due to reduced albedo, and altered snowmelt patterns in seemingly undisturbed areas. Remote sensing aids in understanding road impacts on permafrost.
Anssi Rauhala, Leo-Juhani Meriö, Anton Kuzmin, Pasi Korpelainen, Pertti Ala-aho, Timo Kumpula, Bjørn Kløve, and Hannu Marttila
The Cryosphere, 17, 4343–4362, https://doi.org/10.5194/tc-17-4343-2023, https://doi.org/10.5194/tc-17-4343-2023, 2023
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Snow conditions in the Northern Hemisphere are rapidly changing, and information on snow depth is important for decision-making. We present snow depth measurements using different drones throughout the winter at a subarctic site. Generally, all drones produced good estimates of snow depth in open areas. However, differences were observed in the accuracies produced by the different drones, and a reduction in accuracy was observed when moving from an open mire area to forest-covered areas.
Leo-Juhani Meriö, Anssi Rauhala, Pertti Ala-aho, Anton Kuzmin, Pasi Korpelainen, Timo Kumpula, Bjørn Kløve, and Hannu Marttila
The Cryosphere, 17, 4363–4380, https://doi.org/10.5194/tc-17-4363-2023, https://doi.org/10.5194/tc-17-4363-2023, 2023
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Information on seasonal snow cover is essential in understanding snow processes and operational forecasting. We study the spatiotemporal variability in snow depth and snow processes in a subarctic, boreal landscape using drones. We identified multiple theoretically known snow processes and interactions between snow and vegetation. The results highlight the applicability of the drones to be used for a detailed study of snow depth in multiple land cover types and snow–vegetation interactions.
Kirsty Wivell, Stuart Fox, Melody Sandells, Chawn Harlow, Richard Essery, and Nick Rutter
The Cryosphere, 17, 4325–4341, https://doi.org/10.5194/tc-17-4325-2023, https://doi.org/10.5194/tc-17-4325-2023, 2023
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Satellite microwave observations improve weather forecasts, but to use these observations in the Arctic, snow emission must be known. This study uses airborne and in situ snow observations to validate emissivity simulations for two- and three-layer snowpacks at key frequencies for weather prediction. We assess the impact of thickness, grain size and density in key snow layers, which will help inform development of physical snow models that provide snow profile input to emissivity simulations.
Eunsang Cho, Carrie M. Vuyovich, Sujay V. Kumar, Melissa L. Wrzesien, and Rhae Sung Kim
The Cryosphere, 17, 3915–3931, https://doi.org/10.5194/tc-17-3915-2023, https://doi.org/10.5194/tc-17-3915-2023, 2023
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As a future snow mission concept, active microwave sensors have the potential to measure snow water equivalent (SWE) in deep snowpack and forested environments. We used a modeling and data assimilation approach (a so-called observing system simulation experiment) to quantify the usefulness of active microwave-based SWE retrievals over western Colorado. We found that active microwave sensors with a mature retrieval algorithm can improve SWE simulations by about 20 % in the mountainous domain.
César Deschamps-Berger, Simon Gascoin, David Shean, Hannah Besso, Ambroise Guiot, and Juan Ignacio López-Moreno
The Cryosphere, 17, 2779–2792, https://doi.org/10.5194/tc-17-2779-2023, https://doi.org/10.5194/tc-17-2779-2023, 2023
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The estimation of the snow depth in mountains is hard, despite the importance of the snowpack for human societies and ecosystems. We measured the snow depth in mountains by comparing the elevation of points measured with snow from the high-precision altimetric satellite ICESat-2 to the elevation without snow from various sources. Snow depths derived only from ICESat-2 were too sparse, but using external airborne/satellite products results in spatially richer and sufficiently precise snow depths.
Edward H. Bair, Jeff Dozier, Karl Rittger, Timbo Stillinger, William Kleiber, and Robert E. Davis
The Cryosphere, 17, 2629–2643, https://doi.org/10.5194/tc-17-2629-2023, https://doi.org/10.5194/tc-17-2629-2023, 2023
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To test the title question, three snow cover products were used in a snow model. Contrary to previous work, higher-spatial-resolution snow cover products only improved the model accuracy marginally. Conclusions are as follows: (1) snow cover and albedo from moderate-resolution sensors continue to provide accurate forcings and (2) finer spatial and temporal resolutions are the future for Earth observations, but existing moderate-resolution sensors still offer value.
Valentina Premier, Carlo Marin, Giacomo Bertoldi, Riccardo Barella, Claudia Notarnicola, and Lorenzo Bruzzone
The Cryosphere, 17, 2387–2407, https://doi.org/10.5194/tc-17-2387-2023, https://doi.org/10.5194/tc-17-2387-2023, 2023
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The large amount of information regularly acquired by satellites can provide important information about SWE. We explore the use of multi-source satellite data, in situ observations, and a degree-day model to reconstruct daily SWE at 25 m. The results show spatial patterns that are consistent with the topographical features as well as with a reference product. Being able to also reproduce interannual variability, the method has great potential for hydrological and ecological applications.
Jack Tarricone, Ryan W. Webb, Hans-Peter Marshall, Anne W. Nolin, and Franz J. Meyer
The Cryosphere, 17, 1997–2019, https://doi.org/10.5194/tc-17-1997-2023, https://doi.org/10.5194/tc-17-1997-2023, 2023
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Mountain snowmelt provides water for billions of people across the globe. Despite its importance, we cannot currently measure the amount of water in mountain snowpacks from satellites. In this research, we test the ability of an experimental snow remote sensing technique from an airplane in preparation for the same sensor being launched on a future NASA satellite. We found that the method worked better than expected for estimating important snowpack properties.
