Kuzey Atlantik Salınımı ve Güney Salınım İndeksi İklim Göstergelerinin Sinyal Analizi Yöntemleri İle İncelenmesi
Özet
Climate is expressed as the typical trends of meteorological events such as temperature, humidity, air pressure, amount of precipitation, type of precipitation and wind speed observed over a long period of time in a particular area. Accordingly, the climate system of the world controls the distribution of wind, rain, and temperature of a region by the natural forces of the atmosphere and oceans. When the climate system is considered, it is not a static system, but it is a dynamic system that changes due to various factors over time and this fluctuation affects all the environment and living creature on earth. Changes in climate system are described with climate index. Climate indexes are daily, monthly, yearly time series and consist of parameters such as air pressure, air temperature, precipitation, solar radiation, sea surface temperature. In this thesis, two different climate motions occurring in the North Atlantic Ocean and South Pacific Ocean are investigated, their effects on the earth that are periodic or intermittent are searched. To determine the characteristic of climatic activity in the North Atlantic Ocean, the North Atlantic Oscillation (NAO) climate index that is air pressure index is examined. To determine the characteristic of climatic activity in the South Pacific Ocean, the Southern Oscillation Index (SOI) which is air pressure index is examined. In addition, to examine the effect of radiation from the Sun on climate events in the Earth, Sunspot Number (SSN) climate index is also examined.
In the first stage of thesis, periods of data sets of NAO, SOI and Sunspot Number are determined by separately. For determining periods of data sets, autocorrelation method, periodogram analysis, modified periodogram analysis, and Welch’s method are used. Moreover, the relationship between climate indicators is investigated by using cross correlation method. Afterwards, time-frequency transform analysis of data sets of NAO, SOI and Sunspot Number are examined by using Wigner-Ville Transformation (WVD). Thus, it is possible to observe the signal simultaneously in both time and frequency domain. The correlation between climate indicators is investigated in the time-frequency domain by using the Cross Wigner-Ville Transformation (XWVD) method. In the last part of thesis, a dynamic system model between Sunspot Number, NAO and SOI climate indexes is defined by using Canonical Correlation Analysis method. Thus, the relationship between climatic movements is tried to be modeled. As a result of the analyses, climatic movements in the North Atlantic Ocean and the South Pacific Ocean are tried to characterize and effects of these movements on the Earth are examined.
As a result of the period analysis, it is observed that most of the dominant periods observed in North Atlantic Oscillation and South Oscillation are common periods. In addition, it is determined that the all periods in the two oscillations are within the periods of the Sunspot data set. In cross-analysis results, it is observed that the climatic movements in the North Atlantic Ocean and the South Pacific Ocean are related to each other. As a result of the cross-correlation analysis performed with the Sunspot data set, it is observed that the Sun is effective on two oscillations. It is obtained as an important result of the thesis study that the Sun is a fundamental phenomenon affecting the two oscillations. As a result of the Wigner-Ville Transformation of the Sunspot Number data set, it is observed that the energy density on the solar surface increases and decreases periodically. As a result of the Wigner-Ville Transformation of the North Atlantic Oscillation data set, it is determined that dates with high energy density correspond to strong North Atlantic Oscillation phases. As a result of the Wigner-Ville Transformation of the South Oscillation Index data set, it is observed that the dates with high energy density correspond to important El-Niño and La-Niña phases that affect the Earth climate.
