Articles | Volume 11, issue 5
https://doi.org/10.5194/tc-11-2329-2017
© Author(s) 2017. 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-11-2329-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
06 Oct 2017
Research article |
| 06 Oct 2017
Spatiotemporal patterns of High Mountain Asia's snowmelt season identified with an automated snowmelt detection algorithm, 1987–2016
Institute for Earth and Environmental Sciences, Universität Potsdam, Potsdam, Germany
Bodo Bookhagen
Institute for Earth and Environmental Sciences, Universität Potsdam, Potsdam, Germany
Aljoscha Rheinwalt
Institute for Earth and Environmental Sciences, Universität Potsdam, Potsdam, Germany
Related authors
Taylor Smith, Ruxandra-Maria Zotta, Chris A. Boulton, Timothy M. Lenton, Wouter Dorigo, and Niklas Boers
Earth Syst. Dynam., 14, 173–183, https://doi.org/10.5194/esd-14-173-2023, https://doi.org/10.5194/esd-14-173-2023, 2023
Short summary
Short summary
Multi-instrument records with varying signal-to-noise ratios are becoming increasingly common as legacy sensors are upgraded, and data sets are modernized. Induced changes in higher-order statistics such as the autocorrelation and variance are not always well captured by cross-calibration schemes. Here we investigate using synthetic examples how strong resulting biases can be and how they can be avoided in order to make reliable statements about changes in the resilience of a system.
Taylor Smith, Aljoscha Rheinwalt, and Bodo Bookhagen
Earth Surf. Dynam., 7, 475–489, https://doi.org/10.5194/esurf-7-475-2019, https://doi.org/10.5194/esurf-7-475-2019, 2019
Short summary
Short summary
Representing the surface of the Earth on an equally spaced grid leads to errors and uncertainties in derived slope and aspect. Using synthetic data, we develop a quality metric that can be used to compare the uncertainties in different datasets. We then apply this method to a real-world lidar dataset, and find that 1 m data have larger error bounds than lower-resolution data. The highest data resolution is not always the best choice – it is important to consider the quality of the data.
T. Smith, B. Bookhagen, and F. Cannon
The Cryosphere, 9, 1747–1759, https://doi.org/10.5194/tc-9-1747-2015, https://doi.org/10.5194/tc-9-1747-2015, 2015
Short summary
Short summary
We describe and apply a newly developed glacial mapping algorithm which uses spectral, topographic, velocity, and spatial data to quickly and accurately map glacial extents over a wide area. This method maps both clean glacier ice and debris-covered glacier tongues across diverse topographic, land cover, and spectral settings using primarily open-source tools.
Taylor Smith, Ruxandra-Maria Zotta, Chris A. Boulton, Timothy M. Lenton, Wouter Dorigo, and Niklas Boers
Earth Syst. Dynam., 14, 173–183, https://doi.org/10.5194/esd-14-173-2023, https://doi.org/10.5194/esd-14-173-2023, 2023
Short summary
Short summary
Multi-instrument records with varying signal-to-noise ratios are becoming increasingly common as legacy sensors are upgraded, and data sets are modernized. Induced changes in higher-order statistics such as the autocorrelation and variance are not always well captured by cross-calibration schemes. Here we investigate using synthetic examples how strong resulting biases can be and how they can be avoided in order to make reliable statements about changes in the resilience of a system.
Taylor Smith, Aljoscha Rheinwalt, and Bodo Bookhagen
Earth Surf. Dynam., 7, 475–489, https://doi.org/10.5194/esurf-7-475-2019, https://doi.org/10.5194/esurf-7-475-2019, 2019
Short summary
Short summary
Representing the surface of the Earth on an equally spaced grid leads to errors and uncertainties in derived slope and aspect. Using synthetic data, we develop a quality metric that can be used to compare the uncertainties in different datasets. We then apply this method to a real-world lidar dataset, and find that 1 m data have larger error bounds than lower-resolution data. The highest data resolution is not always the best choice – it is important to consider the quality of the data.
Jordi Tost, Fabian Ehmel, Frank Heidmann, Stephanie M. Olen, and Bodo Bookhagen
Proc. Int. Cartogr. Assoc., 1, 115, https://doi.org/10.5194/ica-proc-1-115-2018, https://doi.org/10.5194/ica-proc-1-115-2018, 2018
Benjamin Purinton and Bodo Bookhagen
Earth Surf. Dynam., 5, 211–237, https://doi.org/10.5194/esurf-5-211-2017, https://doi.org/10.5194/esurf-5-211-2017, 2017
Short summary
Short summary
We evaluate the 12 m TanDEM-X DEM for geomorphometry and compare elevation accuracy (using over 300 000 dGPS measurements) and geomorphic metrics (e.g., slope and curvature) to other modern satellite-derived DEMs. The optically generated 5 m ALOS World 3D is less useful due to high-frequency noise. Despite improvements in radar-derived satellite DEMs, which are useful for elevation differencing and catchment analysis, lidar data are still necessary for fine-scale analysis of hillslope processes.
T. Smith, B. Bookhagen, and F. Cannon
The Cryosphere, 9, 1747–1759, https://doi.org/10.5194/tc-9-1747-2015, https://doi.org/10.5194/tc-9-1747-2015, 2015
Short summary
Short summary
We describe and apply a newly developed glacial mapping algorithm which uses spectral, topographic, velocity, and spatial data to quickly and accurately map glacial extents over a wide area. This method maps both clean glacier ice and debris-covered glacier tongues across diverse topographic, land cover, and spectral settings using primarily open-source tools.