Sara E. Darychuk, Joseph M. Shea, Brian Menounos, Anna Chesnokova, Georg Jost, and Frank Weber
The Cryosphere, 17, 1457–1473, https://doi.org/10.5194/tc-17-1457-2023, https://doi.org/10.5194/tc-17-1457-2023, 2023
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We use synthetic-aperture radar (SAR) and optical observations to map snowmelt timing and duration on the watershed scale. We found that Sentinel-1 SAR time series can be used to approximate snowmelt onset over diverse terrain and land cover types, and we present a low-cost workflow for SAR processing over large, mountainous regions. Our approach provides spatially distributed observations of the snowpack necessary for model calibration and can be used to monitor snowmelt in ungauged basins.
Vasana Dharmadasa, Christophe Kinnard, and Michel Baraër
The Cryosphere, 17, 1225–1246, https://doi.org/10.5194/tc-17-1225-2023, https://doi.org/10.5194/tc-17-1225-2023, 2023
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This study highlights the successful usage of UAV lidar to monitor small-scale snow depth distribution. Our results show that underlying topography and wind redistribution of snow along forest edges govern the snow depth variability at agro-forested sites, while forest structure variability dominates snow depth variability in the coniferous environment. This emphasizes the importance of including and better representing these processes in physically based models for accurate snowpack estimates.
Ruben Urraca and Nadine Gobron
The Cryosphere, 17, 1023–1052, https://doi.org/10.5194/tc-17-1023-2023, https://doi.org/10.5194/tc-17-1023-2023, 2023
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We evaluate the fitness of some of the longest satellite (NOAA CDR, 1966–2020) and reanalysis (ERA5, 1950–2020; ERA5-Land, 1950–2020) products currently available to monitor the Northern Hemisphere snow cover trends using 527 stations as the reference. We found different artificial trends and stepwise discontinuities in all the products that hinder the accurate monitoring of snow trends, at least without bias correction. The study also provides updates on the snow cover trends during 1950–2020.
Annett Bartsch, Helena Bergstedt, Georg Pointner, Xaver Muri, Kimmo Rautiainen, Leena Leppänen, Kyle Joly, Aleksandr Sokolov, Pavel Orekhov, Dorothee Ehrich, and Eeva Mariatta Soininen
The Cryosphere, 17, 889–915, https://doi.org/10.5194/tc-17-889-2023, https://doi.org/10.5194/tc-17-889-2023, 2023
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Rain-on-snow (ROS) events occur across many regions of the terrestrial Arctic in mid-winter. In extreme cases ice layers form which affect wildlife, vegetation and soils beyond the duration of the event. The fusion of multiple types of microwave satellite observations is suggested for the creation of a climate data record. Retrieval is most robust in the tundra biome, where records can be used to identify extremes and the results can be applied to impact studies at regional scale.
Pinja Venäläinen, Kari Luojus, Colleen Mortimer, Juha Lemmetyinen, Jouni Pulliainen, Matias Takala, Mikko Moisander, and Lina Zschenderlein
The Cryosphere, 17, 719–736, https://doi.org/10.5194/tc-17-719-2023, https://doi.org/10.5194/tc-17-719-2023, 2023
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Snow water equivalent (SWE) is a valuable characteristic of snow cover. In this research, we improve the radiometer-based GlobSnow SWE retrieval methodology by implementing spatially and temporally varying snow densities into the retrieval procedure. In addition to improving the accuracy of SWE retrieval, varying snow densities were found to improve the magnitude and seasonal evolution of the Northern Hemisphere snow mass estimate compared to the baseline product.
Dalei Hao, Gautam Bisht, Karl Rittger, Timbo Stillinger, Edward Bair, Yu Gu, and L. Ruby Leung
The Cryosphere, 17, 673–697, https://doi.org/10.5194/tc-17-673-2023, https://doi.org/10.5194/tc-17-673-2023, 2023
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We comprehensively evaluated the snow simulations in E3SM land model over the western United States in terms of spatial patterns, temporal correlations, interannual variabilities, elevation gradients, and change with forest cover of snow properties and snow phenology. Our study underscores the need for diagnosing model biases and improving the model representations of snow properties and snow phenology in mountainous areas for more credible simulation and future projection of mountain snowpack.
Timbo Stillinger, Karl Rittger, Mark S. Raleigh, Alex Michell, Robert E. Davis, and Edward H. Bair
The Cryosphere, 17, 567–590, https://doi.org/10.5194/tc-17-567-2023, https://doi.org/10.5194/tc-17-567-2023, 2023
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Understanding global snow cover is critical for comprehending climate change and its impacts on the lives of billions of people. Satellites are the best way to monitor global snow cover, yet snow varies at a finer spatial resolution than most satellite images. We assessed subpixel snow mapping methods across a spectrum of conditions using airborne lidar. Spectral-unmixing methods outperformed older operational methods and are ready to to advance snow cover mapping at the global scale.
