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Języki publikacji
Abstrakty
The main objective of our work is to estimate the climatic peculiarities of the distribution of wind sea and swell in the Black Sea. The method of our research is numerical modeling. We tuned the spectral wave model DHI MIKE 21 SW for automatic separation of the components of surface waves. We estimated the peculiarities of the spatial distribution of the power of wind seas and swell in the basin of the Black Sea in the last 10 years (2007-2016). We determined the regions of domination of wind seas and swell in the field of mixed waves.
Czasopismo
Rocznik
Tom
Strony
277--287
Opis fizyczny
Bibliogr. 22 poz., mapy, rys., tab., wykr.
Twórcy
autor
- Shirshov Institute of Oceanology, Russian Academy of Sciences, Gelendzhik, Russia
autor
- Shirshov Institute of Oceanology, Russian Academy of Sciences, Gelendzhik, Russia
Bibliografia
- [1] Berkün, U., 2007. Wind and swell wave climate for the Southern Part of Black Sea. (Thesis). Graduate School of Natural and Applied Sciences of Middle East Technical University, Ankara, Turkey, 141 pp.
- [2] Bidlot, J.-R., 2001. ECMWF wave model products. In: ECMWF Newsletter, No. 91, ECMWF, Reading, United Kingdom, 9-15.
- [3] Bitner-Gregersen, E. M., 2015. Joint met-ocean description for design and operations of marine structures. Appl. Ocean Res. 51, 279-292, http://dx.doi.org/10.1016/j.apor.2015.01.007.
- [4] Boukhanovsky, A. V., Lopatoukhin, L. I., 2015. Storms statistics at sea (alternative approach). Fundamentalnaya i prikladnaya gidrofizika 8 (4), 86-94, (in Russian).
- [5] Boyle, G., 2004. Renewable Energy: Power for a Sustainable Future, 2nd ed. Oxford Univ. Press, 464 pp.
- [6] Bukhanovsky, A. V., Lopatukhin, L. I., Rozhkov, V. A., Divinsky, B. V., Kos'yan, R. D., 2000. Typification of instrumentally measured wind waves in the Black Sea. Oceanology (Engl. Transl.) 40 (2), 267-275.
- [7] Chong, W. Z., Chong, Y. L., 2017. Analysis of temporal and spatial characteristics of waves in the Indian Ocean based on ERA-40 wave reanalysis. Appl. Ocean Res. 63, 217-228, http://dx.doi.org/10.1016/j.apor.2017.01.014.
- [8] Christie, D., Vögler, A., Morrison, J., Greenwood, C., Venugopal, V., Topper, M., 2014. The Hebridean wave model. In: Proc. of the 2nd International Conference on Environmental Interactions of Marine Renewable Energy Technologies (EIMR2014), 28 April-02 May, Stornoway, Isle of Lewis, Outer Hebrides, Scotland.
- [9] Dee, D., Uppala, S., Simmons, A., Berrisford, P., Poli, P., Kobayashi, S., et al., 2011. The ERA Interim reanalysis: configuration and performance of the data assimilation system. Q. J. R. Meteorol. Soc. 137 (656), 553-597, http://dx.doi.org/10.1002/qj.828.
- [10] Divinsky, B., Kosyan, R., 2017. Spatiotemporal variability of the Black Sea wave climate in the last 37 years. Cont. Shelf Res. 136, 1-19, http://dx.doi.org/10.1016/j.csr.2017.01.008.
- [11] Ewans, K. C., Bitner-Gregersen, E. M., Guedes Soares, C., 2006. Estimation of wind-sea and swell components in a bimodal sea state. J. Offshore Mech. Arctic Eng. 128 (4), 265-270, http://dx.doi.org/10.1115/1.2166655.
- [12] Kaiwen, Z., Jian, S., Changlong, G., Weizeng, S., 2015. Analysis of the global swell and wind sea energy distribution using WAVE-WATCH III. Adv. Meteorol. 2016, http://dx.doi.org/10.1155/2016/8419580 8419580, 9 pp.
- [13] Kos'yan, R. D., Divinsky, B. V., Pushkarev, O. V., 1998. Measurements of parameters of wave processes in the open sea near Gelendzhik. In: The Eighth Workshop of NATO TU-WAVES/Black Sea, METU, Ankara, Turkey, 5-6.
- [14] Loffredo, L., Monbaliu, J., Bitner-Gregersen, E., Toffoli, A., 2009. The role of spectral multimodality in wave climate design. In: 11th International Workshop on Wave Hindcasting and Forecasting and Coastal Hazard Symposium, Halifax, Canada, October 18-23, 2009, 18-23.
- [15] Pierson Jr., W. J., Moskowitz, L., 1964. A proposed spectral form for fully developed wind seas based on the similarity theory of S. A. Kitaigorodskii. J. Geophys. Res. 69 (24), 5181-5190.
- [16] Portilla, J.,Ocampo-Torres, F.,Monbaliu, J.,2009.Spectralpartitioning and identification of wind sea and swell. J. Atmos. Ocean. Technol. 26, 107-122, http://dx.doi.org/10.1175/2008JTECHO609.1.
- [17] Portilla, J., Caicedo, A., Padilla-Hernández, R., Cavalerie, L., 2015. Spectral wave conditions in the Colombian Pacific Ocean. Ocean Model. 92, 149-168, http://dx.doi.org/10.1016/j.oce-mod.2015.06.005.
- [18] Semedo, A., Suselj, K., Rutgersson, A., Sterl, A., 2011. A global view on the wind sea and swell climate and variability from ERA-40. J. Climate 24 (5), 1461-1479, http://dx.doi.org/10.1175/2010JCLI3718.1.
- [19] Siadatmousavi, S., Jose, F., Stone, G., 2011. Evaluation of two WAM white capping parameterizations using parallel unstructured SWAN with application to the Northern 42 Gulf of Mexico, USA. Appl. Ocean Res. 33 (1), 23-30, http://dx.doi.org/10.1016/j.apor.2010.12.002.
- [20] US Army Corps of Engineers, 2002. Coastal Engineering Manual. Engineer Manual 1110-2-1100, vol. 6. U.S. Army Corps of Engineers, Washington, D.C.
- [21] Van Vledder, G., Akpinar, A., 2016. The swell climate in the black sea. In: The 35th Inernational Conference on Coastal Engineering, ICCE, Antalya, Turkey, 17-20 November, 2016.
- [22] Wang, D., Hwang, P., 2001. An operational method for separating wind sea and swell from ocean wave spectra. J. Atmos. Ocean. Technol. 18 (12), 2052-2062.
Uwagi
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-6f029757-0ffd-4cd5-8fa7-5a03f0128e3c