Articles | Volume 17, issue 4
https://doi.org/10.5194/tc-17-1457-2023
© Author(s) 2023. 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-17-1457-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
05 Apr 2023
Research article |
| 05 Apr 2023
| 05 Apr 2023
Snowmelt characterization from optical and synthetic-aperture radar observations in the La Joie Basin, British Columbia
Sara E. Darychuk
CORRESPONDING AUTHOR
Department of Geography, Earth and Environmental Sciences, University of Northern British Columbia, Prince George, British Colombia, V2N 4Z9, Canada
Joseph M. Shea
Department of Geography, Earth and Environmental Sciences, University of Northern British Columbia, Prince George, British Colombia, V2N 4Z9, Canada
Brian Menounos
Department of Geography, Earth and Environmental Sciences, University of Northern British Columbia, Prince George, British Colombia, V2N 4Z9, Canada
Hakai Institute, Campbell River, British Columbia, V9W 0B7, Canada
Anna Chesnokova
Department of Geography, Earth and Environmental Sciences, University of Northern British Columbia, Prince George, British Colombia, V2N 4Z9, Canada
Georg Jost
BC Hydro, Burnaby, British Columbia, V3N 4X8, Canada
Frank Weber
BC Hydro, Burnaby, British Columbia, V3N 4X8, Canada
Related authors
No articles found.
Etienne Berthier, Jérôme Lebreton, Delphine Fontannaz, Steven Hosford, Joaquín Muñoz-Cobo Belart, Fanny Brun, Liss M. Andreassen, Brian Menounos, and Charlotte Blondel
The Cryosphere, 18, 5551–5571, https://doi.org/10.5194/tc-18-5551-2024, https://doi.org/10.5194/tc-18-5551-2024, 2024
Short summary
Short summary
Repeat elevation measurements are crucial for monitoring glacier health and to understand how glaciers affect river flows and sea level. Until recently, high-resolution elevation data were mostly available for polar regions and High Mountain Asia. Our project, the Pléiades Glacier Observatory, now provides high-resolution topographies of 140 glacier sites worldwide. This is a novel and open dataset to monitor the impact of climate change on glaciers at high resolution and accuracy.
Adam C. Hawkins, Brent M. Goehring, and Brian Menounos
EGUsphere, https://doi.org/10.5194/egusphere-2024-2900, https://doi.org/10.5194/egusphere-2024-2900, 2024
Short summary
Short summary
We use a method called cosmogenic nuclide dating on bedrock surfaces and moraine boulders to determine the relative length of time an alpine glacier was larger or smaller than its current extent over the past 15 thousand years. We also discuss several important limitations to this method. This method gives information on the duration of past ice advances and is useful in areas without other materials that can be dated.
Brian Menounos, Alex Gardner, Caitlyn Florentine, and Andrew Fountain
The Cryosphere, 18, 889–894, https://doi.org/10.5194/tc-18-889-2024, https://doi.org/10.5194/tc-18-889-2024, 2024
Short summary
Short summary
Glaciers in western North American outside of Alaska are often overlooked in global studies because their potential to contribute to changes in sea level is small. Nonetheless, these glaciers represent important sources of freshwater, especially during times of drought. We show that these glaciers lost mass at a rate of about 12 Gt yr-1 for about the period 2013–2021; the rate of mass loss over the period 2018–2022 was similar.
Andrew G. Jones, Shaun A. Marcott, Andrew L. Gorin, Tori M. Kennedy, Jeremy D. Shakun, Brent M. Goehring, Brian Menounos, Douglas H. Clark, Matias Romero, and Marc W. Caffee
The Cryosphere, 17, 5459–5475, https://doi.org/10.5194/tc-17-5459-2023, https://doi.org/10.5194/tc-17-5459-2023, 2023
Short summary
Short summary
Mountain glaciers today are fractions of their sizes 140 years ago, but how do these sizes compare to the past 11,000 years? We find that four glaciers in the United States and Canada have reversed a long-term trend of growth and retreated to positions last occupied thousands of years ago. Notably, each glacier occupies a unique position relative to its long-term history. We hypothesize that unequal modern retreat has caused the glaciers to be out of sync relative to their Holocene histories.
