Detrended fluctuation analysis of forest fires and related weather parameters

Power-law scaling behaviors of the real forest fires and weather parameters are analyzed by means of the detrended fluctuation analysis (DFA) method. It is found that the fire area series behave persistent long-range power-law correlations, with the scaling exponent 0.67, in the timescale larger than 3.9 days. In the smaller timescale it has similar characteristics like that of the white noise. The weather parameters are investigated then to reveal their connection to the forest fire. It is found that the temperature, relative humidity and rainfall records all exhibit long-range power-law correlations in large timescales. The scaling exponents are 0.89, 0.72, and 0.69, corresponding to timescales larger than 5.2 days, 4.67 days and 5.2 days respectively. The results imply that the scaling behaviors, such as the power law and the crossover, of the forest fire and the weather parameters have similar characteristics. The results seem to be helpful to quantify the underlying dynamics of the forest fire and the weather parameters, and to understand the underlying relationship between them.