Full Article: PDF
Scientific Object Identifier: http://s-o-i.org/1.1/TAS-10-102-96
DOI: https://dx.doi.org/10.15863/TAS.2021.10.102.96
Language: Russian
Citation: Zhanatauov, S. U. (2021). A digital model of climate variability. ISJ Theoretical & Applied Science, 10 (102), 846-863. Soi: http://s-o-i.org/1.1/TAS-10-102-96 Doi: https://dx.doi.org/10.15863/TAS.2021.10.102.96 |
Pages: 846-863
Published: 30.10.2021
Abstract: A digital model of climate variability with a number of variables has been developed (5+4+4+4=17) and parameters (5*5+4*4+4=45). Two systems of linear equations for 5 and 4 z-variability. The first is with the right part equal to u-variability (for 5 z-variability), the second is v-variability (for the other 4 z-variability).. A mathematical multidimensional model is correctly transformed into a system of semantic equations with unknown m z-variability, m u-variability, m v-variability, in the presence of knowledge indicators. The uncorrelation of m u-variability with m v-variability exactly corresponds to the independence of the meaning of each u-variability from the meaning of each v-variability. Transformation of one multidimensional linear equation of cognitive meanings of variability zi1,...,zi5 of z-variables z1,z2,...,z5 and the meaning of one u-variable into m linear equations of values of 5 z-variability characterizing the variability of negative consequences for human economic activity gives m values of 5 z-variability and m values of one u-variability. Transformation of one multidimensional linear equation of cognitive meanings of variability zi6,...,zi9 of z-variables z6,...,z9 and one v-variable into m linear equations with 4 z-variability characterizing climate variability gives m values of 4 z-variability, m values of one of the 4 v-variability. The values and the number of indicators are the control parameters of the digital model. They are equal to 4+27=31, where 4 is the number of variances of hidden variables, 16+11=27 is the number of indicators. An example of modeling the values of variability of climate change indicators is carried out. The values of parameters and variables (various in the sense of interpretation) of the digital model of climate variability are found. They numerically and visually show that the types of dependencies of climate change indicators correspond to reality (Figures 4-8).
Key words: digital model, climate, variability.
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