Russell S. Smith, Caren C. Dymond, David L. Spittlehouse, Rita D. Winkler, and Georg Jost
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-248, https://doi.org/10.5194/hess-2023-248, 2023
Manuscript not accepted for further review
Short summary
Short summary
Hydrologic impacts of climate and landcover changes were modeled for a watershed. Combined impacts are offsetting for small peak flows, but additive for large events. Extreme summer low flows are predicted to become common. Low annual runoff is predicted to be more prevalent by 2050, then recover. The modeling suggests landcover change can mitigate low water supply. For managing watershed risk, strategies to reduce one risk may increase others, or effective strategies may become less effective.
Adam C. Hawkins, Brian Menounos, Brent M. Goehring, Gerald Osborn, Ben M. Pelto, Christopher M. Darvill, and Joerg M. Schaefer
The Cryosphere, 17, 4381–4397, https://doi.org/10.5194/tc-17-4381-2023, https://doi.org/10.5194/tc-17-4381-2023, 2023
Short summary
Short summary
Our study developed a record of glacier and climate change in the Mackenzie and Selwyn mountains of northwestern Canada over the past several hundred years. We estimate temperature change in this region using several methods and incorporate our glacier record with models of climate change to estimate how glacier volume in our study area has changed over time. Models of future glacier change show that our study area will become largely ice-free by the end of the 21st century.
Christophe Kinnard, Olivier Larouche, Michael N. Demuth, and Brian Menounos
The Cryosphere, 16, 3071–3099, https://doi.org/10.5194/tc-16-3071-2022, https://doi.org/10.5194/tc-16-3071-2022, 2022
Short summary
Short summary
This study implements a physically based, distributed glacier mass balance model in a context of sparse direct observations. Carefully constraining model parameters with ancillary data allowed for accurately reconstructing the mass balance of Saskatchewan Glacier over a 37-year period. We show that the mass balance sensitivity to warming is dominated by increased melting and that changes in glacier albedo and air humidity are the leading causes of increased glacier melt under warming scenarios.
Brent M. Goehring, Brian Menounos, Gerald Osborn, Adam Hawkins, and Brent Ward
Geochronology, 4, 311–322, https://doi.org/10.5194/gchron-4-311-2022, https://doi.org/10.5194/gchron-4-311-2022, 2022
Short summary
Short summary
We explored surface exposure dating with two nuclides to date two sets of moraines from the Yukon Territory and explain the reasoning for the observed ages. Results suggest multiple processes, including preservation of nuclides from a prior exposure period, and later erosion of the moraines is required to explain the data. Our results only allow for the older moraines to date to Marine Isotope Stage 3 or 4 and the younger moraines to date to the very earliest Holocene.
Dhiraj Pradhananga, John W. Pomeroy, Caroline Aubry-Wake, D. Scott Munro, Joseph Shea, Michael N. Demuth, Nammy Hang Kirat, Brian Menounos, and Kriti Mukherjee
Earth Syst. Sci. Data, 13, 2875–2894, https://doi.org/10.5194/essd-13-2875-2021, https://doi.org/10.5194/essd-13-2875-2021, 2021
Short summary
Short summary
This paper presents hydrological, meteorological, glaciological and geospatial data of Peyto Glacier Basin in the Canadian Rockies. They include high-resolution DEMs derived from air photos and lidar surveys and long-term hydrological and glaciological model forcing datasets derived from bias-corrected reanalysis products. These data are crucial for studying climate change and variability in the basin and understanding the hydrological responses of the basin to both glacier and climate change.
Vincent Vionnet, Christopher B. Marsh, Brian Menounos, Simon Gascoin, Nicholas E. Wayand, Joseph Shea, Kriti Mukherjee, and John W. Pomeroy
The Cryosphere, 15, 743–769, https://doi.org/10.5194/tc-15-743-2021, https://doi.org/10.5194/tc-15-743-2021, 2021
Short summary
Short summary
Mountain snow cover provides critical supplies of fresh water to downstream users. Its accurate prediction requires inclusion of often-ignored processes. A multi-scale modelling strategy is presented that efficiently accounts for snow redistribution. Model accuracy is assessed via airborne lidar and optical satellite imagery. With redistribution the model captures the elevation–snow depth relation. Redistribution processes are required to reproduce spatial variability, such as around ridges.