Related subject area
Remote Sensing
Brief communication: Identification of tundra topsoil frozen/thawed state from SMAP and GCOM-W1 radiometer measurements using the spectral gradient method
New estimates of pan-Arctic sea ice–atmosphere neutral drag coefficients from ICESat-2 elevation data
GLAcier Feature Tracking testkit (GLAFT): a statistically and physically based framework for evaluating glacier velocity products derived from optical satellite image feature tracking
Evaluating the utility of active microwave observations as a snow mission concept using observing system simulation experiments
Relevance of warm air intrusions for Arctic satellite sea ice concentration time series
Observing the evolution of summer melt on multiyear sea ice with ICESat-2 and Sentinel-2
Cast shadows reveal changes in glacier surface elevation
AutoTerm: an automated pipeline for glacier terminus extraction using machine learning and a “big data” repository of Greenland glacier termini
Characterizing the surge behaviour and associated ice-dammed lake evolution of the Kyagar Glacier in the Karakoram
Spaceborne thermal infrared observations of Arctic sea ice leads at 30 m resolution
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
Constraining regional glacier reconstructions using past ice thickness of deglaciating areas – a case study in the European Alps
Wind redistribution of snow impacts the Ka- and Ku-band radar signatures of Arctic sea ice
Estimating snow accumulation and ablation with L-band interferometric synthetic aperture radar (InSAR)
Mapping the extent of giant Antarctic icebergs with Deep Learning
Evaluating Snow Microwave Radiative Transfer (SMRT) model emissivities using observations of Arctic tundra snow
Bedfast and floating-ice dynamics of thermokarst lakes using a temporal deep-learning mapping approach: case study of the Old Crow Flats, Yukon, Canada
First observations of sea ice flexural–gravity waves with ground-based radar interferometry in Utqiaġvik, Alaska
Climatic control on seasonal variations in mountain glacier surface velocity
Snowmelt characterization from optical and synthetic-aperture radar observations in the La Joie Basin, British Columbia
Recent changes in drainage route and outburst magnitude of the Russell Glacier ice-dammed lake, West Greenland
Feasibility of retrieving Arctic sea ice thickness from the Chinese HY-2B Ku-band radar altimeter
Mapping Antarctic Crevasses and their Evolution with Deep Learning Applied to Satellite Radar Imagery
Sea ice classification of TerraSAR-X ScanSAR images for the MOSAiC expedition incorporating per-class incidence angle dependency of image texture
Topographic and vegetation controls of the spatial distribution of snow depth in agro-forested environments by UAV lidar
High-resolution debris-cover mapping using UAV-derived thermal imagery: limits and opportunities
Temporal stability of long-term satellite and reanalysis products to monitor snow cover trends
Grounding line retreat and tide-modulated ocean channels at Moscow University and Totten Glacier ice shelves, East Antarctica
Towards long-term records of rain-on-snow events across the Arctic from satellite data
Aerial observations of sea ice breakup by ship waves
Monitoring Arctic thin ice: a comparison between CryoSat-2 SAR altimetry data and MODIS thermal-infrared imagery
The effects of surface roughness on the calculated, spectral, conical–conical reflectance factor as an alternative to the bidirectional reflectance distribution function of bare sea ice
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
Ice thickness and water level estimation for ice-covered lakes with satellite altimetry waveforms and backscattering coefficients
Inter-comparison and evaluation of Arctic sea ice type products
Snow stratigraphy observations from Operation IceBridge surveys in Alaska using S and C band airborne ultra-wideband FMCW (frequency-modulated continuous wave) radar
Automated ArcticDEM iceberg detection tool: insights into area and volume distributions, and their potential application to satellite imagery and modelling of glacier–iceberg–ocean systems
Measuring the spatiotemporal variability of snow depth in subarctic environments using unmanned aircraft systems (UAS) – Part 2: Snow processes and snow-canopy interactions
Measuring the spatiotemporal variability of snow depth in subarctic environments using unmanned aircraft systems (UAS) – Part 1: Measurements, processing, and accuracy assessment
A simple model for daily basin-wide thermodynamic sea ice thickness growth retrieval
Ice ridge density signatures in high-resolution SAR images
Glacier extraction based on high-spatial-resolution remote-sensing images using a deep-learning approach with attention mechanism
Rain on snow (ROS) understudied in sea ice remote sensing: a multi-sensor analysis of ROS during MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate)
Seasonal land-ice-flow variability in the Antarctic Peninsula
Quantifying the effects of background concentrations of crude oil pollution on sea ice albedo
Brief communication: A continuous formulation of microwave scattering from fresh snow to bubbly ice from first principles
Konstantin Muzalevskiy, Zdenek Ruzicka, Alexandre Roy, Michael Loranty, and Alexander Vasiliev
The Cryosphere, 17, 4155–4164, https://doi.org/10.5194/tc-17-4155-2023, https://doi.org/10.5194/tc-17-4155-2023, 2023
Short summary
Short summary
A new all-weather method for determining the frozen/thawed (FT) state of soils in the Arctic region based on satellite data was proposed. The method is based on multifrequency measurement of brightness temperatures by the SMAP and GCOM-W1/AMSR2 satellites. The created method was tested at sites in Canada, Finland, Russia, and the USA, based on climatic weather station data. The proposed method identifies the FT state of Arctic soils with better accuracy than existing methods.
Alexander Mchedlishvili, Christof Lüpkes, Alek Petty, Michel Tsamados, and Gunnar Spreen
The Cryosphere, 17, 4103–4131, https://doi.org/10.5194/tc-17-4103-2023, https://doi.org/10.5194/tc-17-4103-2023, 2023
Short summary
Short summary
In this study we looked at sea ice–atmosphere drag coefficients, quantities that help with characterizing the friction between the atmosphere and sea ice, and vice versa. Using ICESat-2, a laser altimeter that measures elevation differences by timing how long it takes for photons it sends out to return to itself, we could map the roughness, i.e., how uneven the surface is. From roughness we then estimate drag force, the frictional force between sea ice and the atmosphere, across the Arctic.
Whyjay Zheng, Shashank Bhushan, Maximillian Van Wyk De Vries, William Kochtitzky, David Shean, Luke Copland, Christine Dow, Renette Jones-Ivey, and Fernando Pérez
The Cryosphere, 17, 4063–4078, https://doi.org/10.5194/tc-17-4063-2023, https://doi.org/10.5194/tc-17-4063-2023, 2023
Short summary
Short summary
We design and propose a method that can evaluate the quality of glacier velocity maps. The method includes two numbers that we can calculate for each velocity map. Based on statistics and ice flow physics, velocity maps with numbers close to the recommended values are considered to have good quality. We test the method using the data from Kaskawulsh Glacier, Canada, and release an open-sourced software tool called GLAcier Feature Tracking testkit (GLAFT) to help users assess their velocity maps.
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.
Philip Rostosky and Gunnar Spreen
The Cryosphere, 17, 3867–3881, https://doi.org/10.5194/tc-17-3867-2023, https://doi.org/10.5194/tc-17-3867-2023, 2023
Short summary
Short summary
During winter, storms entering the Arctic region can bring warm air into the cold environment. Strong increases in air temperature modify the characteristics of the Arctic snow and ice cover. The Arctic sea ice cover can be monitored by satellites observing the natural emission of the Earth's surface. In this study, we show that during warm air intrusions the change in the snow characteristics influences the satellite-derived sea ice cover, leading to a false reduction of the estimated ice area.
