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Proceedings Paper

Study of phase clustering method for analyzing large volumes of meteorological observation data
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Paper Abstract

The article describes an iterative parallel phase grouping algorithm for temperature field classification. The algorithm is based on modified method of structure forming by using analytic signal. The developed method allows to solve tasks of climate classification as well as climatic zoning for any time or spatial scale. When used to surface temperature measurement series, the developed algorithm allows to find climatic structures with correlated changes of temperature field, to make conclusion on climate uniformity in a given area and to overview climate changes over time by analyzing offset in type groups. The information on climate type groups specific for selected geographical areas is expanded by genetic scheme of class distribution depending on change in mutual correlation level between ground temperature monthly average.

Paper Details

Date Published: 30 November 2017
PDF: 5 pages
Proc. SPIE 10466, 23rd International Symposium on Atmospheric and Ocean Optics: Atmospheric Physics, 104665L (30 November 2017); doi: 10.1117/12.2286873
Show Author Affiliations
Yu. V. Volkov, Institute of Monitoring of Climatic and Ecological Systems (Russian Federation)
V. A. Krutikov, Institute of Monitoring of Climatic and Ecological Systems (Russian Federation)
I. A. Botygin, Institute of Monitoring of Climatic and Ecological Systems (Russian Federation)
Tomsk Polytechnic Univ. (Russian Federation)
V. S. Sherstnev, Tomsk Polytechnic Univ. (Russian Federation)
A. I. Sherstneva, Tomsk Polytechnic Univ. (Russian Federation)


Published in SPIE Proceedings Vol. 10466:
23rd International Symposium on Atmospheric and Ocean Optics: Atmospheric Physics
Gennadii G. Matvienko; Oleg A. Romanovskii, Editor(s)

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