Journal of The Korean Society of Agricultural Engineers (한국농공학회논문집)

The Korean Society of Agricultural Engineers (한국농공학회)
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Applicability of a Multiplicative Random Cascade Model for Disaggregation of Forecasted Rainfalls

예보강우 시간분해를 위한 Multiplicative Cascade 모형의 적용성 평가

  • Kim, Daeha (Climate Application Department, APEC Climate Center) ;
  • Yoon, Sun-Kwon (Climate Application Department, APEC Climate Center) ;
  • Kang, Moon Seong (Department of Rural Systems Engineering, Research Institute of Agriculture and Life Sciences, Institute of Green Bio Science and Technology, Seoul National University) ;
  • Lee, Kyung-do (National Academy of Agricultural Science, Rural Development Administration)
  • Received : 2016.09.06
  • Accepted : 2016.09.26
  • Published : 2016.09.30
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Abstract

High resolution rainfall data at 1-hour or a finer scale are essential for reliable flood analysis and forecasting; nevertheless, many observations, forecasts, and climate projections are still given at coarse temporal resolutions. This study aims to evaluate a chaotic method for disaggregation of 6-hour rainfall data sets so as to apply operational 6-hour rainfall forecasts of the Korean Meteorological Association to flood models. We computed parameters of a state-of-the-art multiplicative random cascade model with two combinations of cascades, namely uniform splitting and diversion, using rainfall observations at Seoul station, and compared statistical performance. We additionally disaggregated 6-hour rainfall time series at 58 stations with the uniform splitting and evaluated temporal transferability of the parameters and changes in multifractal properties. Results showed that the uniform splitting outperformed the diversion in reproduction of observed statistics, and hence is better to be used for disaggregation of 6-hour rainfall forecasts. We also found that multifractal properties of rainfall observations has adequate temporal consistency with an indication of gradually increasing rainfall intensity across South Korea.

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References

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