Anna Chesnokova, Michel Baraër, and Émilie Bouchard
The Cryosphere, 14, 4145–4164, https://doi.org/10.5194/tc-14-4145-2020, https://doi.org/10.5194/tc-14-4145-2020, 2020
Short summary
Short summary
In the context of a ubiquitous increase in winter discharge in cold regions, our results show that icing formations can help overcome the lack of direct observations in these remote environments and provide new insights into winter runoff generation. The multi-technique approach used in this study provided important information about the water sources active during the winter season in the headwaters of glacierized catchments.
Ben M. Pelto, Brian Menounos, and Shawn J. Marshall
The Cryosphere, 13, 1709–1727, https://doi.org/10.5194/tc-13-1709-2019, https://doi.org/10.5194/tc-13-1709-2019, 2019
Short summary
Short summary
Changes in glacier mass are the direct response to meteorological conditions during the accumulation and melt seasons. We derived multi-year, seasonal mass balance from airborne laser scanning surveys and compared them to field measurements for six glaciers in the Columbia and Rocky Mountains, Canada. Our method can accurately measure seasonal changes in glacier mass and can be easily adapted to derive seasonal mass change for entire mountain ranges.
Noel Fitzpatrick, Valentina Radić, and Brian Menounos
The Cryosphere, 13, 1051–1071, https://doi.org/10.5194/tc-13-1051-2019, https://doi.org/10.5194/tc-13-1051-2019, 2019
Short summary
Short summary
Measurements of surface roughness are rare on glaciers, despite being an important control for heat exchange with the atmosphere and surface melt. In this study, roughness values were determined through measurements at multiple locations and seasons and found to vary across glacier surfaces and to differ from commonly assumed values in melt models. Two new methods that remotely determine roughness from digital elevation models returned good performance and may facilitate improved melt modelling.
Fanny Brun, Patrick Wagnon, Etienne Berthier, Joseph M. Shea, Walter W. Immerzeel, Philip D. A. Kraaijenbrink, Christian Vincent, Camille Reverchon, Dibas Shrestha, and Yves Arnaud
The Cryosphere, 12, 3439–3457, https://doi.org/10.5194/tc-12-3439-2018, https://doi.org/10.5194/tc-12-3439-2018, 2018
Short summary
Short summary
On debris-covered glaciers, steep ice cliffs experience dramatically enhanced melt compared with the surrounding debris-covered ice. Using field measurements, UAV data and submetre satellite imagery, we estimate the cliff contribution to 2 years of ablation on a debris-covered tongue in Nepal, carefully taking into account ice dynamics. While they occupy only 7 to 8 % of the tongue surface, ice cliffs contributed to 23 to 24 % of the total tongue ablation.
Mekdes Ayalew Tessema, Valentina Radić, Brian Menounos, and Noel Fitzpatrick
The Cryosphere Discuss., https://doi.org/10.5194/tc-2018-154, https://doi.org/10.5194/tc-2018-154, 2018
Preprint withdrawn
Short summary
Short summary
To force physics-based models of glacier melt, meteorological variables and energy fluxes are needed at or in vicinity of the glaciers in question. In the absence of observations detailing these variables, the required forcing is commonly derived by downscaling the coarse-resolution output from global climate models (GCMs). This study investigates how the downscaled fields from GCMs can successfully resolve the local processes driving surface melting at three glaciers in British Columbia.
Valentina Radić, Brian Menounos, Joseph Shea, Noel Fitzpatrick, Mekdes A. Tessema, and Stephen J. Déry
The Cryosphere, 11, 2897–2918, https://doi.org/10.5194/tc-11-2897-2017, https://doi.org/10.5194/tc-11-2897-2017, 2017
Short summary
Short summary
Our overall goal is to improve the numerical modeling of glacier melt in order to better predict the future of glaciers in Western Canada and worldwide.
Most commonly used models rely on simplifications of processes that dictate melting at a glacier surface, in particular turbulent processes of heat exchange. We compared modeled against directly measured turbulent heat fluxes at a valley glacier in British Columbia, Canada, and found that more improvements are needed in all the tested models.
