Articles | Volume 15, issue 2
https://doi.org/10.5194/tc-15-547-2021
© 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-15-547-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
08 Feb 2021
Research article |
| 08 Feb 2021
| 08 Feb 2021
Annual and inter-annual variability and trends of albedo of Icelandic glaciers
University of Iceland, Civil and Environmental Engineering, Hjardarhagi 2-6, 107 Reykjavík, Iceland
Landsvirkjun, Department of Research and Development, 107 Reykjavík, Iceland
Sigurdur M. Gardarsson
University of Iceland, Civil and Environmental Engineering, Hjardarhagi 2-6, 107 Reykjavík, Iceland
Finnur Pálsson
Institute of Earth Sciences, University of Iceland, Sturlugata 7, 101 Reykjavík, Iceland
Tómas Jóhannesson
Icelandic Meteorological Office, Bústaðavegi 7–9, 105 Reykjavík, Iceland
Óli G. B. Sveinsson
Landsvirkjun, Department of Research and Development, 107 Reykjavík, Iceland
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Cited articles
Ackerman, S. A., Strabala, K. I., Menzel, W. P., Frey, R. A., Moeller, C. C.,
and Gumley, L. E.: Discriminating clear sky from clouds with MODIS, J.
Geophys. Res.-Atmos., 103, 32141–32157,
https://doi.org/10.1029/1998JD200032, 1998. a
Arnalds, O., Dagsson-Waldhauserova, P., and Ólafsson, H.: The Icelandic
volcanic aeolian environment: Processes and impacts – A review, Aeolian
Res., 20, 176–195, https://doi.org/10.1016/j.aeolia.2016.01.004, 2016. a, b, c
Björnsson, H.: Hydrology of ice caps in volcanic regions, Reykjavik Societas Scientarium Islandica, University of Iceland, Polar Record, 26, 132–132, https://doi.org/10.1017/S0032247400011293, 1988. a
Björnsson, H., Pálsson, F., and Guðmundsson, M. T.: Surface and
bedrock topography of the Mýrdalsjökull ice cap, Iceland: The Katla
caldera, eruption sites and routes of jökulhlaups, Jökull, 49, 29–46,
2000. a
Björnsson, H., Jónsson, T., Gylfadóttir, S. S., and Ólason,
E. Ö.: Mapping the annual cycle of temperature in Iceland,
Meteorol. Z., 16, 45–56, https://doi.org/10.1127/0941-2948/2007/0175,
2007. a
Björnsson, H., Sigurðsson, B. D., Davíðsdóttir, B.,
Ólafsson, Ástþórsson, J., Ólafsdóttir, S., Baldursson, T.,
and Jónsson, T.: Loftslagsbreytingar og áhrif þeirra á
Íslandi: skýrsla vísindanefndar um loftslagsbreytingar 2018.
(Climate Change and it's impact on Iceland – Report of the scientific
committee on Climate),
available at: https://www.vedur.is/media/loftslag/Skyrsla-loftslagsbreytingar-2018-Vefur-NY.pdf (last access: 30 December 2019),
2018. a, b
Butwin, M. K., Löwis, S. V., Pfeffer, M. A., and Thorsteinsson, T.: The
effects of volcanic eruptions on the frequency of particulate matter
suspension events in Iceland, J. Aerosol Sci., 128, 99–113,
https://doi.org/10.1016/j.jaerosci.2018.12.004, 2019. a
Crochet, P., Jóhannesson, T., Jónsson, T., Sigurðsson, O.,
Björnsson, H., Pálsson, F., and Barstad, I.: Estimating the Spatial
Distribution of Precipitation in Iceland Using a Linear Model
of Orographic Precipitation, J. Hydrometeorol., 8, 1285–1306,
https://doi.org/10.1175/2007JHM795.1, 2007. a
Cuffey, K. and Paterson, W.: The Physics of Glaciers, Elsevier Science, 2010. a
Dagsson-Waldhauserova, P., Arnalds, O., and Olafsson, H.: Long-term variability of dust events in Iceland (1949–2011), Atmos. Chem. Phys., 14, 13411–13422, https://doi.org/10.5194/acp-14-13411-2014, 2014. a
Dagsson-Waldhauserova, P., Arnalds, O., Olafsson, H., Hladil, J., Skala, R.,
Navratil, T., Chadimova, L., and Meinander, O.: Snow–Dust Storm:
Unique case study from Iceland, March 6–7, 2013, Aeolian Res.,
16, 69–74, https://doi.org/10.1016/j.aeolia.2014.11.001, 2015. a, b
