Articles | Volume 17, issue 1
https://doi.org/10.5194/tc-17-51-2023
© Author(s) 2023. 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-17-51-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
10 Jan 2023
Research article |
| 10 Jan 2023
| 10 Jan 2023
Observed and predicted trends in Icelandic snow conditions for the period 1930–2100
Faculty of Civil and Environmental Engineering, University of
Iceland, Reykjavik, Iceland
Sigurdur M. Gardarsson
Faculty of Civil and Environmental Engineering, University of
Iceland, Reykjavik, Iceland
Andri Gunnarsson
Research and Development Division, Landsvirkjun, Reykjavik, Iceland
Oli Gretar Blondal Sveinsson
Research and Development Division, Landsvirkjun, Reykjavik, Iceland
Related authors
Darri Eythorsson, Sigurdur M. Gardarsson, Shahryar K. Ahmad, and Oli Gretar Blondal Sveinsson
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2019-564, https://doi.org/10.5194/hess-2019-564, 2019
Preprint withdrawn
Short summary
Short summary
We studied recent trends in the Icelandic climate and snow regimes. Climate was classified based on climate models and snow cover trends were assessed using satellite imagery. Our results showed a significant increase in the frequency of snow cover, especially in the eastern highlands. At the same our results show warmer climate classes spreading both northward and to higher elevations. Based on projected climate, we expect a significant warming of local climates in Iceland during this century.
Andri Gunnarsson, Sigurdur M. Gardarsson, and Finnur Pálsson
The Cryosphere, 17, 3955–3986, https://doi.org/10.5194/tc-17-3955-2023, https://doi.org/10.5194/tc-17-3955-2023, 2023
Short summary
Short summary
A model was developed with the possibility of utilizing satellite-derived daily surface albedo driven by high-resolution climate data to estimate the surface energy balance (SEB) for all Icelandic glaciers for the period 2000–2021.
Andri Gunnarsson, Sigurdur M. Gardarsson, Finnur Pálsson, Tómas Jóhannesson, and Óli G. B. Sveinsson
The Cryosphere, 15, 547–570, https://doi.org/10.5194/tc-15-547-2021, https://doi.org/10.5194/tc-15-547-2021, 2021
Short summary
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.
Darri Eythorsson, Sigurdur M. Gardarsson, Shahryar K. Ahmad, and Oli Gretar Blondal Sveinsson
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2019-564, https://doi.org/10.5194/hess-2019-564, 2019
Preprint withdrawn
Short summary
Short summary
We studied recent trends in the Icelandic climate and snow regimes. Climate was classified based on climate models and snow cover trends were assessed using satellite imagery. Our results showed a significant increase in the frequency of snow cover, especially in the eastern highlands. At the same our results show warmer climate classes spreading both northward and to higher elevations. Based on projected climate, we expect a significant warming of local climates in Iceland during this century.
Andri Gunnarsson, Sigurður M. Garðarsson, and Óli G. B. Sveinsson
Hydrol. Earth Syst. Sci., 23, 3021–3036, https://doi.org/10.5194/hess-23-3021-2019, https://doi.org/10.5194/hess-23-3021-2019, 2019
Short summary
Short summary
In this study a gap-filled snow cover product for Iceland is developed using MODIS satellite data and validated with both in situ observations and alternative remote sensing data sources with good agreement. Information about snow cover extent, duration and changes over time is presented, indicating that snow cover extent has been increasing slightly for the past few years.
Related subject area
Discipline: Snow | Subject: Arctic (e.g. Greenland)
Assessment of Arctic seasonal snow cover rates of change
Snow properties at the forest–tundra ecotone: predominance of water vapor fluxes even in deep, moderately cold snowpacks
Spatial patterns of snow distribution in the sub-Arctic
Snowfall and snow accumulation during the MOSAiC winter and spring seasons
Inter-comparison of snow depth over Arctic sea ice from reanalysis reconstructions and satellite retrieval
Chris Derksen and Lawrence Mudryk
The Cryosphere, 17, 1431–1443, https://doi.org/10.5194/tc-17-1431-2023, https://doi.org/10.5194/tc-17-1431-2023, 2023
Short summary
Short summary
We examine Arctic snow cover trends through the lens of climate assessments. We determine the sensitivity of change in snow cover extent to year-over-year increases in time series length, reference period, the use of a statistical methodology to improve inter-dataset agreement, version changes in snow products, and snow product ensemble size. By identifying the sensitivity to the range of choices available to investigators, we increase confidence in reported Arctic snow extent changes.