Emmy E. Stigter, Niko Wanders, Tuomo M. Saloranta, Joseph M. Shea, Marc F. P. Bierkens, and Walter W. Immerzeel
The Cryosphere, 11, 1647–1664, https://doi.org/10.5194/tc-11-1647-2017, https://doi.org/10.5194/tc-11-1647-2017, 2017
Koji Fujita, Hiroshi Inoue, Takeki Izumi, Satoru Yamaguchi, Ayako Sadakane, Sojiro Sunako, Kouichi Nishimura, Walter W. Immerzeel, Joseph M. Shea, Rijan B. Kayastha, Takanobu Sawagaki, David F. Breashears, Hiroshi Yagi, and Akiko Sakai
Nat. Hazards Earth Syst. Sci., 17, 749–764, https://doi.org/10.5194/nhess-17-749-2017, https://doi.org/10.5194/nhess-17-749-2017, 2017
Short summary
Short summary
We create multiple DEMs from photographs taken by helicopter and UAV and reveal the deposit volumes over the Langtang village, which was destroyed by avalanches induced by the Gorkha earthquake. Estimated snow depth in the source area is consistent with anomalously large snow depths observed at a neighboring glacier. Comparing with a long-term observational data, we conclude that this anomalous winter snow amplified the disaster induced by the 2015 Gorkha earthquake in Nepal.
Tobias Bolch, Tino Pieczonka, Kriti Mukherjee, and Joseph Shea
The Cryosphere, 11, 531–539, https://doi.org/10.5194/tc-11-531-2017, https://doi.org/10.5194/tc-11-531-2017, 2017
Short summary
Short summary
Previous geodetic estimates of glacier mass changes in the Karakoram have revealed balanced budgets or a possible slight mass gain since the year ∼ 2000. We used old US reconnaissance imagery and could show that glaciers in the Hunza River basin (Central Karakoram) experienced on average no significant mass changes also since the 1970s. Likewise the glaciers had heterogeneous behaviour with frequent surge activities during the last 40 years.
Christian Vincent, Patrick Wagnon, Joseph M. Shea, Walter W. Immerzeel, Philip Kraaijenbrink, Dibas Shrestha, Alvaro Soruco, Yves Arnaud, Fanny Brun, Etienne Berthier, and Sonam Futi Sherpa
The Cryosphere, 10, 1845–1858, https://doi.org/10.5194/tc-10-1845-2016, https://doi.org/10.5194/tc-10-1845-2016, 2016
Short summary
Short summary
Approximately 25 % of the glacierized area in the Everest region is covered by debris, yet the surface mass balance of these glaciers has not been measured directly. From terrestrial photogrammetry and unmanned aerial vehicle (UAV) methods, this study shows that the ablation is strongly reduced by the debris cover. The insulating effect of the debris cover has a larger effect on total mass loss than the enhanced ice ablation due to supraglacial ponds and exposed ice cliffs.
W. W. Immerzeel, N. Wanders, A. F. Lutz, J. M. Shea, and M. F. P. Bierkens
Hydrol. Earth Syst. Sci., 19, 4673–4687, https://doi.org/10.5194/hess-19-4673-2015, https://doi.org/10.5194/hess-19-4673-2015, 2015
Short summary
Short summary
The water resources of the upper Indus river basin (UIB) are important for millions of people, yet little is known about the rain and snow fall in the high-altitude regions because of the inaccessibility, the climatic complexity and the lack of observations. In this study we use mass balance of glaciers to reconstruct the amount of precipitation in the UIB and we conclude that this amount is much higher than previously thought.
J. M. Shea, W. W. Immerzeel, P. Wagnon, C. Vincent, and S. Bajracharya
The Cryosphere, 9, 1105–1128, https://doi.org/10.5194/tc-9-1105-2015, https://doi.org/10.5194/tc-9-1105-2015, 2015
Short summary
Short summary
A glacier mass balance and redistribution model that integrates field observations and downscaled climate fields is developed to examine glacier sensitivity to future climate in the Everest region of Nepal. The modelled sensitivity of glaciers to future climate change is high, and glacier mass loss is sustained through the 21st century for both middle- and high-emission scenarios. Projected temperature increases will expose large glacier areas to melt and reduce snow accumulations.
