Articles | Volume 15, issue 9
Research article 24 Sep 2021
Research article | 24 Sep 2021
Mapping seasonal glacier melt across the Hindu Kush Himalaya with time series synthetic aperture radar (SAR)
Corey Scher et al.
No articles found.
Zhen Zhang, Etienne Fluet-Chouinard, Katherine Jensen, Kyle McDonald, Gustaf Hugelius, Thomas Gumbricht, Mark Carroll, Catherine Prigent, Annett Bartsch, and Benjamin Poulter
Earth Syst. Sci. Data, 13, 2001–2023,Short summary
The spatiotemporal distribution of wetlands is one of the important and yet uncertain factors determining the time and locations of methane fluxes. The Wetland Area and Dynamics for Methane Modeling (WAD2M) dataset describes the global data product used to quantify the areal dynamics of natural wetlands and how global wetlands are changing in response to climate.
Sean Hartery, Róisín Commane, Jakob Lindaas, Colm Sweeney, John Henderson, Marikate Mountain, Nicholas Steiner, Kyle McDonald, Steven J. Dinardo, Charles E. Miller, Steven C. Wofsy, and Rachel Y.-W. Chang
Atmos. Chem. Phys., 18, 185–202,Short summary
Methane is the second most important greenhouse gas but its emissions from northern regions are still poorly constrained. This study uses aircraft measurements of methane from Alaska to estimate surface emissions. We found that methane emission rates depend on the soil temperature at depths where its production was taking place, and that total emissions were similar between tundra and boreal regions. These results provide a simple way to predict methane emissions in this region.
A. Anthony Bloom, Kevin W. Bowman, Meemong Lee, Alexander J. Turner, Ronny Schroeder, John R. Worden, Richard Weidner, Kyle C. McDonald, and Daniel J. Jacob
Geosci. Model Dev., 10, 2141–2156,Short summary
Wetland emissions are a principal source of uncertainty in the global atmospheric methane budget due to poor knowledge of wetland processes. We construct a wetland methane emission and uncertainty dataset for use in global atmospheric methane models. Our wetland model ensemble is based on static wetland maps, satellite-derived inundation and carbon cycle models. The ensemble performs favourably against regional flux estimates and atmospheric methane measurements relative to previous studies.
Marielle Saunois, Philippe Bousquet, Ben Poulter, Anna Peregon, Philippe Ciais, Josep G. Canadell, Edward J. Dlugokencky, Giuseppe Etiope, David Bastviken, Sander Houweling, Greet Janssens-Maenhout, Francesco N. Tubiello, Simona Castaldi, Robert B. Jackson, Mihai Alexe, Vivek K. Arora, David J. Beerling, Peter Bergamaschi, Donald R. Blake, Gordon Brailsford, Victor Brovkin, Lori Bruhwiler, Cyril Crevoisier, Patrick Crill, Kristofer Covey, Charles Curry, Christian Frankenberg, Nicola Gedney, Lena Höglund-Isaksson, Misa Ishizawa, Akihiko Ito, Fortunat Joos, Heon-Sook Kim, Thomas Kleinen, Paul Krummel, Jean-François Lamarque, Ray Langenfelds, Robin Locatelli, Toshinobu Machida, Shamil Maksyutov, Kyle C. McDonald, Julia Marshall, Joe R. Melton, Isamu Morino, Vaishali Naik, Simon O'Doherty, Frans-Jan W. Parmentier, Prabir K. Patra, Changhui Peng, Shushi Peng, Glen P. Peters, Isabelle Pison, Catherine Prigent, Ronald Prinn, Michel Ramonet, William J. Riley, Makoto Saito, Monia Santini, Ronny Schroeder, Isobel J. Simpson, Renato Spahni, Paul Steele, Atsushi Takizawa, Brett F. Thornton, Hanqin Tian, Yasunori Tohjima, Nicolas Viovy, Apostolos Voulgarakis, Michiel van Weele, Guido R. van der Werf, Ray Weiss, Christine Wiedinmyer, David J. Wilton, Andy Wiltshire, Doug Worthy, Debra Wunch, Xiyan Xu, Yukio Yoshida, Bowen Zhang, Zhen Zhang, and Qiuan Zhu
Earth Syst. Sci. Data, 8, 697–751,Short summary
An accurate assessment of the methane budget is important to understand the atmospheric methane concentrations and trends and to provide realistic pathways for climate change mitigation. The various and diffuse sources of methane as well and its oxidation by a very short lifetime radical challenge this assessment. We quantify the methane sources and sinks as well as their uncertainties based on both bottom-up and top-down approaches provided by a broad international scientific community.
Xiyan Xu, William J. Riley, Charles D. Koven, Dave P. Billesbach, Rachel Y.-W. Chang, Róisín Commane, Eugénie S. Euskirchen, Sean Hartery, Yoshinobu Harazono, Hiroki Iwata, Kyle C. McDonald, Charles E. Miller, Walter C. Oechel, Benjamin Poulter, Naama Raz-Yaseef, Colm Sweeney, Margaret Torn, Steven C. Wofsy, Zhen Zhang, and Donatella Zona
Biogeosciences, 13, 5043–5056,Short summary
Wetlands are the largest global natural methane source. Peat-rich bogs and fens lying between 50°N and 70°N contribute 10–30% to this source. The predictive capability of the seasonal methane cycle can directly affect the estimation of global methane budget. We present multiscale methane seasonal emission by observations and modeling and find that the uncertainties in predicting the seasonal methane emissions are from the wetland extent, cold-season CH4 production and CH4 transport processes.
