Articles | Volume 10, issue 6
https://doi.org/10.5194/tc-10-2559-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/tc-10-2559-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
02 Nov 2016
Research article |
| 02 Nov 2016
Accuracy of snow depth estimation in mountain and prairie environments by an unmanned aerial vehicle
Centre for Hydrology, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
Michael Schirmer
Centre for Hydrology, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
now at: WSL Institute for Snow and Avalanche Research SLF, Davos, Switzerland
John Pomeroy
Centre for Hydrology, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
Warren Helgason
Centre for Hydrology, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
Department of Civil, Geological, and Environmental Engineering, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
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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
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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.
Richard Essery, Hyungjun Kim, Libo Wang, Paul Bartlett, Aaron Boone, Claire Brutel-Vuilmet, Eleanor Burke, Matthias Cuntz, Bertrand Decharme, Emanuel Dutra, Xing Fang, Yeugeniy Gusev, Stefan Hagemann, Vanessa Haverd, Anna Kontu, Gerhard Krinner, Matthieu Lafaysse, Yves Lejeune, Thomas Marke, Danny Marks, Christoph Marty, Cecile B. Menard, Olga Nasonova, Tomoko Nitta, John Pomeroy, Gerd Schädler, Vladimir Semenov, Tatiana Smirnova, Sean Swenson, Dmitry Turkov, Nander Wever, and Hua Yuan
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Nikolas O. Aksamit and John W. Pomeroy
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Nicholas J. Kinar, John W. Pomeroy, and Bing Si
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Phillip Harder, John W. Pomeroy, and Warren D. Helgason
The Cryosphere, 14, 1919–1935, https://doi.org/10.5194/tc-14-1919-2020, https://doi.org/10.5194/tc-14-1919-2020, 2020
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Xing Fang and John W. Pomeroy
Hydrol. Earth Syst. Sci., 24, 2731–2754, https://doi.org/10.5194/hess-24-2731-2020, https://doi.org/10.5194/hess-24-2731-2020, 2020
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Hydrol. Earth Syst. Sci., 24, 2141–2165, https://doi.org/10.5194/hess-24-2141-2020, https://doi.org/10.5194/hess-24-2141-2020, 2020
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Christopher B. Marsh, John W. Pomeroy, and Howard S. Wheater
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Paul H. Whitfield, Philip D. A. Kraaijenbrink, Kevin R. Shook, and John W. Pomeroy
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2019-671, https://doi.org/10.5194/hess-2019-671, 2020
Revised manuscript not accepted
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Using partial year streamflow records a regime and change classification were produced for ~ 400 watersheds in the Saskatchewan and Mackenzie River basins, and trends in water storage and vegetation were detected from satellite imagery. Three areas show consistent changes; north of 60° [increased streamflow and basin greenness], in the western Boreal Plains [decreased streamflow and basin greenness], and across the Prairies [three different patterns of increased streamflow and basin wetness].
Michael Schirmer and John W. Pomeroy
Hydrol. Earth Syst. Sci., 24, 143–157, https://doi.org/10.5194/hess-24-143-2020, https://doi.org/10.5194/hess-24-143-2020, 2020
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The spatial distribution of snow water equivalent (SWE) and melt are important for hydrological applications in alpine terrain. We measured the spatial distribution of melt using a drone in very high resolution and could relate melt to topographic characteristics. Interestingly, melt and SWE were not related spatially, which influences the speed of areal melt out. We could explain this by melt varying over larger distances than SWE.
Kabir Rasouli, John W. Pomeroy, and Paul H. Whitfield
Hydrol. Earth Syst. Sci., 23, 4933–4954, https://doi.org/10.5194/hess-23-4933-2019, https://doi.org/10.5194/hess-23-4933-2019, 2019
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The combined effects of changes in climate, vegetation, and soils on mountain hydrology were modeled in three mountain basins. In the Yukon, an insignificant increasing effect of vegetation change on snow was found to be important enough to offset the climate change effect. In the Canadian Rockies, a combined effect of soil and climate change on runoff became significant, whereas their individual effects were not significant. Only vegetation change decreased runoff in the basin in Idaho.
Robert N. Armstrong, John W. Pomeroy, and Lawrence W. Martz
Hydrol. Earth Syst. Sci., 23, 4891–4907, https://doi.org/10.5194/hess-23-4891-2019, https://doi.org/10.5194/hess-23-4891-2019, 2019
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Digital and thermal images taken near midday were used to scale daily point observations of key factors driving actual-evaporation estimates across a complex Canadian Prairie landscape. Point estimates of actual evaporation agreed well with observed values via eddy covariance. Impacts of spatial variations on areal estimates were minor, and no covariance was found between model parameters driving the energy term. The methods can be applied further to improve land surface parameterisations.
Zilefac Elvis Asong, Mohamed Elshamy, Daniel Princz, Howard Wheater, John Pomeroy, Alain Pietroniro, and Alex Cannon
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2019-249, https://doi.org/10.5194/hess-2019-249, 2019
Publication in HESS not foreseen
Xing Fang, John W. Pomeroy, Chris M. DeBeer, Phillip Harder, and Evan Siemens
Earth Syst. Sci. Data, 11, 455–471, https://doi.org/10.5194/essd-11-455-2019, https://doi.org/10.5194/essd-11-455-2019, 2019
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Meteorological, snow survey, streamflow, and groundwater data are presented from Marmot Creek Research Basin, a small alpine-montane forest headwater catchment in the Alberta Rockies. It was heavily instrumented, experimented upon, and operated by several federal government agencies between 1962 and 1986 and was re-established starting in 2004 by the University of Saskatchewan Centre for Hydrology. These long-term legacy data serve to advance our knowledge of hydrology of the Canadian Rockies.