F. Brun, M. Dumont, P. Wagnon, E. Berthier, M. F. Azam, J. M. Shea, P. Sirguey, A. Rabatel, and Al. Ramanathan
The Cryosphere, 9, 341–355, https://doi.org/10.5194/tc-9-341-2015, https://doi.org/10.5194/tc-9-341-2015, 2015
M. J. Beedle, B. Menounos, and R. Wheate
The Cryosphere, 9, 65–80, https://doi.org/10.5194/tc-9-65-2015, https://doi.org/10.5194/tc-9-65-2015, 2015
R. S. Smith, R. D. Moore, M. Weiler, and G. Jost
Hydrol. Earth Syst. Sci., 18, 1835–1856, https://doi.org/10.5194/hess-18-1835-2014, https://doi.org/10.5194/hess-18-1835-2014, 2014
P. Wagnon, C. Vincent, Y. Arnaud, E. Berthier, E. Vuillermoz, S. Gruber, M. Ménégoz, A. Gilbert, M. Dumont, J. M. Shea, D. Stumm, and B. K. Pokhrel
The Cryosphere, 7, 1769–1786, https://doi.org/10.5194/tc-7-1769-2013, https://doi.org/10.5194/tc-7-1769-2013, 2013
J. M. Shea, B. Menounos, R. D. Moore, and C. Tennant
The Cryosphere, 7, 667–680, https://doi.org/10.5194/tc-7-667-2013, https://doi.org/10.5194/tc-7-667-2013, 2013
C. Tennant, B. Menounos, R. Wheate, and J. J. Clague
The Cryosphere, 6, 1541–1552, https://doi.org/10.5194/tc-6-1541-2012, https://doi.org/10.5194/tc-6-1541-2012, 2012
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
Tower-based C-band radar measurements of an alpine snowpack
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
Temperature-dominated spatiotemporal variability in snow phenology on the Tibetan Plateau from 2002 to 2022
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)
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
Mapping avalanches with satellites – evaluation of performance and completeness
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Elisabeth D. Hafner, Frank Techel, Silvan Leinss, and Yves Bühler
The Cryosphere, 15, 983–1004, https://doi.org/10.5194/tc-15-983-2021, https://doi.org/10.5194/tc-15-983-2021, 2021
Short summary
Short summary
Satellites prove to be very valuable for documentation of large-scale avalanche periods. To test reliability and completeness, which has not been satisfactorily verified before, we attempt a full validation of avalanches mapped from two optical sensors and one radar sensor. Our results demonstrate the reliability of high-spatial-resolution optical data for avalanche mapping, the suitability of radar for mapping of larger avalanches and the unsuitability of medium-spatial-resolution optical data.
Cited articles
Barnett, T. P., Adam, J. C., and Lettenmaier, D. P.:
Potential impacts of a warming climate on water availability in snow-dominated regions, Nature, 438, 303–309, 2005.
Bernier, P. Y.:
Microwave Remote Sensing of Snowpack Properties: Potential and Limitations, Hydrol. Res., 18, 1–20, https://doi.org/10.2166/nh.1987.0001, 1987.
Darychuk, S.: Export Sentinel-1 SAR Images for Snowmelt Analysis, Github [code], https://github.com/saradarychuk/Snowmelt-Characterization-from-Sentinel-1-SAR, last access: 31 March 2023a.
Darychuk, S.: Snow Disappearance Estimates in Glacierized Basins, Github [code], https://github.com/saradarychuk/Snowmelt-Characterization-from-Sentinel-1-SAR, last access: 31 March 2023b.
Deems, J. S., Fassnacht, S. R., and Elder, K. J.:
Fractal Distribution of Snow Depth from Lidar Data, J. Hydrometerol., 7, 285–297, 2006.
Déry, S. J., Stahl, K., Moore, R. D., Whitfield, P. H., Menounos, B., and Burford, J. E.:
Detection of runoff timing changes in pluvial, nival, and glacial rivers of western Canada: Western Canada Runoff Timing, Water Resour. Res., 45, W04426, https://doi.org/10.1029/2008wr006975, 2009.
