Complexity in Slowly-Driven Interaction-Dominated Threshold Systems: the Case of Rainfall.

Abstract

Many geophysical phenomena present emergent behaviour, which manifested as large-scale statistical regularities such as power-law distributions for the coarse-grained observables of the corresponding systems. In this thesis we investigate the appearance of power-law distributions in geophysical phenomena. We develop a statistical technique for making accurate estimations of the parameters of power-law distributions. The method introduced, which gives an objective criteria to decide the power-law domain of the distribution, is applied to investigate the half-lives of radioactive elements, the seismic moment of earthquakes, the energy of tropical cyclones, the area burnt in forest fires and the waiting time between earthquakes. _x000D_ _x000D_ In addition, the method is applied for investigating the reproducibility of the observation of scale-free rain event avalanche distributions using data across diverse climates and for looking for signs of universality in the associated fitted exponents. Scaling techniques are also applied in order to see the collapse of the distributions. This study contributes to a recent array of statistical measures that give support to the hypothesis that atmospheric convection and precipitation may be a real-world example of Self-Organised Criticality (SOC, a mechanism able to reproduce the observed power laws). Another expectation of the SOC paradigm is universality, but the fitting method is not enough for checking this hypothesis. Therefore, a method based on a permutation test is developed in order to determine if the estimated exponents are statistically compatible. Our alternative permutational tests give clear results: despite the fact that the differences between the exponents are rather small, the universality hypothesis is rejected. However, the fact that the universality hypothesis is rejected in the tests does not mean that one has to rule out the existence of a universal mechanism for atmospheric convection, as uncontrolled systematic errors can be present in the collection of data._x000D_ _x000D_ Finally, we study the consequences of the previous results for the prediction of atmospheric phenomena by analysing the effect of applying thresholds on SOC models and rainfall time series. The predictability of extreme events and extreme intensities is studied by means of a decision variable sensitive to the tendency to cluster or repulse between them and the quality of the predictions is evaluated by the receiver operating characteristics method. On the events scale (large scale), times between events for rainfall data and models renormalise to a trivial point process, and then the predictability decreases when the threshold increases. In the intensity picture (short scale), the prediction is not affected by the threshold, as the process remains mostly unchanged (also their critical corresponding exponents) until very high thresholds are reached.

Date of Award	9 Dec 2013
Original language	English
Supervisor	Alvaro Corral Cano (Director)