Skewness and Kurtosis of the Surface Wave in the Coastal Zone of the Black Sea

A. S. Zapevalov, A. V. Garmashov

Marine Hydrophysical Institute, Russian Academy of Sciences, Sevastopol, Russian Federation

e-mail: sevzepter@mail.ru

Abstract

Purpose. The aim of the study is to analyze variability of the statistical moments characterizing deviations of the sea surface elevation distributions from the Gaussian.

Methods and Results. Field studies of the sea waves’ characteristics were carried out from the stationary oceanographic platform located in the Black Sea near the Southern coast of Crimea. The data obtained both in summer and winter, were used. The statistical moments were calculated separately for wind waves and swell. The measurements were performed in a wide range of meteorological conditions and wave parameters (wind speed varied from 0 to 26 m/s, wave age – from 0 to 5.2 and steepness – from 0.005 to 0.095). For wind waves, the coefficients of skewness correlation with the waves’ steepness and age were equal to 0.46 and 0.38. The kurtosis correlation coefficients with these parameters were small (0.09 and 0.07), but with the confidence level 99.8% – significant. For swell, the correlation coefficients were 1.5 – 2.0 times lower.

Conclusions. The statistical moments of the sea surface elevations of the third and higher orders are the indicators of the wave field nonlinearity, which should be taken into account when solving a wide range of the applied and fundamental problems. The deviations of the surface elevation distributions from the Gaussian one are not described unambiguously by the steepness and wave age. At the fixed values of these parameters, a large scatter in the skewness and kurtosis of the surface elevations is observed. This imposes significant limitations on the possibility of applying the nonlinear wave models based on the wave profile expansion by small parameter (steepness) degrees, in engineering calculations.

Keywords

sea surface, wind waves, swells, skewness, kurtosis, stationary oceanographic platform, Black Sea

Acknowledgements

The investigation was carried out within the framework of the state task on theme No. 0555-2021-0004 “Fundamental studies of the oceanological processes which determine the state and evolution of the marine environment influenced by natural and anthropogenic factors, based on the observation and modeling methods”.

Original russian text

Original Russian Text © A. S. Zapevalov, A. V. Garmashov, 2021, published in MORSKOY GIDROFIZICHESKIY ZHURNAL, Vol. 37, Iss. 4, pp. 447-459 (2021)

For citation

Zapevalov, A.S. and Garmashov, A.V., 2021. Skewness and Kurtosis of the Surface Wave in the Coastal Zone of the Black Sea. Physical Oceanography, 28(4), pp. 414-425. doi:10.22449/1573-160X-2021-4-414-425