Dingman, L. S.:
Physical Hydrology: Third Edition, Waveland Press, ISBN 10 1478611189, ISBN 13 9781478611189, 643 pp., 2015.
Elder, K., Dozier, J., and Michaelsen, J.:
Snow Accumulation and Distribution in an Alpine Watershed, Water Resour. Res., 27, 1541–1552, 1991.
European Space Agency:
Sentinel-1 toolbox, https://sentinel.esa.int/web/sentinel/toolboxes/sentinel-1 (last access: 29 June 2021), 2021.
European Space Agency:
Copernicus Sentinel-1B anomaly (4th update), 28 January 2022, https://sentinels.copernicus.eu/web/sentinel/-/copernicus-sentinel-1b-anomaly-4th-update/1.1?redirect=%2Fweb%2Fsentinel%2F-%2Fcopernicus-sentinel-1b-anomaly-updat-2%2F1.1%3Fredirect%3D%252Fweb%252Fsentinel%252Fmissions%252Fsentinel-1 (last access: 2 February 2022), 2022.
Floricioiu, D. and Rott, H.:
Seasonal and Short-Term Variability of Multifrequency, Polarimetric Radar Backscatter of Alpine Terrain From SIR-C/X-SAR and AIRSAR Data, IEEE T. Geosci. Remote, 39, 2634–2648, 2001.
Government of British Columbia: Automated Snow Weather Station Locations, Environmental Monitoring and Analysis Branch [data set], https://catalogue.data.gov.bc.ca/dataset/automated-snow-weather-station-locations (last access: 13 March 2023), 2017.
Google Earth Engine: Earth Engine Data Catalog, Google Earth Engine [data set], https://developers.google.com/earth-engine/datasets/catalog, last access: 31 March 2023.
Hall, D. K., Riggs, G. A., and Salomonson, V. V.:
Development of methods for mapping global snow cover using moderate resolution imaging spectroradiometer data, Remote Sens. Environ., 54, 127–140, https://doi.org/10.1016/0034-4257(95)00137-p, 1995.
Harpold, A. A., Molotch, N. P., Musselman, K. N., Bales, R. C., Kirchner, P. B., Litvak, M., and Brooks, P. D.:
Soil moisture response to snowmelt timing in mixed-conifer subalpine forests, Hydrol. Process., 29, 2782–2798, https://doi.org/10.1002/hyp.10400, 2015.
He, G., P. Xiao, X. Feng, X. Zhang, Z. Wang and Chen, N.:
Extracting snow cover in mountain areas based on SAR and optical data, IEEE Geosci. Remote S., 12, 1136–1140, 2015.
Kampf, S., Markus, J., Heath, J., and Moore, C.:
Snowmelt runoff and soil moisture dynamics on steep subalpine hillslopes, Hydrol. Process., 29, 712–723, https://doi.org/10.1002/hyp.10179, 2015.
Kinar, N. J. and Pomeroy, W.: Measurement of the physical properties of the snowpack. Rev. Geophys., 53, 481–544, https://doi.org/10.1002/2015RG000481, 2015.
Lewis, A., Lacey, J., Mecklenburg, S., Ross, J., Siqueira, A., Killough, B., Szantoi, Z., Tadono, T., Rosenavist, A., Goryl, P., Miranda, N., and Hosford, S.:
CEOS Analysis Ready Data for Land (CARD4L) Overview, in: IGARSS 2018 – 2018 IEEE Int. Geosci. and Remote Sens. Symp., 7407–7410, 2018.
Liu, H., Wang, L., and Jezek, K. C.:
Automated delineation of dry and melt snow zones in Antarctica using active and passive microwave observations from space, IEEE T. Geosci. Remote, 44, 2152–2163, https://doi.org/10.1109/tgrs.2006.872132, 2006.
Lopes, A., Nezry, E., Touzi, R., and Laur, H.:
Maximum A Posteriori Speckle Filtering And First Order Texture Models In Sar Images, 10th Annual International Symposium on Geoscience and Remote Sensing, 2409–2412, 1990.
