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Home » Archive of journals » Volume 16, No. 1, 2026 » Spatiotemporal variability study of extreme wind waves in the central part of the Barents Sea SPATIOTEMPORAL VARIABILITY STUDY OF EXTREME WIND WAVES IN THE CENTRAL PART OF THE BARENTS SEAJOURNAL: Volume 16, No. 1, 2026, p. 28-39HEADING: Research activities in the Arctic AUTHORS: Chumakov, M.M., Shushpannikov, P.S., Fomin, V.V., Panasenkova, I.I., Nuriyev, M.F., Diansky, N.A. ORGANIZATIONS: Lomonosov Moscow State University, N. N. Zubov’s State Oceanographic Institute, Gazprom VNIIGAZ LLC, PJSC Gazprom DOI: 10.25283/2223-4594-2026-1-28-39 UDC: ÓÄÊ 551.466.3 The article was received on: 19.03.2025 Keywords: Barents sea, retrospective modeling, intense cyclones, storm waves, Mann-Kendall test, Theil-Sen elevation function Bibliographic description: Chumakov, M.M., Shushpannikov, P.S., Fomin, V.V., Panasenkova, I.I., Nuriyev, M.F., Diansky, N.A. Spatiotemporal variability study of extreme wind waves in the central part of the Barents Sea. Arktika: ekologiya i ekonomika. [Arctic: Ecology and Economy], 2026, vol. 16, no. 1, pp. 28-39. DOI: 10.25283/2223-4594-2026-1-28-39. (In Russian). Abstract: Based on the results of retrospective wave modeling conducted for the Barents Sea from 1981 to 2022, the authors analyzed extreme wave characteristics for the central part of the Barents Sea using the SWAN model. The spatial resolution of the SWAN model in the central part of the Barents Sea was 1 km, and 3.5 km on its periphery. References: 1. Barents Sea: Ecological atlas. Moscow, Fund “National Intellectual Development”, 2020, 447 p. (In Russian). 2. Myslenkov S. A., Markina M. Yu., Arkhipkin V. S., Tilinina N. D. Frequency of storms in the Barents Sea under modern climate conditions. Vestnik Moskovskogo universiteta. Seriya 5, Geografiya, 2019, no. 2, pp. 45—54. (In Russian). 3. 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Distributed by OpenTopography. Available at: https://doi.org/10.5069/G9D21VTT. 20. Panasenkova I. I., Fomin V. V., Diansky N. A. Reproduction of hydrothermodynamic characteristics of the Russian Western Arctic Seas with assimilation of sea surface temperature and sea ice concentration data. Moscow University Physics Bulletin, 2025, Iss. 2. In print. 21. Diansky N. A., Fomin V. V., Kabatchenko I. M., Gruzinov V. M. Simulation of circulation of the Kara and Pechora Seas through the system of express diagnosis and prognosis of marine dynamics. Arctic: Ecology and Economy, 2014, no. 1 (13), pp. 57—73. (In Russian). 22. Fomin V. V., Panasenkova I. I., Gusev A. V., Chaplygin A. V., Diansky N. A. Operational forecasting system for Arctic Ocean using the Russian marine circulation model INMOM-Arctic. Arctic: Ecology and Economy, 2021, vol. 11, no. 2, ðð. 205—218. DOI: 10.25283/2223-4594-2021-2-205-218. (In Russian). 23. Stoll P. J. A global climatology of polar lows investigated for local differences and wind-shear environments. Weather and Climate Dynamics, 2022, vol. 3 (2), pp. 483—504. DOI: 10.5194/wcd-3-483-2022. 24. Guide to Hydrological Practices. Vol. II. Management of Water Resources and Application of Hydrological Practices. Sixth edition, 2009, 302 p. WMO No. 168. Available at: https://www.hydrology.nl/images/docs/hwrp/WMO_Guide_168_Vol_II_en.pdf. 25. Yue S., Pilon P. A comparison of the power of the t test, Mann-Kendall and bootstrap tests for trend detection. Hydrological Sciences, 2004, vol. 49 (1), pp. 21—37. 26. Sen P. K. Estimates of the regression coefficient based on Kendall’s tau. J. of the American Statistical Association, 1968, vol. 63, pp. 1379—1389. Download » | ||||
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DOI 10.25283/2223-4594
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