KSCE Journal of Civil and Environmental Engineering Research (대한토목학회논문집)

Korean Society of Civil Engeneers (대한토목학회)
권호 표지
DOI QR코드

DOI QR Code

Development of Multisite Spatio-Temporal Downscaling Model for Rainfall Using GCM Multi Model Ensemble

다중 기상모델 앙상블을 활용한 다지점 강우시나리오 상세화 기법 개발

  • 김태정 (전북대학교 토공공학과, 방재연구센터) ;
  • 김기영 (한국수자원공사 K-water 연구원 기반시설연구소) ;
  • 권현한 (전북대학교 토목공학과)
  • Received : 2014.12.19
  • Accepted : 2015.02.24
  • Published : 2015.04.01
Download PDF
⟨ Previous Next ⟩

Abstract

General Circulation Models (GCMs) are the basic tool used for modelling climate. However, the spatio-temporal discrepancy between GCM and observed value, therefore, the models deliver output that are generally required calibration for applied studies. Which is generally done by Multi-Model Ensemble (MME) approach. Stochastic downscaling methods have been used extensively to generate long-term weather sequences from finite observed records. A primary objective of this study is to develop a forecasting scheme which is able to make use of a MME of different GCMs. This study employed a Nonstationary Hidden Markov Chain Model (NHMM) as a main tool for downscaling seasonal ensemble forecasts over 3 month period, providing daily forecasts. Our results showed that the proposed downscaling scheme can provide the skillful forecasts as inputs for hydrologic modeling, which in turn may improve water resources management. An application to the Nakdong watershed in South Korea illustrates how the proposed approach can lead to potentially reliable information for water resources management.

기후모형으로 가장 널리 사용되는 GCM의 불확실성 및 시공간적 편의로 인하여 GCM으로부터 생산된 기상정보를 응용수문분야에서 직접적으로 이용하기 위해서는 상세화 과정이 필수적으로 요구된다. 본 연구에서는 선행연구에서 개발된 비정상성 은닉 마코프 모형(Non-stationary Hidden Markov Chain Model, NHMM)을 기반으로 다지점 공간상관성을 고려할 수 있는 Chow-Liu Tree 알고리즘과 결합하여 유역단위 강우시나리오 상세화 기법(CLT-NHMM)으로 확장하였으며, 낙동강 유역에 적용하여 적용성을 평가하였다. 상관행렬(correlation matrix)을 통한 강우네트워크의 공간상관성 평가결과 유역상관성이 우수하게 모의하는 것을 확인하였으며, 강수의 빈도 및 양적 관점에서 효과적인 모의가 가능하였다. 본 연구에서 제시한 CLT-NHMM 모형은 수자원뿐만 아니라 수문자료를 입력 자료로 하는 농업, 보건, 환경 및 에너지 등 다양한 응용기상분야에 핵심 기술로 활용이 전망된다.

