DOI QR코드

DOI QR Code

Selecting a mother wavelet for univariate wavelet analysis of time series data

시계열 자료의 단변량 웨이블릿 분석을 위한 모 웨이블릿의 선정

  • Lee, Hyunwook (Department of Civil, Environmental and Architectural Engineering, Korea University) ;
  • Lee, Jinwook (Department of Civil, Environmental and Architectural Engineering, Korea University) ;
  • Yoo, Chulsang (Department of Civil, Environmental and Architectural Engineering, Korea University)
  • 이현욱 (고려대학교 건축사회환경공학과) ;
  • 이진욱 (고려대학교 건축사회환경공학과) ;
  • 유철상 (고려대학교 건축사회환경공학과)
  • Received : 2019.04.24
  • Accepted : 2019.08.22
  • Published : 2019.08.31

Abstract

This study evaluated the effect of a mother wavelet in the wavelet analysis of various times series made by combining white noise and/or sine function. The result derived is also applied to short-memory arctic oscillation index (AOI) and long-memory southern oscillation index (SOI). This study, different from previous studies evaluating one or two mother wavelets, considers a total of four generally-used mother wavelets, Bump, Morlet, Paul, and Mexican Hat. Summarizing the results is as follows. First, the Bump mother wavelet is found to have some limitations to represent the unstationary behavior of the periodic components. Its application results are more or less the same as the spectrum analysis. On the other hand, the Morlet and Paul mother wavelets are found to represent the non-stationary behavior of the periodic components. Finally, the Mexican Hat mother wavelet is found to be too complicated to interpret. Additionally, it is also found that the application result of Paul mother wavelet can be inconsistent for some specific time series. As a result, the Morlet mother wavelet seems to be the most stable one for general applications, which is also assured by the recent trend that the Morlet mother wavelet is most frequently used in the wavelet analysis research.

본 연구에서는 모 웨이블릿(mother wavelet)이 웨이블릿 분석에 미치는 영향을 파악하기 위해 먼저 백색잡음과 사인함수를 다양하게 결합한 시계열의 분석을 수행하고 그 결과를 각각 단기기억특성과 장기기억특성을 보이는 북극진동지수(AOI)와 남방진동지수(SOI)에 대한 적용하였다. 본 연구에서는 기존 연구가 하나 또는 두 개의 모 웨이블릿 평가에 제한된 것과는 달리 총 4가지의 웨이블릿에 대한 비교 평가를 수행하였다. 본 연구에서 선정한 웨이블릿은 기존 연구에 많이 사용된 바 있는 총 4가지의 모 웨이블릿(Bump, Morlet, Paul, Mexican Hat)이다. 그 결과는 다음과 같다. 먼저, Bump 모 웨이블릿을 적용한 결과는 주기성분의 비정상성을 나타내는데 한계가 있는 것으로 확인되었다. 그 결과는 스펙트럼 분석결과와 매우 유사한 수준인 것으로 나타났다. 이에 반해 Morlet과 Paul 모 웨이블릿은 주기성분의 비정상성을 상대적으로 잘 나타내 주는 것으로 확인되었다. 마지막으로 Mexican Hat 모 웨이블릿의 경우에는 그 결과의 해석이 까다로운 것으로 나타났다. 추가로, Paul 모 웨이블릿의 적용 결과가 시계열에 따라 일관적이지 않게 나타날 수 있음도 확인하였다. 결과적으로 Morlet 모 웨이블릿은 본 연구에서 고려한 모 웨이블릿 중 그 적용상 안정성이 가장 높은 것으로 확인되었으며, 이러한 결과는 최근 웨이블릿 관련 연구에서 Morlet 모 웨이블릿이 가장 많이 사용되는 추세와도 일치하는 것이다.

