Predictability of global surface temperature by means of nonlinear analysis

Abstract

The time series of annually averaged global surface temperature anomalies for the years 1856–1998 is studied through nonlinear time series analysis with the aim of estimating the predictability time. Detection of chaotic behaviour in the data indicates that there is some internal structure in the data; the data may be considered to be governed by a deterministic process and some predictability is expected. Several tests are performed on the series, with results indicating possible chaotic behaviour.