Jilu Li, Fernando Rodriguez-Morales, Xavier Fettweis, Oluwanisola Ibikunle, Carl Leuschen, John Paden, Daniel Gomez-Garcia, and Emily Arnold
The Cryosphere, 17, 175–193, https://doi.org/10.5194/tc-17-175-2023, https://doi.org/10.5194/tc-17-175-2023, 2023
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Alaskan glaciers' loss of ice mass contributes significantly to ocean surface rise. It is important to know how deeply and how much snow accumulates on these glaciers to comprehend and analyze the glacial mass loss process. We reported the observed seasonal snow depth distribution from our radar data taken in Alaska in 2018 and 2021, developed a method to estimate the annual snow accumulation rate at Mt. Wrangell caldera, and identified transition zones from wet-snow zones to ablation zones.
Ghislain Picard, Henning Löwe, and Christian Mätzler
The Cryosphere, 16, 3861–3866, https://doi.org/10.5194/tc-16-3861-2022, https://doi.org/10.5194/tc-16-3861-2022, 2022
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Microwave satellite observations used to monitor the cryosphere require radiative transfer models for their interpretation. These models represent how microwaves are scattered by snow and ice. However no existing theory is suitable for all types of snow and ice found on Earth. We adapted a recently published generic scattering theory to snow and show how it may improve the representation of snows with intermediate densities (~500 kg/m3) and/or with coarse grains at high microwave frequencies.
Leung Tsang, Michael Durand, Chris Derksen, Ana P. Barros, Do-Hyuk Kang, Hans Lievens, Hans-Peter Marshall, Jiyue Zhu, Joel Johnson, Joshua King, Juha Lemmetyinen, Melody Sandells, Nick Rutter, Paul Siqueira, Anne Nolin, Batu Osmanoglu, Carrie Vuyovich, Edward Kim, Drew Taylor, Ioanna Merkouriadi, Ludovic Brucker, Mahdi Navari, Marie Dumont, Richard Kelly, Rhae Sung Kim, Tien-Hao Liao, Firoz Borah, and Xiaolan Xu
The Cryosphere, 16, 3531–3573, https://doi.org/10.5194/tc-16-3531-2022, https://doi.org/10.5194/tc-16-3531-2022, 2022
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Snow water equivalent (SWE) is of fundamental importance to water, energy, and geochemical cycles but is poorly observed globally. Synthetic aperture radar (SAR) measurements at X- and Ku-band can address this gap. This review serves to inform the broad snow research, monitoring, and application communities about the progress made in recent decades to move towards a new satellite mission capable of addressing the needs of the geoscience researchers and users.
Elisabeth D. Hafner, Patrick Barton, Rodrigo Caye Daudt, Jan Dirk Wegner, Konrad Schindler, and Yves Bühler
The Cryosphere, 16, 3517–3530, https://doi.org/10.5194/tc-16-3517-2022, https://doi.org/10.5194/tc-16-3517-2022, 2022
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Knowing where avalanches occur is very important information for several disciplines, for example avalanche warning, hazard zonation and risk management. Satellite imagery can provide such data systematically over large regions. In our work we propose a machine learning model to automate the time-consuming manual mapping. Additionally, we investigate expert agreement for manual avalanche mapping, showing that our network is equally as good as the experts in identifying avalanches.
Joëlle Voglimacci-Stephanopoli, Anna Wendleder, Hugues Lantuit, Alexandre Langlois, Samuel Stettner, Andreas Schmitt, Jean-Pierre Dedieu, Achim Roth, and Alain Royer
The Cryosphere, 16, 2163–2181, https://doi.org/10.5194/tc-16-2163-2022, https://doi.org/10.5194/tc-16-2163-2022, 2022
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Changes in the state of the snowpack in the context of observed global warming must be considered to improve our understanding of the processes within the cryosphere. This study aims to characterize an arctic snowpack using the TerraSAR-X satellite. Using a high-spatial-resolution vegetation classification, we were able to quantify the variability in snow depth, as well as the topographic soil wetness index, which provided a better understanding of the electromagnetic wave–ground interaction.
Jayson Eppler, Bernhard Rabus, and Peter Morse
The Cryosphere, 16, 1497–1521, https://doi.org/10.5194/tc-16-1497-2022, https://doi.org/10.5194/tc-16-1497-2022, 2022
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We introduce a new method for mapping changes in the snow water equivalent (SWE) of dry snow based on differences between time-repeated synthetic aperture radar (SAR) images. It correlates phase differences with variations in the topographic slope which allows the method to work without any "reference" targets within the imaged area and without having to numerically unwrap the spatial phase maps. This overcomes the key challenges faced in using SAR interferometry for SWE change mapping.
Sebastian Buchelt, Kirstine Skov, Kerstin Krøier Rasmussen, and Tobias Ullmann
The Cryosphere, 16, 625–646, https://doi.org/10.5194/tc-16-625-2022, https://doi.org/10.5194/tc-16-625-2022, 2022
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In this paper, we present a threshold and a derivative approach using Sentinel-1 synthetic aperture radar time series to capture the small-scale heterogeneity of snow cover (SC) and snowmelt. Thereby, we can identify start of runoff and end of SC as well as perennial snow and SC extent during melt with high spatiotemporal resolution. Hence, our approach could support monitoring of distribution patterns and hydrological cascading effects of SC from the catchment scale to pan-Arctic observations.