DOI

10.22449/1573-160X-2021-4-414-425

References

  1. Taklo, T.M.A., Trulsen, K., Gramstad, O., Krogstad, H.E. and Jensen, A., 2015. Measurement of the Dispersion Relation for Random Surface Gravity Waves. Journal of Fluid Mechanics, 766, pp. 326-336. https://doi.org/10.1017/jfm.2015.25
  2. Longuet-Higgins, M.S., 1963. The Effect of Non-Linearities on Statistical Distribution in the Theory of Sea Waves. Journal of Fluid Mechanics, 17(3), pp. 459-480. https://doi.org/10.1017/S0022112063001452
  3. Phillips, О.М., 1961. On the Dynamics of Unsteady Gravity Waves of Finite Amplitude. Part 2. Local Properties of a Random Wave Field. Journal of Fluid Mechanics, 11(1), pp. 143-155. https://doi.org/10.1017/S0022112061000913
  4. Socquet-Juglard, H., Dysthe, K., Trulsen, K., Krogstad, H.E. and Liu, J., 2005. Probability Distributions of Surface Gravity Waves during Spectral Changes. Journal of Fluid Mechanics, 542, pp. 195-216. https://doi.org/10.1017/S0022112005006312
  5. Babanin, A.V. and Polnikov, V.G., 1995. On the Non-Gaussian Nature of Wind Waves. Physical Oceanography, 6(3), pp. 241-245. https://doi.org/10.1007/BF02197522
  6. Zapevalov, A.S., Bol’shakov, A.N. and Smolov, V.E., 2011. Simulating of the Probability Density of Sea Surface Elevations Using the Gram–Charlier Series. Oceanology, 51(3), pp. 407-414. doi:10.1134/S0001437011030222
  7. Song, J.-B., Wu, Y.-H. and Wiwatanapataphee, B., 2000. Probability Distribution of Random Wave Forces in Weakly Nonlinear Random Waves. Ocean Engineering, 27(12), pp. 1391- 1405. doi:10.1016/s0029-8018(99)00067-0
  8. Agarwal, P. and Manuel, L., 2009. On the Modeling of Nonlinear Waves for Prediction of Long-Term Offshore Wind Turbine Loads. Journal of Offshore Mechanics and Arctic Engineering, 131(4), 041601. doi:10.1115/1.3160647
  9. Xiao, W., Liu, Y., Wu, G. and Yue, D.K.P., 2013. Rogue Wave Occurrence and Dynamics by Direct Simulations of Nonlinear Wave-Field Evolution. Journal of Fluid Mechanics, 720, pp. 357-392. doi:10.1017/jfm.2013.37
  10. Luxmoore, J., Ilic, S., and Mori, N., 2019. On Kurtosis and Extreme Waves in Crossing Directional Seas: A Laboratory Experiment. Journal of Fluid Mechanics, 876, pp. 792-817. doi:10.1017/jfm.2019.575
  11. Gómez-Enri, J., Gommenginger, C.P., Challenor, P.G., Srokosz, M.A. and Drinkwater, M.R., 2006. ENVISAT Radar Altimeter Tracker Bias. Marine Geodesy, 29(1), pp. 19-38. https://doi.org/10.1080/01490410600582296
  12. Zapevalov, A.S., 2012. Effect of Skewness and Kurtosis of Sea-Surface Elevations on the Accuracy of Altimetry Surface Level Measurements. Izvestiya, Atmospheric and Oceanic Physics, 48(2), pp. 200-206. https://doi.org/10.1134/S0001433812020120
  13. Janssen, P.A.E.M., 2003. Nonlinear Four-Wave Interactions and Freak Waves. Journal of Physical Oceanography, 33(4), pp. 863-884. https://doi.org/10.1175/1520- 0485(2003)33%3C863:NFIAFW%3E2.0.CO;2
  14. Gao, Z., Sun, Z. and Liang, S., 2020. Probability Density Function for Wave Elevation Based on Gaussian Mixture Models. Ocean Engineering, 213, 107815. https://doi.org/10.1016/j.oceaneng.2020.107815
  15. Zapevalov, A.S. and Ratner, Yu.B., 2003. Analytic Model of the Probability Density of Slopes of the Sea Surface. Physical Oceanography, 13(1), pp. 1-13. doi:10.1023/A:1022444703787
  16. Jha, A.K. and Winterstein, S.R., 2000. Nonlinear Random Ocean Waves: Prediction and Comparison with Data. In: ASME, 2000. Proceedings of ETCE/OMAE2000 Joint Conference Energy for the New Millenium, February 14-17, 2000, New Orleans, LA, USA. New Orleans, USA, 2000. ETCE/OMAE 2000-6125. Available at: https://www.tamug.edu/sweetman/RMS_Papers/pdf/alok/6125.pdf [Accessed: 31 August 2021].
  17. Huang, N. and Long, S., 1980. An Experimental Study of the Surface Elevation Probability Distribution and Statistics of Wind-Generated Waves. Journal of Fluid Mechanics, 101(1), pp. 179-200. doi:10.1017/S0022112080001590
  18. Yijun, H., Guiting, S., Xixi, Z., Jinbao, S. and Quan'an, Z., 2006. Statistical Distribution of Nonlinear Random Water Wave Surface Elevation. Chinese Journal of Oceanology and Limnology, 24(1), pp. 1-5. doi:10.1007/BF02842767
  19. Tayfun, M.A. and Alkhalidi, M.A., 2016. Distribution of Surface Elevations in Nonlinear Seas. In: OTC, 2016. Offshore Technology Conference Asia: proceedings. Kuala Lumpur, Malaysia. OTC-26436-MS. doi:10.4043/26436-MS
  20. Efimov, V.V. and Komarovskaya, O.I., 2019. Disturbances in the Wind Speed Fields due to the Crimean Mountains. Physical Oceanography, 26(2), pp. 123-134. doi:10.22449/1573- 160X-2019-2-123-134
  21. Solov'ev, Yu.P. and Ivanov, V.A., 2007. Preliminary Results of Measurements of Atmospheric Turbulence over the Sea. Physical Oceanography, 17(3), pp. 154-172. https://doi.org/10.1007/s11110-007-0013-9
  22. Soloviev, Yu.P., 2013. Measurements of the Atmospheric Turbulence in the Coastal Zone of the Sea during Weak Wind from a Mountainous Coast. Izvestiya, Atmospheric and Oceanic Physics, 49(3), pp. 315-328. doi:10.1134/S0001433813030146
  23. Cavaleri, L., Abdalla, S., Benetazzo, A., Bertotti, L., Bidlot, J.-R., Breivik, Ø., Carniel, S., Jensen, R.E. and Portilla-Yandun, J. [et al.], 2018. Wave Modelling in Coastal and Inner Seas. Progress in Oceanography, 167, pp. 164-233. doi:10.1016/j.pocean.2018.03.010
  24. Toloknov, Yu.N., Korovushkin, A.I., 2010. [Hydrometeorological Information Collection System]. In: MHI, 2010. Monitoring Systems of Environment. Sevastopol: MHI. Iss. 13, pp. 50-53 (in Russian).
  25. Thomas, B.R., Kent, E.C. and Swail, V.R., 2005. Methods to Homogenize Wind Speeds from Ships and Buoys. International Journal of Climatology, 25(7), pp. 979-995. https://doi.org/10.1002/joc.1176
  26. Donelan, M.A., Hamilton, J. and Hui, W.H., 1985. Directional Spectra of Wind-Generated Ocean Waves. Philosophical Transactions of the Royal Society of London. Series A, Mathematical and Physical Sciences, 315(1534), pp. 509-562. https://doi.org/10.1098/rsta.1985.0054
  27. Young, I.R. and Donelan, M.A., 2018. On the Determination of Global Ocean Wind and Wave Climate from Satellite Observations. Remote Sensing of Environment, 215, pp. 228- 241. doi:10.1016/j.rse.2018.06.006

Download the article (PDF)