Predictive Analytics of Climate Trends

Main Article Content

Bakhram Nurtaev

Abstract

The accumulation of data in the weather observation will be continued steadily to infinity. To perform weather predictions, a huge amount of data needs to be processed and assimilated to create of acceptable models.

This paper presents a method of estimating a long term (more than 100 years) temperature and precipitation sets for predicting of a future trends. The method uses average solar cycle length as a uniform sampling basis for assessment of weather features. Long-term observation of climatic variables shows that in the theory of weather chaos exists a certain order. The order is expressed as a long-term increasing temperature trends and in rising of ocean levels. Here we demonstrate how the proposed approach can be highly effective in varied large-scale applications involving regional temperature trends in Caucasus region.

Keywords:
climate variability, precipitation, uniform sampling, solar cycle, attractor, Total Solar Irradiance, time series, sets

Article Details

How to Cite
Nurtaev, B. (2020). Predictive Analytics of Climate Trends. Journals of Georgian Geophysical Society, 22(2). Retrieved from https://ggs.openjournals.ge/index.php/GGS/article/view/2625
Section
Articles

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