Keywords

References

  1. Ahn, J. B., Ryu, J. H., Cho, E. H., Park, J. Y., and Ryoo, S. B. (1997). "A study of correlations between air-temperature and precipitation in Korea and SST over the tropical Pacific." Journal of the Korean Meteorological Society, Vol. 33, pp. 487-495.
  2. Baliunas, S., Frick, P., Sokoloff, D., and Soon, W. (1997). "Time scales and trends in the central England temperature data (1659-1990): A wavelet analysis." Geophysical Research Letters, Vol. 24, No. 11, pp. 1351-1354. https://doi.org/10.1029/97GL01184
  3. Bjerknes, J. (1969). "Atmospheric teleconnections from the equatorial Pacific." Monthly Weather Review, Vol. 97, No. 3, pp. 163-172. https://doi.org/10.1175/1520-0493(1969)097<0163:ATFTEP>2.3.CO;2
  4. Chan, T. F., and Shen, J. J. (2005). "Image processing and analysis: variational, PDE," Wavelet, and Stochastic Methods, Vol. 94. Siam, Philadelphia, USA.
  5. De Moortel, I., Munday, S. A., and Hood, A. W. (2004). "Wavelet analysis: the effect of varying basic wavelet parameters." Solar Physics, Vol. 222, No. 2, pp. 203-228. https://doi.org/10.1023/B:SOLA.0000043578.01201.2d
  6. Dyllon, S., and Xiao, P. (2018). Wavelet transform for educational network data traffic analysis. Intechopen, London, U.K.
  7. Echer, M. S., Echer, E., Nordemann, D. J., Rigozo, N. R., and Prestes, A. (2008). "Wavelet analysis of a centennial (1895-1994) southern Brazil rainfall series (Pelotas, 31 46' 19"S 52 20' 33" W)." Climatic Change, Vol. 87, No. 3-4, pp. 489-497. https://doi.org/10.1007/s10584-007-9296-6
  8. Farge, M. (1992). "Wavelet transforms and their applications to turbulence." Annual Review of Fluid Mechanics, Vol. 24, No. 1, pp. 395-458. https://doi.org/10.1146/annurev.fl.24.010192.002143
  9. Jevrejeva, S., Moore, J. C., and Grinsted, A. (2003). "Influence of the Arctic Oscillation and El Nino-Southern Oscillation (ENSO) on ice conditions in the Baltic Sea: The wavelet approach." Journal of Geophysical Research: Atmospheres, Vol. 108, No. D21.
  10. Jiang, Q., and Suter, B. W. (2017). "Instantaneous frequency estimation based on synchrosqueezing wavelet transform." Signal Processing, Vol. 138, pp. 167-181. https://doi.org/10.1016/j.sigpro.2017.03.007
  11. Jung, H. S., Lim, G. H., and Oh, J. H. (1999). "Interpretation of the transient variations in the time series of precipitation amounts in Seoul." Asia-Pacific Journal of Atmospheric Sciences, Vol. 35, No. 3, pp. 354-371.
  12. Kailas, S. V., and Narasimha, R. (2000). "Quasi-cycles in monsoon rainfall by wavelet analysis." Current Science, Vol. 78, No. 5, pp. 592-595.
  13. Kang, I. S. (1998). "Relationship between El-Nino and Korean climate variability." Journal of Korean Meteorological Society, Vol. 34, No. 3, pp. 390-396.
  14. Kuo, C. C., Gan, T. Y., and Yu, P. S. (2010). "Wavelet analysis on the variability, teleconnectivity, and predictability of the seasonal rainfall of Taiwan." Monthly Weather Review, Vol. 138, No. 1, pp. 162-175. https://doi.org/10.1175/2009MWR2718.1
  15. Labat, D., Ronchail, J., and Guyot, J. L. (2005). "Recent advances in wavelet analyses: Part 2-Amazon, Parana, Orinoco and Congo discharges time scale variability." Journal of Hydrology, Vol. 314, No. 1-4, pp. 289-311. https://doi.org/10.1016/j.jhydrol.2005.04.004