Ellen M. Buckley, Sinéad L. Farrell, Ute C. Herzfeld, Melinda A. Webster, Thomas Trantow, Oliwia N. Baney, Kyle A. Duncan, Huilin Han, and Matthew Lawson
The Cryosphere, 17, 3695–3719, https://doi.org/10.5194/tc-17-3695-2023, https://doi.org/10.5194/tc-17-3695-2023, 2023
Short summary
Short summary
In this study, we use satellite observations to investigate the evolution of melt ponds on the Arctic sea ice surface. We derive melt pond depth from ICESat-2 measurements of the pond surface and bathymetry and melt pond fraction (MPF) from the classification of Sentinel-2 imagery. MPF increases to a peak of 16 % in late June and then decreases, while depth increases steadily. This work demonstrates the ability to track evolving melt conditions in three dimensions throughout the summer.
Monika Pfau, Georg Veh, and Wolfgang Schwanghart
The Cryosphere, 17, 3535–3551, https://doi.org/10.5194/tc-17-3535-2023, https://doi.org/10.5194/tc-17-3535-2023, 2023
Short summary
Short summary
Cast shadows have been a recurring problem in remote sensing of glaciers. We show that the length of shadows from surrounding mountains can be used to detect gains or losses in glacier elevation.
Enze Zhang, Ginny Catania, and Daniel T. Trugman
The Cryosphere, 17, 3485–3503, https://doi.org/10.5194/tc-17-3485-2023, https://doi.org/10.5194/tc-17-3485-2023, 2023
Short summary
Short summary
Glacier termini are essential for studying why glaciers retreat, but they need to be mapped automatically due to the volume of satellite images. Existing automated mapping methods have been limited due to limited automation, lack of quality control, and inadequacy in highly diverse terminus environments. We design a fully automated, deep-learning-based method to produce termini with quality control. We produced 278 239 termini in Greenland and provided a way to deliver new termini regularly.
Guanyu Li, Mingyang Lv, Duncan J. Quincey, Liam S. Taylor, Xinwu Li, Shiyong Yan, Yidan Sun, and Huadong Guo
The Cryosphere, 17, 2891–2907, https://doi.org/10.5194/tc-17-2891-2023, https://doi.org/10.5194/tc-17-2891-2023, 2023
Short summary
Short summary
Kyagar Glacier in the Karakoram is well known for its surge history and its frequent blocking of the downstream valley, leading to a series of high-magnitude glacial lake outburst floods. Using it as a test bed, we develop a new approach for quantifying surge behaviour using successive digital elevation models. This method could be applied to other surge studies. Combined with the results from optical satellite images, we also reconstruct the surge process in unprecedented detail.
Yujia Qiu, Xiao-Ming Li, and Huadong Guo
The Cryosphere, 17, 2829–2849, https://doi.org/10.5194/tc-17-2829-2023, https://doi.org/10.5194/tc-17-2829-2023, 2023
Short summary
Short summary
Spaceborne thermal infrared sensors with kilometer-scale resolution cannot support adequate parameterization of Arctic leads. For the first time, we applied the 30 m resolution data from the Thermal Infrared Spectrometer (TIS) on the emerging SDGSAT-1 to detect Arctic leads. Validation with Sentinel-2 data shows high accuracy for the three TIS bands. Compared to MODIS, the TIS presents more narrow leads, demonstrating its great potential for observing previously unresolvable Arctic leads.
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.
Christian Sommer, Johannes J. Fürst, Matthias Huss, and Matthias H. Braun
The Cryosphere, 17, 2285–2303, https://doi.org/10.5194/tc-17-2285-2023, https://doi.org/10.5194/tc-17-2285-2023, 2023
Short summary
Short summary
Knowledge on the volume of glaciers is important to project future runoff. Here, we present a novel approach to reconstruct the regional ice thickness distribution from easily available remote-sensing data. We show that past ice thickness, derived from spaceborne glacier area and elevation datasets, can constrain the estimated ice thickness. Based on the unique glaciological database of the European Alps, the approach will be most beneficial in regions without direct thickness measurements.
Vishnu Nandan, Rosemary Willatt, Robbie Mallett, Julienne Stroeve, Torsten Geldsetzer, Randall Scharien, Rasmus Tonboe, John Yackel, Jack Landy, David Clemens-Sewall, Arttu Jutila, David N. Wagner, Daniela Krampe, Marcus Huntemann, Mallik Mahmud, David Jensen, Thomas Newman, Stefan Hendricks, Gunnar Spreen, Amy Macfarlane, Martin Schneebeli, James Mead, Robert Ricker, Michael Gallagher, Claude Duguay, Ian Raphael, Chris Polashenski, Michel Tsamados, Ilkka Matero, and Mario Hoppmann
The Cryosphere, 17, 2211–2229, https://doi.org/10.5194/tc-17-2211-2023, https://doi.org/10.5194/tc-17-2211-2023, 2023
Short summary
Short summary
We show that wind redistributes snow on Arctic sea ice, and Ka- and Ku-band radar measurements detect both newly deposited snow and buried snow layers that can affect the accuracy of snow depth estimates on sea ice. Radar, laser, meteorological, and snow data were collected during the MOSAiC expedition. With frequent occurrence of storms in the Arctic, our results show that
wind-redistributed snow needs to be accounted for to improve snow depth estimates on sea ice from satellite radars.
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.
Anne Braakmann-Folgmann, Andrew Shepherd, David Hogg, and Ella Redmond
EGUsphere, https://doi.org/10.5194/egusphere-2023-858, https://doi.org/10.5194/egusphere-2023-858, 2023
Short summary
Short summary
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 sec. In terms of accuracy, we find that U-net outperforms two standard segmentation techniques in most metrics and is more robust to challenging scenes including sea ice, coast and other icebergs. The absolute median deviation in iceberg area across 191 images is 4.1 %.
Kirsty Wivell, Stuart Fox, Melody Sandells, Chawn Harlow, Richard Essery, and Nick Rutter
EGUsphere, https://doi.org/10.5194/egusphere-2023-878, https://doi.org/10.5194/egusphere-2023-878, 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 input snow profiles to emissivity simulations.
Maria Shaposhnikova, Claude Duguay, and Pascale Roy-Léveillée
The Cryosphere, 17, 1697–1721, https://doi.org/10.5194/tc-17-1697-2023, https://doi.org/10.5194/tc-17-1697-2023, 2023
Short summary
Short summary
We explore lake ice in the Old Crow Flats, Yukon, Canada, using a novel approach that employs radar imagery and deep learning. Results indicate an 11 % increase in the fraction of lake ice that grounds between 1992/1993 and 2020/2021. We believe this is caused by widespread lake drainage and fluctuations in water level and snow depth. This transition is likely to have implications for permafrost beneath the lakes, with a potential impact on methane ebullition and the regional carbon budget.
