Ice and SnowIce and SnowЛед и снег2076-67342412-3765The Russian Academy of Sciences65687010.31857/S2076673424030079INVIGYSnow cover and avalanchesСнежный покров и снежные лавиныResearch ArticleSnow albedo and its parameterization for natural systems and climate modelingАльбедо снежного покрова и его параметризация для целей моделирования природных систем и климатаTurkovD. V.ТурковД. В.
Russian Federation
drozdov.jeka@yandex.ruDrozdovE. D.ДроздовЕ. Д.
Russian Federation
drozdov.jeka@yandex.ruLomakinA. A.ЛомакинА. А.
Russian Federation
drozdov.jeka@yandex.ruInstitute of Geography RASИнститут географии РАНLomonosov Moscow State UniversityМосковский государственный университет имени М.В. ЛомоносоваNational Research University “Higher School of Economics”Национальный исследовательский университет «Высшая школа экономики»Space Research Institute RASИнститут космических исследований РАН1507202464340341918022025Copyright ©; 2024, Russian Academy of SciencesCopyright ©; 2024, Российская академия наук2024Russian Academy of SciencesРоссийская академия наукhttp://creativecommons.org/licenses/by/4.0https://journals.eco-vector.com/2076-6734/article/view/656870

The physical factors having influence on albedo of snow cover, as well as the main methods for its parameterization in models of natural systems, are considered. Numerous studies by various authors have shown that the most important characteristics determining the snow albedo in the near infrared range (hereinafter referred to as NIR) is the size of snow grains and crystals, and in the visible and UV ranges – the presence of impurities, primarily dust and soot. We have proposed the new scheme for parameterizing the albedo of snow cover, taking into account most of the processes and factors important for the metamorphism of snow and changes in its stratification and microstructure, namely: the influence of weather conditions during snowfall, its age, density and rate of background pollution, air temperature and solar radiation intensity, as well as the height of the Sun (angle of the Sun above the horizon). The proposed parameterization scheme is introduced into the LSM SPONSOR model. A new scheme for parameterizing snow albedo as part of the LSM SPONSOR model was tested using long-term observational data. Observational data were obtained for four ESM-SnowMIP project sites located in the mountainous regions of Europe and North America: Col-de-Porte (France), Weissfluhjoch (Switzerland), Senator Beck and Swamp Angel (USA, Colorado). The series of observational data on the surface noon albedo are 20 years long for the first two sites, and 10 years long for the rest. When compared with the old scheme for parameterizing the albedo of snow cover in the LSM SPONSOR model, based on the dependence of the albedo only on the age of the snow, the new scheme showed a significant increase in the quality of albedo calculations: the correlation coefficients between the observed data and the calculation results are 0.78–0.83, which gives determination coefficients of 0.61–0.69. The new scheme makes it possible to obtain unbiased albedo estimates with statistical distribution characteristics that practically coincide with those obtained for observational data. The set of test sites covers the specific conditions of snow formation in the mountains, both in forested and treeless zones, so the scheme can be recommended for calculating albedo in a wide range of mountain landscapes. The quality of the scheme is also confirmed by the fact that the calculations were carried out with the same values of all model parameters and coefficients for all four test sites located in different climatic conditions.

Предложена новая схема параметризации альбедо снежного покрова, учитывающая большинство факторов, важных для метаморфизма снега. Проведено тестирование новой схемы параметризации альбедо снега в составе модели LSM SPONSOR по данным многолетних наблюдений. Показано, что новая схема позволяет получать несмещённые оценки альбедо со статистическими характеристиками, близкими к тем, что получены для данных наблюдений.

