Trend analysis of spectral peak wave energy on the Black Sea

In this study, it was aimed to investigate the trends of the spectral peak energy and peak period of the waves and the long-term annual, seasonal and monthly average and maximum values by analyzing the wave conditions in the Black Sea. In this context, the outputs of the SWAN third generation wave prediction model and the wave spectra covering the years 1979-2020 of the ERA5 reanalysis were used as the data set to which the trend analysis will be applied. From the outputs of the SWAN wave model and the ERA5 reanalysis data set, data were captured and processed at 36 and 876 stations, respectively, selected on the Black Sea. Hourly spectral peak energy and peak period data were extracted by processing the wave spectra drawn from the data sets over a 42-year period. Then, the mean and maximum values of these parameters on annual, seasonal and monthly time scales were calculated. As the last step, Mann-Kendall and Improved Visualization of Innovative Trend Analysis tests were applied to four parameters in three different time scales. Thus, trend results were examined in a holistically with Mann-Kendall and in sub-categories with innovative method, and it was possible to compare the trend analysis results of regional and global data sets. As a result, , it was determined that the spectral peak energy is increasing in the spring and summer seasons, January, March, April, August and September, and decreasing in the winter and autumn seasons and May, July, November and December in both models. In addition, peak periods show an increasing trend in almost all time scales, and a decreasing trend in autumn season and May and November. The results obtained from the SWAN wave prediction model and ERA5 reanalysis data were found to be similar for both parameters. However, a decreasing trend was determined by the SWAN model in regions where the peak periods showed an increasing trend with ERA5 in the winter and autumn months and on an annual scale. Considering the confidence level in the Mann-Kendall test and the rate of change in the innovative method, it was seen that increasing trends were more severe than decreasing trends.