Dagsson-Waldhauserova, P., Renard, J.-B., Olafsson, H., Vignelles, D., Berthet,
G., Verdier, N., and Duverger, V.: Vertical distribution of aerosols in dust
storms during the Arctic winter, Sci. Rep., 9, 16122,
https://doi.org/10.1038/s41598-019-51764-y, 2019. a, b
de Abreu, R. A., Key, J., Maslanik, J. A., Serreze, M. C., and Ledrew, E. F.:
Comparison of in Situ and AVHRR-Derived Broadband Albedo over Arctic Sea Ice,
Arctic, 47, 288–297,
1994. a
De Ruyter De Wildt, M. S., Oerlemans, J., and Björnsson, H.: A method for
monitoring glacier mass balance using satellite albedo measurements:
application to Vatnajökull, Iceland, J. Glaciol., 48, 267–278,
https://doi.org/10.3189/172756502781831458, 2002. a, b
Dietz, A. J., Wohner, C., and Kuenzer, C.: European Snow Cover
Characteristics between 2000 and 2011 Derived from Improved MODIS
Daily Snow Cover Products, Remote Sensing, 4, 2432–2454,
https://doi.org/10.3390/rs4082432, 2012. a
Donohoe, A. and Battisti, D. S.: Atmospheric and Surface Contributions to
Planetary Albedo, J. Climate, 24, 4402–4418,
https://doi.org/10.1175/2011JCLI3946.1, 2011. a
Đorđević, D., Tošić, I., Sakan, S., Petrović, S.,
Đuričić-Milanković, J., Finger, D. C., and Dagsson-Waldhauserová,
P.: Can Volcanic Dust Suspended From Surface Soil and Deserts of Iceland Be
Transferred to Central Balkan Similarly to African Dust (Sahara)?, Front.
Earth Sci., 7, 142, https://doi.org/10.3389/feart.2019.00142, 2019. a
Dozier, J., Painter, T. H., Rittger, K., and Frew, J. E.: Time–space
continuity of daily maps of fractional snow cover and albedo from MODIS,
Adv. Water Res., 31, 1515–1526,
https://doi.org/10.1016/j.advwatres.2008.08.011, 2008. a
Dragosics, M., Meinander, O., Jónsdóttír, T., Dürig, T.,
De Leeuw, G., Pálsson, F., Dagsson-Waldhauserová, P., and
Thorsteinsson, T.: Insulation Effects of Icelandic Dust and Volcanic Ash
on Snow and Ice, Arab. J. Geosci., 9, 126,
https://doi.org/10.1007/s12517-015-2224-6, 2016. a
Þorsteinsson, Þ., Jóhannesson, T., Sigurðsson, O., and Einarsson,
B.: Afkomumælingar á Hofsjökli 1988–2017, Veðurstofa
Íslands, Reykjavík, 2017-016, 82, 2017. a
Einarsson, B.: Jöklabreytingar (glacier variations) 1930–1970, 1970–1995,
1995–2016 og 2016–2017, Jökull, 68, 95–99, 2018. a
Einarsson, M. Á.: Climates of the oceans, edited by: Van Loon, H., Vol. 15 of World Survey of Climatology, Elsevier, J. Climatol., 5, 673–697,
https://doi.org/10.1002/joc.3370050110, 1984. a, b
Gardner, A. S. and Sharp, M. J.: A review of snow and ice albedo and the
development of a new physically based broadband albedo parameterization,
J. Geophys. Res.-Earth, 115, F01009,
https://doi.org/10.1029/2009JF001444, 2010. a
Gascoin, S., Guðmundsson, S., Aðalgeirsdóttir, G., Pálsson, F.,
Schmidt, L., Berthier, E., and Björnsson, H.: Evaluation of MODIS
Albedo Product over Ice Caps in Iceland and Impact of
Volcanic Eruptions on Their Albedo, Remote Sensing, 9, 399,
https://doi.org/10.3390/rs9050399, 2017. a, b, c, d, e, f, g, h, i, j, k
GDAL/OGR contributors: GDAL/OGR Geospatial Data Abstraction software
Library, Open Source Geospatial Foundation, available at: https://gdal.org (last access: 30 December 2019),
2019. a
Gudmundsson, M. T., Sigmundsson, F., and Björnsson, H.: Ice–volcano
interaction of the 1996 Gjálp subglacial eruption, Vatnajökull,
Iceland, Nature, 389, 954–957, https://doi.org/10.1038/40122, 1997. a
Guðmundsson, M. T., Þórðarson, Þ., Höskuldsson, Á.,
Larsen, G., Björnsson, H., Prata, F. J., Oddsson, B., Magnússon, E.,
Högnadóttir, Þ., Petersen, G. N., Hayward, C. L., Stevenson, J. A.,
and Jónsdóttir, I.: Ash generation and distribution from the
April–May 2010 eruption of Eyjafjallajökull, Iceland, Sci.