Keywords

References

  1. Barnston, A. G., Mason, S. J., Goddard, L., Dewitt, D. G. and Zebiak, S. E. (2003). "Multimodel ensembling in seasonal climate forecasting at IRI." Bulletin of the American Meteorological Society, Vol. 84, No. 12, pp. 1783-1796. https://doi.org/10.1175/BAMS-84-12-1783
  2. Bates, B. C., Charles, S. P. and Hughes, J. P. (1998). "Stochastic downscaling of numerical climate model simulations." Environmental Modeling & Software, Vol. 13, No. 3, pp. 325-331. https://doi.org/10.1016/S1364-8152(98)00037-1
  3. Bundel, A. Y., Kryzhov, V. N., Min, Y. M., Khan, V. M., Vilfand, R. M. and Tishchenko, V. A. (2011). "Assessment of probability multimodel seasonal forecast based on the APCC model data." Russian Meteorology and Hydrology, Vol. 36, No. 3, pp. 145-154. https://doi.org/10.3103/S1068373911030010
  4. Cho, H. R., Hwang, S. H., Cho, Y. S. and Choi, M. H. (2013). "Analysis of spatial precipitation field using downscaling on the korean peninsula." Journal of Korea Water Resources Association, Vol. 46, No. 11, pp. 1129-1140 (in Korean). https://doi.org/10.3741/JKWRA.2013.46.11.1129
  5. Chow, C. K. and Liu, C. N. (1968). "Approximating discrete probability distributions with dependence trees." IEEE Transactions on Information Theory, Vol. 14, pp. 462-467. https://doi.org/10.1109/TIT.1968.1054142
  6. Cox, P. M., Betts, R. A., Jones, C. D., Spall, S. A. and Totterdell, I. J. (2000). "Acceleration of global warming due to carbon-cycle feedbacks in a coupled climate model." Nature, Vol. 408, No. 6809, pp.184-187. https://doi.org/10.1038/35041539
  7. Ekstorm, M. Fowler, H. J., Kilsby, C. G. and Jones, P. D. (2005). "New estimates of future changes in extreme rainfall across the UK using regional climate model integrations. 2. Future estimates and use in impact studies." Journal of Hydrology, Vol. 300, No. 1, pp. 234-251. https://doi.org/10.1016/j.jhydrol.2004.06.019
  8. Fowler, H. J., Ekstrom, M., Kilsby, C. G. and Jones, P. D. (2005). "New estimates of future changes in extreme rainfall across the UK using regional climate model intergrations. 1. Assessment of control climate." Journal of Hydrology, Vol. 300, No. 1, pp. 212-233. https://doi.org/10.1016/j.jhydrol.2004.06.017
  9. Frei, C., Scholl, R., Fukutome, S., Schmidli, J. and Vidale, P. L. (2006). "Future change of precipitation extremes in Europe: Intercomparison of Scenarios from Regional Climate Models." Journal of Geophysical Research: Atmospheres (1984-2012), Vol. 111, No. D6, DOI: 10.1029/2005JD005965.
  10. Grimm, A. M. (2011). "Interannual climate variability in South America: impacts on seasonal precipitation, extreme events, and possible effects of climate change." Stochastic Environmental Research and Risk Assessment, Vol. 25, No. 4, pp. 537-554. https://doi.org/10.1007/s00477-010-0420-1
  11. Grum, M., Jorgensen, A. T., Johansen, R. M. and Linde, J. J. (2006). "The effect of climate change on urban drainage: An Evaluation Based on Regional Climate Model Simulations." Water Science & Technology, Vol. 54, No. 6-7, pp. 9-15. https://doi.org/10.2166/wst.2006.592
  12. Haugen, J. E. and Iversen, T. (2008). "Response in extremes of daily precipitation and wind from a downscaled multi-model ensemble of anthropogenic global climate change scenarios." Tellus A, Vol. 60, No. 3, pp. 411-426. https://doi.org/10.1111/j.1600-0870.2008.00315.x
  13. Hewitson, B. C. and Crane, R. G. (2006). "Consensus between GCm climate change projection with empirical downscaling : Precipitation Downscaling over South Africa." International Journal of Climatology, Vol. 26, No. 10, pp. 1315-1337. https://doi.org/10.1002/joc.1314