Kabir Rasouli, John W. Pomeroy, J. Richard Janowicz, Tyler J. Williams, and Sean K. Carey
Earth Syst. Sci. Data, 11, 89–100, https://doi.org/10.5194/essd-11-89-2019, https://doi.org/10.5194/essd-11-89-2019, 2019
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A set of hydrometeorological data including daily precipitation, hourly air temperature, humidity, wind, solar and net radiation, soil temperature, soil moisture, snow depth and snow water equivalent, streamflow and water level in a groundwater well, and geographical information system data are presented in this paper. This dataset was recorded at different elevation bands in Wolf Creek Research Basin, near Whitehorse, Yukon Territory, Canada.
Phillip Harder, John W. Pomeroy, and Warren D. Helgason
Hydrol. Earth Syst. Sci., 23, 1–17, https://doi.org/10.5194/hess-23-1-2019, https://doi.org/10.5194/hess-23-1-2019, 2019
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As snow cover becomes patchy during snowmelt, energy is advected from warm snow-free surfaces to cold snow-covered surfaces. This paper proposes a simple sensible and latent heat advection model for snowmelt situations that can be coupled to one-dimensional energy balance snowmelt models. The model demonstrates that sensible and latent heat advection fluxes can compensate for one another, especially in early melt periods.
Gerhard Krinner, Chris Derksen, Richard Essery, Mark Flanner, Stefan Hagemann, Martyn Clark, Alex Hall, Helmut Rott, Claire Brutel-Vuilmet, Hyungjun Kim, Cécile B. Ménard, Lawrence Mudryk, Chad Thackeray, Libo Wang, Gabriele Arduini, Gianpaolo Balsamo, Paul Bartlett, Julia Boike, Aaron Boone, Frédérique Chéruy, Jeanne Colin, Matthias Cuntz, Yongjiu Dai, Bertrand Decharme, Jeff Derry, Agnès Ducharne, Emanuel Dutra, Xing Fang, Charles Fierz, Josephine Ghattas, Yeugeniy Gusev, Vanessa Haverd, Anna Kontu, Matthieu Lafaysse, Rachel Law, Dave Lawrence, Weiping Li, Thomas Marke, Danny Marks, Martin Ménégoz, Olga Nasonova, Tomoko Nitta, Masashi Niwano, John Pomeroy, Mark S. Raleigh, Gerd Schaedler, Vladimir Semenov, Tanya G. Smirnova, Tobias Stacke, Ulrich Strasser, Sean Svenson, Dmitry Turkov, Tao Wang, Nander Wever, Hua Yuan, Wenyan Zhou, and Dan Zhu
Geosci. Model Dev., 11, 5027–5049, https://doi.org/10.5194/gmd-11-5027-2018, https://doi.org/10.5194/gmd-11-5027-2018, 2018
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This paper provides an overview of a coordinated international experiment to determine the strengths and weaknesses in how climate models treat snow. The models will be assessed at point locations using high-quality reference measurements and globally using satellite-derived datasets. How well climate models simulate snow-related processes is important because changing snow cover is an important part of the global climate system and provides an important freshwater resource for human use.
Zilefac Elvis Asong, Howard Simon Wheater, John Willard Pomeroy, Alain Pietroniro, Mohamed Ezzat Elshamy, Daniel Princz, and Alex Cannon
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2018-128, https://doi.org/10.5194/essd-2018-128, 2018
Preprint withdrawn
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Cold regions hydrology is very sensitive to the impacts of climate warming. We need better hydrological models driven by reliable climate data in order to assess hydrologic responses to climate change. Cold regions often have sparse surface observations, particularly at high elevations that generate a major amount of runoff. We produce a long-term dataset that can be used to better understand and represent the seasonal/inter-annual variability of hydrological fluxes and the the timing of runoff.
Julie M. Thériault, Ida Hung, Paul Vaquer, Ronald E. Stewart, and John W. Pomeroy
Hydrol. Earth Syst. Sci., 22, 4491–4512, https://doi.org/10.5194/hess-22-4491-2018, https://doi.org/10.5194/hess-22-4491-2018, 2018
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Precipitation events associated with rain and snow on the eastern slopes of the Rocky Mountains, Canada, are a critical aspect of the regional water cycle. The goal is to characterize the precipitation and weather conditions in the Kananaskis Valley, Alberta, during a field experiment. Mainly dense solid precipitation reached the surface and occurred during downslope and upslope conditions. The precipitation phase has critical implications on the severity of flooding events in the area.
Sebastian A. Krogh and John W. Pomeroy
Hydrol. Earth Syst. Sci., 22, 3993–4014, https://doi.org/10.5194/hess-22-3993-2018, https://doi.org/10.5194/hess-22-3993-2018, 2018
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The Arctic has warmed and vegetation has expanded; however, impacts on hydrology are poorly understood. This study used observed meteorology from the last 56 years and changes in vegetation to simulate the water cycle of an Arctic headwater basin. Several changes were found: decreased snow cover duration, deeper permafrost and earlier peak flows. Most changes are from climate change; however, vegetation impacts blowing snow, partially compensating the impact of climate change on streamflow.
Xicai Pan, Warren Helgason, Andrew Ireson, and Howard Wheater
Hydrol. Earth Syst. Sci., 21, 5401–5413, https://doi.org/10.5194/hess-21-5401-2017, https://doi.org/10.5194/hess-21-5401-2017, 2017
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In this paper we present a case study from a heterogeneous pasture site in the Canadian prairies, where we have quantified the various components of the water balance on the field scale, and critically examine some of the simplifying assumptions which are often invoked when applying water budget approaches in applied hydrology. We highlight challenges caused by lateral fluxes of blowing snow and ambiguous partitioning of snow melt water into runoff and infiltration.