Rep., 2, 572, https://doi.org/10.1038/srep00572, 2012. a, b
Gunnarsson, A.: andrigunn/aig2: open (Version 1), Zenodo, https://doi.org/10.5281/zenodo.4445245, 2021. a
Gunnarsson, A., Garðarsson, S. M., and Sveinsson, Ó. G. B.: Icelandic snow cover characteristics derived from a gap-filled MODIS daily snow cover product, Hydrol. Earth Syst. Sci., 23, 3021–3036, https://doi.org/10.5194/hess-23-3021-2019, 2019. a, b, c
Hall, D. K. and Riggs, G. A.: MODIS/Aqua Snow Cover Daily L3 Global
500m Grid, Version 6, Tech. rep., NASA National Snow and Ice Data
Center Distributed Active Archive Center, Boulder, Colorado USA, https://doi.org/10.5067/MODIS/MYD10A1.006,
2016a. a, b
Hall, D. K. and Riggs, G. A.: MODIS/Terra Snow Cover Daily L3 Global
500m Grid, Version 6, Tech. rep., NASA National Snow and Ice Data
Center Distributed Active Archive Center, Boulder, Colorado USA, https://doi.org/10.5067/MODIS/MOD10A1.006,
2016b. a, b
Hanna, E., Jónsson, T., and Box, J. E.: An analysis of Icelandic climate
since the nineteenth century, International Journal of Climatology, 24,
1193–1210, https://doi.org/10.1002/joc.1051, 2004. a
Hannesdóttir, H., Sigurðsson, O., Þrastarson, R., Guðmundasson,
S., Belart, J., Pálsson, F., Magnússon, E., Víkingsson, S., and
Jóhannesson, T.: Variations in glacier extent in Iceland since the end of
the Little Ice Age, Jökull, 1–34, 2020. a
Helsel, D. and Hirsch, R.: Statistical Methods in Water Resources
Techniques of Water Resources Investigations, Tech. Rep. Book 4,
Chapter A3, U.S. Geological Survey, 2002. a
Hjaltason, S., Guðmundsdóttir, M., Haukdal, J. Á., and
Guðmundsson, J. R.: Energy Statistics in Iceland 2017, Energy
Statistics in Iceland, Orkustofnun, available at: https://orkustofnun.is/gogn/Talnaefni/OS-2019-T009-01.pdf (last access: 30 December 2019), 2018. a
Jóhannesson, T., Björnsson, H., Magnússon, E., Guðmundsson, S.,
Pálsson, F., Sigurðsson, O., Thorsteinsson, T., and Berthier, E.:
Ice-volume changes, bias estimation of mass-balance measurements and changes
in subglacial lakes derived by lidar mapping of the surface of Icelandic
glaciers, Ann. Glaciol., 54, 63–74, https://doi.org/10.3189/2013AoG63A422,
2013. a
Klein, A. G. and Stroeve, J.: Development and Validation of a Snow Albedo
Algorithm for the MODIS Instrument, Ann. Glaciol., 34, 45–52,
https://doi.org/10.3189/172756402781817662, 2002. a, b, c
Konzelmann, T. and Ohmura, A.: Radiative Fluxes and Their Impact on the Energy
Balance of the Greenland Ice Sheet, J. Glaciol., 41, 490–502,
https://doi.org/10.3189/S0022143000034833, 1995. a
Liang, S., Stroeve, J., and Box, J. E.: Mapping Daily Snow/Ice Shortwave
Broadband Albedo from Moderate Resolution Imaging Spectroradiometer
(MODIS): The Improved Direct Retrieval Algorithm and Validation with
Greenland in Situ Measurement, J. Geophys. Res.-Atmos., 110, D10109, https://doi.org/10.1029/2004JD005493, 2005. a
Lindsay, R. W. and Rothrock, D. A.: Arctic Sea Ice Albedo from AVHRR, J. Climate, 7, 1737–1749,
https://doi.org/10.1175/1520-0442(1994)007<1737:ASIAFA>2.0.CO;2, 1994. a