J. M. Henderson, J. Eluszkiewicz, M. E. Mountain, T. Nehrkorn, R. Y.-W. Chang, A. Karion, J. B. Miller, C. Sweeney, N. Steiner, S. C. Wofsy, and C. E. Miller
Atmos. Chem. Phys., 15, 4093–4116,Short summary
This paper describes the atmospheric modeling that underlies the science analysis for the NASA Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE). Summary statistics of the WRF meteorological model performance on a 3.3 km grid indicate good overall agreement with surface and radiosonde observations. The high quality of the WRF meteorological fields inspires confidence in their use to drive the STILT transport model for the purpose of computing surface influence fields (“footprints”).
N. Steiner and M. Tedesco
The Cryosphere, 8, 25–40,
Related subject area
Discipline: Glaciers | Subject: Remote SensingEstimating surface mass balance patterns from unoccupied aerial vehicle measurements in the ablation area of the Morteratsch–Pers glacier complex (Switzerland)High-resolution topography of the Antarctic Peninsula combining the TanDEM-X DEM and Reference Elevation Model of Antarctica (REMA) mosaicMeasuring the state and temporal evolution of glaciers in Alaska and Yukon using synthetic-aperture-radar-derived (SAR-derived) 3D time series of glacier surface flowTracking changes in the area, thickness, and volume of the Thwaites tabular iceberg “B30” using satellite altimetry and imageryAnalyzing glacier retreat and mass balances using aerial and UAV photogrammetry in the Ötztal Alps, AustriaSurges of Harald Moltke Bræ, north-western Greenland: seasonal modulation and initiation at the terminusBrief communication: An empirical relation between center frequency and measured thickness for radar sounding of temperate glaciersBrief Communication: Detection of glacier surge activity using cloud computing of Sentinel-1 radar dataGlacier Image Velocimetry: an open-source toolbox for easy and rapid calculation of high-resolution glacier velocity fieldsCalving Front Machine (CALFIN): glacial termini dataset and automated deep learning extraction method for Greenland, 1972–2019Annual and inter-annual variability and trends of albedo of Icelandic glaciersObserving traveling waves in glaciers with remote sensing: new flexible time series methods and application to Sermeq Kujalleq (Jakobshavn Isbræ), GreenlandSurface composition of debris-covered glaciers across the Himalaya using spectral unmixing and multi-sensor imageryDetecting seasonal ice dynamics in satellite imagesInSAR-based characterization of rock glacier movement in the Uinta Mountains, Utah, USASharp contrasts in observed and modeled crevasse patterns at Greenland's marine terminating glaciersImage Classification of Marine-Terminating Outlet Glaciers using Deep Learning MethodsVariability in glacier albedo and links to annual mass balance for the gardens of Eden and Allah, Southern Alps, New ZealandThe seasonal evolution of albedo across glaciers and the surrounding landscape of Taylor Valley, AntarcticaRecent glacier and lake changes in High Mountain Asia and their relation to precipitation changesMultisensor validation of tidewater glacier flow fields derived from synthetic aperture radar (SAR) intensity trackingDetecting dynamics of cave floor ice with selective cloud-to-cloud approachChanges of the tropical glaciers throughout Peru between 2000 and 2016 – mass balance and area fluctuationsIceberg topography and volume classification using TanDEM-X interferometryAutomatically delineating the calving front of Jakobshavn Isbræ from multitemporal TerraSAR-X images: a deep learning approachSensitivity of glacier volume change estimation to DEM void interpolationExtracting recent short-term glacier velocity evolution over southern Alaska and the Yukon from a large collection of Landsat dataChange detection of bare-ice albedo in the Swiss AlpsCharacterizing the behaviour of surge- and non-surge-type glaciers in the Kingata Mountains, eastern Pamir, from 1999 to 2016Automated detection of ice cliffs within supraglacial debris coverBrief communication: Unabated wastage of the Juneau and Stikine icefields (southeast Alaska) in the early 21st century
Lander Van Tricht, Philippe Huybrechts, Jonas Van Breedam, Alexander Vanhulle, Kristof Van Oost, and Harry Zekollari
The Cryosphere, 15, 4445–4464,Short summary
We conducted innovative research on the use of drones to determine the surface mass balance (SMB) of two glaciers. Considering appropriate spatial scales, we succeeded in determining the SMB in the ablation area with large accuracy. Consequently, we are convinced that our method and the use of drones to monitor the mass balance of a glacier’s ablation area can be an add-on to stake measurements in order to obtain a broader picture of the heterogeneity of the SMB of glaciers.
Yuting Dong, Ji Zhao, Dana Floricioiu, Lukas Krieger, Thomas Fritz, and Michael Eineder
The Cryosphere, 15, 4421–4443,Short summary
We generated a consistent, gapless and high-resolution (12 m) topography product of the Antarctic Peninsula by combining the complementary advantages of the two most recent high-resolution digital elevation model (DEM) products: the TanDEM-X DEM and the Reference Elevation Model of Antarctica. The generated DEM maintains the characteristics of the TanDEM-X DEM, has a better quality due to the correction of the residual height errors in the non-edited TanDEM-X DEM and will be freely available.
Sergey Samsonov, Kristy Tiampo, and Ryan Cassotto
The Cryosphere, 15, 4221–4239,Short summary
The direction and intensity of glacier surface flow adjust in response to a warming climate, causing sea level rise, seasonal flooding and droughts, and changing landscapes and habitats. We developed a technique that measures the evolution of surface flow for a glaciated region in three dimensions with high temporal and spatial resolution and used it to map the temporal evolution of glaciers in southeastern Alaska (Agassiz, Seward, Malaspina, Klutlan, Walsh, and Kluane) during 2016–2021.
