How the Chaos Theory is Defeated in the Yabu Meteorological Station, Cuba

Abstract

In this work, 8 weather variables were modeled at the Yabu meteorological station, Cuba, a daily database from the Yabu meteorological station, Cuba, of extreme temperatures, extreme humidity and their average value, precipitation, was used. The force of the wind and the cloudiness corresponding to the period from 1977 to 2021, a linear mathematical model is obtained through the methodology of Regressive Objective Regression (ROR) for each variable that explains their behavior, depending on these 15, 13, 10 and 8 years in advance. It is concluded that these models allow the long-term forecast of the weather, opening a new possibility for the forecast, concluding that the chaos in time can be overcome if this way of predicting is used, the calculation of the mean error regarding the forecast of persistence in temperatures, wind force and cloud cover, while the persistence model is better in humidity, this allows to have valuable information in the long term of the weather in a locality, which results in a better decision making in the different aspects of the economy and society that are impacted by the weather forecast. It is the first time that an ROR model has been applied to the weather forecast processes for a specific day 8, 10, 13 and 15 years in advance.