Marcos R. C. Cordeiro, Henry F. Wilson, Jason Vanrobaeys, John W. Pomeroy, Xing Fang, and The Red-Assiniboine Project Biophysical Modelling Team
Hydrol. Earth Syst. Sci., 21, 3483–3506, https://doi.org/10.5194/hess-21-3483-2017, https://doi.org/10.5194/hess-21-3483-2017, 2017
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The physically based Cold Regions Hydrological Model (CRHM) was utilized to simulate runoff in the La Salle River, located in the northern Great Plains with flat topography, clay soils, and surface drainage. Snow sublimation and transport as well as infiltration to frozen soils were identified as critical in defining snowmelt. Challenges in representing infiltration into frozen but dry clay soils and flow routing under both dry and flooded conditions indicate the need for further study.
Maxime Litt, Jean-Emmanuel Sicart, Delphine Six, Patrick Wagnon, and Warren D. Helgason
The Cryosphere, 11, 971–987, https://doi.org/10.5194/tc-11-971-2017, https://doi.org/10.5194/tc-11-971-2017, 2017
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Climate variations might change the frequency of typical weather conditions. We present a weather pattern classification as an useful tool for identifying changing glacier wind regimes. We show the intensity of turbulent heat exchanges between ice and air changes with these regimes, as well as the importance of discrepancies between bulk-aerodynamic and eddy-covariance fluxes. The results suggest these discrepancies influence melt estimates from surface energy balance calculations.
Craig D. Smith, Anna Kontu, Richard Laffin, and John W. Pomeroy
The Cryosphere, 11, 101–116, https://doi.org/10.5194/tc-11-101-2017, https://doi.org/10.5194/tc-11-101-2017, 2017
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One of the objectives of the WMO Solid Precipitation Intercomparison Experiment (SPICE) was to assess the performance of automated instruments that measure snow water equivalent and make recommendations on the best measurement practices and data interpretation. This study assesses the Campbell Scientific CS725 and the Sommer SSG100 for measuring SWE. Different measurement principals of the instruments as well as site characteristics influence the way that the SWE data should be interpreted.
Nikolas O. Aksamit and John W. Pomeroy
The Cryosphere, 10, 3043–3062, https://doi.org/10.5194/tc-10-3043-2016, https://doi.org/10.5194/tc-10-3043-2016, 2016
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The first implementation of particle tracking velocimetry in outdoor alpine blowing snow has both provided new insight on intermittent snow particle transport initiation and entrainment in the dense near-surface "creep" layer whilst also confirming some wind tunnel observations. Environmental PTV has shown to be a viable avenue for furthering our understanding of the coupling of the atmospheric boundary layer turbulence and blowing snow transport.
Xicai Pan, Daqing Yang, Yanping Li, Alan Barr, Warren Helgason, Masaki Hayashi, Philip Marsh, John Pomeroy, and Richard J. Janowicz
The Cryosphere, 10, 2347–2360, https://doi.org/10.5194/tc-10-2347-2016, https://doi.org/10.5194/tc-10-2347-2016, 2016
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This study demonstrates a robust procedure for accumulating precipitation gauge measurements and provides an analysis of bias corrections of precipitation measurements across experimental sites in different ecoclimatic regions of western Canada. It highlights the need for and importance of precipitation bias corrections at both research sites and operational networks for water balance assessment and the validation of global/regional climate–hydrology models.
Amber M. Peterson, Warren D. Helgason, and Andrew M. Ireson
Hydrol. Earth Syst. Sci., 20, 1373–1385, https://doi.org/10.5194/hess-20-1373-2016, https://doi.org/10.5194/hess-20-1373-2016, 2016
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Remote sensing techniques can provide useful large-scale estimates of soil moisture. However, these methods often only sense near-surface soil moisture, whereas many applications require estimates of the entire root zone. In this study we propose and test methods to "depth-scale" the shallow soil moisture measurements obtained using the cosmic-ray neutron probe to represent the entire root zone, thereby improving the applicability of this measurement approach.
Nicolas R. Leroux and John W. Pomeroy
The Cryosphere Discuss., https://doi.org/10.5194/tc-2016-55, https://doi.org/10.5194/tc-2016-55, 2016
Revised manuscript not accepted
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Snowmelt runoff reaches our rivers and is critical for water management and consumption in cold regions. Preferential flow paths form while snow is melting and accelerate the timing at which meltwater reaches the base of the snowpack and has great impact on basin hydrology. A novel 2D numerical model that simulates water and heat fluxes through a melting snowpack is presented. Its ability to simulate formation and flow through preferential flow paths and impacts on snowmelt runoff are discussed.
M. Litt, J.-E. Sicart, and W. Helgason
Atmos. Meas. Tech., 8, 3229–3250, https://doi.org/10.5194/amt-8-3229-2015, https://doi.org/10.5194/amt-8-3229-2015, 2015
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We deal with surface turbulent flux calculations on a tropical glacier and analyse the related errors. We use data from two eddy-covariance systems and wind speed and temperature profiles collected during a 2-month measurement campaign undertaken within the atmospheric surface layer of the glacier. We show the largest error sources are related to roughness length uncertainties and to nonstationarity of the flow induced by the interaction of outer-layer eddies with the surface-layer flow.
M. Schirmer and B. Jamieson
The Cryosphere, 9, 587–601, https://doi.org/10.5194/tc-9-587-2015, https://doi.org/10.5194/tc-9-587-2015, 2015
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Numerical Weather Prediction (NWP) models are rarely verified for mountainous regions during the winter season, although avalanche forecasters and other decision makers frequently rely on NWP models. We verified two NWP models (GEM-LAM and GEM15) and a precipitation analysis system (CaPA) at approximately 100 stations in the mountains of western Canada and northwestern USA. Ultrasonic snow depth sensors and snow pillows were used to observe daily precipitation amounts.