Hans Lievens, Isis Brangers, Hans-Peter Marshall, Tobias Jonas, Marc Olefs, and Gabriëlle De Lannoy
The Cryosphere, 16, 159–177, https://doi.org/10.5194/tc-16-159-2022, https://doi.org/10.5194/tc-16-159-2022, 2022
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Snow depth observations at high spatial resolution from the Sentinel-1 satellite mission are presented over the European Alps. The novel observations can improve our knowledge of seasonal snow mass in areas with complex topography, where satellite-based estimates are currently lacking, and benefit a number of applications including water resource management, flood forecasting, and numerical weather prediction.
Julien Meloche, Alexandre Langlois, Nick Rutter, Alain Royer, Josh King, Branden Walker, Philip Marsh, and Evan J. Wilcox
The Cryosphere, 16, 87–101, https://doi.org/10.5194/tc-16-87-2022, https://doi.org/10.5194/tc-16-87-2022, 2022
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To estimate snow water equivalent from space, model predictions of the satellite measurement (brightness temperature in our case) have to be used. These models allow us to estimate snow properties from the brightness temperature by inverting the model. To improve SWE estimate, we proposed incorporating the variability of snow in these model as it has not been taken into account yet. A new parameter (coefficient of variation) is proposed because it improved simulation of brightness temperature.
Christopher Donahue, S. McKenzie Skiles, and Kevin Hammonds
The Cryosphere, 16, 43–59, https://doi.org/10.5194/tc-16-43-2022, https://doi.org/10.5194/tc-16-43-2022, 2022
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The amount of water within a snowpack is important information for predicting snowmelt and wet-snow avalanches. From within a controlled laboratory, the optimal method for measuring liquid water content (LWC) at the snow surface or along a snow pit profile using near-infrared imagery was determined. As snow samples melted, multiple models to represent wet-snow reflectance were assessed against a more established LWC instrument. The best model represents snow as separate spheres of ice and water.
Zacharie Barrou Dumont, Simon Gascoin, Olivier Hagolle, Michaël Ablain, Rémi Jugier, Germain Salgues, Florence Marti, Aurore Dupuis, Marie Dumont, and Samuel Morin
The Cryosphere, 15, 4975–4980, https://doi.org/10.5194/tc-15-4975-2021, https://doi.org/10.5194/tc-15-4975-2021, 2021
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Since 2020, the Copernicus High Resolution Snow & Ice Monitoring Service has distributed snow cover maps at 20 m resolution over Europe in near-real time. These products are derived from the Sentinel-2 Earth observation mission, with a revisit time of 5 d or less (cloud-permitting). Here we show the good accuracy of the snow detection over a wide range of regions in Europe, except in dense forest regions where the snow cover is hidden by the trees.
Xiaodan Wu, Kathrin Naegeli, Valentina Premier, Carlo Marin, Dujuan Ma, Jingping Wang, and Stefan Wunderle
The Cryosphere, 15, 4261–4279, https://doi.org/10.5194/tc-15-4261-2021, https://doi.org/10.5194/tc-15-4261-2021, 2021
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We performed a comprehensive accuracy assessment of an Advanced Very High Resolution Radiometer global area coverage snow-cover extent time series dataset for the Hindu Kush Himalayan (HKH) region. The sensor-to-sensor consistency, the accuracy related to snow depth, elevations, land-cover types, slope, and aspects, and topographical variability were also explored. Our analysis shows an overall accuracy of 94 % in comparison with in situ station data, which is the same with MOD10A1 V006.
Pia Nielsen-Englyst, Jacob L. Høyer, Kristine S. Madsen, Rasmus T. Tonboe, Gorm Dybkjær, and Sotirios Skarpalezos
The Cryosphere, 15, 3035–3057, https://doi.org/10.5194/tc-15-3035-2021, https://doi.org/10.5194/tc-15-3035-2021, 2021
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The Arctic region is responding heavily to climate change, and yet, the air temperature of Arctic ice-covered areas is heavily under-sampled when it comes to in situ measurements. This paper presents a method for estimating daily mean 2 m air temperatures (T2m) in the Arctic from satellite observations of skin temperature, providing spatially detailed observations of the Arctic. The satellite-derived T2m product covers clear-sky snow and ice surfaces in the Arctic for the period 2000–2009.
Pinja Venäläinen, Kari Luojus, Juha Lemmetyinen, Jouni Pulliainen, Mikko Moisander, and Matias Takala
The Cryosphere, 15, 2969–2981, https://doi.org/10.5194/tc-15-2969-2021, https://doi.org/10.5194/tc-15-2969-2021, 2021
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Information about snow water equivalent (SWE) is needed in many applications, including climate model evaluation and forecasting fresh water availability. Space-borne radiometer observations combined with ground snow depth measurements can be used to make global estimates of SWE. In this study, we investigate the possibility of using sparse snow density measurement in satellite-based SWE retrieval and show that using the snow density information in post-processing improves SWE estimations.
Linlu Mei, Vladimir Rozanov, Christine Pohl, Marco Vountas, and John P. Burrows
The Cryosphere, 15, 2757–2780, https://doi.org/10.5194/tc-15-2757-2021, https://doi.org/10.5194/tc-15-2757-2021, 2021
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This paper presents a new snow property retrieval algorithm from satellite observations. This is Part 1 of two companion papers and shows the method description and sensitivity study. The paper investigates the major factors, including the assumptions of snow optical properties, snow particle distribution and atmospheric conditions (cloud and aerosol), impacting snow property retrievals from satellite observation.
