Multivariate nonlinear analysis of climatological variables and its effect on local temperature.

Atmospheric temperature describes the specific heat content of the air at particular places and times. In this sense, the presented work proposes a multivariable system that takes data sets of different climatological variables, with the aim of regulating the temperature level. The diversity in climatological variables significantly affects precipitation, humidity, wind speed and temperature. Thus, a study has been carried out on these variables in terms of nonlinear dynamics. The aim of the work is to obtain a better understanding of the dynamics of local climatological variables. On the other hand, due to the fact that the time series analyzed are small, the analysis becomes complex, at the moment of joining all the variables in conjunction, and processing them by means of multivariate statistical prediction methodologies. The results have shown the mean values in the different variables with which a temperature is maintained between and , which shows possible work with multi-objective optimization of the obtained model.