C. B. Ménard, R. Essery, and J. Pomeroy
Hydrol. Earth Syst. Sci., 18, 2375–2392, https://doi.org/10.5194/hess-18-2375-2014, https://doi.org/10.5194/hess-18-2375-2014, 2014
M. Schirmer and B. Jamieson
The Cryosphere, 8, 387–394, https://doi.org/10.5194/tc-8-387-2014, https://doi.org/10.5194/tc-8-387-2014, 2014
X. Fang, J. W. Pomeroy, C. R. Ellis, M. K. MacDonald, C. M. DeBeer, and T. Brown
Hydrol. Earth Syst. Sci., 17, 1635–1659, https://doi.org/10.5194/hess-17-1635-2013, https://doi.org/10.5194/hess-17-1635-2013, 2013
Related subject area
Remote Sensing
Improved snow property retrievals by solving for topography in the inversion of at-sensor radiance measurements
Change in grounding line location on the Antarctic Peninsula measured using a tidal motion offset correlation method
Land cover succession for recently drained lakes in permafrost on the Yamal Peninsula, Western Siberia
Assessing sea ice microwave emissivity up to submillimeter waves from airborne and satellite observations
Simulation of Arctic snow microwave emission in surface-sensitive atmosphere channels
AWI-ICENet1: a convolutional neural network retracker for ice altimetry
Monthly velocity and seasonal variations of the Mont Blanc glaciers derived from Sentinel-2 between 2016 and 2024
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
Toward long-term monitoring of regional permafrost thaw with satellite interferometric synthetic aperture radar
Improved records of glacier flow instabilities using customized NASA autoRIFT (CautoRIFT) applied to PlanetScope imagery
Reanalyzing the spatial representativeness of snow depth at automated monitoring stations using airborne lidar data
The AutoICE Challenge
Observing glacier elevation changes from spaceborne optical and radar sensors – an inter-comparison experiment using ASTER and TanDEM-X data
Tower-based C-band radar measurements of an alpine snowpack
A study of sea ice topography in the Weddell and Ross seas using dual-polarimetric TanDEM-X imagery
Estimating differential penetration of green (532 nm) laser light over sea ice with NASA's Airborne Topographic Mapper: observations and models
Mapping surface hoar from near-infrared texture in a laboratory
Sentinel-1 detection of ice slabs on the Greenland Ice Sheet
Estimating the uncertainty of sea-ice area and sea-ice extent from satellite retrievals
Land surface temperature trends derived from Landsat imagery in the Swiss Alps
A Framework for Automated Supraglacial Lake Detection and Depth Retrieval in ICESat-2 Photon Data Across the Greenland and Antarctic Ice Sheets
Thermal infrared shadow-hiding in GOES-R ABI imagery: snow and forest temperature observations from the SnowEx 2020 Grand Mesa field campaign
Sea ice transport and replenishment across and within the Canadian Arctic Archipelago, 2016–2022
SAR deep learning sea ice retrieval trained with airborne laser scanner measurements from the MOSAiC expedition
Lake ice break-up in Greenland: timing and spatiotemporal variability
Evaluating Snow Depth Retrievals from Sentinel-1 Volume Scattering over NASA SnowEx Sites
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
MMSeaIce: a collection of techniques for improving sea ice mapping with a multi-task model
Snow water equivalent retrieved from X- and dual Ku-band scatterometer measurements at Sodankylä using the Markov Chain Monte Carlo method
Lead fractions from SAR-derived sea ice divergence during MOSAiC
Multitemporal UAV LiDAR detects seasonal heave and subsidence on palsas
The Pléiades Glacier Observatory: high resolution digital elevation models and ortho-imagery to monitor glacier change
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
A low-cost and open-source approach for supraglacial debris thickness mapping using UAV-based infrared thermography
Snow water equivalent retrieval over Idaho – Part 1: Using Sentinel-1 repeat-pass interferometry
Pan-Arctic Sea Ice Concentration from SAR and Passive Microwave
Passive microwave remote-sensing-based high-resolution snow depth mapping for Western Himalayan zones using multifactor modeling approach
Refined glacial lake extraction in a high-Asia region by deep neural network and superpixel-based conditional random field methods
Retrieval of snow water equivalent from dual-frequency radar measurements: using time series to overcome the need for accurate a priori information
Ice floe segmentation and floe size distribution in airborne and high-resolution optical satellite images: towards an automated labelling deep learning approach
Annual to seasonal glacier mass balance in High Mountain Asia derived from Pléiades stereo images: examples from the Pamir and the Tibetan Plateau
Snow accumulation, albedo and melt patterns following road construction on permafrost, Inuvik–Tuktoyaktuk Highway, Canada
Co-registration and residual correction of digital elevation models: a comparative study
Out-of-the-box calving-front detection method using deep learning
Mapping the extent of giant Antarctic icebergs with deep learning
Allometric scaling of retrogressive thaw slumps
Mapping Antarctic crevasses and their evolution with deep learning applied to satellite radar imagery
Measuring the spatiotemporal variability in snow depth in subarctic environments using UASs – Part 1: Measurements, processing, and accuracy assessment
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.
Benjamin J. Wallis, Anna E. Hogg, Yikai Zhu, and Andrew Hooper
The Cryosphere, 18, 4723–4742, https://doi.org/10.5194/tc-18-4723-2024, https://doi.org/10.5194/tc-18-4723-2024, 2024
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The grounding line, where ice begins to float, is an essential variable to understand ice dynamics, but in some locations it can be challenging to measure with established techniques. Using satellite data and a new method, Wallis et al. measure the grounding line position of glaciers and ice shelves in the Antarctic Peninsula and find retreats of up to 16.3 km have occurred since the last time measurements were made in the 1990s.
