Pasifik Okyanusu dalga iklimi değişkenliğine büyük ölçekli iklim indislerinin etkisinin değerlendirilmesi

Wave variability and connections with climate indices were analyzed in the Pacific Ocean. Monthly significant wave data from five stations were used. The dominant modes of significant wave height variability were determined by continuous wavelet transform. The wave climate variability along with large scale climate indices was investigated at 5 buoy stations located in the Pacific Ocean. The monthly mean values of 𝐻𝑠 indicates that the summer seasons have the lower wave height and the winter season have the higher wave height. The trend test analysis on both significant wave heights 𝐻𝑠 and climate indices by using the XLSTAT software and Mann-Kendall trend test method demonstrated that there is no trend in buoy stations and the indices of Niño 3.4, PNA, MEI, PDO, except SOI that there is a significant increasing in this index. In the monthly correlation between significant wave heights and climate indices it is found that, there is weak correlations between significant wave height and MEI index with a correlation coefficient of r = 0.32 in the Santa Maria region (46011) and with a correlation coefficient of r = 0.31 in the Papa region (46006). Also, there is weak correlation between 𝐻𝑠 and PNA index with a correlation ceofficent of r = 0.43 in the buoy (46011) which is located in the region of Papa. The cross correlation analysis also is done over the data and it is figured out that there is a strong correlation between climate waves and climate indices in compare of normal correlation. The wavelet power spectrum was determined from the data of length of 38, 37, 36, 32, and 18 years in buoys 46002, 46005, 46006, 46011, and 46059, respectively. This analysis illustrated that there is a significant power at annual scale during whole measurement period of significant wave height in 4 stations. And, also in 46011, there is a significant power at annual scale during the whole measurement period of significant wave height except between 1989-1991 years. Furthermore, the power spectrum analysis illustrated that there is an annual cycle in stations and climate indices. Cross-wavelet power spectrum is used to measure the relationship between two time series. This spectrum was employed to explore the possible effects of ENSO events on the wave climate variation. The results of the cross-wavelet transform analysis in this study demonstrated that there is anti-phase behavior between the significant wave heights and climate indices in 46002 and 46011 buoys. Also, it is found that wave climate variabilites have in-phase behavior with PDO index in 46005, and in-phase behavior with SOI in 46006 and 46059.