Journal of Wetlands Research (한국습지학회지)

Korean Wetlands Society (한국습지학회)
권호 표지
DOI QR코드

DOI QR Code

Investigating Changes over Time of Precipitation Indicators

강수지표의 시간에 따른 변화 조사

  • Han, Bong-Koo (Department of Civil Engineering, Seoul national university of science & technology) ;
  • Chung, Eun-Sung (Department of Civil Engineering, Seoul national university of science & technology) ;
  • Lee, Bo-Ram (Department of Civil Engineering, Seoul national university of science & technology) ;
  • Sung, Jang Hyun (Yeongsan river flood control office, Ministry of Land, Infrastructure and Transport)
  • 한봉구 (서울과학기술대학교 건설시스템디자인공학과) ;
  • 정은성 (서울과학기술대학교 건설시스템디자인공학과) ;
  • 이보람 (서울과학기술대학교 건설시스템디자인공학과) ;
  • 성장현 (국토교통부 영산강홍수통제소)
  • Received : 2013.04.10
  • Accepted : 2013.05.08
  • Published : 2013.05.31
Download PDF
⟨ Previous Next ⟩

Abstract

Gradually or radically change how the characteristics of the climate characteristic using change point analysis for the precipitation indicators were investigated. Significantly the amount, extreme and frequency were separated by precipitation indicators, each indicator RIA(Rainfall Index for Amount), RIE(Rainfall Index for Extremes) and RIF(Rainfall Index for Frequency) was defined. Bayesian Change Point was applied to investigate changing over time of precipitation indicators calculated. As the result of analysis, precipitation indicators in South Korea was found to recently increase all indicators except for the annual precipitation days and 200-yr precipitation. RIA revealed that there was a very clear point of significance for the change in Ulleungdo, Relatively significant results for RIE were identified in Gumi, Jecheon and Seogwipo. Also, since the 1990s, an increase in the number of variation points, and the horizontal width of the fluctuation point was being relatively wider. Based on these results, rethink the precipitation on the assumption of stationarity was judged necessary.

강수지표의 변화시점(change point) 분석을 이용하여 기후의 특성이 점진적 또는 급진적으로 변화하는지에 대하여 조사하였다. 강수지표를 크게 총량(amount), 극치(extremes)와 빈도(frequency)로 구분하였고, 각각의 지수를 RIA(Rainfall Index for Amount), RIE(Rainfall Index for Extremes)와 RIF(Rainfall Index for Frequency)로 정의하였다. 계산된 강수지표의 시간에 따른 변화를 알아보기 위하여 BCP(Bayesian Change Point)를 적용하였다. 분석 결과, 남한지역의 강수지표는 연 강우일수와 200년 빈도 확률 강수량을 제외하고는 모두 증가 하는 것으로 확인되었다. RIA는 울릉도 지점에서 변화지점의 유의성에 대해 매우 명확한 모습을 보였고 RIE는 제천, 서귀포와 구미 등에서 비교적 유의한 결과가 확인되었다. 또한, 1990년대 이후에 변동지점의 개수가 증가하고 있으며, 변동지점의 횡적인 폭 또한 비교적 넓어지고 있었다. 이러한 사실에 근거하여 볼 때 강수에 대한 정상성 가정에 대한 재고가 필요하리라 판단되었다.