Dyre Oliver Dammann, Mark A. Johnson, Andrew R. Mahoney, and Emily R. Fedders
The Cryosphere, 17, 1609–1622, https://doi.org/10.5194/tc-17-1609-2023, https://doi.org/10.5194/tc-17-1609-2023, 2023
Short summary
Short summary
We investigate the GAMMA Portable Radar Interferometer (GPRI) as a tool for evaluating flexural–gravity waves in sea ice in near real time. With a GPRI mounted on grounded ice near Utqiaġvik, Alaska, we identify 20–50 s infragravity waves in landfast ice with ~1 mm amplitude during 23–24 April 2021. Observed wave speed and periods compare well with modeled wave propagation and on-ice accelerometers, confirming the ability to track propagation and properties of waves over hundreds of meters.
Ugo Nanni, Dirk Scherler, Francois Ayoub, Romain Millan, Frederic Herman, and Jean-Philippe Avouac
The Cryosphere, 17, 1567–1583, https://doi.org/10.5194/tc-17-1567-2023, https://doi.org/10.5194/tc-17-1567-2023, 2023
Short summary
Short summary
Surface melt is a major factor driving glacier movement. Using satellite images, we have tracked the movements of 38 glaciers in the Pamirs over 7 years, capturing their responses to rapid meteorological changes with unprecedented resolution. We show that in spring, glacier accelerations propagate upglacier, while in autumn, they propagate downglacier – all resulting from changes in meltwater input. This provides critical insights into the interplay between surface melt and glacier movement.
Sara E. Darychuk, Joseph M. Shea, Brian Menounos, Anna Chesnokova, Georg Jost, and Frank Weber
The Cryosphere, 17, 1457–1473, https://doi.org/10.5194/tc-17-1457-2023, https://doi.org/10.5194/tc-17-1457-2023, 2023
Short summary
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.
Mads Dømgaard, Kristian K. Kjeldsen, Flora Huiban, Jonathan L. Carrivick, Shfaqat A. Khan, and Anders A. Bjørk
The Cryosphere, 17, 1373–1387, https://doi.org/10.5194/tc-17-1373-2023, https://doi.org/10.5194/tc-17-1373-2023, 2023
Short summary
Short summary
Sudden releases of meltwater from glacier-dammed lakes can influence ice flow, cause flooding hazards and landscape changes. This study presents a record of 14 drainages from 2007–2021 from a lake in west Greenland. The time series reveals how the lake fluctuates between releasing large and small amounts of drainage water which is caused by a weakening of the damming glacier following the large events. We also find a shift in the water drainage route which increases the risk of flooding hazards.
Zhaoqing Dong, Lijian Shi, Mingsen Lin, Yongjun Jia, Tao Zeng, and Suhui Wu
The Cryosphere, 17, 1389–1410, https://doi.org/10.5194/tc-17-1389-2023, https://doi.org/10.5194/tc-17-1389-2023, 2023
Short summary
Short summary
We try to explore the application of SGDR data in polar sea ice thickness. Through this study, we find that it seems difficult to obtain reasonable results by using conventional methods. So we use the 15 lowest points per 25 km to estimate SSHA to retrieve more reasonable Arctic radar freeboard and thickness. This study also provides reference for reprocessing L1 data. We will release products that are more reasonable and suitable for polar sea ice thickness retrieval to better evaluate HY-2B.
Trystan Surawy-Stepney, Anna E. Hogg, Stephen L. Cornford, and David C. Hogg
The Cryosphere Discuss., https://doi.org/10.5194/tc-2023-42, https://doi.org/10.5194/tc-2023-42, 2023
Revised manuscript accepted for TC
Short summary
Short summary
The presence of crevasses in Antarctica influences how the ice sheet behaves. It is essential, 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 the majority of Antarctica. We further develop a method of measuring change in the density of crevasses and quantify increased fracturing in important parts of the West Antarctic Ice Sheet.
Wenkai Guo, Polona Itkin, Suman Singha, Anthony P. Doulgeris, Malin Johansson, and Gunnar Spreen
The Cryosphere, 17, 1279–1297, https://doi.org/10.5194/tc-17-1279-2023, https://doi.org/10.5194/tc-17-1279-2023, 2023
Short summary
Short summary
Sea ice maps are produced to cover the MOSAiC Arctic expedition (2019–2020) and divide sea ice into scientifically meaningful classes. We use a high-resolution X-band synthetic aperture radar dataset and show how image brightness and texture systematically vary across the images. We use an algorithm that reliably corrects this effect and achieve good results, as evaluated by comparisons to ground observations and other studies. The sea ice maps are useful as a basis for future MOSAiC studies.
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.
Deniz Tobias Gök, Dirk Scherler, and Leif Stefan Anderson
The Cryosphere, 17, 1165–1184, https://doi.org/10.5194/tc-17-1165-2023, https://doi.org/10.5194/tc-17-1165-2023, 2023
Short summary
Short summary
We performed high-resolution debris-thickness mapping using land surface temperature (LST) measured from an unpiloted aerial vehicle (UAV) at various times of the day. LSTs from UAVs require calibration that varies in time. We test two approaches to quantify supraglacial debris cover, and we find that the non-linearity of the relationship between LST and debris thickness increases with LST. Choosing the best model to predict debris thickness depends on the time of the day and the terrain aspect.
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.
Tian Li, Geoffrey J. Dawson, Stephen J. Chuter, and Jonathan L. Bamber
The Cryosphere, 17, 1003–1022, https://doi.org/10.5194/tc-17-1003-2023, https://doi.org/10.5194/tc-17-1003-2023, 2023
Short summary
Short summary
The Totten and Moscow University glaciers in East Antarctica have the potential to make a significant contribution to future sea-level rise. We used a combination of different satellite measurements to show that the grounding lines have been retreating along the fast-flowing ice streams across these two glaciers. We also found two tide-modulated ocean channels that might open new pathways for the warm ocean water to enter the ice shelf cavity.
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.
Elie Dumas-Lefebvre and Dany Dumont
The Cryosphere, 17, 827–842, https://doi.org/10.5194/tc-17-827-2023, https://doi.org/10.5194/tc-17-827-2023, 2023
Short summary
Short summary
By changing the shape of ice floes, wave-induced sea ice breakup dramatically affects the large-scale dynamics of sea ice. As this process is also the trigger of multiple others, it was deemed relevant to study how breakup itself affects the ice floe size distribution. To do so, a ship sailed close to ice floes, and the breakup that it generated was recorded with a drone. The obtained data shed light on the underlying physics of wave-induced sea ice breakup.