Georg Lackner, Florent Domine, Daniel F. Nadeau, Matthieu Lafaysse, and Marie Dumont
The Cryosphere, 16, 3357–3373, https://doi.org/10.5194/tc-16-3357-2022, https://doi.org/10.5194/tc-16-3357-2022, 2022
Short summary
Short summary
We compared the snowpack at two sites separated by less than 1 km, one in shrub tundra and the other one within the boreal forest. Even though the snowpack was twice as thick at the forested site, we found evidence that the vertical transport of water vapor from the bottom of the snowpack to its surface was important at both sites. The snow model Crocus simulates no water vapor fluxes and consequently failed to correctly simulate the observed density profiles.
Katrina E. Bennett, Greta Miller, Robert Busey, Min Chen, Emma R. Lathrop, Julian B. Dann, Mara Nutt, Ryan Crumley, Shannon L. Dillard, Baptiste Dafflon, Jitendra Kumar, W. Robert Bolton, Cathy J. Wilson, Colleen M. Iversen, and Stan D. Wullschleger
The Cryosphere, 16, 3269–3293, https://doi.org/10.5194/tc-16-3269-2022, https://doi.org/10.5194/tc-16-3269-2022, 2022
Short summary
Short summary
In the Arctic and sub-Arctic, climate shifts are changing ecosystems, resulting in alterations in snow, shrubs, and permafrost. Thicker snow under shrubs can lead to warmer permafrost because deeper snow will insulate the ground from the cold winter. In this paper, we use modeling to characterize snow to better understand the drivers of snow distribution. Eventually, this work will be used to improve models used to study future changes in Arctic and sub-Arctic snow patterns.
David N. Wagner, Matthew D. Shupe, Christopher Cox, Ola G. Persson, Taneil Uttal, Markus M. Frey, Amélie Kirchgaessner, Martin Schneebeli, Matthias Jaggi, Amy R. Macfarlane, Polona Itkin, Stefanie Arndt, Stefan Hendricks, Daniela Krampe, Marcel Nicolaus, Robert Ricker, Julia Regnery, Nikolai Kolabutin, Egor Shimanshuck, Marc Oggier, Ian Raphael, Julienne Stroeve, and Michael Lehning
The Cryosphere, 16, 2373–2402, https://doi.org/10.5194/tc-16-2373-2022, https://doi.org/10.5194/tc-16-2373-2022, 2022
Short summary
Short summary
Based on measurements of the snow cover over sea ice and atmospheric measurements, we estimate snowfall and snow accumulation for the MOSAiC ice floe, between November 2019 and May 2020. For this period, we estimate 98–114 mm of precipitation. We suggest that about 34 mm of snow water equivalent accumulated until the end of April 2020 and that at least about 50 % of the precipitated snow was eroded or sublimated. Further, we suggest explanations for potential snowfall overestimation.
Lu Zhou, Julienne Stroeve, Shiming Xu, Alek Petty, Rachel Tilling, Mai Winstrup, Philip Rostosky, Isobel R. Lawrence, Glen E. Liston, Andy Ridout, Michel Tsamados, and Vishnu Nandan
The Cryosphere, 15, 345–367, https://doi.org/10.5194/tc-15-345-2021, https://doi.org/10.5194/tc-15-345-2021, 2021
Short summary
Short summary
Snow on sea ice plays an important role in the Arctic climate system. Large spatial and temporal discrepancies among the eight snow depth products are analyzed together with their seasonal variability and long-term trends. These snow products are further compared against various ground-truth observations. More analyses on representation error of sea ice parameters are needed for systematic comparison and fusion of airborne, in situ and remote sensing observations.
Cited articles
Aalstad, K., Westermann, S., and Bertino, L.: Evaluating satellite retrieved
fractional snow-covered area at a high-Arctic site using terrestrial
photography, Remote Sens. Environ., 239, 111618,
https://doi.org/10.1016/J.RSE.2019.111618, 2020.