Linlu Mei, Vladimir Rozanov, Evelyn Jäkel, Xiao Cheng, Marco Vountas, and John P. Burrows
The Cryosphere, 15, 2781–2802, https://doi.org/10.5194/tc-15-2781-2021, https://doi.org/10.5194/tc-15-2781-2021, 2021
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This paper presents a new snow property retrieval algorithm from satellite observations. This is Part 2 of two companion papers and shows the results and validation. The paper performs the new retrieval algorithm on the Sea and Land
Surface Temperature Radiometer (SLSTR) instrument and compares the retrieved snow properties with ground-based measurements, aircraft measurements and other satellite products.
Ahmad Hojatimalekshah, Zachary Uhlmann, Nancy F. Glenn, Christopher A. Hiemstra, Christopher J. Tennant, Jake D. Graham, Lucas Spaete, Arthur Gelvin, Hans-Peter Marshall, James P. McNamara, and Josh Enterkine
The Cryosphere, 15, 2187–2209, https://doi.org/10.5194/tc-15-2187-2021, https://doi.org/10.5194/tc-15-2187-2021, 2021
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We describe the relationships between snow depth, vegetation canopy, and local-scale processes during the snow accumulation period using terrestrial laser scanning (TLS). In addition to topography and wind, our findings suggest the importance of fine-scale tree structure, species type, and distributions on snow depth. Snow depth increases from the canopy edge toward the open areas, but wind and topographic controls may affect this trend. TLS data are complementary to wide-area lidar surveys.
Jennifer M. Jacobs, Adam G. Hunsaker, Franklin B. Sullivan, Michael Palace, Elizabeth A. Burakowski, Christina Herrick, and Eunsang Cho
The Cryosphere, 15, 1485–1500, https://doi.org/10.5194/tc-15-1485-2021, https://doi.org/10.5194/tc-15-1485-2021, 2021
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This pilot study describes a proof of concept for using lidar on an unpiloted aerial vehicle to map shallow snowpack (< 20 cm) depth in open terrain and forests. The 1 m2 resolution snow depth map, generated by subtracting snow-off from snow-on lidar-derived digital terrain models, consistently had 0.5 to 1 cm precision in the field, with a considerable reduction in accuracy in the forest. Performance depends on the point cloud density and the ground surface variability and vegetation.
Cited articles
Bark, R. H., Colby, B. G., and Dominguez, F.: Snow days? Snowmaking
adaptation and the future of low latitude, high elevation skiing in Arizona,
USA, Clim. Change, 102, 467–491, https://doi.org/10.1007/s10584-009-9708-x, 2010.
Bednarik, M., Magulova, B., Matys, M., and Marschalko, M.: Landslide
susceptibility assessment of the Kralovany–Liptovsky Mikulaš railway
case study, Phys. Chem. Earth, 35, 162–171,
https://doi.org/10.1016/j.pce.2009.12.002, 2010.
Bian, Z., Xu, Z., Xiao, L., Dong, H., and Xu, Q.: Selection of optimal
access point for offshore wind farm based on multi-objective decision
making, Int. J. Elec. Power, 103, 43–49,
https://doi.org/10.1016/j.ijepes.2018.05.025, 2018.
Brambilla, M., Pedrini, P., Rolando, A., and Chamberlain, D. E.: Climate
change will increase the potential conflict between skiing and
high-elevation bird species in the Alps, J. Biogeogr., 43, 2299–2309,
https://doi.org/10.1111/jbi.12796, 2016.
Buhalis, D.: Marketing the competitive destination of the future, Environ.
Manag., 21, 97–116, https://doi.org/10.1016/S0261-5177(99)00095-3, 2000.
Burt, J. W.: Developing restoration planting mixes for active ski slopes: A
multi-site reference community approach, Environ. Manage., 49, 636–648,
https://doi.org/10.1007/s00267-011-9797-y, 2012.
Burt, J. W. and Rice, K. J.: Not all ski slopes are created equal:
Disturbance intensity affects ecosystem properties, Ecol. Appl., 19,
2242–2253, https://doi.org/10.1890/08-0719.1, 2009.
Cai, W. Y., Di, H., and Liu, X. P.: Estimation of the spatial suitability of
winter tourism destinations based on copula functions, Int. J. Env. Res.
Pub. He., 16, 2–18, https://doi.org/10.3390/ijerph16020186, 2019.
Che, T., Li, X., Jin, R., Armstrong, R., and Zhang, T.: Snow depth derived
from passive microwave remote-sensing data in China, Ann. Glaciol., 49,
145–154, https://doi.org/10.3189/172756408787814690, 2008.
Crowe, R. B., McKay, G. A., and Baker, W. M.: The tourist and outdoor
recreation climate of Ontario, Vol. 1. Objectives and definitions of seasons
Atmospheric Environment Service, Environment Canada, Toronto, Canada, 1973.
Damm, A., Koeberl, J., and Prettenthaler, F.: Does artificial snow
production pay under future climate conditions? – A case study for a
vulnerable ski area in Austria, Tour. Manag., 43, 8–21,
https://doi.org/10.1016/j.tourman.2014.01.009, 2014.
Damm, A., Greuell, W., Landgren, O., and Prettenthaler, F.: Impacts of +2 ∘C global warming on winter tourism demand in Europe, Clim. Serv., 7, 31–46,
https://doi.org/10.1016/j.cliser.2016.07.003, 2017.
