Non-stationary statistical estimation of wind speeds of rare recurrence in the Azov and Black Sea region

V.P. Evstigneev 1, 2, V.A. Naumova1, 2, N.A. Lemeshko3

 1Sevastopol State University, RF, Sevastopol, Universitetskaya St., 33

2Institute of Natural and Technical Systems, RF, Sevastopol, Lenin St., 28

3Saint-Petersburg State University, RF, Saint-Petersburg, Universitetskaya Emb., 7

E-mail: vald_e@rambler.ru

DOI: 10.33075/2220-5861-2021-3-15-22

UDC 551.582.2+551.55

Abstract:

   In the paper statistical distribution of the highest wind speed per year in the Azov and Black Sea region was analyzed using data of 33 meteorological stations for 1958-2013. A statistical estimation of the wind speed extremes was carried out by approximation of the empirical sample with a function of Generalized distribution of Extreme Values (GEV) and by extrapolating it to the low probabilities’ region. We used two methodologies and applied statistical distribution functions corresponding to them. The first method is based on the assumption of stationarity of GEV function parameters. The second one is based on the non-stationary assumption of time dependence of extremum localization parameter μ.

   The results of this work indicate that, for at least 13 out of 33 stations in the Azov-Black Sea region the distribution of the highest wind speeds is significantly affected by climatic non-stationarity of wind data series. The use of stationary estimates of wind speeds will create difficulties in engineering design of construction objects in the vicinity of these stations. For example, according to the current building standards, when calculating normative wind load on buildings, it is required to calculate mean velocity value corresponded to 50-year recurrence rate. The reliability of the calculation depends on the presence of non-stationarity in the time series. Thus, a pronounced trend and climate-driven long-period variations in climatic series create an urgent need to take them into account in climatic support of construction on land and offshore operations in the coastal zone as well as in the analysis of risks and probable damage from dangerous hydrometeorological events.

Keywords: wind speed, extreme values distribution function, extremum, non-stationarity of time series, climate change.

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