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

Результат исследований: Материалы для книги/типы отчетовМатериалы для конференции

Аннотация

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.

Язык оригиналаАнглийский
Название основной публикации23rd International Symposium on Atmospheric and Ocean Optics
Подзаголовок основной публикацииAtmospheric Physics
РедакторыGennadii G. Matvienko, Oleg A. Romanovskii
ИздательSPIE
ISBN (электронное издание)9781510614130
DOI
СостояниеОпубликовано - 2017
Событие23rd International Symposium on Atmospheric and Ocean Optics: Atmospheric Physics - Irkutsk, Российская Федерация
Продолжительность: 3 июл 20177 июл 2017

Серия публикаций

НазваниеProceedings of SPIE - The International Society for Optical Engineering
Том10466
ISSN (печатное издание)0277-786X
ISSN (электронное издание)1996-756X

Конференция

Конференция23rd International Symposium on Atmospheric and Ocean Optics: Atmospheric Physics
СтранаРоссийская Федерация
ГородIrkutsk
Период3.7.177.7.17

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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