Dawson, J., Scott, D., and McBoyle, G.: Climate change analogue analysis of
ski tourism in the northeastern USA, Clim. Res., 39, 1–9,
https://doi.org/10.3354/cr00793, 2009.
De Freitas, C. R.: The climate-tourism relationship and its relevance to
climate change impact assessment, in: Tourism,
Recreation and Climate Change: International Perspectives, edited by: Hall, C. M. and Higham, J., Channelview
Press, UK, 2005.
Delgado, R., Sánchez-Marañón, M., Martín-García, J.
M., Aranda, V., Serrano-Bernardo, F., and Rosúa, J. L.: Impact of ski
pistes on soil properties: A case study from a mountainous area in the
Mediterranean region, Soil Use Manage., 23, 269–277,
https://doi.org/10.1111/j.1475-2743.2007.00093.x, 2007.
Dezsi, S., Nistor, M. M., Man, T., and Rusu, R.: The GIS assessment of a
winter sports resort location. Case study: Beliş District, Western
Carpathians, Carpath. J. Earth Env., 10, 223–230, 2015.
Doll, C. H., Muller, J.-P., and Elvidge, C. D.: Night-time imagery as a tool
for global mapping of socioeconomic parameters and greenhouse gas emissions,
Ambio, 29, 157–162, https://doi.org/10.1579/0044-7447-29.3.157, 2000.
Duglio, S. and Beltramo, R.: Environmental management and sustainable
labels in the ski industry: A critical review, Sustainability, 8, 1–13,
https://doi.org/10.3390/su8090851, 2016.
Eadington, W. R. and Redman, M.: Economics and tourism, Ann. Tour. Res.,
18, 41–56, https://doi.org/10.1016/0160-7383(91)90038-D, 1991.
Fukushima, T., Kureha, M., Ozaki, N., Fujimori, Y., and Harasawa, H.:
Influences of air temperature change on leisure industries: Case study on
ski activities, Mitig. Adapt. Strat. Clim. Chang., 7, 173–189,
https://doi.org/10.1023/A:1022803405470, 2002.
Geneletti, D.: Impact assessment of proposed ski areas: A GIS approach
integrating biological, physical and landscape indicators, Environ. Impact
Assess., 28, 116–130, https://doi.org/10.1016/j.eiar.2007.05.011, 2008.
Gilaberte-Búrdalo, M., López-Moreno, J. I., Morán-Tejeda, E.,
Jerez, S., Alonso-González, E., López-Martín, F., and
Pino-Otín, M. R.: Assessment of ski condition reliability in the
Spanish and Andorran Pyrenees for the second half of the 20th century, Appl.
Geogr., 79, 127–142, https://doi.org/10.1016/j.apgeog.2016.12.013, 2017.
Hall, D. K., Riggs, G. A., Salomonson, V. V., DiGirolamo, N. E., and Bayr, K.
J.: MODIS snow-cover products, Remote Sens. Environ., 83, 181–194,
https://doi.org/10.1016/s0034-4257(02)00095-0, 2002.
Hanzer, F., Marke, T., and Strasser, U.: Distributed, explicit modeling of
technical snow production for a ski area in the Schladming region (Austrian
Alps), Cold Reg. Sci. Tech., 108, 113–124,
https://doi.org/10.1016/j.coldregions.2014.08.003, 2014.
Hennessy, K. J., Whetton, P. H., Walsh, K., Smith, I. N., Bathols, J. M.,
Hutchinson, M., and Sharples, J.: Climate change effects on snow conditions
in mainland Australia and adaptation at ski resorts through snowmaking,
Clim. Res., 35, 255–270, https://doi.org/10.3354/cr00706, 2008.
Huang, X., Deng, J., Ma, X., Wang, Y., Feng, Q., Hao, X., and Liang, T.: Spatiotemporal dynamics of snow cover based on multi-source remote sensing data in China, The Cryosphere, 10, 2453–2463, https://doi.org/10.5194/tc-10-2453-2016, 2016.
Ji, Z. and Kang, S.: Projection of snow cover changes over china under RCP
scenarios, Clim. Dynam., 41, 589–600, https://doi.org/10.1007/s00382-012-1473-2, 2013.
Kaenzig, R., Rebetez, M., and Serquet, G.: Climate change adaptation of the
tourism sector in the Bolivian Andes, Tour. Geogr., 18, 111–128,
https://doi.org/10.1080/14616688.2016.1144642, 2016.
Lasanta, T., Laguna, M., and Vicente-Serrano, S. M.: Do tourism-based ski
resorts contribute to the homogeneous development of the Mediterranean
mountains? A case study in the Central Spanish Pyrenees, Tour. Manag., 28,
1326–1339, https://doi.org/10.1016/j.tourman.2007.01.003, 2007.
McKercher, B.: The impact of distance on tourism: a tourism geography law,
Tour. Geogr., 20, 905–909, https://doi.org/10.1080/14616688.2018.1434813, 2018.
Morales, L., Lang, F., and Mattar, C.: Mesoscale wind speed simulation using
CALMET model and reanalysis information: An application to wind potential,
Renew. Energ., 48, 57–71, https://doi.org/10.1016/j.renene.2012.04.048, 2012.
Morey, E.: The choice of ski areas: estimation of a generalized CES
preference ordering with characteristics, Rev. Econ. Stat., 66, 584–590,
https://doi.org/10.2307/1935982, 1984.
