The possibility of comparing the climatic data of various years with using rank distributions is considered in this paper. As a climatic data, the annual variation of temperature on the spatial areas of meteorological observations with high variability in average temperatures is considered. The results of clustering of the monthly average temperatures values by means of a recurrent neural network were used as the basis of comparing. For a given space of weather observations the rank distribution of the clusters cardinality identified for each year of observation, is being constructed. The resulting rank distributions allow you to compare the spatial temperature distributions of various years. An experimental comparison for rank distributions of the annual variation of monthly average temperatures has confirmed the presence of scatter for various years, associated with different spatio-Temporal distribution of temperature. An experimental comparison of rank distributions revealed a difference in the integral annual variation of monthly average temperatures of various years for the Northern Hemisphere.
|Title of host publication||Proceedings of SPIE - The International Society for Optical Engineering|
|Publication status||Published - 2015|
|Event||21st International Symposium on Atmospheric and Ocean Optics: Atmospheric Physics - Tomsk, Russian Federation|
Duration: 22 Jun 2015 → 26 Jun 2015
|Conference||21st International Symposium on Atmospheric and Ocean Optics: Atmospheric Physics|
|Period||22.6.15 → 26.6.15|
- cluster and climate.
- Rank distribution
ASJC Scopus subject areas
- Applied Mathematics
- Computer Science Applications
- Electrical and Electronic Engineering
- Electronic, Optical and Magnetic Materials
- Condensed Matter Physics