  16. Lee, H., and Yoo, C. (2019). "Evaluation of Arctic Oscillation effect on monsoons and typhoons in Korea using bivariate wavelet analysis." Journal of the Korean Society of Hazard Mitigation, Vol. 19, No. 1, pp. 71-84. https://doi.org/10.9798/kosham.2019.19.1.71
  17. Meyers, C., and Jones, T. B. (1993). Promoting active learning. Strategies for the college classroom." Jossey-Bass Inc., San Francisco, C.A., p. 192.
  18. Mi, X., Ren, H., Ouyang, Z., Wei, W., and Ma, K. (2005). "The use of the Mexican Hat and the Morlet wavelets for detection of ecological patterns." Plant Ecology, Vol. 179, No. 1, pp. 1-19. https://doi.org/10.1007/s11258-004-5089-4
  19. Misiti, M., Misiti, Y., Oppenheim, G., and Poggi, J. M. (2013). Wavelets and their Applications. John Wiley & Sons, N.Y., p. 330.
  20. Nakken, M. (1999). "Wavelet analysis of rainfall-runoff variability isolating climatic from anthropogenic patterns." Environmental Modelling & Software, Vol. 14, No. 4, pp. 283-295. https://doi.org/10.1016/S1364-8152(98)00080-2
  21. Park, C. E. (2017). "Spatial and temporal aspects of drought in South Korea based on Standardized Precipitation Index (SPI) and Palmer Drought Severity Index (PDSI)." Journal of Agricultural, Life and Environmental Sciences, Vol. 29, No. 3, pp. 202-214.
  22. Ropelewski, C. F., and Halpert, M. S. (1986). "North American precipitation and temperature patterns associated with the El Nino/Southern Oscillation (ENSO)." Monthly Weather Review, Vol. 114, No. 12, pp. 2352-2362. https://doi.org/10.1175/1520-0493(1986)114<2352:NAPATP>2.0.CO;2
  23. Ryu, Y., Shin, J. Y., Nam, W., and Heo, J. H. (2012). "Forecast of the daily inflow with artificial neural network using wavelet transform at Chungju Dam." Journal of Korea Water Resources Association, Vol. 45, No. 12, pp. 1321-1330. https://doi.org/10.3741/JKWRA.2012.45.12.1321
  24. Smith, L. C., Turcotte, D. L., and Isacks, B. L. (1998). "Stream flow characterization and feature detection using a discrete wavelet transform." Hydrological processes, Vol. 12, No. 2, pp. 233-249. https://doi.org/10.1002/(SICI)1099-1085(199802)12:2<233::AID-HYP573>3.0.CO;2-3
  25. Thompson, D. W., and Wallace, J. M. (1998) "The Arctic Oscillation signature in the wintertime geopotential Height and temperature fields." Geophysical Research Letters, Vol. 25. No. 9, pp. 1297-1300. https://doi.org/10.1029/98GL00950
  26. Torrence, C., and Webster, P. J. (1999). "Interdecadal changes in the ENSO-monsoon system." Journal of climate, Vol. 12, No. 8, pp. 2679-2690. https://doi.org/10.1175/1520-0442(1999)012<2679:ICITEM>2.0.CO;2
  27. Troup, A. J. (1965). "The 'southern oscillation'." Quarterly Journal of the Royal Meteorological Society, Vol. 91, No. 390, pp. 490-506. https://doi.org/10.1002/qj.49709139009
  28. Walker, G. T. (1932). "World Weather V Memories." Memories of the Royal Meteorological Society. Vol. 4, pp. 53-84.
  29. Zhou, Z., and Adeli, H. (2003). "Time-frequency signal analysis of earthquake records using Mexican hat wavelets." Computer-Aided Civil and Infrastructure Engineering, Vol. 18, No. 5, pp. 379-389. https://doi.org/10.1111/1467-8667.t01-1-00315