Arctic: ecology and economy
ISSN 2223-4594
Home » Archive of journals » Issue 2(30) 2018 » Sources of data for numerical simulation of the White Sea for developing the Russian Arctic area


JOURNAL: 2018, №2(30), p. 45-55

HEADING: Research activities in the Arctic

AUTHORS: Tolstikov A.V., Chernov I.A., Martynova D.M.

ORGANIZATIONS: Northern Water Problems Institute of the Karelian Research Centre of the RAS, Institute of Applied Mathematical Research of the Karelian Research Centre of the Russian Academy of Sciences, White Sea Biological Station, Zoological Institute of the Russian Academy of Sciences

DOI: 10.25283/2223-4594-2018-2-45-55

UDC: 556.5.072(268.46)(98)

The article was received on: 01.03.2018

Keywords: White sea, BFM, JASMINE, remote sensing, data in situ, numerical model

Bibliographic description: Tolstikov A.V., Chernov I.A., Martynova D.M. Sources of data for numerical simulation of the White Sea for developing the Russian Arctic area. Arctic: ecology and economy, 2018, no. 2(30), pp. 45-55. DOI: 10.25283/2223-4594-2018-2-45-55. (In Russian).


In the paper we discuss the problem of getting data for numerical modelling of the White sea. It completely belongs to Russia and is important due to a number of human activities including fisheries, mollusk farms, mining, tourism, maritime shipping. Also, the Northern Sea Route begins in the White Sea. Large projects demand complete understanding of variability of hydrophysical and biogeochemical processes in the sea, so it is important to reproduce the most important processes by numerical models. This is important not only for the White sea, but for the Arctic region in general. By data we mean hydrophysical (water temperature, salinity, density, ice and snow thickness, etc), hydrobiological (biomass of plankton, productivity, etc), biogeochemical (dissolved or suspended biogen or organic matter, detritus, etc) fields. Also meteorological and miscellaneous data (bathymetry, rivers) are necessary. Values of these and other fields can be obtained by three different ways. First, this is in situ measurements (from scientific vessels or by automatic devices); then, remote sensing, usually by satellites; finally, numerical models are able to evaluate the data. However, tuning and verification of models also demand in situ or satellite data. We survey the in situ data sources and collections, together with institutions that gather data and conditions of data availability. Also, an overview of satellite data sources is presented. Finally, we discuss simulation of the sea by numerical models and present our model JASMINE with BFM as a biogeochemical component, focusing on necessary initial, boundary, and forcing data.

Finance info: Работа выполнена по теме НИР «Закономерности изменений экосистем Белого моря при интенсификации освоения Арктической зоны региона и под влиянием изменений климата», номер государственной регистрации АААА-А18-118032290034-5, грант РФФИ № 16-45-100162 р_а.