Aðalgeirsdóttir, G., Johannesson, T., Bjornsson, H., Palsson, F., and
Sigurosson, O.: Response of Hofsjokull and southern Vatnajokull, Iceland, to
climate change, J. Geophys. Res. Surf., 111, F03001, https://doi.org/10.1029/2005jf000388, 2006.
Aðalgeirsdóttir, G., Magnússon, E., Pálsson, F.,
Thorsteinsson, T., Belart, J. M. C., Jóhannesson, T., Hannesdóttir,
H., Sigurðsson, O., Gunnarsson, A., Einarsson, B., Berthier, E.,
Schmidt, L. S., Haraldsson, H. H., and Björnsson, H.: Glacier Changes in
Iceland From ∼1890 to 2019, Front. Earth Sci., 8, 523646,
https://doi.org/10.3389/FEART.2020.523646, 2020.
Alonso-González, E., Gutmann, E., Aalstad, K., Fayad, A., Bouchet, M., and Gascoin, S.: Snowpack dynamics in the Lebanese mountains from quasi-dynamically downscaled ERA5 reanalysis updated by assimilating remotely sensed fractional snow-covered area, Hydrol. Earth Syst. Sci., 25, 4455–4471, https://doi.org/10.5194/hess-25-4455-2021, 2021.
Anderson, E. A.: Calibration of conceptual models for use in river forecasting, Hydrology Lab., Silver Spring, MD, National Weather Service, 2002.
Anderson, E.: Snow Accumulation and Ablation Model–SNOW-17, Office of
Hydrologic Development, National Weather Service,
https://doi.org/10.1038/177563a0, 2006.
Beaudoing, H. and Rodell, M.: GLDAS Noah Land Surface Model L4 3 hourly 0.25 × 0.25 degree V2.1, Greenbelt, Maryland, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), NASA/GSFC/HSL [data set], https://doi.org/10.5067/E7TYRXPJKWOQ, 2022.
Bjornsson, H. and Palsson, F.: Icelandic glaciers, Jökull, 58, 365–386,
2008.
Bjornsson, H., Olason, E. O., Jónsson, T., and Henriksen, S.: Analysis
of a smooth seasonal cycle with daily resolution and degree day maps for
Iceland, Meteorol. Z., 16, 57–69,
https://doi.org/10.1127/0941-2948/2007/0188, 2007.
Bjornsson, H., Palsson, F., Gudmundsson, S., Magnusson, E., Adalgeirsdottir,
G., Johannesson, T., Berthier, E., Sigurdsson, O., and Thorsteinsson, T.:
Contribution of Icelandic ice caps to sea level rise: Trends and variability
since the Little Ice Age, Geophys. Res. Lett., 40, 1546–1550,
https://doi.org/10.1002/grl.50278, 2013.
Bjornsson, H., Sigurdsson, B., Davidsdottir, B., Olafsson, J., Astthorsson,
O., Olafsdottir, S., Baldursson, T., and Jonsson, T.: Climate Change and
it's impact on Iceland – Report of the scientific committee on Climate
Change, Icelandic Meteorological Office, ISSN 978-9935-9414-0-4, 2018.
Blöschl, G., Hall, J., Parajka, J., Perdigão, R. A. P., Merz, B.,
Arheimer, B., Aronica, G. T., Bilibashi, A., Bonacci, O., Borga, M.,
Čanjevac, I., Castellarin, A., Chirico, G. B., Claps, P., Fiala, K.,
Frolova, N., Gorbachova, L., Gül, A., Hannaford, J., Harrigan, S.,
Kireeva, M., Kiss, A., Kjeldsen, T. R., Kohnová, S., Koskela, J. J.,
Ledvinka, O., Macdonald, N., Mavrova-Guirguinova, M., Mediero, L., Merz, R.,
Molnar, P., Montanari, A., Murphy, C., Osuch, M., Ovcharuk, V., Radevski,
I., Rogger, M., Salinas, J. L., Sauquet, E., Šraj, M., Szolgay, J.,
Viglione, A., Volpi, E., Wilson, D., Zaimi, K., and Živković, N.:
Changing climate shifts timing of European floods, Science, 357,
588–590, https://doi.org/10.1126/SCIENCE.AAN2506, 2017.