Clemens von Baeckmann, Annett Bartsch, Helena Bergstedt, Aleksandra Efimova, Barbara Widhalm, Dorothee Ehrich, Timo Kumpula, Alexander Sokolov, and Svetlana Abdulmanova
The Cryosphere, 18, 4703–4722, https://doi.org/10.5194/tc-18-4703-2024, https://doi.org/10.5194/tc-18-4703-2024, 2024
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Lakes are common features in Arctic permafrost areas. Land cover change following their drainage needs to be monitored since it has implications for ecology and the carbon cycle. Satellite data are key in this context. We compared a common vegetation index approach with a novel land-cover-monitoring scheme. Land cover information provides specific information on wetland features. We also showed that the bioclimatic gradients play a significant role after drainage within the first 10 years.
Nils Risse, Mario Mech, Catherine Prigent, Gunnar Spreen, and Susanne Crewell
The Cryosphere, 18, 4137–4163, https://doi.org/10.5194/tc-18-4137-2024, https://doi.org/10.5194/tc-18-4137-2024, 2024
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Passive microwave observations from satellites are crucial for monitoring Arctic sea ice and atmosphere. To do this effectively, it is important to understand how sea ice emits microwaves. Through unique Arctic sea ice observations, we improved our understanding, identified four distinct emission types, and expanded current knowledge to include higher frequencies. These findings will enhance our ability to monitor the Arctic climate and provide valuable information for new satellite missions.
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.
Veit Helm, Alireza Dehghanpour, Ronny Hänsch, Erik Loebel, Martin Horwath, and Angelika Humbert
The Cryosphere, 18, 3933–3970, https://doi.org/10.5194/tc-18-3933-2024, https://doi.org/10.5194/tc-18-3933-2024, 2024
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We present a new approach (AWI-ICENet1), based on a deep convolutional neural network, for analysing satellite radar altimeter measurements to accurately determine the surface height of ice sheets. Surface height estimates obtained with AWI-ICENet1 (along with related products, such as ice sheet height change and volume change) show improved and unbiased results compared to other products. This is important for the long-term monitoring of ice sheet mass loss and its impact on sea level rise.
Fabrizio Troilo, Niccolò Dematteis, Francesco Zucca, Martin Funk, and Daniele Giordan
The Cryosphere, 18, 3891–3909, https://doi.org/10.5194/tc-18-3891-2024, https://doi.org/10.5194/tc-18-3891-2024, 2024
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The study of glacier sliding along slopes is relevant in many aspects of glaciology. We processed Sentinel-2 satellite optical images of Mont Blanc, obtaining surface velocities of 30 glaciers between 2016 and 2024. The study revealed different behaviours and velocity variations that have relationships with glacier morphology. A velocity anomaly was observed in some glaciers of the southern side in 2020–2022, but its origin needs to be investigated further.
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.
Taha Sadeghi Chorsi, Franz J. Meyer, and Timothy H. Dixon
The Cryosphere, 18, 3723–3740, https://doi.org/10.5194/tc-18-3723-2024, https://doi.org/10.5194/tc-18-3723-2024, 2024
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The active layer thaws and freezes seasonally. The annual freeze–thaw cycle of the active layer causes significant surface height changes due to the volume difference between ice and liquid water. We estimate the subsidence rate and active-layer thickness (ALT) for part of northern Alaska for summer 2017 to 2022 using interferometric synthetic aperture radar and lidar. ALT estimates range from ~20 cm to larger than 150 cm in area. Subsidence rate varies between close points (2–18 mm per month).
Jukes Liu, Madeline Gendreau, Ellyn Mary Enderlin, and Rainey Aberle
The Cryosphere, 18, 3571–3590, https://doi.org/10.5194/tc-18-3571-2024, https://doi.org/10.5194/tc-18-3571-2024, 2024
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There are sometimes gaps in global glacier velocity records produced using satellite image feature-tracking algorithms during times of rapid glacier acceleration, which hinders the study of glacier flow processes. We present an open-source pipeline for customizing the feature-tracking parameters and for including images from an additional source. We applied it to five glaciers and found that it produced accurate velocity data that supplemented their velocity records during rapid acceleration.
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.
Andreas Stokholm, Jørgen Buus-Hinkler, Tore Wulf, Anton Korosov, Roberto Saldo, Leif Toudal Pedersen, David Arthurs, Ionut Dragan, Iacopo Modica, Juan Pedro, Annekatrien Debien, Xinwei Chen, Muhammed Patel, Fernando Jose Pena Cantu, Javier Noa Turnes, Jinman Park, Linlin Xu, Katharine Andrea Scott, David Anthony Clausi, Yuan Fang, Mingzhe Jiang, Saeid Taleghanidoozdoozan, Neil Curtis Brubacher, Armina Soleymani, Zacharie Gousseau, Michał Smaczny, Patryk Kowalski, Jacek Komorowski, David Rijlaarsdam, Jan Nicolaas van Rijn, Jens Jakobsen, Martin Samuel James Rogers, Nick Hughes, Tom Zagon, Rune Solberg, Nicolas Longépé, and Matilde Brandt Kreiner
The Cryosphere, 18, 3471–3494, https://doi.org/10.5194/tc-18-3471-2024, https://doi.org/10.5194/tc-18-3471-2024, 2024
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The AutoICE challenge encouraged the development of deep learning models to map multiple aspects of sea ice – the amount of sea ice in an area and the age and ice floe size – using multiple sources of satellite and weather data across the Canadian and Greenlandic Arctic. Professionally drawn operational sea ice charts were used as a reference. A total of 179 students and sea ice and AI specialists participated and produced maps in broad agreement with the sea ice charts.
