Abstract
Abstract Climate variability is simply represented by teleconnection patterns such as the Arctic Oscillation (AO), Antarctic Oscillation (AAO), North Atlantic Oscillation (NAO), Pacific–North American pattern (PNA), and Southern Oscillation (SO) with associated indices. Two approaches can be used to predict the indices: forward and backward methods. The forward method is commonly used to predict the index fluctuation ρ at time t with a given temporal increment τ. Using this method, it was found that the index (such as for NAO) has the Brownian fluctuations. On the basis of the first passage time (FPT) concept, the backward method is introduced in this study to predict the typical time span (τ) needed to generate a fluctuation in the index of a given increment ρ. After the five monthly indices (AO, AAO, NAO, PNA, and SO) run through the past history, the FPT density functions are obtained. FPT presents a new way to detect the temporal variability of the climate indices. The basic features for the index prediction are also discussed.
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