Felix L. Müller, Stephan Paul, Stefan Hendricks, and Denise Dettmering
The Cryosphere, 17, 809–825, https://doi.org/10.5194/tc-17-809-2023, https://doi.org/10.5194/tc-17-809-2023, 2023
Short summary
Short summary
Thinning sea ice has significant impacts on the energy exchange between the atmosphere and the ocean. In this study we present visual and quantitative comparisons of thin-ice detections obtained from classified Cryosat-2 radar reflections and thin-ice-thickness estimates derived from MODIS thermal-infrared imagery. In addition to good comparability, the results of the study indicate the potential for a deeper understanding of sea ice in the polar seas and improved processing of altimeter data.
Maxim L. Lamare, John D. Hedley, and Martin D. King
The Cryosphere, 17, 737–751, https://doi.org/10.5194/tc-17-737-2023, https://doi.org/10.5194/tc-17-737-2023, 2023
Short summary
Short summary
The reflectivity of sea ice is crucial for modern climate change and for monitoring sea ice from satellites. The reflectivity depends on the angle at which the ice is viewed and the angle illuminated. The directional reflectivity is calculated as a function of viewing angle, illuminating angle, thickness, wavelength and surface roughness. Roughness cannot be considered independent of thickness, illumination angle and the wavelength. Remote sensors will use the data to image sea ice from space.
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.
Xingdong Li, Di Long, Yanhong Cui, Tingxi Liu, Jing Lu, Mohamed A. Hamouda, and Mohamed M. Mohamed
The Cryosphere, 17, 349–369, https://doi.org/10.5194/tc-17-349-2023, https://doi.org/10.5194/tc-17-349-2023, 2023
Short summary
Short summary
This study blends advantages of altimetry backscattering coefficients and waveforms to estimate ice thickness for lakes without in situ data and provides an improved water level estimation for ice-covered lakes by jointly using different threshold retracking methods. Our results show that a logarithmic regression model is more adaptive in converting altimetry backscattering coefficients into ice thickness, and lake surface snow has differential impacts on different threshold retracking methods.
Yufang Ye, Yanbing Luo, Yan Sun, Mohammed Shokr, Signe Aaboe, Fanny Girard-Ardhuin, Fengming Hui, Xiao Cheng, and Zhuoqi Chen
The Cryosphere, 17, 279–308, https://doi.org/10.5194/tc-17-279-2023, https://doi.org/10.5194/tc-17-279-2023, 2023
Short summary
Short summary
Arctic sea ice type (SITY) variation is a sensitive indicator of climate change. This study gives a systematic inter-comparison and evaluation of eight SITY products. Main results include differences in SITY products being significant, with average Arctic multiyear ice extent up to 1.8×106 km2; Ku-band scatterometer SITY products generally performing better; and factors such as satellite inputs, classification methods, training datasets and post-processing highly impacting their performance.
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.
Connor J. Shiggins, James M. Lea, and Stephen Brough
The Cryosphere, 17, 15–32, https://doi.org/10.5194/tc-17-15-2023, https://doi.org/10.5194/tc-17-15-2023, 2023
Short summary
Short summary
Iceberg detection is spatially and temporally limited around the Greenland Ice Sheet. This study presents a new, accessible workflow to automatically detect icebergs from timestamped ArcticDEM strip data. The workflow successfully produces comparable output to manual digitisation, with results revealing new iceberg area-to-volume conversion equations that can be widely applied to datasets where only iceberg outlines can be extracted (e.g. optical and SAR imagery).
Leo-Juhani Meriö, Anssi Rauhala, Pertti Ala-aho, Anton Kuzmin, Pasi Korpelainen, Timo Kumpula, Bjørn Kløve, and Hannu Marttila
The Cryosphere Discuss., https://doi.org/10.5194/tc-2022-242, https://doi.org/10.5194/tc-2022-242, 2023
Revised manuscript accepted for TC
Short summary
Short summary
Information on seasonal snow cover is essential to the understanding of snow processes and operational forecasting. We study the spatiotemporal variability of snow depth and snow processes in subarctic, boreal landscape using drones. We identified multiple theoretically known snow processes and interactions between snow and vegetation. The results highlight the potential of the drones to be used for a detailed study of snow depth in multiple land cover types and snow-vegetation interactions.
Anssi Rauhala, Leo-Juhani Meriö, Anton Kuzmin, Pasi Korpelainen, Pertti Ala-aho, Timo Kumpula, Bjørn Kløve, and Hannu Marttila
The Cryosphere Discuss., https://doi.org/10.5194/tc-2022-239, https://doi.org/10.5194/tc-2022-239, 2022
Revised manuscript accepted for TC
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 in 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.
James Anheuser, Yinghui Liu, and Jeffrey R. Key
The Cryosphere, 16, 4403–4421, https://doi.org/10.5194/tc-16-4403-2022, https://doi.org/10.5194/tc-16-4403-2022, 2022
Short summary
Short summary
A prominent part of the polar climate system is sea ice, a better understanding of which would lead to better understanding Earth's climate. Newly published methods for observing the temperature of sea ice have made possible a new method for estimating daily sea ice thickness growth from space using an energy balance. The method compares well with existing sea ice thickness observations.
Mikko Lensu and Markku Similä
The Cryosphere, 16, 4363–4377, https://doi.org/10.5194/tc-16-4363-2022, https://doi.org/10.5194/tc-16-4363-2022, 2022
Short summary
Short summary
Ice ridges form a compressing ice cover. From above they appear as walls of up to few metres in height and extend even kilometres across the ice. Below they may reach tens of metres under the sea surface. Ridges need to be observed for the purposes of ice forecasting and ice information production. This relies mostly on ridging signatures discernible in radar satellite (SAR) images. New methods to quantify ridging from SAR have been developed and are shown to agree with field observations.
Xinde Chu, Xiaojun Yao, Hongyu Duan, Cong Chen, Jing Li, and Wenlong Pang
The Cryosphere, 16, 4273–4289, https://doi.org/10.5194/tc-16-4273-2022, https://doi.org/10.5194/tc-16-4273-2022, 2022
Short summary
Short summary
The available remote-sensing data are increasingly abundant, and the efficient and rapid acquisition of glacier boundaries based on these data is currently a frontier issue in glacier research. In this study, we designed a complete solution to automatically extract glacier outlines from the high-resolution images. Compared with other methods, our method achieves the best performance for glacier boundary extraction in parts of the Tanggula Mountains, Kunlun Mountains and Qilian Mountains.
