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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Cheung, H.N., Zhou, W., Mok, H.Y., Wu, M.C.: Relationship between Ural-Siberian blocking and the East Asian winter monsoon in relation to the Arctic Oscillation and the El Niño-Southern Oscillation. J. Clim. 25, 4242–4257 (2012)
Grinsted, A., Moore, J.C., Jevrejeva, S.: Application of the cross wavelet transform and wavelet coherence to geophysical time series. Nonlinear Proc. Geophys. 11, 561–566 (2004)
Higgins, R.W., Kim, H.K., Unger, D.: Long-lead seasonal temperature and precipitation prediction using tropical Pacific SST consolidation forecasts. J. Clim. 17, 3398–3414 (2004)
Hurrell, J.W.: Decadal trends in the North Atlantic oscillation regional temperatures and precipitation. Science 269, 676–679 (1995)
Jin, Y.H., Kawamura, A., Jinno, K., Berndtsson, R.: Detection of ENSO-influence on the monthly precipitation in South Korea. Hydrol. Proc. 19, 4081–4092 (2005)
Pal, J.S., Giorgi, F., Bi, X.Q.: Consistency of recent European summer precipitation trends and extremes with future regional climate projections. Geophys. Res. Lett. 31, L13202 (2004)
Portis, D.H., Walsh, J.E., El Hamly, M., Lamb, P.J.: Seasonality of the North Atlantic oscillation. J. Clim. 14, 2069–2078 (2001)
Schwing, F.B., Murphree, T., Green, P.M.: The Northern Oscillation Index (NOI): a new climate index for the northeast Pacific. Progr. Oceanogr. 53, 115–139 (2002)
Silverman, D., Dracup, J.A.: Artificial neural networks and long-range precipitation prediction in California. J. Appl. Meteorol. 39, 57–66 (2000)
Stenseth, N.C., Mysterud, A., Ottersen, G., Hurrell, J.W., Chan, K.S., Lima, M.: Ecological effects of climate fluctuations. Science 297, 1292–1296 (2002)
Stenseth, N.C., Ottersen, G., Hurrell, J.W., Mysterud, A., Lima, M., Chan, K.S., Yoccoz, N.G., Ådlandsvik, B.: Studying climate effects on ecology through the use of climate indices: the North Atlantic Oscillation, El Niño Southern Oscillation and beyond. Proc. Roy. Soc. Lond. B 270, 2087–2096 (2003)
Torrence, C., Compo, G.P.: A practical guide to wavelet analysis. Bull. Am. Meteorol. Soc. 79, 61–78 (1998)
Trenberth, K.E.: The definition of El Ninño. Bull. Am. Meteorol. Soc. 78, 2771–2777 (1997)
Trenberth, K.E., Stepaniak, D.P.: Indices of El Niño evolution. J. Clim. 14, 1697–1701 (2001)
Wang, B., Ding, Q., Jhun, J.G.: Trends in Seoul (1778-2004) summer precipitation. Geophys. Res. Lett. 33, L15803 (2006)
Zhou, B.T., Wang, H.J.: Relationship between the boreal spring Hadley circulation and the summer precipitation in the Yangtze River valley. J. Geophys. Res. 111, D16109 (2006)
Acknowledgements
The research funding was provided by the Major Science and Technology Program for Water Pollution Control and Treatment in China (2014ZX07203010), the Chinese Academy of Sciences’ key project (KZZD-EW-10-02), and the RCEES “One-Three-Five” project (YSW2013B02-4).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Sun, M., Li, X., Kim, G. (2018). Correlation Analysis of Climate Indices and Precipitation Using Wavelet Image Processing Approach. In: Hung, J., Yen, N., Hui, L. (eds) Frontier Computing. FC 2017. Lecture Notes in Electrical Engineering, vol 464. Springer, Singapore. https://doi.org/10.1007/978-981-10-7398-4_25
Download citation
DOI: https://doi.org/10.1007/978-981-10-7398-4_25
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-7397-7
Online ISBN: 978-981-10-7398-4
eBook Packages: EngineeringEngineering (R0)