Livia Piermattei, Michael Zemp, Christian Sommer, Fanny Brun, Matthias H. Braun, Liss M. Andreassen, Joaquín M. C. Belart, Etienne Berthier, Atanu Bhattacharya, Laura Boehm Vock, Tobias Bolch, Amaury Dehecq, Inés Dussaillant, Daniel Falaschi, Caitlyn Florentine, Dana Floricioiu, Christian Ginzler, Gregoire Guillet, Romain Hugonnet, Matthias Huss, Andreas Kääb, Owen King, Christoph Klug, Friedrich Knuth, Lukas Krieger, Jeff La Frenierre, Robert McNabb, Christopher McNeil, Rainer Prinz, Louis Sass, Thorsten Seehaus, David Shean, Désirée Treichler, Anja Wendt, and Ruitang Yang
The Cryosphere, 18, 3195–3230, https://doi.org/10.5194/tc-18-3195-2024, https://doi.org/10.5194/tc-18-3195-2024, 2024
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Satellites have made it possible to observe glacier elevation changes from all around the world. In the present study, we compared the results produced from two different types of satellite data between different research groups and against validation measurements from aeroplanes. We found a large spread between individual results but showed that the group ensemble can be used to reliably estimate glacier elevation changes and related errors from satellite data.
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.
Lanqing Huang and Irena Hajnsek
The Cryosphere, 18, 3117–3140, https://doi.org/10.5194/tc-18-3117-2024, https://doi.org/10.5194/tc-18-3117-2024, 2024
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Interferometric synthetic aperture radar can measure the total freeboard of sea ice but can be biased when radar signals penetrate snow and ice. We develop a new method to retrieve the total freeboard and analyze the regional variation of total freeboard and roughness in the Weddell and Ross seas. We also investigate the statistical behavior of the total freeboard for diverse ice types. The findings enhance the understanding of Antarctic sea ice topography and its dynamics in a changing climate.
Michael Studinger, Benjamin E. Smith, Nathan Kurtz, Alek Petty, Tyler Sutterley, and Rachel Tilling
The Cryosphere, 18, 2625–2652, https://doi.org/10.5194/tc-18-2625-2024, https://doi.org/10.5194/tc-18-2625-2024, 2024
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We use green lidar data and natural-color imagery over sea ice to quantify elevation biases potentially impacting estimates of change in ice thickness of the polar regions. We complement our analysis using a model of scattering of light in snow and ice that predicts the shape of lidar waveforms reflecting from snow and ice surfaces based on the shape of the transmitted pulse. We find that biased elevations exist in airborne and spaceborne data products from green lidars.
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 %.
Riley Culberg, Roger J. Michaelides, and Julie Z. Miller
The Cryosphere, 18, 2531–2555, https://doi.org/10.5194/tc-18-2531-2024, https://doi.org/10.5194/tc-18-2531-2024, 2024
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Ice slabs enhance meltwater runoff from the Greenland Ice Sheet. Therefore, it is important to understand their extent and change in extent over time. We present a new method for detecting ice slabs in satellite radar data, which we use to map ice slabs at 500 m resolution across the entire ice sheet in winter 2016–2017. Our results provide better spatial coverage and resolution than previous maps from airborne radar and lay the groundwork for long-term monitoring of ice slabs from space.
Andreas Wernecke, Dirk Notz, Stefan Kern, and Thomas Lavergne
The Cryosphere, 18, 2473–2486, https://doi.org/10.5194/tc-18-2473-2024, https://doi.org/10.5194/tc-18-2473-2024, 2024
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The total Arctic sea-ice area (SIA), which is an important climate indicator, is routinely monitored with the help of satellite measurements. Uncertainties in observations of sea-ice concentration (SIC) partly cancel out when summed up to the total SIA, but the degree to which this is happening has been unclear. Here we find that the uncertainty daily SIA estimates, based on uncertainties in SIC, are about 300 000 km2. The 2002 to 2017 September decline in SIA is approx. 105 000 ± 9000 km2 a−1.
Deniz Tobias Gök, Dirk Scherler, and Hendrik Wulf
EGUsphere, https://doi.org/10.5194/egusphere-2024-1228, https://doi.org/10.5194/egusphere-2024-1228, 2024
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We derived Landsat Collection 2 land surface temperature (LST) trends in the Swiss Alps using a harmonic model with linear trend. Validation with LST data from 119 high-altitude weather stations yielded robust results, but Landsat LST trends are biased due to unstable acquisition times. The bias varies with topographic slope and aspect. We discuss its origin and propose a simple correction method in relation to modeled changes in shortwave radiation.
Philipp Sebastian Arndt and Helen Amanda Fricker
EGUsphere, https://doi.org/10.5194/egusphere-2024-1156, https://doi.org/10.5194/egusphere-2024-1156, 2024
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We develop a method for ice-sheet-scale retrieval of supraglacial meltwater depths using ICESat-2 photon data. We report results for two drainage basins in Greenland and Antarctica during two contrasting melt seasons, where our method reveals a total of 1249 lakes up to 25 m deep. The large volume and wide variety of accurate depth data that our method provides enables the development of data-driven models of meltwater volumes in satellite imagery.
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.
Stephen E. L. Howell, David G. Babb, Jack C. Landy, Isolde A. Glissenaar, Kaitlin McNeil, Benoit Montpetit, and Mike Brady
The Cryosphere, 18, 2321–2333, https://doi.org/10.5194/tc-18-2321-2024, https://doi.org/10.5194/tc-18-2321-2024, 2024
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The CAA serves as both a source and a sink for sea ice from the Arctic Ocean, while also exporting sea ice into Baffin Bay. It is also an important region with respect to navigating the Northwest Passage. Here, we quantify sea ice transport and replenishment across and within the CAA from 2016 to 2022. We also provide the first estimates of the ice area and volume flux within the CAA from the Queen Elizabeth Islands to Parry Channel, which spans the central region of the Northwest Passage.
