@inproceedings{cb1e6b6c64044a6c92eb5e952098de29,
title = "Correlation analysis of climate indices and precipitation using wavelet image processing approach",
abstract = "For extensive research on the connection and the phase relationships between climate indices and the precipitation time series in Korea, three wavelet image processing are applied to examine the relation between the climate indices (NAO, SOI, NOI, PDO, WP and NP) and precipitation in Korea. The continuous wavelet, cross-wavelet analysis and wavelet coherence is utilized to expand and present regions with common high significant frequency and phase features of the precipitation and these climate indices time series. It is found that the all wavelet frequency spectrum of these climate indices time series have some similar significant frequency features as the spectrum of precipitation time series in Korea have. There are significant variations of around 4–6 years of periodicities in all spectrum analysis. It is illustrated that there is strong underlying connection between precipitation variability and climate indices that implied by the cross wavelet and wavelet coherence analysis. The results clearly demonstrate that the climate indices have the influential consistent correlation relationship with the precipitation variation in Korea.",
keywords = "Climate indices, Correlation analysis, Precipitation, Wavelet image processing",
author = "Mingdong Sun and Xuyong Li and Gwangseob Kim",
note = "Publisher Copyright: {\textcopyright} 2018, Springer Nature Singapore Pte Ltd.; 6th International Conference on Frontier Computing, FC 2017 ; Conference date: 12-07-2017 Through 14-07-2017",
year = "2018",
doi = "10.1007/978-981-10-7398-4_25",
language = "English",
isbn = "9789811073977",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer Verlag",
pages = "231--240",
editor = "Yen, {Neil Y.} and Hung, {Jason C.} and Lin Hui",
booktitle = "Frontier Computing - Theory, Technologies and Applications FC 2017",
address = "Germany",
}