Brown, J., Ferrians, O., Higginbottom, J. A., and Melnikov, E.:
Circum-Arctic Map of Permafrost and Ground-Ice Conditions, Version 2,
Boulder, Colorado USA, National Snow and Ice Data Center [data set], https://doi.org/10.7265/skbg-kf16, 2002.
Brown, R. D. and Mote, P. W.: The response of Northern Hemisphere snow cover
to a changing climate, J. Clim., 22, 2124–2145,
https://doi.org/10.1175/2008JCLI2665.1, 2009.
Caesar, L., Rahmstorf, S., Robinson, A., Feulner, G., and Saba, V.: Observed
fingerprint of a weakening Atlantic Ocean overturning circulation, Nature, 556, 191–196,
https://doi.org/10.1038/s41586-018-0006-5, 2018.
Callaghan, T. V., Johansson, M., Brown, R. D., Groisman, P. Y., Labba, N.,
Radionov, V., Bradley, R. S., Blangy, S., Bulygina, O. N., Christensen, T.
R., Colman, J. E., Essery, R. L. H., Forbes, B. C., Forchhammer, M. C.,
Golubev, V. N., Honrath, R. E., Juday, G. P., Meshcherskaya, A. V., Phoenix,
G. K., Pomeroy, J., Rautio, A., Robinson, D. A., Schmidt, N. M., Serreze, M.
C., Shevchenko, V. P., Shiklomanov, A. I., Shmakin, A. B., Sköld, P.,
Sturm, M., Woo, M. K., and Wood, E. F.: Multiple effects of changes in
arctic snow cover, Ambio, 40, 32–45,
https://doi.org/10.1007/s13280-011-0213-x, 2011.
Cohen, J.: Snow cover and climate, Weather, 49, 150–156,
https://doi.org/10.1002/j.1477-8696.1994.tb05997.x, 1994.
Cortés, G., Girotto, M., and Margulis, S. A.: Analysis of sub-pixel snow
and ice extent over the extratropical Andes using spectral unmixing of
historical Landsat imagery, Remote Sens. Environ., 141, 64–78,
https://doi.org/10.1016/J.RSE.2013.10.023, 2014.
Danabasoglu, G., Lamarque, J. F., Bacmeister, J., Bailey, D. A., DuVivier,
A. K., Edwards, J., Emmons, L. K., Fasullo, J., Garcia, R., Gettelman, A.,
Hannay, C., Holland, M. M., Large, W. G., Lauritzen, P. H., Lawrence, D. M.,
Lenaerts, J. T. M., Lindsay, K., Lipscomb, W. H., Mills, M. J., Neale, R.,
Oleson, K. W., Otto-Bliesner, B., Phillips, A. S., Sacks, W., Tilmes, S.,
van Kampenhout, L., Vertenstein, M., Bertini, A., Dennis, J., Deser, C.,
Fischer, C., Fox-Kemper, B., Kay, J. E., Kinnison, D., Kushner, P. J.,
Larson, V. E., Long, M. C., Mickelson, S., Moore, J. K., Nienhouse, E.,
Polvani, L., Rasch, P. J., and Strand, W. G.: The Community Earth System
Model Version 2 (CESM2), J. Adv. Model. Earth Syst., 12, e2019MS001916,
https://doi.org/10.1029/2019MS001916, 2020.
Dietz, A. J., Kuenzer, C., Gessner, U., and Dech, S.: Remote sensing of snow
– a review of available methods, Int. J. Remote Sens., 33, 4094–4134,
https://doi.org/10.1080/01431161.2011.640964, 2012.
Dong, C.: Remote sensing, hydrological modeling and in situ observations in
snow cover research: A review, J. Hydrol., 561, 573–583,
https://doi.org/10.1016/j.jhydrol.2018.04.027, 2018.
Dozier, J.: Spectral signature of alpine snow cover from the landsat
thematic mapper, Remote Sens. Environ., 28, 9–22,
https://doi.org/10.1016/0034-4257(89)90101-6, 1989.
Eliasson, K., Ulfarsson, G. F., Valsson, T., and Gardarsson, S. M.:
Identification of development areas in a warming Arctic with respect to
natural resources, transportation, protected areas, and geography, Futures,
85, 14–29, https://doi.org/10.1016/j.futures.2016.11.005, 2017.