Keywords

References

  1. Alley, R. B., Marotzke, J., Nordhaus, W. D., Overpeck, J. T., Peteet, D. M., Pielke, R., Pierrehumbert, R. T., Rhines, P. B., Stocker, T. F., Talley, L. D., and Wallace, J. M. (2003). Abrupt climate change, Science, 299, 2005-2010.
  2. Barry, D., and Hartigan, J. A. (1993). A bayesian analysis for change point problems, Journal of the American Statistical Association, 88(421), pp. 309-319.
  3. Choi, Y. E. (2004). Trends on Temperature and Precipitation Extreme Events in Korea, Journal of the Korean Geographical Society, 39(5), pp. 711-721
  4. Choi, Y. E., Park, C. Y. (2010). Distribution of Cold Surges and Their Changes in the Joongbu Region, the Republic of Korea, Journal of The Korean Association of Professional Geographers, 44(4), pp. 713-725.
  5. Cox, D. R., Isham, V. S., and Northrop, P. J. (2002). Floods: some probabilistic and statistical approaches, Philosophical Transactions of the Royal Society of London, Series A, 360, pp. 1389-1408. https://doi.org/10.1098/rsta.2002.1006
  6. Elsner, J. B., Niu, X., and Bossak, B. H. (2004). Detecting shifts in hurricane rates using a Markov chain Monte Carlo approach, Journal of Climate, 17, pp. 2652-2666. https://doi.org/10.1175/1520-0442(2004)017<2652:DSIHRU>2.0.CO;2
  7. Erdman, C., and Emerson, J. W. (2007). bcp: A Package for Performing a Bayesian Analysis of Change Point Problems, R package version 1.8.4, URL (http://CRAN. Rproject.org/).
  8. Hare, S. R. and Mantua, N. J. (2000). Empirical evidence for North Pacific regime shifts in 1977 and 1989, Progress In Oceanography, 47, pp. 103-145. https://doi.org/10.1016/S0079-6611(00)00033-1
  9. Hwang, S. H., Kim, J. H., Yoo, C. S., Jung, S. W. (2010). A Probabilistic Estimation of Changing Points of Seoul Rainfall Using BH Bayesian Analysis, Journal of Korea Water Resources Association, 43(7), pp. 645-655. https://doi.org/10.3741/JKWRA.2010.43.7.645
  10. Iwashima, T., and Yamamoto, R. (1993). A statistical analysis of the extreme events. Long-term trend of heavy daily precipitation, J. of Meteor, Soc. of Japan, 71, pp. 37-640.
  11. IPCC (2007). Climate Change 2007: The Physical Science Basis-Summary for Pol.
  12. Jeong, D. I., Stedinger, J. R., Sung, J. H., Kim, Y. O. (2008). Flood Risk Assessment with Climate Change, Journal of Korean Society of Civil Engineers, 28(1B), pp. 55-64.
  13. Kim, B. S., Lee, J. K., Kim, H. S., Lee, J. W. (2011). Non-stationary Frequency Analysis with Climate Variability using Conditional Generalized Extreme Value Distribution, Journal of Korean Wetlands Society, 13(3), pp. 499-514.
  14. Kim, B. K., Kim, B. S., Kim, H. S. (2008). On the Change of Extreme Weather Event using Extreme Indices, Journal of Korean Society of Civil Engineers, 28(1B), pp. 41-53.
  15. Lee, K. M., Baek, H. J., Jo, C. H., Kwon, W. T. (2011). The recent (2001-2010) changes on temperature and precipitation related to normals (1971-2000) in Korea, Journal of The Korean Association of Professional Geographers, 45(2), pp. 237-248.
  16. Lee, K. M., Sung, J. H., Kim, Y. O., Lee, S. H. (2011). Change-point Analysis of Mean Temperature and Extreme Temperature in the Public of Korea, Journal of the Korean Geographical Society, 6(5), pp. 583-596. icymakers. R. Alley et al. (http://ipcc-wg1.ucar.edu/).
  17. Lund, R. and Reeves, J. (2002). Detection of undocumented change points: a revision of the two-phase regression model, Journal of Climate, 15, pp. 2547-2554. https://doi.org/10.1175/1520-0442(2002)015<2547:DOUCAR>2.0.CO;2
  18. Lupikasza, E. (2009). Spatial and temporal variability of extreme precipitation in Poland in the period 1951- 2006, International Journal of Climatology, 30(7), pp. 991-1007.
  19. National Institute of Meteorological Research (NIMR). (2008). Development of Regional Climate Change Scenario for the National Climate Change(Ⅳ). Study result.
  20. National Institute of Meteorological Research (NIMR) (2009) 기후변화 이해하기III. 서울의 기후변화.
  21. Solow, A. R. (1987). Testing for climate change: An application of two-phase regression model, Journal of Applied Meteorology, 26, pp. 1401-1405. https://doi.org/10.1175/1520-0450(1987)026<1401:TFCCAA>2.0.CO;2

Cited by

  1. A Study on the Change of Non-Working Days of Incheon Metropolitan through BCP Analysis vol.16, pp.4, 2015, https://doi.org/10.6106/KJCEM.2015.16.4.080