Julienne Stroeve, Vishnu Nandan, Rosemary Willatt, Ruzica Dadic, Philip Rostosky, Michael Gallagher, Robbie Mallett, Andrew Barrett, Stefan Hendricks, Rasmus Tonboe, Michelle McCrystall, Mark Serreze, Linda Thielke, Gunnar Spreen, Thomas Newman, John Yackel, Robert Ricker, Michel Tsamados, Amy Macfarlane, Henna-Reetta Hannula, and Martin Schneebeli
The Cryosphere, 16, 4223–4250, https://doi.org/10.5194/tc-16-4223-2022, https://doi.org/10.5194/tc-16-4223-2022, 2022
Short summary
Short summary
Impacts of rain on snow (ROS) on satellite-retrieved sea ice variables remain to be fully understood. This study evaluates the impacts of ROS over sea ice on active and passive microwave data collected during the 2019–20 MOSAiC expedition. Rainfall and subsequent refreezing of the snowpack significantly altered emitted and backscattered radar energy, laying important groundwork for understanding their impacts on operational satellite retrievals of various sea ice geophysical variables.
Karla Boxall, Frazer D. W. Christie, Ian C. Willis, Jan Wuite, and Thomas Nagler
The Cryosphere, 16, 3907–3932, https://doi.org/10.5194/tc-16-3907-2022, https://doi.org/10.5194/tc-16-3907-2022, 2022
Short summary
Short summary
Using high-spatial- and high-temporal-resolution satellite imagery, we provide the first evidence for seasonal flow variability of land ice draining to George VI Ice Shelf (GVIIS), Antarctica. Ultimately, our findings imply that other glaciers in Antarctica may be susceptible to – and/or currently undergoing – similar ice-flow seasonality, including at the highly vulnerable and rapidly retreating Pine Island and Thwaites glaciers.
Benjamin Heikki Redmond Roche and Martin D. King
The Cryosphere, 16, 3949–3970, https://doi.org/10.5194/tc-16-3949-2022, https://doi.org/10.5194/tc-16-3949-2022, 2022
Short summary
Short summary
Sea ice is bright, playing an important role in reflecting incoming solar radiation. The reflectivity of sea ice is affected by the presence of pollutants, such as crude oil, even at low concentrations. Modelling how the brightness of three types of sea ice is affected by increasing concentrations of crude oils shows that the type of oil, the type of ice, the thickness of the ice, and the size of the oil droplets are important factors. This shows that sea ice is vulnerable to oil pollution.
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.
Cited articles
Abdalati, W. and Steffen, K.: Passive microwave-derived snow melt regions on the Greenland Ice Sheet, Geophys. Res. Lett., 22, 787–790, 1995.
Apgar, J. D., Ramage, J. M., McKenney, R. A., and Maltais, P.: AMSR-E algorithm for snowmelt onset detection in sub-arctic heterogeneous terrain, Hydrol. Process., 21, 1587–1596, 2007.
Archer, D. R. and Fowler, H. J.: Spatial and temporal variations in precipitation in the Upper Indus Basin, global teleconnections and hydrological implications, Hydrol. Earth Syst. Sci., 8, 47–61, https://doi.org/10.5194/hess-8-47-2004, 2004.
Armstrong, R. and Brodzik, M.: Recent Northern Hemisphere snow extent: a comparison of data derived from visible and microwave satellite sensors, Geophys. Res. Lett., 28, 3673–3676, 2001.
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.
Bolch, T., Kulkarni, A., Kääb, A., Huggel, C., Paul, F., Cogley, J. G., Frey, H., Kargel, J. S., Fujita, K., Scheel, M., Bajracharya, S., and Stoffel, M.: The state and fate of Himalayan glaciers, Science, 336, 310–314, 2012.
Bookhagen, B.: Chapter 11: The influence of hydrology and glaciology on wetlands in the Himalaya, in: Bird Migration Across the Himalayas: Wetland Functioning Amidst Mountains and Glaciers, edited by: Prins, H. and Namgail, T., Cambridge University press, Cambridge, UK, 2017.
Bookhagen, B. and Burbank, D. W.: Toward a complete Himalayan hydrological budget: spatiotemporal distribution of snowmelt and rainfall and their impact on river discharge, J. Geophys. Res.-Earth, 115, 2156–2202, 2010.
Cannon, F., Carvalho, L., Jones, C., and Bookhagen, B.: Multi-annual variations in winter westerly disturbance activity affecting the Himalaya, Clim. Dynam., 1–15, 2014.
Cannon, F., Carvalho, L. M., Jones, C., and Norris, J.: Winter westerly disturbance dynamics and precipitation in the western Himalaya and Karakoram: a wave-tracking approach, Theor. Appl. Climatol., 125, 1–18, 2015.
Cannon, F., Carvalho, L., Jones, C., Hoell, A., Norris, J., Kiladis, G., and Tahir, A.: The influence of tropical forcing on extreme winter precipitation in the western Himalaya, Clim. Dynam., 48, 1213–1232, 2016.
Cannon, F., Carvalho, L. M. V., Jones, C., Norris, J., Bookhagen, B., and Kiladis, G. N.: Effects of Topographic Smoothing on the Simulation of Winter Precipitation in High Mountain Asia, J. Geophys. Res.-Atmos., 122, https://doi.org/10.1002/2016JD026038, 2017.
Chang, A., Foster, J., and Hall, D.: Nimbus-7 SMMR derived global snow cover parameters, Ann. Glaciol., 9, 39–44, 1987.
Che, T., Xin, L., Jin, R., Armstrong, R., and Zhang, T.: Snow depth derived from passive microwave remote-sensing data in China, Ann. Glaciol., 49, 145–154, 2008.
Corpet, F.: Multiple sequence alignment with hierarchical clustering, Nucleic Acids Res., 16, 10881–10890, 1988.
Dahe, Q., Shiyin, L., and Peiji, L.: Snow cover distribution, variability, and response to climate change in western China, J. Climate, 19, 1820–1833, 2006.
Daly, S. F., Vuyovich, C. M., Deeb, E. J., Newman, S. D., Baldwin, T. B., and Gagnon, J. J.: Assessment of the snow conditions in the major watersheds of Afghanistan using multispectral and passive microwave remote sensing, Hydrol. Process., 26, 2631–2642, 2012.
Dietz, A. J., Conrad, C., Kuenzer, C., Gesell, G., and Dech, S.: Identifying changing snow cover characteristics in Central Asia between 1986 and 2014 from remote sensing data, Remote Sensing, 6, 12752–12775, 2014.
Drobot, S. D. and Anderson, M. R.: An improved method for determining snowmelt onset dates over Arctic sea ice using scanning multichannel microwave radiometer and Special Sensor Microwave/Imager data, J. Geophys. Res., 106, 24033–24049, https://doi.org/10.1029/2000JD00017, 2001.
Gardelle, J., Berthier, E., and Arnaud, Y.: Slight mass gain of Karakoram glaciers in the early twenty-first century, Nat. Geosci., 5, 322–325, 2012.