Eythorsson, D., Gardarsson, S. M., Gunnarsson, A., and Hrafnkelsson, B.:
Statistical summer mass-balance forecast model with application to
Brúarjökull glacier, South East Iceland, J. Glaciol., 64, 311–320,
https://doi.org/10.1017/jog.2018.22, 2018.
Fiddes, J., Aalstad, K., and Westermann, S.: Hyper-resolution ensemble-based snow reanalysis in mountain regions using clustering, Hydrol. Earth Syst. Sci., 23, 4717–4736, https://doi.org/10.5194/hess-23-4717-2019, 2019.
Fiddes, J., Aalstad, K., and Lehning, M.: TopoCLIM: rapid topography-based downscaling of regional climate model output in complex terrain v1.1, Geosci. Model Dev., 15, 1753–1768, https://doi.org/10.5194/gmd-15-1753-2022, 2022.
Franz, K. J. and Karsten, L. R.: Calibration of a distributed snow model
using MODIS snow covered area data, J. Hydrol., 494, 160–175,
https://doi.org/10.1016/j.jhydrol.2013.04.026, 2013.
Frei, A., Tedesco, M., Lee, S., Foster, J., Hall, D. K., Kelly, R., and
Robinson, D. A.: A review of global satellite-derived snow products, Adv. Space Res., 50, 1007–1029,
https://doi.org/10.1016/j.asr.2011.12.021, 2012.
Frei, P., Kotlarski, S., Liniger, M. A., and Schär, C.: Future snowfall in the Alps: projections based on the EURO-CORDEX regional climate models, The Cryosphere, 12, 1–24, https://doi.org/10.5194/tc-12-1-2018, 2018.
Gascoin, S., Dumont, Z. B., Deschamps-Berger, C., Marti, F., Salgues, G.,
López-Moreno, J. I., Revuelto, J., Michon, T., Schattan, P., and
Hagolle, O.: Estimating fractional snow cover in open terrain from
Sentinel-2 using the normalized difference snow index, Remote Sens., 12, 2904,
https://doi.org/10.3390/RS12182904, 2020.
Geirsdóttir, Á., Miller, G. H., Larsen, D. J., and
Ólafsdóttir, S.: Abrupt holocene climate transitions in the northern
north atlantic region recorded by synchronized lacustrine records in
iceland, Quat. Sci. Rev., 70, 48–62,
https://doi.org/10.1016/J.QUASCIREV.2013.03.010, 2013.
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, https://doi.org/10.1016/j.rse.2017.06.031, 2016.
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.
Hall, D. K. and Riggs, G. A.: MODIS/Aqua Snow Cover Daily L3 Global 500m SIN Grid, Version 6, Boulder, Colorado USA, NASA National Snow and Ice Data Center Distributed Active Archive Center [data set], https://doi.org/10.5067/MODIS/MYD10A1.006 (last access: 22 December 2022), 2016a.
Hall, D. K. and Riggs, G. A.: MODIS/Terra Snow Cover Daily L3 Global 500m SIN Grid, Version 6, Boulder, Colorado USA, NASA National Snow and Ice Data Center Distributed Active Archive Center [sata set], https://doi.org/10.5067/MODIS/MOD10A1.006 (last access: 22 December 2022), 2016b.
Hanna, E., Jónsson, T., and Box, J. E.: An analysis of Icelandic climate
since the nineteenth century, Int. J. Climatol., 24, 1193–1210,
https://doi.org/10.1002/joc.1051, 2004.
Hannesdóttir, H., Sigurðsson, O., Þrastarson, R. H.,
Guðmundsson, S., Belart, J. M. C., Pálsson, F., Magnússon, E.,
Víkingsson, S., Kaldal, I., and Jóhannesson, T.: A national glacier
inventory and variations in glacier extent in Iceland from the Little Ice
Age maximum to 2019, Jökull, 70, 111–118,
https://doi.org/10.33799/jokull2020.70.001, 2019.
Hannesdóttir, H., Sigurðsson, O., Þrastarson, R. H.,
Guðmundsson, S., Belart, J. M. C., Pálsson, F., Magnússon, E.,
Víkingsson, S., Kaldal, I., and Jóhannesson, T.: A national glacier
inventory and variations in glacier extent in Iceland from the Little Ice
Age maximum to 2019, Jokull, 2020, 1–34,
https://doi.org/10.33799/JOKULL2020.70.001, 2020.