  14. Karl, T. R., Wang, W. C., Schlesinger, M. E., Knight, R. W. and Portman, D. (1990). "A method of relating general circulation model simulated climate to the observed local climate. Part 1 : Seasonal Statistics." Journal of Climate, Vol. 3, No. 10, pp. 1053-1079. https://doi.org/10.1175/1520-0442(1990)003<1053:AMORGC>2.0.CO;2
  15. Khalil, A. F., Kwon, H. H., Lall, U. and Kaheil, Y. H. (2010). "Predictive downscaling based on non-homegeneous hidden markov models." Hydrological Sciences Journal-Journal des Sciences Hydrologiques, Vol. 55, No. 3, pp. 333-350. https://doi.org/10.1080/02626661003780342
  16. Kim, T. J. (2014). Development of nonstationary spatio-temporal downscaling technique using general circulation model multimodel ensemble, Master's Thesis, Chonbuk National University, Jeonju, Jeollabuk, Republic of Korea.
  17. Kim, T. J., Kwon, H. H., Lee, D. R. and Yoon, S. K. (2014). "Development of stochastic downscaling method for rainfall data using GCM." Journal of Korea Water Resources Association, Vol. 47, No. 9, pp. 825-838 (in Korean). https://doi.org/10.3741/JKWRA.2014.47.9.825
  18. Kirshner, S., Smyth, P. and Robertson, A. W. (2004). "Conditional chow-liu tree structures for modeling discrete-valued vector time series." Appears in Proceedings of the Twentieth Conference on Uncertainty in Artificial Intelligence (UAI2004), pp. 317-324.
  19. Krishnamurti, T. N., Kishtawal, C. M., LaRow, T. E., Bachiochi, D. R., Zhang, Z., Williford, C. E., Gadgil, S. and Surendran, S. (1999). "Improved weather and seasonal climate forecasts from multimodel superensemble." Science, Vol. 285, No. 5433, pp. 1548-1550. https://doi.org/10.1126/science.285.5433.1548
  20. Kwon, H. H., Kim, T. J., Hwang, S. H. and Kim, T. W. (2013a). "Development of daily rainfall simulation model based on homegeneous hidden markov chain." Journal of the Korean Society of Civil Engineers, Vol. 33, No. 5, pp. 1861-1870 (in Korean). https://doi.org/10.12652/Ksce.2013.33.5.1861
  21. Kwon, H. H., Kim, T. J., Kim, O. K. and Lee, D. R. (2013b). "Development of multi-site daily rainfall simulation based on homogeneous hidden markov chain model coupled with chow-liu tree structure." Journal of Korea Water Resources Association, Vol. 46, No. 10, pp. 1029-1040 (in Korean). https://doi.org/10.3741/JKWRA.2013.46.10.1029
  22. Kwon, H. H., Lall, U. and Obeysekera, J. (2009). "Simulation of daily rainfall scenarios with interannual and multidecadal climate cycles for south Florida." Stochastic Environmental Research Risk Assessment., Vol. 23, No. 7, pp. 879-896. https://doi.org/10.1007/s00477-008-0270-2
  23. Kwon, H. H., Sivakumar, B., Moon, Y. I. and Kim, B. S. (2011). "Assessment of change in design flood frequency under climate change using a multivariate downscaling model and a precipitationrunoff model." Stochastic Environmental Research and Risk Assessment, Vol. 25, No. 4, pp. 567-581. https://doi.org/10.1007/s00477-010-0422-z
  24. Mailhot, A., Duchesne, S., Caya, D. and Talbot, G. (2007). "Assessment of future change in intensity-duration-frequency (IDF) curves for southern quebec using the canadian regional cliamte model (CRCM)." Journal of Hydrology, Vol. 347, No. 1, pp. 197-210. https://doi.org/10.1016/j.jhydrol.2007.09.019
  25. Mailhot, A., Kingumbi, A., Talbot, G. and Poulin, A. (2010). "Future changes in intensity and seasonal pattern of occurrence of daily and multi-day annual maximum precipitation over Canada." Journal of Hydrology, Vol. 388, No. 3, pp. 173-185. https://doi.org/10.1016/j.jhydrol.2010.04.038
