Articles | Volume 15, issue 9
https://doi.org/10.5194/tc-15-4465-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-15-4465-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Mapping seasonal glacier melt across the Hindu Kush Himalaya with time series synthetic aperture radar (SAR)
Corey Scher
Department of Earth and Environmental Sciences, The Graduate Center,
City University of New York, New York, NY 10031, USA
Department of Earth and Atmospheric Sciences, The City College of New
York, City University of New York, New York, NY 10031, USA
Nicholas C. Steiner
CORRESPONDING AUTHOR
Department of Earth and Atmospheric Sciences, The City College of New
York, City University of New York, New York, NY 10031, USA
Kyle C. McDonald
Department of Earth and Environmental Sciences, The Graduate Center,
City University of New York, New York, NY 10031, USA
Department of Earth and Atmospheric Sciences, The City College of New
York, City University of New York, New York, NY 10031, USA
Carbon Cycle and Ecosystems Group, Jet Propulsion Laboratory,
California Institute of Technology, 4800 Oak Grove Drive, Pasadena, CA
91001, USA
Related authors
No articles found.
Marielle Saunois, Adrien Martinez, Benjamin Poulter, Zhen Zhang, Peter A. Raymond, Pierre Regnier, Josep G. Canadell, Robert B. Jackson, Prabir K. Patra, Philippe Bousquet, Philippe Ciais, Edward J. Dlugokencky, Xin Lan, George H. Allen, David Bastviken, David J. Beerling, Dmitry A. Belikov, Donald R. Blake, Simona Castaldi, Monica Crippa, Bridget R. Deemer, Fraser Dennison, Giuseppe Etiope, Nicola Gedney, Lena Höglund-Isaksson, Meredith A. Holgerson, Peter O. Hopcroft, Gustaf Hugelius, Akihiko Ito, Atul K. Jain, Rajesh Janardanan, Matthew S. Johnson, Thomas Kleinen, Paul B. Krummel, Ronny Lauerwald, Tingting Li, Xiangyu Liu, Kyle C. McDonald, Joe R. Melton, Jens Mühle, Jurek Müller, Fabiola Murguia-Flores, Yosuke Niwa, Sergio Noce, Shufen Pan, Robert J. Parker, Changhui Peng, Michel Ramonet, William J. Riley, Gerard Rocher-Ros, Judith A. Rosentreter, Motoki Sasakawa, Arjo Segers, Steven J. Smith, Emily H. Stanley, Joël Thanwerdas, Hanqin Tian, Aki Tsuruta, Francesco N. Tubiello, Thomas S. Weber, Guido R. van der Werf, Douglas E. J. Worthy, Yi Xi, Yukio Yoshida, Wenxin Zhang, Bo Zheng, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
Earth Syst. Sci. Data, 17, 1873–1958, https://doi.org/10.5194/essd-17-1873-2025, https://doi.org/10.5194/essd-17-1873-2025, 2025
Short summary
Short summary
Methane (CH4) is the second most important human-influenced greenhouse gas in terms of climate forcing after carbon dioxide (CO2). A consortium of multi-disciplinary scientists synthesise and update the budget of the sources and sinks of CH4. This edition benefits from important progress in estimating emissions from lakes and ponds, reservoirs, and streams and rivers. For the 2010s decade, global CH4 emissions are estimated at 575 Tg CH4 yr-1, including ~65 % from anthropogenic sources.
Zhen Zhang, Benjamin Poulter, Joe R. Melton, William J. Riley, George H. Allen, David J. Beerling, Philippe Bousquet, Josep G. Canadell, Etienne Fluet-Chouinard, Philippe Ciais, Nicola Gedney, Peter O. Hopcroft, Akihiko Ito, Robert B. Jackson, Atul K. Jain, Katherine Jensen, Fortunat Joos, Thomas Kleinen, Sara H. Knox, Tingting Li, Xin Li, Xiangyu Liu, Kyle McDonald, Gavin McNicol, Paul A. Miller, Jurek Müller, Prabir K. Patra, Changhui Peng, Shushi Peng, Zhangcai Qin, Ryan M. Riggs, Marielle Saunois, Qing Sun, Hanqin Tian, Xiaoming Xu, Yuanzhi Yao, Yi Xi, Wenxin Zhang, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
Biogeosciences, 22, 305–321, https://doi.org/10.5194/bg-22-305-2025, https://doi.org/10.5194/bg-22-305-2025, 2025
Short summary
Short summary
This study assesses global methane emissions from wetlands between 2000 and 2020 using multiple models. We found that wetland emissions increased by 6–7 Tg CH4 yr-1 in the 2010s compared to the 2000s. Rising temperatures primarily drove this increase, while changes in precipitation and CO2 levels also played roles. Our findings highlight the importance of wetlands in the global methane budget and the need for continuous monitoring to understand their impact on climate change.
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, https://doi.org/10.5194/essd-13-2001-2021, https://doi.org/10.5194/essd-13-2001-2021, 2021
Short summary
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.
Cited articles
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.-S., Chen, Q., Liu, J.-L., and Zhang, R.:
Classification and snow line detection for glacial areas using the
polarimetric SAR image, Remote Sens. Environ., 115, 1721–1732, 2011.
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.
Kapnick, S. B., Delworth, T. L., Ashfaq, M., Malyshev, S., and Milly, P. C.:
Snowfall less sensitive to warming in Karakoram than in Himalayas due to a
unique seasonal cycle, Nat. Geosci., 7, 834–840, 2014.
Kayastha, R. B., Steiner, N., Kayastha, R., Mishra, S. K., and McDonald, K.:
Comparative study of hydrology and icemelt in three Nepal river basins using
the glacio-hydrological degree-day model (GDM) and observations from the
Advance Scatterometer (ASCAT), FrEaS, 7, 354, 2020.
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.
Lievens, H., Demuzere, M., Marshall, H.-P., Reichle, R. H., Brucker, L.,
Brangers, I., de Rosnay, P., Dumont, M., Girotto, M., and Immerzeel, W. W.:
Snow depth variability in the Northern Hemisphere mountains observed from
space, Nat. Commun., 10, 1–12, 2019.
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.
Nagler, T., Rott, H., Ripper, E., Bippus, G., and Hetzenecker, M.:
Advancements for Snowmelt Monitoring by Means of Sentinel-1 SAR, Remote
Sens., 8, 348, 2016.
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.
Zemp, M., Huss, M., Thibert, E., Eckert, N., McNabb, R., Huber, J.,
Barandun, M., Machguth, H., Nussbaumer, S. U., and Gärtner-Roer, I.:
Global glacier mass changes and their contributions to sea-level rise from
1961 to 2016, Nature, 568, 382–386, 2019.
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.
Short summary
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...