Magnússon, E., Belart, J. M. C., Pálsson, F., Anderson, L. S.,
Gunnlaugsson, A., Berthier, E., Ágústsson, H., and Geirsdóttir, A.:
The subglacial topography of Drangajökull ice cap, NW-Iceland, deduced from
dense RES-profiling, Jökull, 66, 1–26, 2016. a
Matlab: R2017a, The Mathworks Inc., Natick, Massachusetts, 2017. a
Meinander, O., Kontu, A., Virkkula, A., Arola, A., Backman, L., Dagsson-Waldhauserová, P., Järvinen, O., Manninen, T., Svensson, J., de Leeuw, G., and Leppäranta, M.: Brief communication: Light-absorbing impurities can reduce the density of melting snow, The Cryosphere, 8, 991–995, https://doi.org/10.5194/tc-8-991-2014, 2014. a
Möller, R., Möller, M., Björnsson, H., Gudmundsson, S., Pálsson, F.,
Oddsson, B., Kukla, P., and Schneider, C.: MODIS-derived albedo changes of
Vatnajökull (Iceland) due to tephra deposition from the 2004 Grimsvötn
eruption, Int. J. Appl. Earth Obs., 26, 256–269, https://doi.org/10.1016/j.jag.2013.08.005, 2014. a, b, c, d
Möller, R., Dagsson-Waldhauserova, P., Möller, M., Kukla, P. A., Schneider,
C., and Gudmundsson, M. T.: Persistent albedo reduction on southern Icelandic
glaciers due to ashfall from the 2010 Eyjafjallajökull eruption, Remote
Sens. Environ., 233, 111396,
https://doi.org/10.1016/j.rse.2019.111396, 2019. a, b
Naegeli, K., Damm, A., Huss, M., Wulf, H., Schaepman, M., and Hoelzle, M.:
Cross-Comparison of Albedo Products for Glacier Surfaces Derived from
Airborne and Satellite (Sentinel-2 and Landsat 8) Optical Data, Remote
Sensing, 9, 110, https://doi.org/10.3390/rs9020110, 2017. a
Naegeli, K., Huss, M., and Hoelzle, M.: Change detection of bare-ice albedo in the Swiss Alps , The Cryosphere, 13, 397–412, https://doi.org/10.5194/tc-13-397-2019, 2019. a
National Land Survey of Iceland (NLSI): IS 50V geospatial data, available at: https://atlas.lmi.is, last access: 30 December 2019. a
Painter, T. H., Bryant, A. C., and Skiles, S. M.: Radiative forcing by light
absorbing impurities in snow from MODIS surface reflectance data, Geophys.
Res. Lett., 39, L17502, https://doi.org/10.1029/2012GL052457, 2012. a
Pálsson, F., Gunnarsson, A., Pálsson, H. S., and Steinþórsson,
S.: Afkomu- og hraðamælingar á Langjökli jökulárið
2012–2013, Landsvirkjun, Reykjavík, LV-2015-076, 37, 2015. a
Pálsson, F., Gunnarsson, A., Pálsson, H. S., and Steinþórsson,
S.: Afkomu-og hraðamælingar á Langjökli jökulárið
2018–2019, Landsvirkjun, Reykjavík, RH-10-20/LV-2020-017, 27,
2020b. a
Peltoniemi, J. I., Gritsevich, M., Hakala, T., Dagsson-Waldhauserová, P., Arnalds, Ó., Anttila, K., Hannula, H.-R., Kivekäs, N., Lihavainen, H., Meinander, O., Svensson, J., Virkkula, A., and de Leeuw, G.: Soot on Snow experiment: bidirectional reflectance factor measurements of contaminated snow, The Cryosphere, 9, 2323–2337, https://doi.org/10.5194/tc-9-2323-2015, 2015. a
Pope, E. L., Willis, I. C., Pope, A., Miles, E. S., Arnold, N. S., and Rees,
W. G.: Contrasting snow and ice albedos derived from MODIS, Landsat
ETM+ and airborne data from Langjökull, Iceland, Remote Sens.
