Temporal Variability of the Wind Wave Parameters in the Baltic Sea in 1979–2018 Based on the Numerical Modeling Results

A. N. Sokolov1, 2, ✉, B. V. Chubarenko1

1 Shirshov Institute of Oceanology, Russian Academy of Sciences, Moscow, Russian Federation

2 Immanuel Kant Baltic Federal University, Kaliningrad, Russian Federation

✉ e-mail: tengritag@gmail.com

Abstract

Purpose. The aim of the paper is to identify possible trends in the wave climate dynamics in the Baltic Sea, and to analyze statistical significance of the coefficients of these trends based on the results of their numerical modeling for 1979–2018.

Methods and Results. The simulations for 1979–2018 (40 years) were carried out on an irregular grid using the MIKE 21 SW spectral wave model. The wind forcing was preset according to the ERA-Interim reanalysis data. The model was calibrated and validated against the data of wave buoys located in the northern and southern parts of the Baltic Sea. Based on the calibrated model, the wind wave parameters were calculated for the whole Baltic Sea area from 1979 to 2018 with the interval 1 hour. These parameters became the initial data for estimating temporal variability of the wind wave heights in the Baltic Sea for 40 years. The simulation results obtained on the irregular grid were interpolated to the regular one. It permitted to construct the maps of distribution of the maximum and average (for the 40-year period) significant wave heights in the Baltic Sea. The time trends for the average annual significant wave height values were revealed, and statistical significance of the coefficients of these trends was estimated.

Conclusions. The average annual values of the significant wave heights over almost the whole Baltic Sea area for 1979–2018 (40 years) tend to decrease with the rate not exceeding 2–3 cm (~2–3 %) per 10 years. The highest rate reduction is observed in the southeastern part of the Baltic Sea, the lowest – in the Gulf of Bothnia and the Gulf of Finland. Interannual variability of the average annual significant wave heights and the changes along the trend during the entire 40-years period are of the same order.

Keywords

Baltic Sea, wind waves, temporal variability, numerical simulation

Acknowledgements

The work was carried out within the framework of theme No. 0149-2019-0013 of the State Assignment of IO RAS and with the RFBR support, grant No. 18-05-80035 (methodological part).

Original russian text

Original Russian Text © A. N. Sokolov, B. V. Chubarenko, 2020, published in MORSKOY GIDROFIZICHESKIY ZHURNAL, Vol. 36, Iss. 4, pp. 383–395 (2020)

For citation

Sokolov, A.N. and Chubarenko, B.V., 2020. Temporal Variability of the Wind Wave Parameters in the Baltic Sea in 1979–2018 Based on the Numerical Modeling Results. Physical Oceanography, 27(4), pp. 352-363. doi:10.22449/1573-160X-2020-4-352-363

DOI

10.22449/1573-160X-2020-4-352-363

References

  1. Broman, B., Hammarklint, T., Rannat, K., Soomere, T. and Valdmann, A., 2006. Trends and Extremes of Wave Fields in the North-Eastern Part of the Baltic Proper. Oceanologia, 48(S), pp. 165-184. Available at: https://www.etis.ee/File/DownloadPublic/942d20a6-1b59-40f6-a000-45bd8a3c504c?name=Fail_Oceanologia_2006_Broman_etal.pdf&type=application%2Fpdf [Accessed: 03 July 2020].
  2. Cieślikiewicz, W. and Paplińska-Swerpel, B., 2008. A 44-year Hindcast of Wind Wave Fields over the Baltic Sea. Coastal Engineering, 55(11), pp. 894-905. https://doi.org/10.1016/j.coastaleng.2008.02.017
  3. Medvedeva, A.Yu., Arkhipkin, V.S., Myslenkov, S.A. and Zilitinkevich, S.S., 2015. Wave Climate of the Baltic Sea Following the Results of the Swan Spectral Model Application. Vestnik Moskovskogo Universiteta. Seriya 5, Geografiya, (1), pp. 12-22 (in Russian).
  4. Björkqvist, J.-V., Lukas, I., Alari, V., van Vledder, G.Ph., Hulst, E., Pettersson, H., Behrens, A. and Männik, A., 2018. Comparing a 41-year Model Hindcast with Decades of Wave Measurements from the Baltic Sea. Ocean Engineering, 152, pp. 57-71. https://doi.org/10.1016/j.oceaneng.2018.01.048
  5. Soomere, T. and Räämet, A., 2011. Spatial Patterns of the Wave Climate in the Baltic Proper and the Gulf of Finland. Oceanologia, 53(1-TI), pp. 335-371. Available at: https://www.iopan.pl/oceanologia/531Tsoom.pdf [Accessed: 03 July 2020].
  6. Soomere, T. and Räämet, A., 2011. Long-Term Spatial Variations in the Baltic Sea Wave Fields. Ocean Science, 7(1), pp. 141-150. doi:10.5194/os-7-141-2011
  7. Drabkin, V.V., Fokina, M.L., Klyachkin, S.V. and Gasnikova, N.V., 1992. [Ice Regime of the Baltic Sea]. In: F. S. Terziyeva, V. A. Rozhkova, A. I. Smirnovoy, eds., 1992. [Hydrometeorology and Hydrochemistry of the USSR Seas. Vol. 3. Baltic Sea. Issue 1. Hydrometeorological Conditions]. Saint Petersburg: Gidrometeoizdat. Chapter 4.6, pp. 320-329 (in Russian).
  8. Divinsky, B.V. and Kosyan, R.D., 2017. Spatiotemporal Variability of the Black Sea Wave Climate in the Last 37 years. Continental Shelf Research, 136, pp. 1-19. https://doi.org/10.1016/j.csr.2017.01.008
  9. DHI, 2007. MIKE 21 Wave Modelling. MIKE 21 Spectral Waves FM: Short description. Horsholm: DHI, 14 p. Available at: https://www.mikepoweredbydhi.com/-/media/shared%20content/mike%20by%20dhi/flyers%20and%20pdf/product-documentation/short%20descriptions/mike21_sw_fm_short_description.pdf [Accessed: 03 July 2020].
  10. Sokolov, A.N. and Chubarenko, B.V., 2014. Sensitivity Analysis for Wave Regime in Wave-Deformation Zone in the South-Eastern Baltic in a View of Possible Climate Changes. KSTU News, (34), pp. 43-51. Available at: http://klgtu.ru/upload/science/magazine/news_kstu/2014_34/sokolov.pdf [Accessed: 06 July 2020] (in Russian).
  11. Sokolov, A. and Chubarenko, B., 2018. Numerical Simulation of Dynamics of Sediments Disposed in the Marine Coastal Zone of the South-Eastern Baltic. Baltica, 31(1), pp. 13-23. https://doi.org/10.5200/baltica.2018.31.02
  12. Draper, N.R. and Smith, H., 1981. Applied Regression Analysis. 2-nd ed. New York: John Wiley and Sons, 709 p.
  13. Pakhteev, A. and Stepanov, A., 2019. On Simulation of Normal Records. Communications in Statistics - Simulation and Computation, 48(8), pp. 2413-2424. doi:10.1080/03610918.2018.1457692

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