snow coveralbedomodellingparameterizationLSM SPONSORснежный покровальбедомоделированиепараметризациямодель SPONSORПравительство РФGovernment of RFFMWS-2024-0004Российский научный фондRussian Science Foundation23-17-00247Drozdov E.D., Turkov D.V., Toropov P.A., Artamonov A. Yu. Thermal regime of snow cover in winter in the high-mountainous part of Elbrus according to observational data and modeling results. Led i Sneg. Ice and Snow. 2023, 2 (63): 225–242. https://doi.org/10.31857/S2076673423020059 [In Russian].Дроздов Е.Д., Турков Д.В., Торопов П.А., Артамонов А.Ю. Термический режим снежного покрова зимой в высокогорной части Эльбруса по натурным данным и результатам моделирования // Лёд и Снег. 2023. Т. 63. № 2. С. 225–242. https://doi.org/10.31857/S2076673423020059Kondratiev K.Ya. Aktinometriya. Actinometry. Leningrad: Hydrometeoizdat, 1965: 691 p. [In Russian].Кондратьев К.Я. Актинометрия. Л.: Гидрометеоиздат, 1965. 691 с.Kotlyakov V.M. Cryosphere and climate. Ekologia i zhizn. Ecology and Life. 2010, 11: 51–59 [In Russian].Котляков В.М. Криосфера и климат // Экология и жизнь. 2010. № 11. С. 51–59.Krass M.S., Merzlikin V.G. Radiatsionnaya fizika snega i l’da. Radiational physics of snow and ice. Leningrad: Hydrometeoizdat, 1990: 264 p. [In Russian].Красс М.С., Мерзликин В.Г. Радиационная физика снега и льда. Л.: Гидрометеоиздат, 1990. 264 с.Kuzmin P.P. Fizicheskie svoystva snezhnogo pokrova. Physical properties of snow. Leningrad: Hydrometeoizdat, 1957: 179 p. [In Russian].Кузьмин П.П. Физические свойства снежного покрова. Л.: Гидрометеоиздат, 1957. 179 с.Kuzmin P.P. Protsess tayaniya snezhnogo pokrova. The process of snow cover melting. Leningrad: Hydrometeoizdat, 1961: 344 p. [In Russian].Кузьмин П.П. Процесс таяния снежного покрова. Л.: Гидрометеоиздат, 1961. 344 с.Matveev L.T. Kurs obshchey meteorologii. Fizika atmosfery. General meteorology course. Atmospheric physics. Leningrad: Hydrometeoizdat, 1984: 752 p. [In Russian].Матвеев Л.Т. Курс общей метеорологии. Физика атмосферы. Л.: Гидрометеоиздат, 1984. 752 с.Sneg: Spravochnik. Snow: Handbook. ed. by D.M. Gray, D.H. Mail; Trans. from Eng. ed. by V.M. Kotlyakov. Leningrad: Hydrometeoizdat, 1986: 751 p. [In Russian].Снег: Справочник / Под ред. Д.М. Грея, Д.Х. Мэйла. Пер. с англ. под ред. В.М. Котлякова. Л.: Гидрометеоиздат, 1986. 751 с.Turkov D.V., Sokratov V.S. Calculating of snow cover characteristics on a plain territory using the model SPONSOR and data of reanalyses (by the example of Moscow region). Led i Sneg. Ice and Snow. 2016, 3 (56): 369–380. https://doi.org/10.15356/2076-6734-2016-3-369-380 [In Russian].Турков Д.В., Сократов В.С. Расчёт характеристик снежного покрова равнинных территорий с использованием модели локального тепловлагообмена SPONSOR и данных реанализа на примере Московской области // Лёд и Снег. 2016. Т. 56. № 3. С. 369–380. https://doi.org/10.15356/2076-6734-2016-3-369-380Shmakin A.B., Turkov D.V., Michailov A.Yu. Snow cover model taking into account the layered structure and its seasonal evolution. Kriosfera Zemli. Earth Cryosphere. 2009, 13 (4): 69–79 [In Russian].Шмакин А.Б., Турков Д.В., Михайлов А.Ю. Модель снежного покрова с учётом слоистой структуры и её сезонной эволюции // Криосфера Земли. 2009. Т. XIII (4). С. 69–79.Barlett P.A., MacKay M.D., Verseghy D.L. Modified snow algorithms in the Canadian land surface scheme: Model runs and sensitivity analysis at three boreal forest stands. Atmosphere-Ocean. 