A Simple Stochastic Model for Long-term Climatic Variability

Abstract:

In its fifth Assessment Report, IPCC (Hartmann et al. 2013, Climate Change 2013, Contribution of Working Group I to the Fifth Assessment Report) referred for the first time to the statistical implications of the natural long-term climatic variability. In our recent work (Markonis and Koutsoyiannis, Surveys in Geophysics, 2013) we showed that natural temperature variability exhibits Hurst-Kolmogorov (HK) behaviour (also known as long term persistence) for time scales spanning nine orders of magnitude with Hurst coefficient near 0.92. However, this is a negatively biased estimate, as no bias correction technique was applied; this implies that the true value should be higher. Here, we adapt the estimation to account for bias and provide a possible stochastic model for an important variable of the climatic system: temperature. We also compare the behaviour of this model with other models which are widely used in climatology, including AR and ARMA models.