Karl Kortum, Suman Singha, Gunnar Spreen, Nils Hutter, Arttu Jutila, and Christian Haas
The Cryosphere, 18, 2207–2222, https://doi.org/10.5194/tc-18-2207-2024, https://doi.org/10.5194/tc-18-2207-2024, 2024
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A dataset of 20 radar satellite acquisitions and near-simultaneous helicopter-based surveys of the ice topography during the MOSAiC expedition is constructed and used to train a variety of deep learning algorithms. The results give realistic insights into the accuracy of retrieval of measured ice classes using modern deep learning models. The models able to learn from the spatial distribution of the measured sea ice classes are shown to have a clear advantage over those that cannot.
Christoph Posch, Jakob Abermann, and Tiago Silva
The Cryosphere, 18, 2035–2059, https://doi.org/10.5194/tc-18-2035-2024, https://doi.org/10.5194/tc-18-2035-2024, 2024
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Radar beams from satellites exhibit reflection differences between water and ice. This condition, as well as the comprehensive coverage and high temporal resolution of the Sentinel-1 satellites, allows automatically detecting the timing of when ice cover of lakes in Greenland disappear. We found that lake ice breaks up 3 d later per 100 m elevation gain and that the average break-up timing varies by ±8 d in 2017–2021, which has major implications for the energy budget of the lakes.
Zachary Hoppinen, Ross T. Palomaki, George Brencher, Devon Dunmire, Eric Gagliano, Adrian Marziliano, Jack Tarricone, and Hans-Peter Marshall
EGUsphere, https://doi.org/10.5194/egusphere-2024-1018, https://doi.org/10.5194/egusphere-2024-1018, 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 9 automated snow monitoring stations.
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.
Xinwei Chen, Muhammed Patel, Fernando J. Pena Cantu, Jinman Park, Javier Noa Turnes, Linlin Xu, K. Andrea Scott, and David A. Clausi
The Cryosphere, 18, 1621–1632, https://doi.org/10.5194/tc-18-1621-2024, https://doi.org/10.5194/tc-18-1621-2024, 2024
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This paper introduces an automated sea ice mapping pipeline utilizing a multi-task U-Net architecture. It attained the top score of 86.3 % in the AutoICE challenge. Ablation studies revealed that incorporating brightness temperature data and spatial–temporal information significantly enhanced model accuracy. Accurate sea ice mapping is vital for comprehending the Arctic environment and its global climate effects, underscoring the potential of deep learning.
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.
Luisa von Albedyll, Stefan Hendricks, Nils Hutter, Dmitrii Murashkin, Lars Kaleschke, Sascha Willmes, Linda Thielke, Xiangshan Tian-Kunze, Gunnar Spreen, and Christian Haas
The Cryosphere, 18, 1259–1285, https://doi.org/10.5194/tc-18-1259-2024, https://doi.org/10.5194/tc-18-1259-2024, 2024
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Leads (openings in sea ice cover) are created by sea ice dynamics. Because they are important for many processes in the Arctic winter climate, we aim to detect them with satellites. We present two new techniques to detect lead widths of a few hundred meters at high spatial resolution (700 m) and independent of clouds or sun illumination. We use the MOSAiC drift 2019–2020 in the Arctic for our case study and compare our new products to other existing lead products.
Cas Renette, Mats Olvmo, Sofia Thorsson, Björn Holmer, and Heather Reese
EGUsphere, https://doi.org/10.5194/egusphere-2024-141, https://doi.org/10.5194/egusphere-2024-141, 2024
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We used a drone to monitor seasonal changes in the height of subarctic permafrost mounds (palsas). With five drone flights in one year, we found a seasonal fluctuation of ca. 15 cm as result of freeze/thaw cycles. On one mound, a large area sank down between each flight as a result of permafrost thaw. The approach of using repeated high-resolution scans from such drone is unique for such environments and highlights its effectiveness in capturing the subtle dynamics of permafrost landscapes.
Etienne Berthier, Jérôme Lebreton, Delphine Fontannaz, Steven Hosford, Joaquin Munoz Cobo Belart, Fanny Brun, Liss Marie Andreassen, Brian Menounos, and Charlotte Blondel
EGUsphere, https://doi.org/10.5194/egusphere-2024-250, https://doi.org/10.5194/egusphere-2024-250, 2024
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Repeat elevation measurements are crucial for monitoring glacier health and how they affect river flows and sea levels. Until recently, high resolution elevation data were mostly available for polar regions and High Mountain Asia. Our project, the Pléiades Glacier Observatory (PGO), 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 glacier at high resolution and accuracy.
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.
Jérôme Messmer and Alexander Raphael Groos
The Cryosphere, 18, 719–746, https://doi.org/10.5194/tc-18-719-2024, https://doi.org/10.5194/tc-18-719-2024, 2024
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The lower part of mountain glaciers is often covered with debris. Knowing the thickness of the debris is important as it influences the melting and future evolution of the affected glaciers. We have developed an open-source approach to map variations in debris thickness on glaciers using a low-cost drone equipped with a thermal infrared camera. The resulting high-resolution maps of debris surface temperature and thickness enable more accurate monitoring and modelling of debris-covered glaciers.
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.
Tore Wulf, Jørgen Buus-Hinkler, Suman Singha, Hoyeon Shi, and Matilde Brandt Kreiner
EGUsphere, https://doi.org/10.5194/egusphere-2024-178, https://doi.org/10.5194/egusphere-2024-178, 2024
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Here, we present ASIP (Automated Sea Ice Products): a new and comprehensive deep learning-based methodology to retrieve high-resolution sea ice concentration with accompanying well-calibrated uncertainties from Sentinel-1 SAR and AMSR2 passive microwave observations at a pan-Arctic scale for all seasons. In a comparative study against pan-Arctic ice charts and passive microwave-based sea ice products, we show that ASIP generalizes well to the pan-Arctic region.
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.