2006, 44 (3): 207–222. https://doi.org/10.3137/ao.440301Barlett P.A., MacKay M.D., Verseghy D.L. Modified snow algorithms in the Canadian land surface scheme: Model runs and sensitivity analysis at three boreal forest stands // Atmosphere-Ocean. 2006. 44. № 3. P. 207–222. https://doi.org/10.3137/ao.440301Chandrasekhar S. Radiative transfer. New York: Dover Publications. 2016: 393 p.Chandrasekhar S. Radiative transfer. New York: Dover Publications, 2016. 393 p.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., Strand W.G. The Community Earth System Model Version 2 (CESM2). Journ. Adv Model Earth Syst. 2020, 12 (2): e2019MS001916. https://doi.org/10.1029/2019MS001916Danabasoglu 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‐BliesnerB., 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., Strand W.G. The Community Earth System Model Version 2 (CESM2) // Journ. Adv Model Earth System 2020. 12 (2). P. e2019MS001916. https:// doi.org/10.1029/2019MS001916Dang C., Zender C.S., Flanner M.G. Intercomparison and improvement of two-stream shortwave radiative transfer schemes in Earth system models for a unified treatment of cryospheric surfaces. The Cryosphere. 2019, 13 (9): 2325–2343. https://doi.org/10.5194/tc-13-2325-2019Dang C., Zender C.S., Flanner M.G. Intercomparison and improvement of two-stream shortwave radiative transfer schemes in Earth system models for a unified treatment of cryospheric surfaces // The Cryosphere. 2019. V. 13. P. 2325–2343. https://doi.org/10.5194/tc-13-2325-2019Decharme B., Brun E., Boone A., Delire C., Le Moigne P., Morin S. Impacts of snow and organic soils parameterization on northern Eurasian soil temperature profiles simulated by the ISBA land surface model. The Cryosphere. 2016, 2 (10): 853–877. https://doi.org/10.5194/tc-10-853-2016Decharme B., Brun E., Boone A., Delire C., Le Moigne P., Morin S. Impacts of snow and organic soils parameterization on northern Eurasian soil temperature profiles simulated by the ISBA land surface model // The Cryosphere. 2016. V. 10. № 2. P. 853–877. https:// doi.org/10.5194/tc-10-853-2016Dickinson R., Henderson-Sellers A., Kennedy P. Biosphere-Atmosphere Transfer Scheme (BATS) Version le as Coupled to the NCAR Community Climate Model. 1993: 80 p. https://doi.org/10.5065/D67W6959Dickinson R., Henderson-Sellers A., Kennedy P. Biosphere-Atmosphere Transfer Scheme (BATS) Version le as Coupled to the NCAR Community Climate Model. 1993. 80 p. https://doi.org/10.5065/D67W6959Flanner M.G., Arnheim J.B., Cook J.M., Dang C., He C., Huang X., Singh D., Skiles S.M., Whicker C.A., Zender C.S. SNICAR-ADv3: a community tool for modeling spectral snow albedo. Geosci. Model Dev. 2021, 14 (12): 7673–7704. https://doi.org/10.5194/gmd-14-7673-2021Flanner M.G., Arnheim J.B., Cook J.M., Dang C., He C., Huang X., Singh D., Skiles S.M., Whicker C.A., Zender C.S. SNICAR-ADv3: a community tool for modeling spectral snow albedo // Geosci. Model Dev. 2021. V. 14. P. 7673–7704. https://doi.org/10.5194/gmd-14-7673-2021He C., Liou K.-N., Takano Y., Yang P., Qi L., Chen F. Impact of Grain Shape and Multiple Black Carbon Internal Mixing on Snow Albedo: Parameterization and Radiative Effect Analysis. Journ. of Geophysical Research: Atmospheres. 2018, 123 (2): 1253–1268. https://doi.org/10.1002/2017JD027752He C., Liou K.-N., Takano Y., Yang P., Qi L., Chen F. Impact of Grain Shape and Multiple Black Carbon Internal Mixing on Snow Albedo: Parameterization and Radiative Effect Analysis // Journ. of Geophysical Research: Atmospheres. 2018. V. 123. № 2. P. 1253–1268. https://doi.org/10.1002/2017JD027752Hedstrom N., Pomeroy J.W. Intercepted snow in boreal forest: measurement and modelling. Hydrol. Process. 