Global Temperature Anomaly by Volterra-Laguerre Model from CO2 Emission, Solar Irradiance, Population, and the Oceans Heat Content

This paper presents a model based on the first-order Volterra series with Laguerre polynomials to identify the dynamics of global temperature anomalies in the last century. The independent variables to use in the model must be capable of predicting future anomalies, which should be chosen after analyzing the parameters used in significant models to predict global warming. Consequently, based on such studies and the criteria of this research, the selected set of parameters related to the proposed model is the following: the anthropogenic CO2, the total solar irradiance, global population, and ocean heat content. Focused on obtaining that model, the Volterra series, six Laguerre polynomials, unitary normalization, and the correlation factors between variables were applied to identify such anomalies. Results show a mathematical model multivariate techniques consistently can outperform other models like statistical models.Further, the performance of the Volterra-Laguerre model provides evidence that the variables in this proposal can forecast temperature anomalies with an error of less than 5% in the last thirty years of the period study. The proposed model has identified the dynamics of the global temperature anomaly, and the variables reveal that industrial activities and human actions must be part of the reflection to implement international policies that cushion climatic anomalies. Safely, only effective rules will prevent the increasing global warming effect and consequently deterioration of the marine habitat, the alteration of the water cycle, and the reproductive change of vegetables.