  26. Malcolm. M. R., Cawley, G. C., Harpham, C., Wilby, R. L. and Clare, M. G. (2006). "Downscaling heavy precipitation over the united kingdom: A Comparison of Dynamical and Statistical Methods and their Future Scenarios." International Journal of Climatology., Vol. 26, No. 10, pp. 1397-1415. https://doi.org/10.1002/joc.1318
  27. Matsuyma, Y. (2011). "Hidden markov model based on alpha-EM algorithm : Discrete and Continuous Alpha-HMMs." International Joint Conference, Vol. 7, No. 5, pp. 808-816.
  28. Meehl, G. A., Zwiers, F., Evans, J., Knutson, T., Mearns, L. and Whetton, P. (2000). "Trends in extreme weather and climate events: Issues related to modeling extremes in projections of future climate change." Bulletin of the American Meteorological Society, Vol. 81, No. 3, pp. 427-436. https://doi.org/10.1175/1520-0477(2000)081<0427:TIEWAC>2.3.CO;2
  29. Min, Y. M., Kryjov, V. N. and Oh, J. H. (2011). "Probabilistic interpretation of regression-based downscaled seasonal ensemble predictions with the estimation of uncertainty." Journal of Geophysical Research: Atmospheres (1984-2012), Vol. 116, No. D8. DOI : 10.1029/2010JD015284.
  30. Min, Y. M., Kryjov, V. N. and Park, C. K. (2009). "A probabilistic multimodel ensemble approach to seasonal prediction." Weather and Forecasting, Vol. 24, No. 3, pp. 812-828. https://doi.org/10.1175/2008WAF2222140.1
  31. Muhammad, Z. H., Asaad, Y. S. and Bruce, W. M. (2011). "Comparison of SDSM and LARS-WG for simulation and downscaling of extreme precipitation events in a watershed." Stochastic Environmental Research and Risk Assessment, Vol. 25, No. 4, pp. 475-484. https://doi.org/10.1007/s00477-010-0416-x
  32. Palmer, T., Andersen, U., Cantelaube, P., Davey, M., Deque, M., Doblas-Reyes, F. J., Feddersen, H., Graham, R., Gualdi, S., Gueremy, J. F., Hagedorn, R., Hoshen, M., Keenlyside, Noel, Latif, Mojib, Lazar, A., Maisonnave, E., Marletto, V., Morse, A. P., Orfila, B., Rogel, P., Terres, J. M. and Thomsen, M. C. (2004). "Development of a european multi-model ensemble system for seasonal to inter-annual prediction (DEMETER)." Bulletin of the American Meteorological Society, Vol. 85 No. 6. pp. 853-872. DOI : 10.1175/BAMS-85-6-853.
  33. Shukla, J., Marx, L., Paolino, D., Straus, D., Anderson, J., Ploshay, J., Brankovic, C., Palmer, T., Chang, Y., Schubert, S., Suarez, M. and Kalnay, E. (2000). "Dynamical seasonal prediction." Bulletin of the American Meteorological Society, Vol. 81, No. 11, pp. 2593-2606. https://doi.org/10.1175/1520-0477(2000)081<2593:DSP>2.3.CO;2
  34. Sohn, S. J., Tam, C. Y. and Ahn, J. B. (2013). "Development of a multimodel based seasonal prediction system for extreme droughts and floods: A Case Study for South Korea." International Journal of Climatology, Vol. 33, No. 4, pp. 793-805. https://doi.org/10.1002/joc.3464
  35. Sohn, S. J., Tam, C. Y., Ashok, K. and Ahn, J. B. (2012). "Quantifying the reliability of precipitation datasets for monitoring large-scale East Asian precipitation variations." International Journal of Climatology, Vol. 32, No. 10, pp. 1520-1526. https://doi.org/10.1002/joc.2380
  36. Wang, B., Kang, I. S. and Lee, J. Y. (2004). "Ensemble simulations of asian-australian monsoon variability by 11 AGCMs." Journal of Climate, Vol. 17, No. 4, pp. 803-818. https://doi.org/10.1175/1520-0442(2004)017<0803:ESOAMV>2.0.CO;2
  37. Willems, P. and Vrac, M. (2011). "Statistical precipitation downscaling for small-scale hydrological impact investigations of climate change." Journal of Hydrology, Vol. 402, No. 3, pp. 193-205. https://doi.org/10.1016/j.jhydrol.2011.02.030

Cited by

  1. Development of Radar Tracking Technique for the Short -Term Rainfall Field Forecasting- vol.48, pp.12, 2015, https://doi.org/10.3741/JKWRA.2015.48.12.995