  1. Filatov N. N., Terzhevik A. Yu., Druzhinin P. V. Belomor’e — region dlya resheniya aktual’nykh problem Arktiki. [Belomorie is the region of the Arctic challenges solving]. Arktika: ekologiya i ekonomika, 2011, no. 2, pp. 90—101. (In Russian).
  2. Kholod A. L. Overview of the Copernicus marine environment monitoring service products available for the Arctic region Physical Oceanography, 2017, no. 2, pp. 25—35.
  3. Chernov I. A., Tolstikov A. V., Yakovlev N. G. Kompleksnaya model’ Belogo morya: gidrotermodinamika vod i morskogo l’da. [Comprehensive model of the White Sea: hydrothermodynamics of water and sea ice]. Tr. KarNTs RAN, 2016, vol. 8, pp. 116—128. (In Russian).
  4. Gidrometeorologiya i gidrokhimiya morei SSSR. Vol. 4: Beloe more. Iss. 1: Gidrometeorologicheskie usloviya. [Hydrometeorology and hydrochemistry of seas of the USSR. The White Sea. Reference book “Seas of the USSR”]. Leningrad, Gidrometeoizdat, 1991, 196 p. (Spravochnik “Morya SSSR”). (In Russian).
  5. Ilyash L. V., Belevich T. A., Stupnikova A. N. et al. Effects of local hydrophysical conditions on the spatial variability of phytoplankton in the White Sea. Oceanology, 2015, vol. 55, no. 2, pp. 216—225.
  6. Shevchenko V. P., Starodymova D. P., Vinogradova A. A. et al. Elemental and organic carbon in atmospheric aerosols over the northwestern coast of Kandalaksha Bay of the White Sea. Doklady Earth Sciences, 2015, vol. 461, no. 1, pp. 242—246.
  7. Kobylyanskii S. G., Drits A. V., Mishin A. V. et al. Small scale distribution of the White sea herring larvae (Clupea pallasii marisalbi) in relation to hydrophysical feature. Oceanology, 2014, vol. 54, no. 6, pp 752—762.
  8. Zimin A. V., Atadzhanova O. A., Romanenkov D. A. et al. Submezomasshtabnye vikhri v Belom more po dannym sputnikovykh radiolokatsionnykh izmerenii. [Sub-Mesoscale Eddies in the White sea according to satellite radar measurements]. Issledovanie Zemli iz kosmosa, 2016, vol. 1—2, pp. 129—135. (In Russian).
  9. Tolstikov A. V., Filatov N. N., Zdorovennov R. E. The White Sea and its watershed. Database registration certificate no. 2010620435. 16 August 2010.
  10. Kaitala S., Shavykin A., Volkov V. Environmental GIS database for the White sea // Proceedings of the Open source GIS-GRASS users conference. — Trento, Italy, 2002.
  11. Nikiforov C. L., Koshel’ S. M., Frol’ V. V. Tsifrovaya model’ rel’efa dna Belogo morya. [Digital terrain model of the White Sea bottom]. Vestn. Mosk. un-ta, 2012, no. 3, pp. 86—92. (In Russian).
  12. Okeanograficheskie usloviya i biologicheskaya produktivnost’ Belogo morya: Annotirovannyi atlas. [Oceanographic Conditions and biological productivity of the White sea: Annotated atlas]. Murmansk, PINRO, 1991, 115 p. (In Russian).
  13. Biologicheskii atlas morei Arktiki 2000: Plankton Barentseva i Karskogo morei. [Biological Atlas of Arctic Seas 2000: Plankton of the Barents and Kara seas]. Pod red. G. G. Matishova, P. R. Makarevicha, S. F. Timofeeva et al. Murmansk, MMBI KNTs RAN, 2000. (In Russian).
  14. Final report of INCO-Copernicus Project “WHITESEA” № ICA2-CT-2000-10014: “Sustainable management of the marine ecosystem and living resources of the White Sea”. [S. l.], NERSC, 2003, 220 p.
  15. Klimaticheskii atlas morei Arktiki 2004: Chast’ Bazy dannykh Barentseva i Belogo morei — okeanografiya i morskaya biologiya. [Climate Atlas of the Arctic Seas 2004: A part of the database for the Barents and White seas — Oceanography and marine biology]. G. G. Matishov, A. N. Zuev, V. A. Golubev et al. Silver Spring, MD, 2004. (In Russian).
  16. Atlas biologicheskogo raznoobraziya morei i poberezhii rossiiskoi Arktiki. [Atlas of biodiversity of Russian arctic seas and coasts]. Pod red. V. A. Spiridonova, M. V. Gavrilo, E. D. Krasnova, N. G. Nikolaeva. Moscow, WWF Rossii, 2011, 64 p. (In Russian).
  17. Filatov N. N., Tolstikov A. V., Bogdanova M. S. et al. Sozdanie informatsionnoi sistemy i elektronnogo atlasa po ispol’zovaniyu resursov Belogo morya i ego vodosbora. [Development of an information system and electronic atlas for using resources of the White Sea and its watershed]. Arktika: ekologiya i ekonomika, 2014, no. 3 (15), pp. 18—29. (In Russian).
  18. Tolstikov A. V., Filatov N. N., Bogdanova M. S. et al. Electronic atlas of the White Sea and its watershed. Database registration certificate no. 2017620252, 1 March 2017. 2017.
  19. Spravochnye dannye po rezhimu vetra i volneniya Beringova i Belogo morei (elektronnyi analog pechatnogo izdaniya, utverzhdennogo 07.12.10): Otchet. [Reference data on wind and waves of the Bering and White seas (Electronic version of the printed edition, published 07.12.10): Report]. Ros. mor. registr sudokhodstva. St. Petersburg, 2010. (In Russian).
  20. Kravchishina M. D., Burenkov V. I., Kopelevich O. V. et al. New data on the spatial and temporal variability of the chlorophyll a concentration in the White sea. Doklady Earth Sciences, 2013, vol. 448, no. 1, pp 120—125.
  21. Marchuk G. I., Zalesnyi V. B. Modeling of the world ocean circulation with the four-dimensional assimilation of temperature and salinity fields. Izvestiya. Atmospheric and Oceanic Physics, 2012, vol. 48, no. 1, pp. 15—29.
  22. Beloe more i ego vodosbor pod vliyaniem klimaticheskikh i antropogennykh faktorov. [The White Sea and its watershed under influences of climate and anthropogenic impact]. Pod red. N. N. Filatova, A. Yu. Terzhevika. Petrozavodsk, Karel. nauch. tsentr RAN, 2007, 335 p. (In Russian).
  23. Semenov E. V. Chislennoe modelirovanie dinamiki Belogo morya i problema monitoring. [Numerical modelling of the White Sea dynamics and monitoring problem]. Izv. RAN. Ser. Fizika atmosfery i okeana, 2004, vol. 40, no. 1, pp. 128—141. (In Russian).
  24. Volzhenskii M. N., Rodionov A. A., Semenov E. V. et al. Opyt verifikatsii operativnoi modeli dlya monitoringa gidrofizicheskikh polei Belogo morya. [Experience of verification of an operational model for monitoring hydrophysical fields of the White Sea]. Fundament. i priklad. gidrofizika, 2009, vol. 2, no. 3, pp. 33—41. (In Russian).
  25. Yakovlev N. G. On the simulation of temperature and salinity fields in the Arctic Ocean. Izvestiya. Atmospheric and Oceanic Physics, 2012, vol. 48, no. 1, pp. 86–—101.
  26. Vichi M., Lovato T., Lazzari P. et al. The Biogeochemical Flux Model (BFM): Equation Description and User Manual. BFM version 5.1 BFM Consortium. [S. l.], 2015.
  27. Vichi M., Lovato T., Gutierrez Mlot E., McKiver W. Coupling BFM with Ocean models: the NEMO model (Nucleus for the European Modelling of the Ocean). BFM Consortium. [S. l.], 2015.
  28. Cossarini G., Querin S., Solidoro C. et al. Development of BFMCOUPLER (v1.0), the coupling scheme that links the MITgcm and BFM models for ocean biogeochemistry simulations. Geoscientific Model Development, 2017, vol. 10, pp. 1423—1445.

Download »

© 2011-2020 Arctic: ecology and economy
DOI 10.25283/2223-4594