Lopez-Moreno, J. I., Revuelto, J, Fassnacht, R., Azorn-Molina, C., Vicente-Serrano, S. M., Moran-Tejeda, E., and Sexstone, G. A.:
Snowpack Variability Across Various Spatio-Temporal Resolutions, Hydrol. Process., 29, 1213–1224, 2015.
Luce, C. H. and Holden, Z. A.:
Declining annual streamflow distributions in the Pacific Northwest United States, 1948–2006, Geophys. Res. Lett., 36, L16401, https://doi.org/10.1029/2009gl039407, 2009.
Luce, C. H., Tarboton, D. G., and Cooley, K. R.:
The Influence of the Spatial Distribution of Snow on Basin-Averaged Snowmelt, Hydrol. Process., 12, 1671–1683, 1998.
Lui, Y., X. Chen, Hao, J.-S., and Li, L.:
Snow cover estimation from MODIS and Sentinel-1 SAR data using machine learning algorithms in the western part of the Tianshan Mountains, J. Mt. Sci., 17, 884–897, 2020.
Manickam, S. and Barros, A.:
Parsing Synthetic Aperture Radar Measurements of Snow in Complex Terrain: Scaling Behaviour and Sensitivity to Snow Wetness and Landcover, Remote Sens.-Basel, 12, 483, https://doi.org/10.3390/rs12030483, 2020.
Marin, C., Bertoldi, G., Premier, V., Callegari, M., Brida, C., Hürkamp, K., Tschiersch, J., Zebisch, M., and Notarnicola, C.:
Use of Sentinel-1 radar observations to evaluate snowmelt dynamics in alpine regions, The Cryosphere, 14, 935–956, https://doi.org/10.5194/tc-14-935-2020, 2020.
Mätzler, C.:
Applications of the Interaction of Microwaves with the Natural Snow Cover, Routledge, 133 pp., https://doi.org/10.1080/02757258709532086, 1987.
Meybeck, M., Green, P., and Vörösmarty, C.:
A New Typology for Mountains and Other Relief Classes, Mt. Res. Dev., 21, 34–45, 2001.
Mote, P. W., Hamlet, A. F., Clark, M. P., and Lettenmaier, D. P.:
Declining Mountain Snowpack in Western North America, B. Am. Meteorol Soc., 21, 34–45, https://doi.org/10.1175/bams-86-1-39, 2005.
Muggeo, V. M.:
Interval Estimation for the Breakpoint in Segmented Regression: a Smoothed Score-Based Approach, Aust. NZ J. Stat., 59, 311–322, 2017.
Nagler, T. and Rott, H.:
Retrieval of wet snow by means of multitemporal SAR data, IEEE T. Geosci. Remote, 38, 754–765, 2000.
Nagler, T., Rott, H., Ripper, E., Bippus, G., and Hetzenecker, M.:
Advancements for Snowmelt Monitoring by Means of Sentinel-1 SAR, Remote Sens.-Basel, 8, 348, https://doi.org/10.3390/rs8040348, 2016.
Neumann, N. N., Derksen, C., Smith, C., and Goodison, B.:
Characterizing Local Scale Snow Cover Using Point Measurements During the Winter Season, Atmos. Ocean, 44, 257–259, 2006.
Park, S. E., Moon, W. M., and Potter, E.:
Assessment of Scattering Mechanism of Polarimetric SAR Signal From Mountainous Forest Areas, IEEE T. Geosci. Remote, 44, 4711–4719,
https://doi.org/10.1109/TGRS.2012.2194153, 2012.
Pelto, B. M., Menounos, B., and Marshall, S. J.: Multi-year evaluation of airborne geodetic surveys to estimate seasonal mass balance, Columbia and Rocky Mountains, Canada, The Cryosphere, 13, 1709–1727, https://doi.org/10.5194/tc-13-1709-2019, 2019.
Pivot, F. C.:
C-Band SAR Imagery for Snow-Cover Monitoring at Treeline, Churchill, Manitoba, Canada, Remote Sens.-Basel, 4, 2133–2155, https://doi.org/10.3390/rs4072133, 2012.
Pojar, J., Klinka, K., and Meidinger, D. V.:
Biogeoclimatic ecosystem classification in British Columbia, Forest Ecol. Manag., 22, 119–154, https://doi.org/10.1016/0378-1127(87)90100-9, 1987.
