A sequential method of detecting abrupt changes in the correlation coefficient and its application to Bering Sea climate

TL;DR

This paper introduces a sequential method for detecting multiple change-points in correlation coefficients within time series, enabling real-time regime shift monitoring, and applies it to identify a major climate shift in the Bering Sea around 1967.

Contribution

It presents a novel sequential approach for detecting multiple change-points in correlation coefficients, with real-time monitoring capabilities, and demonstrates its effectiveness on climate data.

Findings

Detected a major climate shift in the Bering Sea in 1967.

Identified a transition from zonal to meridional atmospheric circulation.

Analyzed the influence of Siberian and Alaskan centers on winter temperatures.

Abstract

A new method of regime shift detection in the correlation coefficient is proposed. The method is designed to find multiple change-points with unknown locations in time series. It signals a possible regime shift in real time and allows for its monitoring. The method is tested on randomly generated time series with predefined change-points. It is applied to examine structural changes in the Bering Sea climate. A major shift is found in 1967, which coincides with a transition from a zonal type of atmospheric circulation to a meridional one. The roles of the Siberian and Alaskan centers of action on winter temperatures in the eastern Bering Sea have been investigated.