Anne Braakmann-Folgmann, Andrew Shepherd, and Andy Ridout
The Cryosphere, 15, 3861–3876,Short summary
We investigate the disintegration of the B30 iceberg using satellite remote sensing and find that the iceberg lost 378 km3 of ice in 6.5 years, corresponding to 80 % of its initial volume. About two thirds are due to fragmentation at the sides, and one third is due to melting at the iceberg’s base. The release of fresh water and nutrients impacts ocean circulation, sea ice formation, and biological production. We show that adding a snow layer is important when deriving iceberg thickness.
Joschka Geissler, Christoph Mayer, Juilson Jubanski, Ulrich Münzer, and Florian Siegert
The Cryosphere, 15, 3699–3717,Short summary
The study demonstrates the potential of photogrammetry for analyzing glacier retreat with high spatial resolution. Twenty-three glaciers within the Ötztal Alps are analyzed. We compare photogrammetric and glaciologic mass balances of the Vernagtferner by using the ELA for our density assumption and an UAV survey for a temporal correction of the geodetic mass balances. The results reveal regions of anomalous mass balance and allow estimates of the imbalance between mass balances and ice dynamics.
Lukas Müller, Martin Horwath, Mirko Scheinert, Christoph Mayer, Benjamin Ebermann, Dana Floricioiu, Lukas Krieger, Ralf Rosenau, and Saurabh Vijay
The Cryosphere, 15, 3355–3375,Short summary
Harald Moltke Bræ, a marine-terminating glacier in north-western Greenland, undergoes remarkable surges of episodic character. Our data show that a recent surge from 2013 to 2019 was initiated at the glacier front and exhibits a pronounced seasonality with flow velocities varying by 1 order of magnitude, which has not been observed at Harald Moltke Bræ in this way before. These findings are crucial for understanding surge mechanisms at Harald Moltke Bræ and other marine-terminating glaciers.
Joseph A. MacGregor, Michael Studinger, Emily Arnold, Carlton J. Leuschen, Fernando Rodríguez-Morales, and John D. Paden
The Cryosphere, 15, 2569–2574,Short summary
We combine multiple recent global glacier datasets and extend one of them (GlaThiDa) to evaluate past performance of radar-sounding surveys of the thickness of Earth's temperate glaciers. An empirical envelope for radar performance as a function of center frequency is determined, its limitations are discussed and its relevance to future radar-sounder survey and system designs is considered.
Paul Willem Leclercq, Andreas Kääb, and Bas Altena
The Cryosphere Discuss.,
Revised manuscript accepted for TCShort summary
In this study we present a novel method to detect glacier surge activity. Surges are relevant as they disturb the link between glacier change and climate and studying surges can also increase understanding of glacier flow. We use variations in Sentinel-1 radar backscatter strength, calculated with the use of Google Earth Engine, to detect surge activity. In our case study for the year 2018–2019 we find 69 cases of surging glaciers globally. Many of these were not previously known to be surging.
Maximillian Van Wyk de Vries and Andrew D. Wickert
The Cryosphere, 15, 2115–2132,Short summary
We can measure glacier flow and sliding velocity by tracking patterns on the ice surface in satellite images. The surface velocity of glaciers provides important information to support assessments of glacier response to climate change, to improve regional assessments of ice thickness, and to assist with glacier fieldwork. Our paper describes Glacier Image Velocimetry (GIV), a new, easy-to-use, and open-source toolbox for calculating high-resolution velocity time series for any glacier on earth.
Daniel Cheng, Wayne Hayes, Eric Larour, Yara Mohajerani, Michael Wood, Isabella Velicogna, and Eric Rignot
The Cryosphere, 15, 1663–1675,Short summary
Tracking changes in Greenland's glaciers is important for understanding Earth's climate, but it is time consuming to do so by hand. We train a program, called CALFIN, to automatically track these changes with human levels of accuracy. CALFIN is a special type of program called a neural network. This method can be applied to other glaciers and eventually other tracking tasks. This will enhance our understanding of the Greenland Ice Sheet and permit better models of Earth's climate.
Andri Gunnarsson, Sigurdur M. Gardarsson, Finnur Pálsson, Tómas Jóhannesson, and Óli G. B. Sveinsson
The Cryosphere, 15, 547–570,Short summary
Surface albedo quantifies the fraction of the sunlight reflected by the surface of the Earth. During the melt season in the Northern Hemisphere solar energy absorbed by snow- and ice-covered surfaces is mainly controlled by surface albedo. For Icelandic glaciers, air temperature and surface albedo are the dominating factors governing annual variability of glacier surface melt. Satellite data from the MODIS sensor are used to create a data set spanning the glacier melt season.
Bryan Riel, Brent Minchew, and Ian Joughin
The Cryosphere, 15, 407–429,Short summary
The availability of large volumes of publicly available remote sensing data over terrestrial glaciers provides new opportunities for studying the response of glaciers to a changing climate. We present an efficient method for tracking changes in glacier speeds at high spatial and temporal resolutions from surface observations, demonstrating the recovery of traveling waves over Jakobshavn Isbræ, Greenland. Quantification of wave properties may ultimately enhance understanding of glacier dynamics.
Adina E. Racoviteanu, Lindsey Nicholson, and Neil F. Glasser
The Cryosphere Discuss.,
Revised manuscript accepted for TCShort summary
High mountain glaciers are often characterized by supraglacial debris comprising ponds, exposed ice cliffs and dry vegetation. Quantifying the composition of these surfaces is essential to understand glacier hydrology and related hazards. We used linear spectral unmixing of satellite data to map supraglacial features across the Himalaya. One of the highlights of this study is the automated mapping of supraglacial ponds, which complements and expands the existing lake databases for the year 2015.