Hanzer, F., Förster, K., Nemec, J., and Strasser, U.: Projected cryospheric and hydrological impacts of 21st century climate change in the Ötztal Alps (Austria) simulated using a physically based approach, Hydrol. Earth Syst. Sci., 22, 1593–1614, https://doi.org/10.5194/hess-22-1593-2018, 2018.
Hauser, S. and Schmitt, A.: Glacier Retreat in Iceland Mapped from Space:
Time Series Analysis of Geodata from 1941 to 2018, PFG – J. Photogramm.
Remote Sens. Geoinf. Sci. 2021, 1, 1–19,
https://doi.org/10.1007/S41064-021-00139-Y, 2021.
Icelandic Meterologocial Office: Reglur um veðurathuganir,
skýrslurfærslu og skeytasendingar á skeytastöðvum,
Reykjavik, https://www.vedur.is/media/vedurstofan/utgafa/greinargerdir/1995/leidbeiningar_2003_v2.pdf (last access: 22 December 2022), 2008.
Icelandic Meterologocial Office: Gagnabanki Veðurstofu Íslands,
afgreiðsla nr. 2021-12-15/01 [data set], Reykjavik, 2021 (can be accessed by direct communication with the IMO).
Johannesson, T., Aðalgeirsdottir, G., Bjornsson, H., Palsson, F., and Sigurdsson, O.: Response of glaciers and glacier runoff in Iceland to climate change, edited by: Jarvet, A., in: Proceedings of the 23rd Nordic Hydrological Conference, 8–12 August 2004, Tallinn, Estonia, 2004.
Johannesson, T., Adalgeirsdottir, G., Bjornsson, H., Crochet, P., Eliasson,
B. E., Gudmundsson, S., Jonsdóttir, J. F., Olafsson, H., Palsson, F.,
Rognvaldss, On, O., Sigurdsson, O., Snorrasson, A., Sveinsson, O. G. B., and
Thorsteinsson, T.: Effect of climate change on hydrology and hydro-resoures
in Iceland, Reykjavik, Report for the VO project, National Energy Authority, ISBN 978-9979-68-224-0, 2007.
Jónsdóttir, J. F., Uvo, C. B., and Clarke, R. T.: Trend analysis in
Icelandic discharge, temperature and precipitation series by parametric
methods, Hydrol. Res., 39, 425–436, https://doi.org/10.2166/NH.2008.002,
2008.
Knudsen, K. L., Søndergaard, M. K. B., Eiríksson, J., and Jiang, H.:
Holocene thermal maximum off North Iceland: Evidence from benthic and
planktonic foraminifera in the 8600–5200 cal year BP time slice, Mar.
Micropaleontol., 67, 120–142,
https://doi.org/10.1016/J.MARMICRO.2007.11.003, 2008.
Krinner, G., Derksen, C., Essery, R., Flanner, M., Hagemann, S., Clark, M., Hall, A., Rott, H., Brutel-Vuilmet, C., Kim, H., Ménard, C. B., Mudryk, L., Thackeray, C., Wang, L., Arduini, G., Balsamo, G., Bartlett, P., Boike, J., Boone, A., Chéruy, F., Colin, J., Cuntz, M., Dai, Y., Decharme, B., Derry, J., Ducharne, A., Dutra, E., Fang, X., Fierz, C., Ghattas, J., Gusev, Y., Haverd, V., Kontu, A., Lafaysse, M., Law, R., Lawrence, D., Li, W., Marke, T., Marks, D., Ménégoz, M., Nasonova, O., Nitta, T., Niwano, M., Pomeroy, J., Raleigh, M. S., Schaedler, G., Semenov, V., Smirnova, T. G., Stacke, T., Strasser, U., Svenson, S., Turkov, D., Wang, T., Wever, N., Yuan, H., Zhou, W., and Zhu, D.: ESM-SnowMIP: assessing snow models and quantifying snow-related climate feedbacks, Geosci. Model Dev., 11, 5027–5049, https://doi.org/10.5194/gmd-11-5027-2018, 2018.