Environ., 175, 183–195, https://doi.org/10.1016/j.rse.2015.12.051,
2016. a, b
Schaaf, C. K. and Wang, Z.: MCD43A3/MODIS/Terra+Aqua BRDF/Albedo Daily L3
Global – 500m V006 500m Grid, Version 6, Tech. rep., NASA EOSDIS
Land Processes DAAC, Boulder, Colorado USA, https://doi.org/10.5067/MODIS/MCD43A3.006, 2015. a
Schmidt, L., Langen, P., Aðalgeirsdóttir, G., Pálsson, F.,
Guðmundsson, S., and Gunnarsson, A.: Sensitivity of Glacier Runoff to
Winter Snow Thickness Investigated for Vatnajökull Ice Cap,
Iceland, Using Numerical Models and Observations, Atmosphere, 9, 11,
https://doi.org/10.3390/atmos9110450, 2018. a
Schmidt, L. S., Aðalgeirsdóttir, G., Guðmundsson, S., Langen, P. L., Pálsson, F., Mottram, R., Gascoin, S., and Björnsson, H.: The importance of accurate glacier albedo for estimates of surface mass balance on Vatnajökull: evaluating the surface energy budget in a regional climate model with automatic weather station observations, The Cryosphere, 11, 1665–1684, https://doi.org/10.5194/tc-11-1665-2017, 2017. a
Sirguey, P.: Simple correction of multiple reflection effects in rugged
terrain, Int. J. Remote Sens., 30, 1075–1081,
https://doi.org/10.1080/01431160802348101, 2009. a
Sirguey, P., Mathieu, R., and Arnaud, Y.: Subpixel monitoring of the seasonal
snow cover with MODIS at 250 m spatial resolution in the Southern Alps of New
Zealand: Methodology and accuracy assessment, Remote Sens. Environ.,
113, 160–181, https://doi.org/10.1016/j.rse.2008.09.008, 2009. a
Skiles, S. M., Flanner, M., Cook, J. M., Dumont, M., and Painter, T. H.:
Radiative Forcing by Light-Absorbing Particles in Snow, Nature Climate
Change, 8, 964, https://doi.org/10.1038/s41558-018-0296-5, 2018. a
Steffen, K., Abdalati, W., and Stroeve, J.: Climate sensitivity studies of the
Greenland ice sheet using satellite AVHRR, SMMR, SSM/I and in situ data,
Meteorol. Atmos. Phys., 51, 239–258, https://doi.org/10.1007/BF01030497,
1993. a
Stibal, M., Box, J. E., Cameron, K. A., Langen, P. L., Yallop, M. L., Mottram,
R. H., Khan, A. L., Molotch, N. P., Chrismas, N. A. M., Calì Quaglia, F.,
Remias, D., Smeets, C. J. P. P., van den Broeke, M. R., Ryan, J. C.,
Hubbard, A., Tranter, M., van As, D., and Ahlstrøm, A. P.: Algae Drive
Enhanced Darkening of Bare Ice on the Greenland Ice Sheet,
Geophys. Res. Lett., 44, 11463–11471, https://doi.org/10.1002/2017GL075958,
2017. a
Stroeve, J.: Assessment of Greenland Albedo Variability from the Advanced
Very High Resolution Radiometer Polar Pathfinder Data Set, J.
Geophys. Res.-Atmos., 106, 33989–34006,
https://doi.org/10.1029/2001JD900072, 2001. a
Stroeve, J., Nolin, A., and Steffen, K.: Comparison of AVHRR-Derived and in
Situ Surface Albedo over the Greenland Ice Sheet, Remote Sens.