Chad A. Greene, Alex S. Gardner, and Lauren C. Andrews
The Cryosphere, 14, 4365–4378,Short summary
Seasonal variability is a fundamental characteristic of any Earth surface system, but we do not fully understand which of the world's glaciers speed up and slow down on an annual cycle. Such short-timescale accelerations may offer clues about how individual glaciers will respond to longer-term changes in climate, but understanding any behavior requires an ability to observe it. We describe how to use satellite image feature tracking to determine the magnitude and timing of seasonal ice dynamics.
George Brencher, Alexander L. Handwerger, and Jeffrey S. Munroe
The Cryosphere Discuss.,
Revised manuscript accepted for TCShort summary
We use satellite InSAR to inventory and monitor rock glaciers, frozen bodies of ice and rock debris that are an important water resource in the Uinta Mountains, Utah, USA. Our inventory contains 255 active rock glaciers, which occur within a narrow elevation band and deform at 2.52 cm/yr on average. Uinta rock glacier movement changes seasonally and appears to be driven by spring snowmelt. The role of rock glaciers as a perennial water resource is threatened by ice loss due to climate change.
Ellyn M. Enderlin and Timothy C. Bartholomaus
The Cryosphere, 14, 4121–4133,Short summary
Accurate predictions of future changes in glacier flow require the realistic simulation of glacier terminus position change in numerical models. We use crevasse observations for 19 Greenland glaciers to explore whether the two commonly used crevasse depth models match observations. The models cannot reproduce spatial patterns, and we largely attribute discrepancies between modeled and observed depths to the models' inability to account for advection.
Melanie Marochov, Chris R. Stokes, and Patrice E. Carbonneau
The Cryosphere Discuss.,
Preprint under review for TCShort summary
Research into the use of deep learning for pixel-level classification of landscapes containing marine-terminating glaciers is lacking. We adapt a novel and transferable deep learning workflow to classify satellite imagery containing marine-terminating outlet glaciers in Greenland. Our workflow achieves high accuracy and mimics human visual performance, potentially providing a useful tool to monitor glacier change and further understand the impacts of climate change in complex glacial settings.
Angus J. Dowson, Pascal Sirguey, and Nicolas J. Cullen
The Cryosphere, 14, 3425–3448,Short summary
Satellite observations over 19 years are used to characterise the spatial and temporal variability of surface albedo across the gardens of Eden and Allah, two of New Zealand’s largest ice fields. The variability in response of individual glaciers reveals the role of topographic setting and suggests that glaciers in the Southern Alps do not behave as a single climatic unit. There is evidence that the timing of the minimum surface albedo has shifted to later in the summer on 10 of the 12 glaciers.
Anna Bergstrom, Michael N. Gooseff, Madeline Myers, Peter T. Doran, and Julian M. Cross
The Cryosphere, 14, 769–788,Short summary
This study sought to understand patterns of reflectance of visible light across the landscape of the McMurdo Dry Valleys, Antarctica. We used a helicopter-based platform to measure reflectance along an entire valley with a particular focus on the glaciers, as reflectance strongly controls glacier melt and available water to the downstream ecosystem. We found that patterns are controlled by gradients in snowfall, wind redistribution, and landscape structure, which can trap snow and sediment.
Désirée Treichler, Andreas Kääb, Nadine Salzmann, and Chong-Yu Xu
The Cryosphere, 13, 2977–3005,Short summary
Glacier growth such as that found on the Tibetan Plateau (TP) is counterintuitive in a warming world. Climate models and meteorological data are conflicting about the reasons for this glacier anomaly. We quantify the glacier changes in High Mountain Asia using satellite laser altimetry as well as the growth of over 1300 inland lakes on the TP. Our study suggests that increased summer precipitation is likely the largest contributor to the recently observed increases in glacier and lake masses.
Christoph Rohner, David Small, Jan Beutel, Daniel Henke, Martin P. Lüthi, and Andreas Vieli
The Cryosphere, 13, 2953–2975,Short summary
The recent increase in ice flow and calving rates of ocean–terminating glaciers contributes substantially to the mass loss of the Greenland Ice Sheet. Using in situ reference observations, we validate the satellite–based method of iterative offset tracking of Sentinel–1A data for deriving flow speeds. Our investigations highlight the importance of spatial resolution near the fast–flowing calving front, resulting in significantly higher ice velocities compared to large–scale operational products.
Jozef Šupinský, Ján Kaňuk, Zdenko Hochmuth, and Michal Gallay
The Cryosphere, 13, 2835–2851,Short summary
Cave ice formations can be considered an indicator of long-term changes in the landscape. Using terrestrial laser scanning we generated a time series database of a 3-D cave model. We present a novel approach toward registration of scan missions into a unified coordinate system and methodology for detection of cave floor ice changes. We demonstrate the results of the ice dynamics monitoring correlated with meteorological observations in the Silická ľadnica cave situated in the Slovak Karst.
Thorsten Seehaus, Philipp Malz, Christian Sommer, Stefan Lippl, Alejo Cochachin, and Matthias Braun
The Cryosphere, 13, 2537–2556,Short summary
The glaciers in Peru are strongly affected by climate change and have shown significant ice loss in the last century. We present the first multi-temporal, countrywide quantification of glacier area and ice mass changes. A glacier area loss of −548.5 ± 65.7 km2 (−29 %) and ice mass loss of −7.62 ± 1.05 Gt is obtained for the period 2000–2016. The ice loss rate increased towards the end of the observation period. The glacier changes revealed can be attributed to regional climatic changes and ENSO.
Dyre O. Dammann, Leif E. B. Eriksson, Son V. Nghiem, Erin C. Pettit, Nathan T. Kurtz, John G. Sonntag, Thomas E. Busche, Franz J. Meyer, and Andrew R. Mahoney
The Cryosphere, 13, 1861–1875,Short summary
We validate TanDEM-X interferometry as a tool for deriving iceberg subaerial morphology using Operation IceBridge data. This approach enables a volumetric classification of icebergs, according to volume relevant to iceberg drift and decay, freshwater contribution, and potential impact on structures. We find iceberg volumes to generally match within 7 %. These results suggest that TanDEM-X could pave the way for future interferometric systems of scientific and operational iceberg classification.