Langdon, P. G., Caseldine, C. J., Croudace, I. W., Jarvis, S.,
Wastegård, S., and Crowford, T. C.: A chironomid-based reconstruction of
summer temperatures in NW Iceland since AD 1650, Quat. Res., 75, 451–460,
https://doi.org/10.1016/J.YQRES.2010.11.007, 2011.
Larsen, D. J., Miller, G. H., Geirsdóttir, Á., and Thordarson, T.: A
3000-year varved record of glacier activity and climate change from the
proglacial lake Hvítárvatn, Iceland, Quat. Sci. Rev., 30,
2715–2731, https://doi.org/10.1016/J.QUASCIREV.2011.05.026, 2011.
Magnusson, J., Wever, N., Essery, R., Helbig, N., Winstral, A., and Jonas,
T.: Evaluating snow models with varying process representations for
hydrological applications, Water Resour. Res., 51, 2707–2723,
https://doi.org/10.1002/2014WR016498, 2015.
Massé, G., Rowland, S. J., Sicre, M. A., Jacob, J., Jansen, E., and
Belt, S. T.: Abrupt climate changes for Iceland during the last millennium:
Evidence from high resolution sea ice reconstructions, Earth Planet. Sci.
Lett., 269, 565–569, https://doi.org/10.1016/j.epsl.2008.03.017, 2008.
Matiu, M. and Hanzer, F.: Bias adjustment and downscaling of snow cover fraction projections from regional climate models using remote sensing for the European Alps, Hydrol. Earth Syst. Sci., 26, 3037–3054, https://doi.org/10.5194/hess-26-3037-2022, 2022.
Miller, W. P., Piechota, T. C., Gangopadhyay, S., and Pruitt, T.: Development of streamflow projections under changing climate conditions over Colorado River basin headwaters, Hydrol. Earth Syst. Sci., 15, 2145–2164, https://doi.org/10.5194/hess-15-2145-2011, 2011.
Mizukami, N., and Koren, V.: Methodology and evaluation of melt factor parameterization for distributed SNOW-17, AGU Fall Meeting Abstracts, Vol. 2008, 2008.
National Land Survey of Iceland: IcelandDEM_2016, Akranes, National Land Survey of Iceland [data set], https://www.lmi.is/is/landupplysingar/gagnagrunnar/nidurhal (last access: 22 December 2022), 2016.
Nguyen, H. M., Ouillon, S., and Vu, V. D.: Sea Level Variation and Trend
Analysis by Comparing Mann–Kendall Test and Innovative Trend Analysis in
Front of the Red River Delta, Vietnam (1961–2020), Water (Switzerland), 14, 1709,
https://doi.org/10.3390/W14111709, 2022.
Noël, B., Aðalgeirsdóttir, G., Pálsson, F., Wouters, B.,
Lhermitte, S., Haacker, J. M., and van den Broeke, M. R.: North Atlantic
Cooling is Slowing Down Mass Loss of Icelandic Glaciers, Geophys. Res.
Lett., 49, e2021GL095697, https://doi.org/10.1029/2021GL095697, 2022.
Nolin, A. W., Sproles, E. A., Rupp, D. E., Crumley, R. L., Webb, M. J.,
Palomaki, R. T., and Mar, E.: New snow metrics for a warming world, Hydrol.
Process., 35, e14262, https://doi.org/10.1002/HYP.14262, 2021.
Notarnicola, C.: Hotspots of snow cover changes in global mountain regions
over 2000–2018, Remote Sens. Environ., 243, 111781,
https://doi.org/10.1016/J.RSE.2020.111781, 2020.
Notaro, M., Lorenz, D., Hoving, C., and Schummer, M.: Twenty-first-century
projections of snowfall and winter severity across central-eastern North
America, J. Clim., 27, 6526–6550, https://doi.org/10.1175/JCLI-D-13-00520.1, 2014.
Ólafsson, H., Furger, M., and Brümmer, B.: The weather and climate
of Iceland, Meteorol. Z., 16, 5–8,
https://doi.org/10.1127/0941-2948/2007/0185, 2007.
Oliphant, T. E.: Python for scientific computing, Comput. Sci. Eng., 9,
10–20, https://doi.org/10.1109/MCSE.2007.58, 2007.