Gardner, A. S., Moholdt, G., Cogley, J. G., Wouters, B., Arendt, A. A., Wahr, J., Berthier, E., Hock, R., Pfeffer, W. T., Kaser, G., Ligtenberg, S. R. M., Bolch, T., Sharp, M. J., Hagen, J. O., van den Broeke, M. R., and Paul, F.: A reconciled estimate of glacier contributions to sea level rise: 2003 to 2009, Science, 340, 852–857, 2013.
Hall, D. K. and Riggs, G. A.: MODIS/Terra Snow Cover Daily L3 Global 0.05Deg CMG, Version 6, Boulder, Colorado USA, NASA National Snow and Ice Data Center Distributed Active Archive Center, https://doi.org/10.5067/MODIS/MOD10C1.006, 2016.
Hall, D. K., Williams Jr., R. S., Steffen, K., and Chien, J. Y.: Analysis of summer 2002 melt extent on the Greenland Ice Sheet using MODIS and SSM/I data, in: Geoscience and Remote Sensing Symposium, 2004, IGARSS'04, Proceedings, 2004 IEEE International, vol. 5, IEEE, Anchorage, AK, USA, 20–24 September 2004, 3029–3032, 2004.
Hewitt, K.: The Karakoram anomaly? Glacier expansion and the “elevation effect”, Karakoram Himalaya, Mt. Res. Dev., 25, 332–340, 2005.
Immerzeel, W. and Bierkens, M.: Asia's water balance, Nat. Geosci., 5, 841–842, 2012.
Immerzeel, W. W., Van Beek, L. P., and Bierkens, M. F.: Climate change will affect the Asian water towers, Science, 328, 1382–1385, 2010.
Jain, A. K., Murty, M. N., and Flynn, P. J.: Data clustering: a review, ACM Comput. Surv., 31, 264–323, 1999.
Johnson, S. C.: Hierarchical clustering schemes, Psychometrika, 32, 241–254, 1967.
Joshi, M., Merry, C. J., Jezek, K. C., and Bolzan, J. F.: An edge detection technique to estimate melt duration, season and melt extent on the Greenland ice sheet using passive microwave data, Geophys. Res. Lett., 28, 3497–3500, 2001.
Kääb, A., Berthier, E., Nuth, C., Gardelle, J., and Arnaud, Y.: Contrasting patterns of early twenty-first-century glacier mass change in the Himalayas, Nature, 488, 495–498, 2012.
Kääb, A., Treichler, D., Nuth, C., and Berthier, E.: Brief Communication: Contending estimates of 2003–2008 glacier mass balance over the Pamir–Karakoram–Himalaya, The Cryosphere, 9, 557–564, https://doi.org/10.5194/tc-9-557-2015, 2015.
Kang, S., Xu, Y., You, Q., Flügel, W.-A., Pepin, N., and Yao, T.: Review of climate and cryospheric change in the Tibetan Plateau, Environ. Res. Lett., 5, 015101, https://doi.org/10.1088/1748-9326/5/1/015101, 2010.
Kapnick, S. B., Delworth, T. L., Ashfaq, M., Malyshev, S., and Milly, P.: Snowfall less sensitive to warming in Karakoram than in Himalayas due to a unique seasonal cycle, Nat. Geosci., 7, 834–840, 2014.
Kelly, R.: The AMSR-E snow depth algorithm: description and initial results, Journal of the Remote Sensing Society of Japan, 29, 307–317, 2009.
Kelly, R. E., Chang, A. T., Tsang, L., and Foster, J. L.: A prototype AMSR-E global snow area and snow depth algorithm, IEEE T. Geosci. Remote, 41, 230–242, 2003.
Lau, W. K., Kim, M.-K., Kim, K.-M., and Lee, W.-S.: Enhanced surface warming and accelerated snow melt in the Himalayas and Tibetan Plateau induced by absorbing aerosols, Environ. Res. Lett., 5, 025204, https://doi.org/10.1088/1748-9326/5/2/025204, 2010.
Lioubimtseva, E. and Henebry, G. M.: Climate and environmental change in arid Central Asia: impacts, vulnerability, and adaptations, J. Arid Environ., 73, 963–977, 2009.
Liu, H., Wang, L., and Jezek, K. C.: Wavelet-transform based edge detection approach to derivation of snowmelt onset, end and duration from satellite passive microwave measurements, Int. J. Remote Sens., 26, 4639–4660, 2005.
Lutz, A., Immerzeel, W., Shrestha, A., and Bierkens, M.: Consistent increase in High Asia's runoff due to increasing glacier melt and precipitation, Nat. Clim. Change, 4, 587–592, 2014.
Malik, N., Bookhagen, B., and Mucha, P. J.: Spatiotemporal patterns and trends of Indian monsoonal rainfall extremes, Geophys. Res. Lett., 43, 1710–1717, 2016.
Maussion, F., Scherer, D., Mölg, T., Collier, E., Curio, J., and Finkelnburg, R.: Precipitation seasonality and variability over the Tibetan Plateau as resolved by the High Asia reanalysis*, J. Climate, 27, 1910–1927, 2014.
Monahan, P. A. and Ramage, J.: AMSR-E melt patterns on the Southern Patagonia Icefield, J. Glaciol., 56, 699–708, 2010.
Murtagh, F. and Contreras, P.: Algorithms for hierarchical clustering: an overview, Wires. Data Min. Knowl., 2, 86–97, 2012.
Norris, J., Carvalho, L. M., Jones, C., and Cannon, F.: WRF simulations of two extreme snowfall events associated with contrasting extratropical cyclones over the western and central Himalaya, J. Geophys. Res.-Atmos., 120, 3114–3138, 2015.
Norris, J., Carvalho, L. M., Jones, C., Cannon, F., Bookhagen, B., Palazzi, E., and Tahir, A. A.: The spatiotemporal variability of precipitation over the Himalaya: evaluation of one-year WRF model simulation, Clim. Dynam., 49, 1–26, 2016.
Panday, P. K., Frey, K. E., and Ghimire, B.: Detection of the timing and duration of snowmelt in the Hindu Kush-Himalaya using QuikSCAT, 2000–2008, Environ. Res. Lett., 6, 024007, https://doi.org/10.1088/1748-9326/6/2/024007, 2011.
Rheinwalt, A.: Python C-extension for memory efficient and multithreaded Pearson product-moment correlation coefficient estimation using OpenMP, available at: https://github.com/UP-RS-ESP/CorrCoef, 2017a.
Rheinwalt, A.: Normalize time series by quantile normalization to the normal distribution, available at: https://github.com/UP-RS-ESP/Normalize, 2017b.
