DIAGNOSTIC PREDICTIONS OF SST IN THE EQUATORIAL EASTERN PACIFIC OCEAN BASED ON FUZZY INFERRING AND WAVELETDECOMPOSITION

Abstract:

Methods and approaches are discussed that identify and filter off affecting factors (noise) above primary signals,based on the Adaptive-Nework-Based Fuzzy Inference System. Influences of the zonal winds in equatorial eastern and middle/western Pacific on the SSTA in the equatorial region and their contribution to the latter are diagnosed and verified with observations of a number of significant El Nino and La Nina episodes. New viewpoints are propsed. The methods of wavelet decomposition and reconstruction are used to build a predictive model based on independent domains of frequency,which shows some advantages in composite prediction and prediction validity.The methods presented above are of non-linearity, error-allowing and auto-adaptive/learning, in addition to rapid and easy access,illustrative and quantitative presentation,and analyzed results that agree generally with facts. They are useful in diagnosing and predicting the El Nino and La Nina problems that are just roughly described in dynamics.