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ISSN 2070-7401 (Print), ISSN 2411-0280 (Online)
Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa
CURRENT PROBLEMS IN REMOTE SENSING OF THE EARTH FROM SPACE

  

Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2020, Vol. 17, No. 1, pp. 164-175

Accuracy of reproduction of interannual variability of snow storages of the East European Plain by satellite data illustrated by the example of the GlobSnow (SWE) product

L.M. Kitaev 1 , T.B. Titkova 1 , D.V. Turkov 1 
1 Institute of Geography RAS, Moscow, Russia
Accepted: 10.02.2020
DOI: 10.21046/2070-7401-2020-17-1-164-175
Peculiarities of reproducing the long-term variability of snow storages of the East European Plain by data recovered from satellite information were studied using the GlobSnow (SWE) product of the second version (European Space Agency) as an example. The variability of the recovered data is considered in comparison with the variability of the actual data of meteorological stations and the data calculated by the SPONSOR model (Institute of Geography RAS). The snow storages calculated according to the model and reconstructed from satellite information exceed the actual snow reserves, varying, however, in space according to the change of natural zones. the discrepancy regarding evidence remains high. Nevertheless, according to the developers, the tightness of the correlation between the calculated and actual data of the reference seasons and years is high, which, however, does not always ensure similar interannual variability of characteristics. The best coincidences of years with anomalous actual snow storages are noted for the characteristics calculated by the model, as well as in this case the similarity of the Fourier harmonics, especially for open spaces of forest-steppes and steppes.
Keywords: snow reserves, interannual and multi-year variability, actual and model data, satellite information
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References:

  1. Bokuchava D. D., Semenov V. A., Analiz anomalii prizemnoi temperatury vozdukha v severnom polusharii v techenie XX veka po dannym nablyudenii i reanalizov (Analysis of surface air temperature anomalies in the northern hemisphere during the 20th century based on observational and reanalysis data), Fundamenta’naya i prikladnaya klimatologiya, 2018, No. 1, pp. 28–51.
  2. Vaganov E. A., Shiyatov S. G., Mazepa V. S., Dendroklimatologicheskie issledovaniya v Uralo-Sibirskoi Sub­arktike (Dendroclimatological studies in the Ural-Siberian Subarctic), Novosibirsk: Nauka, 1996, 246 p.
  3. Kireeva M. B., Frolova N. L., Rets E. P., Samsonov T. E., Vodnyi rezhim rek evropeiskoi territorii Rossii i ego transformatsiya v XXI veke pod vliyaniem menyayushchegosya klimata (The water regime of rivers in the European territory of Russia and its transformation in the XXI century under the influence of a chan­ging climate), Vodnye resursy Rossii: sovremennoe sostoyanie i upravlenie (Water resources of Russia: current status and management), Proc. All-Russia Scientific and Practical Conf., 2018, pp. 49–55.
  4. Kislov A. V., Kitaev L. M., Konstantinov I. S., Statisticheskaya struktura krupnomasshtabnykh osobennostei polya snezhnogo pokrova (Statistical structure of large-scale features of the snow cover field), Meteorologiya i gidrologiya, 2001, No. 8, pp. 98–104.
  5. Kitaev L. M., Izmenchivost’ snegozapasov severnoi Evrazii v predvesennii i vesennii periody (Variability of snow reserves in northern Eurasia in the pre-spring and spring periods), Kriosfera Zemli, 2013, Vol. 17, No. 2, pp. 70–73.
  6. Kuzmin P. P., Fizicheskie svoistva snezhnogo pokrova (Physical properties of snow cover), Leningrad: Gidrometeoizdat, 1957, 179 p.
  7. Nikolaev A. N., Skachkov Yu. B., Vliyanie snezhnogo pokrova i temperaturnogo rezhima merzlotnykh ­pochv na radial’nyi prirost derev’ev Tsentral’noi Yakutii (The influence of snow cover and temperature regime of permafrost soils on the radial growth of trees in Central Yakutia), Zhurnal Sibirskogo federal’nogo universiteta. Ser. Biologiya, 2012, No. 5, pp. 43–51.
  8. Petrushina M. N., Golubev V. N., Zakonomernosti i osobennosti prostranstvenno-vremennogo raspre­deleniya struktury snezhnogo pokrova v Severnoi Evrazii (na primere 2004/05 gg.) (Regularities and features of the spatial and temporal distribution of the snow cover structure in Northern Eurasia (for examp­le, 2004/05)), Geoprostranstvennye sistemy: struktura, dinamika, vzaimosvyazi: Trudy 12-go sʺezda Russkogo geograficheskogo obshchestva (Geospatial systems: structure, dynamics, interconnections: Proc. 12th Congress of the Russian Geographical Society), Vol. 2, Saint Petersburg, 2005, pp. 137–140.
  9. Popova V. V., Morozova P. A., Titkova T. B., Semenov V. A., Cherenkova E. A., Shiryaeva A. V., Kita­ev L. M., Regional’nye osobennosti sovremennykh izmenenii zimnei akkumulyatsii snega na severe Evrazii po dannym nablyudenii, reanaliza i sputnikovykh izmerenii (Regional features of modern changes in winter snow accumulation in the north of Eurasia according to observations, reanalysis and satellite measurements), Led i sneg, 2015, Vol. 55, No. 4, pp. 73–86.
  10. Turkov D. V., Sokratov V. S., Raschet kharakteristik snezhnogo pokrova ravninnykh territorii s ispol’zo­vaniem modeli lokal’nogo teplovlagoobmena sponsor i dannykh reanaliza na primere Moskovskoi oblasti (Calculation of snow cover characteristics of lowland territories using the local model of local heat and moisture exchange SPONSOR and reanalysis data on the example of the Moscow region), Led i sneg, 2016, Vol. 56, No. 3, pp. 369–380.
  11. Khan V. M., Rubinshtein K. G., Shmakin A. B., Sravnenie sezonnoi i mezhgodovoi izmenchivosti snezhnogo pokrova v basseinakh rek Rossii po dannym nablyudenii i reanalizov (Snow cover model taking into account the layered structure and its seasonal evolution), Izvestiya Rossiiskoi akademii nauk. Fizika atmosfery i okeana, 2007, Vol. 43, No. 1, pp. 69–80.
  12. Shmakin A. B., Turkov D. V., Mikhailov A. Yu., Model’ snezhnogo pokrova s uchetom sloistoi struktury i ee sezonnoi evolyutsii (Snow cover model taking into account the layered structure and its seasonal evolution), Kriosfera Zemli, 2009, Vol. 13, No. 4, pp. 69–79.
  13. Fierz Ch., Field observation and modelling of weak-layer evolution, Annals of Glaciology, 1998, Vol. 26, pp. 7–13.
  14. Kelly R. E., Chang A. T., Tsang L., Foster J. L., A prototype AMSRE global snow area and snow depth algorithm, IEEE Trans. Geoscience and Remote Sensing, 2003, Vol. 41, pp. 230–242.
  15. Koenig L. S., Forster R. R., Evaluation of passive microwave snow water equivalent algorithms in the depth hoar-dominated snowpack of the Kuparuk River watershed, Alaska, USA, Remote Sensing of Environment, 2004, Vol. 93, pp. 511–527.
  16. Kruopis N., Praks J., Arslan A. N., Alasalmi H., Koskinen J., Hallikainen M., Passive microwave measurements of snow-covered forest areas in EMAC’95, IEEE Trans. Geoscience and Remote Sensing, 1999, Vol. 37, pp. 2699–2705.
  17. Metsämäki S., Anttila S., Huttunen M., Vepsäläinen J., A feasible method for fractional snow cover mapping in boreal zone based on a reflectance model, Remote Sensing of Environment, 2005, Vol. 95, No. 1, pp. 77–95.
  18. Pulliainen J., Mapping of snow water equivalent and snow depth in boreal and sub-arctic zones by assimilating space-borne microwave radiometer data and ground-based observations, Remote Sensing of Environment, 2006, Vol. 101, pp. 257–269.
  19. Pulliainen J., Hallikainen M., Retrieval of regional snow water equivalent from space-borne passive microwave observations, Remote Sensing of Environment, 2001, Vol. 75, pp. 76–85.
  20. Snow and Climate, R. L. Armstrong, E. Brun (eds.), Cambridge University Press, 2008, 222 p.
  21. Takala M., Pulliainen J., Sari J., Metsämäki O., Koskinen J. T., Detection of Snowmelt Using Spaceborne Microwave Radiometer Data in Eurasia from 1979 to 2007, IEEE Trans. Geoscience and Remote Sensing, 2009, Vol. 4, No. 9, pp. 299–3007.
  22. Uppala S. M., Kallberg P. W., The ERA-40 re-analysis, Quarterly J. Royal Meteorological Society, 2005, Vol. 131, No. 612, pp. 2961–3012.
  23. Vavrus S., The role of terrestrial snow cover in the climate system, Climate Dynamics, 2007, Vol. 29, pp. 73–88.