Premier, V., Marin, C., Steger, S., Notarnicola, C., and Bruzzone, L.:
A novel approach based on a hierarchical multiresolution analysis of optical time series to reconstruct the daily high resolution snow cover area, IEEE J. Sel. Top. Appl., 14, 9223–9240, 2021.
Rauscher, S. A., Pal, J. S., Diffenbaugh, N. S., and Benedetti, M. M.:
Future changes in snowmelt-driven runoff timing over the western US, Geophys. Res. Lett., 35, L16703, https://doi.org/10.1029/2008gl034424, 2008.
Revuelto, J., Alonso-Gonzalez, E., Gascoin, S., Rodriguez-Lopez, G., and Lopez-Moreno, J. I.:
Spatial downscaling of MODIS snow cover observations using Sentinel-2 snow products, Remote Sens.-Basel, 13, 4513, https://doi.org/10.3390/rs13224513, 2021.
RStudio Team:
RStudio: Integrated Development Environment for R, RStudio [code], PBC, Boston, MA, http://www.rstudio.com/ (last access: 13 March 2023), 2021.
Rumsey, C. A., Miller, M. P., and Sexstone, G. A.:
Relating Hydroclimatic Change to Streamflow, Baseflow, and Hydrologic Partitioning in the Upper Rio Grande Basin, 1980 to 2015, J. Hydrol., 584, 124715, https://doi.org/10.1016/j.jhydrol.2020.124715, 2020.
Schmid, L., Heilig, A., Mitterer, C., Jürg Schweizer, Maurer, H., Okorn, R., and Eisen, O.:
Continuous snowpack monitoring using upward-looking ground-penetrating radar technology, J. Glaciol., 60, 509–525, https://doi.org/10.3189/2014jog13j084, 2014.
Shea, J. M., Menounos, B., Moore, R. D., and Tennant, C.:
An approach to derive regional snow lines and glacier mass change from MODIS imagery, western North America, The Cryosphere, 7, 667–680, https://doi.org/10.5194/tc-7-667-2013, 2013.
Shi, J. and Dozier, J.:
Inferring snow wetness using C-band data from SIR-C's polarimetric synthetic aperture radar, IEEE T. Geosci. Remote, 33, 905–914, https://doi.org/10.1109/36.406676, 1995.
Stähli, M., Stacheder, M., Gustafsson, D., Schlaeger, S., Schneebeli, M., and Brandelik, A.:
A new in situ sensor for large-scale snow-cover monitoring, Ann. Glaciol., 38, 273–278, https://doi.org/10.3189/172756404781814933, 2004.
Vollrath, A., Mullissa, A., and Reiche, J.:
Angular-Based Radiometric Slope Correction for Sentinel-1 on Google Earth Engine, Remote Sens.-Basel, 12, 1867, https://doi.org/10.3390/rs12111867, 2020.
Wang, X. Y., Wang, J., Jiang, Z. Y., Li, H. Y., and Hao, X. H.:
An Effective Method for Snow-Cover Mapping of Dense Coniferous Forests in the Upper Heihe River Basin Using Landsat Operational Land Imager Data, Remote Sens.-Basel, 7, 17246–17257, https://doi.org/10.3390/rs71215882, 2015.
Westerling, A. L.:
Increasing western US forest wildfire activity: sensitivity to changes in the timing of spring, Philos. T. Roy. Soc. B, 371, 20150178, https://doi.org/10.1098/rstb.2015.0178, 2016.
Westerling, A. L., Hidalgo, H. G., Cayan, D. R., and Swetnam, T. W.:
Warming and earlier spring increase western U. S. forest wildfire activity, Science, 313, 940–943, 2006.
Wood, S. N.:
Minimizing Model Fitting Objectives that Contain Spurious Local Minima by Bootstrap Restarting, Biometrics, 57, 240–244, 2001.
Yamaguchi, S., Katsuchima, T., Sato, A., and Kumakura, T.: Water retention curve of snow with different grain sizes,Cold Reg. Sci. Technol., 64, 87–93, 2010.
Short summary
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.
We use synthetic-aperture radar (SAR) and optical observations to map snowmelt timing and...
