The relationship between NAO and temperature in Hungary and its nonlinear connection with ENSO

摘要

Homogenized monthly and annual mean temperatures for ten locations in Hungary from 1901 to 1999 are analyzed. A principal component analysis was performed and the first new component containing 94.5% of the total variance has been retained. A linear regression of this variable on a sea level pressure NAO index results in relatively weak correlations. In order to consider the trends in both data series, a polynomial of years is added to the regression. After a selection of the optimal polynomial orders by Akaike's criteria the correlation coefficients are significantly increased. The Southern Oscillation Index (SO index) characterizing the El Nino - Southern Oscillation (ENSO) is then incorporated in the relationship via a nonlinear, threshold model. The threshold model consists of the above linear regressions but is conditioned on the SO index threshold variable. The rationale behind this approach is to allow a change of model performance according to ENSO phase. The thresholds are not pre-specified but are estimated from the data, while the number of thresholds is chosen by Akaike's criteria. A likelihood ratio test shows an improvement of these models over the linear model with very strong significance levels, except in June.