1998, 12: 1611–1625. https://doi.org/10.1002/(SICI)1099-1085(199808/09)12:10/11<1611::AID-HYP684>3.0.CO;2-4Hedstrom N., Pomeroy J.W. Intercepted snow in boreal forest: measurement and modelling // Hydrol. Process. 1998. V. 12. № 11-12. P. 1611–1625. https://doi.org/10.1002/(SICI)1099-1085(199808/09)12:10/11<1611::AID-HYP684>3.0.CO;2-4Krinner G., Derksen C., Richard E. ESM-SnowMIP: assessing snow models and quantifying snow-related climate feedbacks. Geosci. Model Dev. 2018, 11: 5027–5049. https://doi.org/10.5194/gmd-11-5027-2018Krinner G., Derksen C., Richard E. ESM-SnowMIP: assessing snow models and quantifying snow-related climate feedbacks // Geosci. Model Dev. 2018. V. 11. P. 5027–5049. https://doi.org/10.5194/gmd-11-5027-2018Landry C.C., Buck K.A., Raleigh M.S., Clark M.P. Mountain system monitoring at Senator Beck Basin, San Juan Mountains, Colorado: A new integrative data source to develop and evaluate models of snow and hydrologic processes. Water Resour. Res. 2014, 50: 1773–1788. https://doi.org/10.1002/2013WR013711Landry C. C., Buck K.A., Raleigh M.S., Clark M.P. Mountain system monitoring at Senator Beck Basin, San Juan Mountains, Colorado: A new integrative data source to develop and evaluate models of snow and hydrologic processes // Water Resource Research 2014. V. 50. P. 1773–1788. https://doi.org/10.1002/2013WR013711Lee W.Y., Gim H.J., Park S.K. Parameterizations of Snow Cover, Snow Albedo and Snow Density in Land Surface Models: A Comparative Review. Asia-Pac Journ. Atmos Sci. 2023. 60: 185–210. https://doi.org/10.1007/s13143-023-00344-2Lee W.Y., Gim H.J., Park S.K. Parameterizations of Snow Cover, Snow Albedo and Snow Density in Land Surface Models: A Comparative Review // Asia-Pacific Journal of Atmospheric Science. 2023. V. 60. P. 185–210. https://doi.org/10.1007/s13143-023-00344-2Lejeune Y., Dumont M., Panel J.M., Lafaysse M., Lapalus P., Le Gac E., Lesaffre B., Morin S. 57 years (1960-2017) of snow and meteorological observations from a mid-altitude mountain site (Col de Porte, France, 1325 m alt.). Earth System Science Data. 2019, 11: 71–88. https://doi.org/10.5194/essd-11-71-2019Lejeune Y., Dumont M., Panel J.M., Lafaysse M., Lapalus P., Le Gac E., Lesaffre B., Morin S. 57 years (1960–2017) of snow and meteorological observations from a mid-altitude mountain site (Col de Porte, France, 1325 m alt.) // Earth System Science Data. 2019. V. 11. P. 71–88. https://doi.org/10.5194/essd-11-71-2019Menard C., Essery R., Turkov D. Scientific and human errors in a snow model intercomparison. Bulletin of the American Meteorological Society. 2021, 201 (1): E61–E79. https://doi.org/10.1175/BAMS-D-19-0329.1Menard C., Essery R., Turkov D. Scientific and human errors in a snow model intercomparison // Bulletin of the American Meteorological Society. 2021. V. 201. № 1. P. E61–E79. https://doi.org/10.1175/BAMS-D-19-0329.1Rowe P.M., Fergoda M., Neshyba S. Temperature‐Dependent Optical Properties of Liquid Water From 240 to 298 K. JGR Atmospheres. 2020, 125 (17): e2020JD032624. https://doi.org/10.1029/2020JD032624Rowe P.M., Fergoda M., Neshyba S. Temperature‐Dependent Optical Properties of Liquid Water From 240 to 298 K // JGR Atmospheres. 2020. V. 125. № 17. P. e2020JD032624. https://doi.org/10.1029/2020JD032624Snow and Climate. Ed. by R.L. Armstrong, E. Brun. Cambridge, U.K. Cambridge Univ. Press, 2008: 222 p.Snow and Climate. Ed. by R.L. Armstrong, E. Brun. Cambridge, U.K. Cambridge Univ. Press, 2008. 