Enze Zhang, Lin Liu, and Lingcao Huang
The Cryosphere, 13, 1729–1741,Short summary
Conventionally, calving front positions have been manually delineated from remote sensing images. We design a novel method to automatically delineate the calving front positions of Jakobshavn Isbræ based on deep learning, the first of this kind for Greenland outlet glaciers. We generate high-temporal-resolution (about two measurements every month) calving fronts, demonstrating our methodology can be applied to many other tidewater glaciers through this successful case study on Jakobshavn Isbræ.
Robert McNabb, Christopher Nuth, Andreas Kääb, and Luc Girod
The Cryosphere, 13, 895–910,Short summary
Estimating glacier changes involves measuring elevation changes, often using elevation models derived from satellites. Many elevation models have data gaps (voids), which affect estimates of glacier change. We compare 11 methods for interpolating voids, finding that some methods bias estimates of glacier change by up to 20 %, though most methods have a smaller effect. Some methods produce reliable results even with large void areas, suggesting that noisy elevation data are still useful.
Bas Altena, Ted Scambos, Mark Fahnestock, and Andreas Kääb
The Cryosphere, 13, 795–814,Short summary
Many glaciers in southern Alaska and the Yukon experience changes in flow speed, which occur in episodes or sporadically. These flow changes can be measured with satellites, but the resulting raw velocity products are messy. Thus in this study we developed an automatic method to produce a synthesized velocity product over a large glacier region of roughly 600 km by 200 km. Velocities are at a monthly resolution and at 300 m resolution, making all kinds of glacier dynamics observable.
Kathrin Naegeli, Matthias Huss, and Martin Hoelzle
The Cryosphere, 13, 397–412,Short summary
The paper investigates the temporal changes of bare-ice glacier surface albedo in the Swiss Alps between 1999 and 2016 from a regional to local scale using satellite data. Significant negative trends were found in the lowermost elevations and margins of the ablation zones. Although significant changes of glacier ice albedo are only present over a limited area, we emphasize that albedo feedback will considerably enhance the rate of glacier mass loss in the Swiss Alps in the near future.
Mingyang Lv, Huadong Guo, Xiancai Lu, Guang Liu, Shiyong Yan, Zhixing Ruan, Yixing Ding, and Duncan J. Quincey
The Cryosphere, 13, 219–236,Short summary
We highlight 28 glaciers in the Kingata Mountains, among which 17 have changed markedly over the last decade. We identify four advancing and 13 surge-type glaciers. The dynamic evolution of the surges is similar to that of Karakoram, suggesting that both hydrological and thermal controls are important for surge initiation and recession. Topography seems to be a dominant control on non-surge glacier behaviour. Most glaciers experienced a significant and diverse change in their motion patterns.
Sam Herreid and Francesca Pellicciotti
The Cryosphere, 12, 1811–1829,Short summary
Ice cliffs are steep, bare ice features that can develop on the lower reaches of a glacier where the surface is covered by a layer of rock debris. Debris cover generally slows the rate of glacier melt, but ice cliffs act as small windows of higher rates of melt. It is therefore important to map these features, a process which we have automated. On a global scale, ice cliffs have variable geometries and characteristics. The method we have developed can accommodate this variability automatically.
Etienne Berthier, Christopher Larsen, William J. Durkin, Michael J. Willis, and Matthew E. Pritchard
The Cryosphere, 12, 1523–1530,Short summary
Two recent studies suggested a slowdown in mass loss after 2000 of the Juneau and Stikine icefields, accounting for 10% of the total ice cover in Alaska. Here, the ASTER-based geodetic mass balances are revisited, carefully avoiding the use of the SRTM DEM, because of the unknown penetration depth of the SRTM C-band radar signal. We find strongly negative mass balances from 2000 to 2016 for both icefields, in agreement with airborne laser altimetry. Mass losses are thus continuing unabated.
Abdalati, W. and Steffen, K.: Greenland Ice Sheet melt extent: 1979–1999, J. Geophys. Res.-Atmos., 106, 33983–33988, 2001.
Adam, S., Pietroniro, A., and Brugman, M. M.: Glacier snow line mapping using ERS-1 SAR imagery, Remote Sens. Environ., 61, 46–54, 1997.
Alexander, P., Tedesco, M., Koenig, L., and Fettweis, X.: Evaluating a regional climate model simulation of Greenland ice sheet snow and firn density for improved surface mass balance estimates, Geophys. Res. Lett., 46, 12073–12082, 2019.
Anthwal, A., Joshi, V., Sharma, A., and Anthwal, S.: Retreat of Himalayan glaciers–indicator of climate change, Nat. Sci., 4, 53–59, 2006.
Ashcraft, I. S. and Long, D. G.: Differentiation between melt and freeze stages of the melt cycle using SSM/I channel ratios, IEEE Trans. Geosci. Remote Sens., 43, 1317–1323, 2005.
Ashcraft, I. S. and Long, D. G.: Comparison of methods for melt detection over Greenland using active and passive microwave measurements, Int. J. Remote Sens., 27, 2469–2488, 2007.
Baghdadi, N., Gauthier, Y., and Bernier, M.: Capability of multitemporal ERS-1 SAR data for wet-snow mapping, Remote Sens. Environ., 60, 174–186, 1997.
Bahr, D. B., Meier, M. F., and Peckham, S. D.: The physical basis of glacier volume-area scaling, J. Geophys. Res.-Sol. Ea., 102, 20355–20362, 1997.
