Translator Disclaimer
19 November 2015 Using of rank distributions in the study of perennial changes for monthly average temperatures
Author Affiliations +
Proceedings Volume 9680, 21st International Symposium Atmospheric and Ocean Optics: Atmospheric Physics; 96805R (2015) https://doi.org/10.1117/12.2205298
Event: XXI International Symposium Atmospheric and Ocean Optics. Atmospheric Physics, 2015, Tomsk, Russian Federation
Abstract
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.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
V. B. Nemirovskiy, A. K. Stoyanov, and V. A. Tartakovsky "Using of rank distributions in the study of perennial changes for monthly average temperatures", Proc. SPIE 9680, 21st International Symposium Atmospheric and Ocean Optics: Atmospheric Physics, 96805R (19 November 2015); https://doi.org/10.1117/12.2205298
PROCEEDINGS
4 PAGES


SHARE
Advertisement
Advertisement
Back to Top