222 p.Stamnes K., Tsay S.C., Wiscombe W., Jayaweera K. Numerically stable algorithm for discrete-ordinate-method radiative transfer in multiple scattering and emitting layered media. Appl. Opt. 1988, 27 (12): 2502. https://doi.org/10.1364/AO.27.002502Stamnes K., Tsay S.C., Wiscombe W., Jayaweera K. Numerically stable algorithm for discrete-ordinate-method radiative transfer in multiple scattering and emitting layered media // Applied Opt. 1988. V. 27. № 12. P. 2502. https://doi.org/10.1364/AO.27.002502Vavrus S. The role of terrestrial snow cover in the climate system. Climate Dynamics. 2007, 29: 73–88. https://doi.org/10.1007/s00382-007-0226-0Vavrus S. The role of terrestrial snow cover in the climate system // Climate Dynamics. 2007. V. 29. P. 73–88. https://doi.org/10.1007/s00382-007-0226-0Verseghy D. CLASS–The Canadian land surface scheme (version 3.6). Environment Canada Science and Technology Branch Tech. Rep. 2012.Verseghy D. CLASS–The Canadian land surface scheme (version 3.6) // Environment Canada Science and Technology Branch Tech. Rep. 2012.Vionnet V., Brun E., Morin S., Boone A., Faroux S., Moigne P.L., Martin E., Willemet J.M. The detailed snowpack scheme Crocus and its implementation in SURFEX v7.2. Geoscientific Model Development. 2012, 5: 773–791. https://doi.org/10.5194/gmd-5-773-2012Vionnet V., Brun E., Morin S., Boone A., Faroux S., Moigne P.L., Martin E., Willemet J.M. The detailed snowpack scheme Crocus and its implementation in SURFEX v7.2 // Geoscientific Model Development. 2012. V. 5. P. 773–791. https://doi.org/10.5194/gmd-5-773-2012Warren S.Q. Optical Properties of Snow. Reviews of Geophysics. 1982, 20: 67–89. https://doi.org/10.1029/RG020i001p00067Warren S.Q. Optical Properties of Snow // Reviews of Geophysics. 1982. V. 20. P. 67–89. https://doi.org/10.1029/RG020i001p00067Warren S.G., Brandt R.E. Optical constants of ice from the ultraviolet to the microwave: A revised compilation. Journ. Geophys. Res. 2008, 113 (D14220): 2007JD009744. https://doi.org/10.1029/2007JD009744Warren S.G., Brandt R.E. Optical constants of ice from the ultraviolet to the microwave: A revised compilation // Journal of Geophys. Research. 2008. V. 113. D14220 P. 2007JD009744. https://doi.org/10.1029/2007JD009744Wever N., Schmid L., Heilig A., Eisen O., Fierz C., Lehning M. Verification of the multi-layer SNOWPACK model with different water transport schemes. The Cryosphere. 2015, 9: 2271–2293. https://doi.org/10.5194/tc-9-2271-2015Wever N., Schmid L., Heilig A., Eisen O., Fierz C., Lehning M. Verification of the multi-layer SNOWPACK model with different water transport schemes // The Cryosphere. 2015. V 9. P. 2271–2293. https://doi.org/10.5194/tc-9-2271-2015Whicker C.A., Flanner M.G., Dang C., Zender C.S., Cook J.M., Gardner A.S. SNICAR-ADv4: a physically based radiative transfer model to represent the spectral albedo of glacier ice. The Cryosphere. 2022, 16: 1197–1220. https://doi.org/10.5194/tc-16-1197-2022Whicker C.A., Flanner M.G., Dang C., Zender C.S., Cook J.M., Gardner A.S. SNICAR-ADv4: a physically based radiative transfer model to represent the spectral albedo of glacier ice // The Cryosphere. 2022. V. 16. P. 1197–1220. https://doi.org/10.5194/tc-16-1197-2022Wiscombe W.J., Warren S.G. A model for the spectral albedo of snow. I: Pure snow. Journ. Atmos. Sci. 1980, 37: 2712–2733. https://doi.org/10.1175/1520-0469(1980)037<2712:AMFTSA>2.0.CO;2Wiscombe W.J., Warren S.G. A model for the spectral albedo of snow. I: Pure snow // Journal of Atmosphere Science. 1980. V. 37. P. 2712–2733. https://doi.org/10.1175/1520-0469(1980)037<2712:AMFTSA>2.0.CO;2