Baral, P., Kayastha, R. B., Immerzeel, W. W., Pradhananga, N. S., Bhattarai, B. C., Shahi, S., Galos, S., Springer, C., Joshi, S. P., and Mool, P. K.: Preliminary results of mass-balance observations of Yala Glacier and analysis of temperature and precipitation gradients in Langtang Valley, Nepal, Ann. Glaciol., 55, 9–14, 2014.
Bhattacharya, I., Jezek, K. C., Wang, L., and Liu, H.: Surface melt area variability of the Greenland ice sheet: 1979–2008, Geophys. Res. Lett., 20, 1–6, 2009.
Bindschadler, R., Jezek, K., and Crawford, J.: Glaciological investigations using the synthetic aperture radar imaging system, Ann. Glaciol., 9, 11–19, 1987.
Bogardi, J. J., Dudgeon, D., Lawford, R., Flinkerbusch, E., Meyn, A., Pahl-Wostl, C., Vielhauer, K., and Vörösmarty, C.: Water security for a planet under pressure: interconnected challenges of a changing world call for sustainable solutions, Curr. Opin. Environ. Sustain., 4, 35–43, 2012.
Bolch, T., Kulkarni, A., Kääb, A., Huggel, C., Paul, F., Cogley, J. G., Frey, H., Kargel, J. S., Fujita, K., and Scheel, M. J. S.: The state and fate of Himalayan glaciers, Science, 336, 310–314, 2012.
Bolch, T., Shea, J. M., Liu, S., Azam, F. M., Gao, Y., Gruber, S., Immerzeel, W. W., Kulkarni, A., Li, H., and Tahir, A. A.: Status and change of the cryosphere in the Extended Hindu Kush Himalaya Region, in: The Hindu Kush Himalaya Assessment, Springer, Cham, 209–255, 2019a.
Bolch, T., Bhattacharya, A., King, O., and Allen, S.: Characteristics and changes of glaciers, rock glaciers and glacial lakes in High Mountain Asia since the 1960s, American Geophysical Union, Fall Meeting 2019, abstract #C43A-05, 2019b.
Brangers, I., Lievens, H., Miege, C., Demuzere, M., Brucker, L., and De Lannoy, G. J. M.: Sentinel‐1 detects firn aquifers in the Greenland Ice Sheet, Geophys. Res. Lett., 47, e2019GL085192, 2020.
Brock, B. W., Willis, I. C., and Sharp, M. J.: Measurement and parameterization of aerodynamic roughness length variations at Haut Glacier d'Arolla, Switzerland, J. Glaciol., 52, 281–297, 2006.
Brown, L. E., Hannah, D. M., and Milner, A. M.: Vulnerability of alpine stream biodiversity to shrinking glaciers and snowpacks, Glob. Change Biol., 13, 958–966, 2007.
Brun, F., Berthier, E., Wagnon, P., Kaab, A., and Treichler, D.: A spatially resolved estimate of High Mountain Asia glacier mass balances, 2000–2016, Nat. Geosci., 10, 668–673, 2017.
Carrivick, J. L. and Tweed, F. S.: A global assessment of the societal impacts of glacier outburst floods, Glob. Planet. Change, 144, 1–16, 2016.
Engeset, R., Kohler, J., Melvold, K., and Lundén, B.: Change detection and monitoring of glacier mass balance and facies using ERS SAR winter images over Svalbard, Int. J. Remote Sens., 23, 2023–2050, 2002.
Farinotti, D., Immerzeel, W. W., de Kok, R. J., Quincey, D. J., and Dehecq, A.: Manifestations and mechanisms of the Karakoram glacier Anomaly, Nat. Geosci., 13, 8–16, 2020.
Farr, T. G., Rosen, P. A., Caro, E., Crippen, R., Duren, R., Hensley, S., Kobrick, M., Paller, M., Rodriguez, E., Roth, L., Seal, D., Shaffer, S., Shimada, J., Umland, J., Werner, M., Oskin, M., Burbank, D., and Alsdorf, D.E.: The shuttle radar topography mission, Rev. Geophys., 45, RG2004, https://doi.org/10.1029/2005RG000183, 2007.
Fischer, G., Jäger, M., Papathanassiou, K. P., and Hajnsek, I.: Modeling the Vertical Backscattering Distribution in the Percolation Zone of the Greenland Ice Sheet with SAR Tomography, IEEE J. Select. Top. Appl. Earth Obs. Remote Sens., 12, 4389–4405, 2019.
Forster, R. R., Box, J. E., Van Den Broeke, M. R., Miège, C., Burgess, E. W., Van Angelen, J. H., Lenaerts, J. T., Koenig, L. S., Paden, J., and Lewis, C.: Extensive liquid meltwater storage in firn within the Greenland ice sheet, Nat. Geosci., 7, 95–98, 2014.
Fujita, K. and Nuimura, T.: Spatially heterogeneous wastage of Himalayan glaciers, P. Natl. Acad. Sci. USA, 108, 14011–14014, 2011.
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.
Google: Sentinel-1 Preprocessing, Google Earth Engine Guides, available at: https://developers.google.com/earth-engine/guides/sentinel1, last access: 30 Novermber 2020.
Gorelick, N., Hancher, M., Dixon, M., Ilyushchenko, S., Thau, D., and Moore, R.: Google Earth Engine: Planetary-scale geospatial analysis for everyone, Remote Sens. Environ., 202, 18–27, 2017.
Hallikainen, M., Ulaby, F., and Abdelrazik, M.: Dielectric properties of snow in the 3 to 37 GHz range, IEEE T. Antenn. Propag., 34, 1329–1340, 1986.
Hock, R., Bliss, A., Marzeion, B., Giesen, R. H., Hirabayashi, Y., Huss, M., Radić, V., and Slangen, A. B.: GlacierMIP – A model intercomparison of global-scale glacier mass-balance models and projections, J. Glaciol., 65, 453–467, 2019.