Morey, R.: Characteristics, consumer surplus, and new activities: A proposed
ski area, J. Pub. Econ., 26, 221–236, https://doi.org/10.1016/0047-2727(85)90006-4,
1985.
Mudryk, L. R., Derksen, C., Kushner, P. J., and Brown, R.: Characterization
of northern hemisphere snow water equivalent datasets, 1981–2010, J. Climate, 28, 8037–8051, https://doi.org/10.1175/JCLI-D-15-0229.1,
2015.
Pons, M., López-Moreno, J. I., Rosas-Casals, M., and Jover, È.: The
vulnerability of Pyrenean ski resorts to climate-induced changes in the
snowpack, Clim. Change, 131, 591–605, https://doi.org/10.1007/s10584-015-1400-8, 2015.
Pons-Pons, M., Johnson, P. A., Rosas-Casals, M., Sureda, B., and Jover, E.:
Modeling climate change effects on winter ski tourism in Andorra, Clim.
Res., 54, 197–207, https://doi.org/10.3354/cr01117, 2012.
Pourghasemi, H. R., Mohammady, M., and Pradhan, B.: Landslide susceptibility
mapping using index of entropy and conditional probability models in GIS:
Safarood Basin, Iran, Catena, 97, 71–84, https://doi.org/10.1016/j.catena.2012.05.005,
2012.
Ristić, R., Kašanin-Grubin, M., Radić, B., Nikić, Z., and
Vasiljević, N.: Land degradation at the Stara Planina ski resort,
Environ. Manag., 49, 580–592, https://doi.org/10.1007/s00267-012-9812-y, 2012.
Rutty, M. and Andrey, J.: Weather forecast use for winter recreation,
Weather Clim. Soc., 6, 293–306, https://doi.org/10.1175/WCAS-D-13-00052.1, 2014.
Rutty, M., Scott, D., Johnson, P., Pons, M., Steiger, R., and Vilella, M.:
Using ski industry response to climatic variability to assess climate change
risk: An analogue study in Eastern Canada, Tour. Manag., 58, 196–204,
https://doi.org/10.1016/j.tourman.2016.10.020, 2017.
Rybnikova, N. A. and Portnov, B. A.: Using light-at-night (LAN) satellite
data for identifying clusters of economic activities in Europe, Curr. Issues
Tour., 8, 307–334, https://doi.org/10.1007/s12076-015-0143-5, 2015.
Sato, C. F., Wood, J. T., Schroder, M., Michael, D. R., Osborne, W. S.,
Green, K., and Lindenmayer, D. B.: Designing for conservation outcomes: The
value of remnant habitat for reptiles on ski runs in subalpine landscapes,
Landscape Ecol., 29, 1225–1236, https://doi.org/10.1007/s10980-014-0058-3, 2014.
Scott, D., McBoyle, G., and Mills, B.: Climate change and the skiing
industry in southern Ontario (Canada): Exploring the importance of
snowmaking as a technical adaptation, Clim. Res., 23, 171–181,
https://doi.org/10.3354/cr023171, 2003.
Scott, D., Steiger, R., Rutty, M., Pons, M., and Johnson, P.: The
differential futures of ski tourism in Ontario (Canada) under climate
change: the limits of snowmaking adaptation, Curr. Issues Tour., 22, 1327–1342,
https://doi.org/10.1080/13683500.2017.1401984, 2017.
Scott, D., Steiger, R., Dannevig, H., and Aall, C.: Climate change and the
future of the Norwegian alpine ski industry, Curr. Issues Tour.,
https://doi.org/10.1080/13683500.2019.1608919, online first, 2019.
Silberman, J. A. and Rees, P. W.: Reinventing mountain settlements: A GIS
model for identifying possible ski towns in the U.S. Rocky Mountains, Appl.
Geogr., 30, 36–49, https://doi.org/10.1016/j.apgeog.2009.10.005, 2010.
Spandre, P., François, H., Thibert, E., Morin, S., and George-Marcelpoil, E.: Determination of snowmaking efficiency on a ski slope from observations and modelling of snowmaking events and seasonal snow accumulation, The Cryosphere, 11, 891–909, https://doi.org/10.5194/tc-11-891-2017, 2017.
Spulerova, J., Gajdoš, P., Matušicová, N., Krnáčová,
Z., and Kenderessy, P.: Sustainable tourism development in a selected area
of the low tatras national park – landscape planning versus urban planning,
Carpath. J. Earth Envi., 11, 485–496, 2016.
Srdjevic, B., Medeiros, Y. D. P., and Faria, A. S.: An Objective
Multi-Criteria Evaluation of Water Management Scenarios, Water Resour.
Manag., 18, 35–54, https://doi.org/10.1023/b:warm.0000015348.88832.52, 2004.
Steiger, R.: The impact of climate change on ski season length and
snowmaking requirements in Tyrol, Austria, Clim. Res., 43, 251–262,
https://doi.org/10.3354/cr00941, 2010.
Steiger, R.: Scenarios for skiing tourism in Austria: Integrating
demographics with an analysis of climate change, J. Sustain. Tour., 20,
867–882, https://doi.org/10.1080/09669582.2012.680464, 2012.