Rheinwalt, A., Goswami, B., Boers, N., Heitzig, J., Marwan, N., Krishnan, R., and Kurths, J.: Teleconnections in climate networks: a network-of-networks approach to investigate the influence of sea surface temperature variability on monsoon systems, in: Machine Learning and Data Mining Approaches to Climate Science, Springer, 23–33, 2015.
Romanov, P.: Global Multisensor Automated satellite-based Snow and Ice Mapping System (GMASI) for cryosphere monitoring, Remote Sens. Environ., 196, 42–55, 2017.
Scherler, D., Bookhagen, B., and Strecker, M. R.: Spatially variable response of Himalayan glaciers to climate change affected by debris cover, Nat. Geosci., 4, 156–159, 2011.
Shrestha, M., Koike, T., Hirabayashi, Y., Xue, Y., Wang, L., Rasul, G., and Ahmad, B.: Integrated simulation of snow and glacier melt in water and energy balance-based, distributed hydrological modeling framework at Hunza River Basin of Pakistan Karakoram region, J. Geophys. Res.-Atmos., 120, 4889–4919, 2015.
Smith, T. and Bookhagen, B.: Assessing uncertainty and sensor biases in passive microwave data across High Mountain Asia, Remote Sens. Environ., 181, 174–185, 2016.
Smith, T. and Bookhagen, B.: Snowmelt Paramaters, 1987–2016, High Mountain Asia. V. 1.0. GFZ German Research Center for Geosciences, https://doi.org/10.5880/fidgeo.2017.006, 2017.
Stewart, I. T.: Changes in snowpack and snowmelt runoff for key mountain regions, Hydrol. Process., 23, 78–94, 2009.
Takala, M., Pulliainen, J., Huttunen, M., and Hallikainen, M.: Estimation of the beginning of snow melt period using SSM/I data, in: Geoscience and Remote Sensing Symposium, 2003, IGARSS'03, Proceedings, 2003 IEEE International, vol. 4, IEEE, 21–25 July 2003, Toulouse, France, 2841–2843, 2003.
Takala, M., Pulliainen, J., Huttunen, M., and Hallikainen, M.: Detecting the onset of snow-melt using SSM/I data and the self-organizing map, Int. J. Remote Sens., 29, 755–766, 2008.
Takala, M., Pulliainen, J., Metsämäki, S. J., and Koskinen, J. T.: Detection of snowmelt using spaceborne microwave radiometer data in Eurasia from 1979 to 2007, IEEE T. Geosci. Remote, 47, 2996–3007, 2009.
Takala, M., Luojus, K., Pulliainen, J., Derksen, C., Lemmetyinen, J., Kärnä, J.-P., Koskinen, J., and Bojkov, B.: Estimating Northern Hemisphere snow water equivalent for climate research through assimilation of space-borne radiometer data and ground-based measurements, Remote Sens. Environ., 115, 3517–3529, 2011.
Tedesco, M.: Snowmelt detection over the Greenland ice sheet from SSM/I brightness temperature daily variations, Geophys. Res. Lett., 34, L02504, https://doi.org/10.1029/2006GL028466, 2007.
Tedesco, M. and Narvekar, P. S.: Assessment of the NASA AMSR-E SWE product, selected topics in applied earth observations and remote sensing, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 3, 141–159, 2010.
Tedesco, M., Derksen, C., Deems, J. S., and Foster, J. L.: Remote sensing of snow depth and snow water equivalent, in: Remote Sensing of the Cryosphere, edited by: Tedesco, M., John Wiley & Sons, Ltd, Chichester, UK, https://doi.org/10.1002/9781118368909.ch5, 2015.
Treydte, K. S., Schleser, G. H., Helle, G., Frank, D. C., Winiger, M., Haug, G. H., and Esper, J.: The twentieth century was the wettest period in northern Pakistan over the past millennium, Nature, 440, 1179–1182, 2006.
Vaughan, D., Comiso, J., Allison, I., Carrasco, J., Kaser, G., Kwok, R., Mote, P., Murray, T., Paul, F., Ren, J., Rignot, E., Solomina, O., Steffen, K., and Zhang, T.: Observations: cryosphere, in: Climate Change 2013: The Physical Science Basis, Contribution of Working Group I to the Fifth Assessment Report of the IPCC, Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 2013.
Wang, Q., Yi, S., and Sun, W.: Precipitation-driven glacier changes in the Pamir and Hindu Kush mountains, Geophys. Res. Lett., 44, 2817–2824, https://doi.org/10.1002/2017GL072646, 2017.
Wang, T., Peng, S., Lin, X., and Chang, J.: Declining snow cover may affect spring phenological trend on the Tibetan Plateau, P. Natl. Acad. Sci. USA, 110, E2854–E2855, 2013.
Wentz, F. J.: SSM/I version-7 calibration report, Remote Sensing Systems Rep., Remote Sensing Systems, Santa Rosa, CA, 11012, 46, 2013.
Willis, I. C., Arnold, N. S., and Brock, B. W.: Effect of snowpack removal on energy balance, melt and runoff in a small supraglacial catchment, Hydrol. Process., 16, 2721–2749, https://doi.org/10.1002/hyp.1067, 2002.
Xiong, C., Shi, J., Cui, Y., and Peng, B.: Snowmelt pattern over High-Mountain Asia detected from active and passive microwave remote sensing, IEEE Geosci. Remote S., in press, https://doi.org/10.1109/LGRS.2017.2698448, 2017.
Xu, W., Ma, L., Ma, M., Zhang, H., and Yuan, W.: Spatial–temporal variability of snow cover and depth in the Qinghai–Tibetan Plateau, J. Climate, 30, 1521–1533, 2017.
Yao, T., Thompson, L., Yang, W., Yu, W., Gao, Y., Guo, X., Yang, X., Duan, K., Zhao, H., Xu, B., Pu, J., Lu, A., Xiang, Y., Kattel, D. B., and Joswiak, D.: Different glacier status with atmospheric circulations in Tibetan Plateau and surroundings, Nat. Clim. Change, 2, 663–667, 2012.
Zhang, Y., Li, T., and Wang, B.: Decadal change of the spring snow depth over the Tibetan Plateau: the associated circulation and influence on the east Asian summer monsoon*, J. Climate, 17, 2780–2793, 2004.
Short summary
High Mountain Asia’s rivers, which serve more than a billion people, receive a significant portion of their water budget in the form of snow. We develop an algorithm to track timing of the snowmelt season using passive microwave data from 1987 to 2016. We find that most of High Mountain Asia has experienced shorter melt seasons, earlier snow clearance, and earlier snowmelt onset, but that these changes are highly spatially and temporally heterogeneous.
High Mountain Asia’s rivers, which serve more than a billion people, receive a significant...