Painter, T. H., Rittger, K., McKenzie, C., Slaughter, P., Davis, R. E., and
Dozier, J.: Retrieval of subpixel snow covered area, grain size, and albedo
from MODIS, Remote Sens. Environ., 113, 868–879,
https://doi.org/10.1016/j.rse.2009.01.001, 2009.
Robinson, D. A., Dewey, K. F., and Heim, R. R.: Global Snow Cover
Monitoring: An Update, Bull. Am. Meteorol. Soc., 74, 1689–1696,
https://doi.org/10.1175/1520-0477(1993)074<1689:GSCMAU>2.0.CO;2, 1993.
Rodell, M., Houser, P. R., Jambor, U., Gottschalck, J., Mitchell, K., Meng,
C. J., Arsenault, K., Cosgrove, B., Radakovich, J., Bosilovich, M., Entin,
J. K., Walker, J. P., Lohmann, D., and Toll, D.: The Global Land Data
Assimilation System, Bull. Am. Meteorol. Soc., 85, 381–394,
https://doi.org/10.1175/BAMS-85-3-381, 2004.
Salomonson, V. V. and Appel, I.: Development of the aqua MODIS NDSI
fractional snow cover algorithm and validation results, IEEE Trans. Geosci.
Remote Sens., 44, 1747–1756, https://doi.org/10.1109/TGRS.2006.876029, 2006.
Schmidt, L. S., Ađalgeirsdóttir, G., Pálsson, F., Langen, P. L.,
Guđmundsson, S., and Björnsson, H.: Dynamic simulations of
Vatnajökull ice cap from 1980 to 2300, J. Glaciol., 66, 97–112,
https://doi.org/10.1017/jog.2019.90, 2020.
Sicre, M.-A., Hall, I. R., Mignot, J., Khodri, M., Ezat, U., Truong, M.-X.,
Eiríksson, J., and Knudsen, K.-L.: Sea surface temperature variability
in the subpolar Atlantic over the last two millennia, Paleoceanography, 26, PA4218,
https://doi.org/10.1029/2011PA002169, 2011.
Smiatek, G., Kunstmann, H., and Senatore, A.: EURO-CORDEX regional climate
model analysis for the Greater Alpine Region: Performance and expected
future change, J. Geophys. Res.-Atmos., 121, 7710–7728,
https://doi.org/10.1002/2015JD024727, 2016.
NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP)|CDS: https://cds.nccs.nasa.gov/nex-gddp/, last access: 1 May 2017.
Thrasher, B., Maurer, E. P., McKellar, C., and Duffy, P. B.: Technical Note: Bias correcting climate model simulated daily temperature extremes with quantile mapping, Hydrol. Earth Syst. Sci., 16, 3309–3314, https://doi.org/10.5194/hess-16-3309-2012 (data available at: https://ds.nccs.nasa.gov/thredds/catalog/bypass/NEX-GDDP/catalog.html, last access: 6 December 2022), 2012.
Thrasher, B., Wang, W., Michaelis, A., Melton, F., Lee, T., and Nemani, R.:
NASA Global Daily Downscaled Projections, CMIP6, Sci. Data, 9, 1–6, 2022.
Verfaillie, D., Lafaysse, M., Déqué, M., Eckert, N., Lejeune, Y., and Morin, S.: Multi-component ensembles of future meteorological and natural snow conditions for 1500 m altitude in the Chartreuse mountain range, Northern French Alps, The Cryosphere, 12, 1249–1271, https://doi.org/10.5194/tc-12-1249-2018, 2018.
Yilmaz, Y. A., Aalstad, K., and Sen, O. L.: Multiple Remotely Sensed Lines
of Evidence for a Depleting Seasonal Snowpack in the Near East, Remote Sens.
2019, 11, 483, https://doi.org/10.3390/RS11050483, 2019.
Short summary
In this study we researched past and predicted snow conditions in Iceland based on manual snow observations recorded in Iceland and compared these with satellite observations. Future snow conditions were predicted through numerical computer modeling based on climate models. The results showed that average snow depth and snow cover frequency have increased over the historical period but are projected to significantly decrease when projected into the future.
In this study we researched past and predicted snow conditions in Iceland based on manual snow...