Steiger, R. and Abegg, B.: Ski areas' competitiveness in the light of
climate change: Comparative analysis in the Eastern Alps, in: Tourism in
Transitions, edited by: Müller, D. K. and Więckowski, M., Springer
International Publishing, Cham, Switzerland, 187–199, 2018.
Steiger, R. and Stötter, J.: Climate change impact assessment of ski
tourism in Tyrol, Tour. Geogr., 15, 577–600,
https://doi.org/10.1080/14616688.2012.762539, 2013.
Steiger, R., Scott, D., Abegg, B., Pons, M., and Aall, C.: A critical review
of climate change risk for ski tourism, Curr. Issues Tour., 22, 1343–1379,
https://doi.org/10.1080/13683500.2017.1410110, 2017.
Tang, Z.: An integrated approach to evaluating the coupling coordination
between tourism and the environment, Tour. Manag., 46, 11–19,
https://doi.org/10.1016/j.tourman.2014.06.001, 2015.
Tervo, K.: The operational and regional vulnerability of winter tourism to
climate variability and change: The case of the Finnish nature-based tourism
entrepreneurs, Scand. J. Hosp. Tour., 8, 317–332,
https://doi.org/10.1080/15022250802553696, 2008.
Tervo-Kankare, K., Kaján, E., and Saarinen, J.: Costs and benefits of
environmental change: tourism industry's responses in Arctic Finland, Tour.
Geogr., 20, 202–223, https://doi.org/10.1080/14616688.2017.1375973, 2017.
Tolvanen, A. and Kangas, K.: Tourism, biodiversity and protected areas –
Review from northern Fennoscandia, J. Environ. Manag., 169, 58–66,
https://doi.org/10.1016/j.jenvman.2015.12.011, 2016.
Tsuyuzaki, S.: Environmental deterioration resulting from ski-resort
construction in Japan, Environ. Conserv., 21, 121–125,
https://doi.org/10.1017/S0376892900024541, 1994.
Vanat, L.: 2018 International Report on Snow & Mountain Tourism: Overview
of the key industry figures for ski resorts, Genève, available at:
https://www.thebookedition.com/fr/2018-international-report-on-snow-p-357878.html, last access: 17 May 2019.
Verfaillie, D., Lafaysse, M., Déqué, M., Eckert, N., Lejeune, Y., and Morin, S.: Multi-component ensembles of future meteorological and natural snow conditions for 1500 m altitude in the Chartreuse mountain range, Northern French Alps, The Cryosphere, 12, 1249–1271, https://doi.org/10.5194/tc-12-1249-2018, 2018.
Vranešević, M., Belić, S., Kolaković, S., Kadović, R.,
and Bezdan, A.: Estimating Suitability of Localities for Biotechnical
Measures on Drainage System Application in Vojvodina, Irrig. Drain., 66,
129–140, https://doi.org/10.1002/ird.2024, 2016.
Wemple, B., Shanley, J., Denner, J., Ross, D., and Mills, K.: Hydrology and
water quality in two mountain basins of the northeastern US: assessing
baseline conditions and effects of ski area development, Hydrol. Process.,
21, 1639–1650, https://doi.org/10.1002/hyp.6700, 2007.
Wilson, G., Green, M., and Mack, K.: Historical Climate warming in the White
Mountains of New Hampshire (USA): Implications for snowmaking water needs at
ski areas, Mt. Res. Dev., 38, 164–171, https://doi.org/10.1659/MRD-JOURNAL-D-17-00117,
2018.
Wipf, S., Rixen, C., Fischer, M., Schmid, B., and Stoeckli, V.: Effects of
ski piste preparation on alpine vegetation, J. Appl. Ecol., 42, 306–316,
https://doi.org/10.1111/j.1365-2664.2005.01011.x, 2005.
Wu, J. and Gao, X.: A gridded daily observation dataset over China region and
comparison with the other datasets, Chinese J. Geophys.-CH, 56, 1102–1111,
https://doi.org/10.6038/cjg20130406, 2013 (in Chinese).
Young, I.: Public-private sector cooperation: Enhancing tourism
competitiveness, Ann. Tour. Res., 29, 573–574,
https://doi.org/10.1016/S0160-7383(01)00056-1, 2002.
Zhao, N., Currit, N., and Samson, E.: Net primary production and gross domestic product in China derived from satellite imagery, Ecol. Econ., 70, 921–928, https://doi.org/10.1016/j.ecolecon.2010.12.023, 2011.
Zhao, N., Liu, Y., Cao, G., Samson, E. L., and Zhang, J.: Forecasting
China's GDP at the pixel level using nighttime lights time series and
population images, GISci. Remote Sens., 54, 407–425,
https://doi.org/10.1080/15481603.2016.1276705, 2017.
Zhou, B., Wang, Z., Shi, Y., Xu, Y., and Han, Z.: Historical and Future
Changes of Snowfall Events in China under a Warming Background, J. Climate,
31, 5873–5889, https://doi.org/10.1175/jcli-d-17-0428.1, 2018.
Short summary
The Chinese ski industry is rapidly booming driven by enormous market demand and government support with the coming 2022 Beijing Winter Olympics. We evaluate the locational suitability of ski areas in China by integrating the natural and socioeconomic conditions. Corresponding development strategies for decision-makers are proposed based on the multi-criteria metrics, which will be extended to incorporate potential influences from future climate change and socioeconomic development.
The Chinese ski industry is rapidly booming driven by enormous market demand and government...