Environ., 62, 262–276, https://doi.org/10.1016/S0034-4257(97)00107-7, 1997. a, b, c
Stroeve, J., Box, J. E., Gao, F., Liang, S., Nolin, A., and Schaaf, C.:
Accuracy Assessment of the MODIS 16-Day Albedo Product for Snow:
Comparisons with Greenland in Situ Measurements, Remote Sens.
Environ., 94, 46–60, https://doi.org/10.1016/j.rse.2004.09.001, 2005. a, b, c
Stroeve, J., Box, J. E., Wang, Z., Schaaf, C., and Barrett, A.: Re-Evaluation
of MODIS MCD43 Greenland Albedo Accuracy and Trends, Remote Sens.
Environ., 138, 199–214, https://doi.org/10.1016/j.rse.2013.07.023, 2013. a, b, c
Tesche, M., Glantz, P., Johansson, C., Norman, M., Hiebsch, A., Ansmann, A.,
Althausen, D., Engelmann, R., and Seifert, P.: Volcanic ash over Scandinavia
originating from the Grímsvötn eruptions in May 2011, J.
Geophys. Res.-Atmos., 117, D09201, https://doi.org/10.1029/2011JD017090, 2012. a
Van den Broeke, M., Reijmer, C. H., and Van De Wal, R. S.: A study of the
surface mass balance in Dronning Maud Land, Antarctica, using automatic
weather stations, J. Glaciol., 50, 565–582,
https://doi.org/10.3189/172756504781829756, 2004a. a
Van den Broeke, M., van As, D., Reijmer, C., and Wal, R.: Assessing and
Improving the Quality of Unattended Radiation Observations in Antarctica,
J. Atmos. Ocean. Tech., 21, 1417–1431,
https://doi.org/10.1175/1520-0426(2004)021<1417:AAITQO>2.0.CO;2, 2004b. a, b
Warren, S. G.: Optical Properties of Snow, Rev. Geophys., 20, 67–89,
https://doi.org/10.1029/RG020i001p00067, 1982. a
Warren, S. G. and Wiscombe, W. J.: A Model for the Spectral Albedo of Snow. II:
Snow Containing Atmospheric Aerosols, J. Atmos. Sci.,
37, 2734–2745, https://doi.org/10.1175/1520-0469(1980)037<2734:AMFTSA>2.0.CO;2, 1980. a
Watson, E., Swindles, G., Stevenson, J., Savov, I., and Lawson, I.: The
transport of Icelandic volcanic ash: insights from northern European
cryptotephra records: Cryptotephra records of volcanic ash, J.
Geophys. Res.-Sol. Ea., 121, 7177–7192, https://doi.org/10.1002/2016JB013350, 2016. a
Winther, J.-G.: Landsat TM derived and in situ summer reflectance of glaciers
in Svalbard, Polar Res., 12, 37–55, https://doi.org/10.3402/polar.v12i1.6702,
1993. a
Wittmann, M., Groot Zwaaftink, C. D., Steffensen Schmidt, L., Guðmundsson, S., Pálsson, F., Arnalds, O., Björnsson, H., Thorsteinsson, T., and Stohl, A.: Impact of dust deposition on the albedo of Vatnajökull ice cap, Iceland, The Cryosphere, 11, 741–754, https://doi.org/10.5194/tc-11-741-2017, 2017.
a, b, c, d
Xiong, X., Butler, J., Cao, C., and Wu, X.: 1.13 – Optical
Sensors–VIS/NIR/SWIR, in: Comprehensive Remote Sensing, edited by: Liang,
S., Elsevier, Oxford, 353–375,
https://doi.org/10.1016/B978-0-12-409548-9.10325-2, 2018. a
Zhou, C., Zhang, T., and Zheng, L.: The Characteristics of Surface Albedo
Change Trends over the Antarctic Sea Ice Region during Recent Decades, Remote
Sensing, 11, 821, https://doi.org/10.3390/rs11070821, 2019. a
Zubko, N., Muñoz, O., Zubko, E., Gritsevich, M., Escobar-Cerezo, J., Berg,
M. J., and Peltoniemi, J.: Light scattering from volcanic-sand particles in
deposited and aerosol form, Atmos. Environ., 215, 116813,
https://doi.org/10.1016/j.atmosenv.2019.06.051, 2019. a
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.
Surface albedo quantifies the fraction of the sunlight reflected by the surface of the Earth....
