Comparative Study of Results in the Determination of the Ambiental Thermal Sensation in an Area of the Gulf of Mexico during Solar Cycle 23 based on Daily Data and Monthly Average Data

The Environmental Thermal Sensation (STA) in solar cycle 23 was determined from the daily data and the monthly data of the meteorological variables Temperature (T), Relative Humidity (H) and Wind Speed (VV), this calculation is performed using algorithms used by weather stations around the world. Being able to select a database that provides the most accurate information is essential to achieve the most accurate results that allow finding viable solutions for present and future decision-making. Therefore, a mathematical representation of the calculations performed is presented, which allows determining that the use of daily data validates all the generated equations, contrary to the monthly data, which eliminates all the equations in which the variable H appears. This comparative study allows us to find a change in the p-value of the variable H depending on the type of data used, presenting p-values > 0.05 with the use of monthly average data and a p-value < 0.05 with daily data. The best result of the resulting equation, with monthly average data of the combination of the variables T, H and VV presents a correlation coefficient of 0.999638 and a determination coefficient of 0.999261, but the variable H presents a p-value > 0.05, which rules it out, however, this same combination of variables with daily data gives a correlation coefficient of 0.997600 and a determination coefficient of 0.995203. The selection of daily data or monthly average data is definitive in the desired result to determine the Environmental Thermal Sensation of solar cycle 23 in the Veracruz-Boca del Rio Conurbation Zone. This research is in line with SDG 13 in the framework of the scientific need to know a problem from the root, allowing from the results obtained, to have a clarity in the use of scientific information necessary for the development of new strategies for the study of climate change.