Huang, L., Li, Z., Tian, B., Han, H., Liu, Y., Zhou, J., and Chen, Q.: Estimation of supraglacial debris thickness using a novel target decomposition on L‐band polarimetric SAR images in the Tianshan Mountains, J. Geophys. Res.-Earth Surf., 122, 925–940, 2017.
Huang, W., DeVries, B., Huang, C., Lang, M., Jones, J., Creed, I., and Carroll, M.: Automated Extraction of Surface Water Extent from Sentinel-1 Data, Remote Sens., 10, 797, 2018.
Jacobsen, D., Milner, A. M., Brown, L. E., and Dangles, O.: Biodiversity under threat in glacier-fed river systems, Nat. Clim. Change, 2, 361–364, 2012.
Jezek, K. C., Gogineni, P., and Shanableh, M.: Radar measurements of melt zones on the Greenland ice sheet, Geophys. Res. Lett., 21, 33–36, 1994.
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.
Kendra, J. R., Sarabandi, K., and Ulaby, F.: Radar measurements of snow: Experiment and analysis, IEEE T. Geosci. Remote, 36, 864–879, 1998.
Koskinen, J. T., Pulliainen, J. T., and Hallikainen, M. T.: The use of ERS-1 SAR data in snow melt monitoring, IEEE Tran. Geosci. Remote Sens., 35, 601–610, 1997.
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.
Litt, M., Shea, J., Wagnon, P., Steiner, J., Koch, I., Stigter, E., and Immerzeel, W.: Glacier ablation and temperature indexed melt models in the Nepalese Himalaya, Sci. Rep., 9, 5264, https://doi.org/10.1038/s41598-019-41657-5, 2019.
Lund, J., Forster, R. R., Rupper, S. B., Marshall, H., Deeb, E. J., and Hashmi, M. Z. U. R.: Mapping snowmelt progression in the Upper Indus Basin with synthetic aperture radar, Front. Earth Sci., 7, 318, 2019.
MacDougall, A. H., Wheler, B. A., and Flowers, G. E.: A preliminary assessment of glacier melt-model parameter sensitivity and transferability in a dry subarctic environment, The Cryosphere, 5, 1011–1028, https://doi.org/10.5194/tc-5-1011-2011, 2011.
Margulis, S. A., Liu, Y., and Baldo, E.: A joint Landsat-and MODIS-based reanalysis approach for midlatitude montane seasonal snow characterization, Front. Earth Sci., 7, 272, 2019.
Marzeion, B., Hock, R., Anderson, B., Bliss, A., Champollion, N., Fujita, K., Huss, M., Immerzeel, W. W., Kraaijenbrink, P., and Malles, J. H.: Partitioning the uncertainty of ensemble projections of global glacier mass change, Earth's Future, 8, e2019EF001470, https://doi.org/10.1029/2019EF001470, 2020.
Matthews, T., Perry, B., Aryal, D., Shrestha, D., and Khadka, A.: New Heights in Glacier-Climate Research: Initial Insights From the Highest Weather Stations on Earth, American Geophysical Union, Fall Meeting 2019, abstract #GC52B-05, 2019.
Matthews, T., Perry, L. B., Koch, I., Aryal, D., Khadka, A., Shrestha, D., Abernathy, K., Elmore, A., Seimon, A., and Tait, A.: Going to Extremes: Installing the World's Highest Weather Stations on Mount Everest, B. Am. Meteorol. Soc., 101.11, E1870–E1890, 2020.
Matzler, C.: Microwave properties of ice and snow, in: Solar System Ices, Springer, 241–257, 1998.
Miège, C., Forster, R. R., Brucker, L., Koenig, L. S., Solomon, D. K., Paden, J. D., Box, J. E., Burgess, E. W., Miller, J. Z., and McNerney, L.: Spatial extent and temporal variability of Greenland firn aquifers detected by ground and airborne radars, J. Geophys. Res.-Earth Surf., 121, 2381–2398, 2016.
Miles, K. E., Hubbard, B., Quincey, D. J., Miles, E. S., Sherpa, T. C., Rowan, A. V., and Doyle, S. H.: Polythermal structure of a Himalayan debris-covered glacier revealed by borehole thermometry, Sci. Rep., 8, 1–9, 2018.
Milner, A. M., Khamis, K., Battin, T. J., Brittain, J. E., Barrand, N. E., Fureder, L., Cauvy-Fraunie, S., Gislason, G. M., Jacobsen, D., Hannah, D. M., Hodson, A. J., Hood, E., Lencioni, V., Olafsson, J. S., Robinson, C. T., Tranter, M., and Brown, L. E.: Glacier shrinkage driving global changes in downstream systems, P. Natl. Acad. Sci. USA, 114, 9770–9778, 2017.
Nagler, T. and Rott, H.: Retrieval of wet snow by means of multitemporal SAR data, IEEE Trans. Geosci. Remote Sens., 38, 754–765, 2000.
Nuimura, T., Sakai, A., Taniguchi, K., Nagai, H., Lamsal, D., Tsutaki, S., Kozawa, A., Hoshina, Y., Takenaka, S., Omiya, S., Tsunematsu, K., Tshering, P., and Fujita, K.: The GAMDAM glacier inventory: a quality-controlled inventory of Asian glaciers, The Cryosphere, 9, 849–864, https://doi.org/10.5194/tc-9-849-2015, 2015.
Oza, S., Singh, R., Vyas, N., and Sarkar, A.: Study of inter-annual variations in surface melting over Amery Ice Shelf, East Antarctica, using space-borne scatterometer data, J. Earth Syst. Sci., 120, 329–336, 2011.
