Quantum Biophysics of the Atmosphere: Factor Analysis of the Annual Dynamics of Maximum, Minimum and Average Temperatures from 1879 to 2017 to Hadley English Temperature Center (Hadcet)

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DOI: https://doi.org/10.30564/jees.v3i1.2489

Abstract:

Factor analysis of annual dynamics from 1879 to 2017 was carried out by the method of identification of stable regularities: maximum, minimum and average air temperature of Central England according to HadCET. The sample capacity was 139 rows. In factor analysis, time is excluded, and it acts only as a system-forming factor that ensures the relationship between the three parameters of climate and weather. Therefore, the adequacy of the dynamics models is taken into account in the diagonal cells of the correlation matrix. In addition to time, different lists of objects are possible in factor analysis. The coefficient of correlation variation, that is, a measure of the functional relationship between the parameters of the system (annual weather at the weather station in Central England) is 0.8230 for trends, 0.8603 taking into account the annual dynamics of the four-membered model obtained from the computational capabilities of the software environment CurveExpert-1.40, and 0.9578 for the full up to the error of measurement wavelet analysis of the dynamics of the values of three factors. In all three methods of factor analysis, the meteorological parameter «average Annual temperature» was in the first place as the influencing variable, the «Maximum temperature» was in the second place, and the «Minimum temperature» was in the third place. As the dependent measure in these areas there are three kinds of temperature. The comparison shows that among the binary relations between the three temperatures, the average temperature on the maximum air temperature in the surface layer of the atmosphere has the greatest influence on the correlation coefficient 0.9765. At the same time, all six equations refer to strong connections, so there is a high quantum certainty between the three types of temperature. But when predicting the most meaningful essence showed the maximum temperature.

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