Research On Fractal Characteristics Of Climate Change Time Series

Research on global climate change is one of the hotspots research in the international scientific, it is not only a major event in the evolution of the earth, but also an important factor of the life and the species. Similarly, in the process of development of human society, the weather has been playing a very important role, which directly affects the human daily production activities. To handle the relationship between climate and social development has become a great challenge of human currently. Global warming become more and more serious, any change in climate will bring incalculable consequences to human survival and development. In recent years, scientists are trying to use a variety of methods to study the city climate issues, and achieved some important results. In this paper, we use linear fit, fractal interpolation simulation, the multi-fractal analysis method to study the part of meteorological data of Changsha and obtained the following conclusions:(1) Using fractal theory to analysis, we found that the average daily temperature, atmospheric pressure, precipitation and wind speed are presence of fractal characteristics. We found the box dimension of temperature and atmospheric pressure are less than precipitation and wind speed by calculate the box dimension of time series, it can infer that the fluctuation in precipitation and wind speed is greater than atmospheric pressure and temperature.(2) To further investigate the influence of temperature, atmospheric pressure, wind speed and precipitation to climate change, we get the fractal interpolation simulation curve of climate time series and calculated the box dimension of interpolation curve, it also found the fluctuation of precipitation and wind speed is greater than atmospheric pressure and temperature, and the box dimension of interpolation simulation curve is similar to the climate time series, it shows that the fractal interpolation simulation curve can keep the original features.(3) Multi-fractal analysis of temperature, atmospheric pressure, precipitation and wind speed are tried and the conclusion shows that the climate time series has obvious multi-fractal characteristics. By the figures of In(?q(?))-In(?), q-Dq and ?-f(?), we get various fractal index. By comparing the various fractal index of climate change time series, we found multi-fractal characteristics of daily average wind speed< temperature< atmospheric pressure< precipitation.