Browse > Article
http://dx.doi.org/10.17663/JWR.2013.15.2.233

Investigating Changes over Time of Precipitation Indicators  

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)
Publication Information
Journal of Wetlands Research / v.15, no.2, 2013 , pp. 233-250 More about this Journal
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.
Keywords
change point; BCP; precipitation indicators;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
연도 인용수 순위
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.   DOI   ScienceOn
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.   DOI   ScienceOn
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.   DOI   ScienceOn
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.   DOI   ScienceOn
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.   DOI   ScienceOn
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.   DOI