Palazzi, E., Von Hardenberg, J., and Provenzale, A.: Precipitation in the Hindu-Kush Karakoram Himalaya: observations and future scenarios, J. Geophys. Res.-Atmos., 118, 85–100, 2013.
Paterson, W. S. B.: The physics of glaciers, Butterworth-Heinemann, 1994.
Pritchard, D. M. W., Forsythe, N., O'Donnell, G., Fowler, H. J., and Rutter, N.: Multi-physics ensemble snow modelling in the western Himalaya, The Cryosphere, 14, 1225–1244, https://doi.org/10.5194/tc-14-1225-2020, 2020.
Ramage, J. M., Isacks, B. L., and Miller, M. M.: Radar glacier zones in southeast Alaska, USA: field and satellite observations, J. Glaciol., 46, 287–296, 2000.
Rau, F., Braun, M., Friedrich, M., Weber, F., and Goßmann, H.: Radar glacier zones and their boundaries as indicators of glacier mass balance and climatic variability, Proceedings of the 2nd EARSeL Workshop-Special Interest Group Land Ice and Snow, 317–327, 2000.
Rott, H. and Mätzler, C.: Possibilities and limits of synthetic aperture radar for snow and glacier surveying, Ann. Glaciol., 9, 195–199, 1987.
Sakai, A.: Brief communication: Updated GAMDAM glacier inventory over high-mountain Asia , The Cryosphere, 13, 2043–2049, https://doi.org/10.5194/tc-13-2043-2019, 2019.
Scher, C.: Glacier Melt, GitHub repository, available at: https://github.com/porefluid/glacier_melt (last access: 23 September 2021), GitHub [code], 2021.
Scott, C. A., Zhang, F., Mukherji, A., Immerzeel, W., Mustafa, D., and Bharati, L.: Water in the Hindu Kush Himalaya, in: The Hindu Kush Himalaya Assessment, Springer, Cham, 2019.
Shea, J.: Meteorological data from Yala Base Camp automatic weather station, edited by: ICIMOD [data set], 2016.
Shean, D. E., Bhushan, S., Montesano, P., Rounce, D. R., Arendt, A., and Osmanoglu, B.: A Systematic, Regional Assessment of High Mountain Asia Glacier Mass Balance, Front. Earth Sci., 7, 2020.
Shi, J. and Dozier, J.: Inferring snow wetness using C-band data from SIR-C's polarimetric synthetic aperture radar, IEEE Trans. Geosci. Remote Sens., 33, 905–914, 1995.
Shi, J., Dozier, J., and Rott, H.: Snow mapping in alpine regions with synthetic aperture radar, IEEE Trans. Geosci. Remote Sens., 32, 152–158, 1994.
Steiner, N. and Tedesco, M.: A wavelet melt detection algorithm applied to enhanced-resolution scatterometer data over Antarctica (2000–2009), The Cryosphere, 8, 25–40, https://doi.org/10.5194/tc-8-25-2014, 2014.
Steiner, N., McDonald, K. C., and Scher, C.: High mountain Asia 90 m Glacier Surface Melt/Freeze Phenology from SAR Imagery, Boulder, Colorado USA, NASA National Snow and Ice Data Center Distributed Active Archive Center [data set], https://doi.org/10.5067/05I6ZHZWHSVV, 2021.
Trusel, L. D., Frey, K. E., and Das, S. B.: Antarctic surface melting dynamics: Enhanced perspectives from radar scatterometer data, J. Geophys. Res.-Earth, 117, F2, 2012.
Winebrenner, D. P., Nelson, E. D., Colony, R., and West, R. D.: Observation of melt onset on multiyear Arctic sea ice using the ERS 1 synthetic aperture radar, J. Geophys. Res., 99, 22425–22441, 1994.
Winsvold, S. H., Kääb, A., Nuth, C., Andreassen, L. M., van Pelt, W. J. J., and Schellenberger, T.: Using SAR satellite data time series for regional glacier mapping, The Cryosphere, 12, 867–890, https://doi.org/10.5194/tc-12-867-2018, 2018.
Wiscombe, W. J. and Warren, S. G.: A model for the spectral albedo of snow, II: Snow Containing Atmospheric Aerosols, 37, 2712–2733, 1980.
Wood, L. R., Neumann, K., Nicholson, K. N., Bird, B. W., Dowling, C. B., and Sharma, S.: Melting Himalayan Glaciers Threaten Domestic Water Resources in the Mount Everest Region, Nepal, Front. Earth Sci., 8, 128, 2020.
Yao, T., Thompson, L. G., Mosbrugger, V., Zhang, F., Ma, Y., Luo, T., Xu, B., Yang, X., Joswiak, D. R., and Wang, W.: Third pole environment (TPE), Environ. Dev., 3, 52–64, 2012.
Zemp, M., Haeberli, W., Hoelzle, M., and Paul, F.: Alpine glaciers to disappear within decades?, Geophys. Res. Lett., 33, L13504, https://doi.org/10.1029/2006GL026319, 2006.
Zhou, C. and Zheng, L.: Mapping Radar Glacier Zones and Dry Snow Line in the Antarctic Peninsula Using Sentinel-1 Images, Remote Sens., 9, L13504, https://doi.org/10.3390/rs9111171, 2017.
Time series synthetic aperture radar enables detection of seasonal reach-scale glacier surface melting across continents, a key component of surface energy balance for mountain glaciers. We observe melting across all areas of the Hindu Kush Himalaya (HKH) cryosphere. Surface melting for the HKH lasts for close to 5 months per year on average and for just below 2 months at elevations exceeding 7000 m a.s.l. Further, there are indications that melting is more than superficial at high elevations.
Time series synthetic aperture radar enables detection of seasonal reach-scale glacier surface...