Cross-Sample Entropy Analysis for Climate Data

Currently due to intense modification of the natural environment and global climate change, many researches has been motivated to investigate relationships between El Ni?o phenomena dynamics and climatological variables. Understanding the dynamics that govern the climate can be done through analysis of nonlinear dynamical systems because the phenomenon involved has chaotic behavior. The reconstruction of the system dynamics that originated the possible climate changes patterns, with only one measurement scale, it is possible, through specific techniques of time series analysis. The description of the level of complexity or irregularity of time series can be made through the analysis of their Cross-Sample Entropy.The study was conducted with data from the meteorological station of Cuiab?, provided by INMET (National Institute of Meteorology) through of BDMEP (Meteorological Data Bank for Education and Research) in the 1961-2013 periods. The evidence of a possible connection between air temperature dynamic states and the Oceanic Ni?o Index - ONI, were verifying by Cross-Sample Entropy analysis of the series. The results point to the existence of a climate system with climate dynamic regulation of low dimensional and presence of deterministic chaos. The temporal evolution of nonlinear parameters obtained present a complex dynamics that may have related and influence of the fluctuations in ONI index.

Keywords: Complex dynamics, Air temperature, Oceanic Ni?o Index.