Yungang Cao, Rumeng Pan, Meng Pan, Ruodan Lei, Puying Du, and Xueqin Bai
The Cryosphere, 18, 153–168, https://doi.org/10.5194/tc-18-153-2024, https://doi.org/10.5194/tc-18-153-2024, 2024
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This study built a glacial lake dataset with 15376 samples in seven types and proposed an automatic method by two-stage (the semantic segmentation network and post-processing) optimizations to detect glacial lakes. The proposed method for glacial lake extraction has achieved the best results so far, in which the F1 score and IoU reached 0.945 and 0.907, respectively. The area of the minimum glacial lake that can be entirely and correctly extracted has been raised to the 100 m2 level.
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.
Qin Zhang and Nick Hughes
The Cryosphere, 17, 5519–5537, https://doi.org/10.5194/tc-17-5519-2023, https://doi.org/10.5194/tc-17-5519-2023, 2023
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To alleviate tedious manual image annotations for training deep learning (DL) models in floe instance segmentation, we employ a classical image processing technique to automatically label floes in images. We then apply a DL semantic method for fast and adaptive floe instance segmentation from high-resolution airborne and satellite images. A post-processing algorithm is also proposed to refine the segmentation and further to derive acceptable floe size distributions at local and global scales.
Daniel Falaschi, Atanu Bhattacharya, Gregoire Guillet, Lei Huang, Owen King, Kriti Mukherjee, Philipp Rastner, Tandong Yao, and Tobias Bolch
The Cryosphere, 17, 5435–5458, https://doi.org/10.5194/tc-17-5435-2023, https://doi.org/10.5194/tc-17-5435-2023, 2023
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Because glaciers are crucial freshwater sources in the lowlands surrounding High Mountain Asia, constraining short-term glacier mass changes is essential. We investigate the potential of state-of-the-art satellite elevation data to measure glacier mass changes in two selected regions. The results demonstrate the ability of our dataset to characterize glacier changes of different magnitudes, allowing for an increase in the number of inaccessible glaciers that can be readily monitored.
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.
Tao Li, Yuanlin Hu, Bin Liu, Liming Jiang, Hansheng Wang, and Xiang Shen
The Cryosphere, 17, 5299–5316, https://doi.org/10.5194/tc-17-5299-2023, https://doi.org/10.5194/tc-17-5299-2023, 2023
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Raw DEMs are often misaligned with each other due to georeferencing errors, and a co-registration process is required before DEM differencing. We present a comparative analysis of the two classical DEM co-registration and three residual correction algorithms. The experimental results show that rotation and scale biases should be considered in DEM co-registration. The new non-parametric regression technique can eliminate the complex systematic errors, which existed in the co-registration results.
Oskar Herrmann, Nora Gourmelon, Thorsten Seehaus, Andreas Maier, Johannes J. Fürst, Matthias H. Braun, and Vincent Christlein
The Cryosphere, 17, 4957–4977, https://doi.org/10.5194/tc-17-4957-2023, https://doi.org/10.5194/tc-17-4957-2023, 2023
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Delineating calving fronts of marine-terminating glaciers in satellite images is a labour-intensive task. We propose a method based on deep learning that automates this task. We choose a deep learning framework that adapts to any given dataset without needing deep learning expertise. The method is evaluated on a benchmark dataset for calving-front detection and glacier zone segmentation. The framework can beat the benchmark baseline without major modifications.
Anne Braakmann-Folgmann, Andrew Shepherd, David Hogg, and Ella Redmond
The Cryosphere, 17, 4675–4690, https://doi.org/10.5194/tc-17-4675-2023, https://doi.org/10.5194/tc-17-4675-2023, 2023
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In this study, we propose a deep neural network to map the extent of giant Antarctic icebergs in Sentinel-1 images automatically. While each manual delineation requires several minutes, our U-net takes less than 0.01 s. In terms of accuracy, we find that U-net outperforms two standard segmentation techniques (Otsu, k-means) in most metrics and is more robust to challenging scenes with sea ice, coast and other icebergs. The absolute median deviation in iceberg area across 191 images is 4.1 %.
Jurjen van der Sluijs, Steven V. Kokelj, and Jon F. Tunnicliffe
The Cryosphere, 17, 4511–4533, https://doi.org/10.5194/tc-17-4511-2023, https://doi.org/10.5194/tc-17-4511-2023, 2023
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There is an urgent need to obtain size and erosion estimates of climate-driven landslides, such as retrogressive thaw slumps. We evaluated surface interpolation techniques to estimate slump erosional volumes and developed a new inventory method by which the size and activity of these landslides are tracked through time. Models between slump area and volume reveal non-linear intensification, whereby model coefficients improve our understanding of how permafrost landscapes may evolve over time.
Trystan Surawy-Stepney, Anna E. Hogg, Stephen L. Cornford, and David C. Hogg
The Cryosphere, 17, 4421–4445, https://doi.org/10.5194/tc-17-4421-2023, https://doi.org/10.5194/tc-17-4421-2023, 2023
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The presence of crevasses in Antarctica influences how the ice sheet behaves. It is important, therefore, to collect data on the spatial distribution of crevasses and how they are changing. We present a method of mapping crevasses from satellite radar imagery and apply it to 7.5 years of images, covering Antarctica's floating and grounded ice. We develop a method of measuring change in the density of crevasses and quantify increased fracturing in important parts of the West Antarctic Ice Sheet.
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.
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Short summary
This paper assesses the accuracy of high-resolution snow depth maps generated from unmanned aerial vehicle imagery. Snow depth maps are generated from differencing snow-covered and snow-free digital surface models produced from structure from motion techniques. On average, the estimated snow depth error was 10 cm. This technique is therefore useful for observing snow accumulation and melt in deep snow but is restricted to observing peak snow accumulation in shallow snow.
This paper assesses the accuracy of high-resolution snow depth maps generated from unmanned...
