WAVELET ANALYSIS OF THE El NIÑO - LA NIÑA PHENOMENON DYNAMICS AND ITS FORECASTING

Abstract

Having calculated the frequency content of a solar constant, solar activity from the time series in (1610-2012), the El Niño curve in both (1470-1984) and (1950-2075), it has been found that the frequency content of an El Niño - La Niña curve is induced by frequency contents of solar variables. The frequency contents of the variables have been calculated by developing their wavelet phase-frequency responses. Instantaneous phase differences of the solar variables curves CO2(t), global surface air temperature, El Niño in the two time intervals, in (1891-1950) and (1950-2009), have been calculated; linear approximations with coefficients of instantaneous phase differences between variables in these time intervals have been obtained. Based on relational approximation coefficient analysis of the two time intervals, it has been identified that rising surface air temperature and El Niño alike had been markedly influenced by solar variables variations during the first time interval, with the El Niño rise being affected by that of the surface air temperature amid the global climate change in 1950-2009. The predicted El Niño curves have been obtained from the 2015/16 to 2050 time period by the trained data curve in 1950-2015/16 in two versions as the sum of predicted wavelet approximating and detailing components of the original signal according to the Mallat rule. The accuracy of the predictive El Niño curve values is » 83%. On the obtained curves, coordinates of local maximum and minimum are nearly matching. Wavelet phase-frequency response imaging of one curve reflects an impact on El Niño - La Niña variations of the Earth's solar and climatic variables in the past and the future alike.