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Climate Prediction by a Hybrid Method with Emphasizing Future Precipitation Change of East Asia

  • Lim, Yae-Ji (Department of Statistics, Seoul National University) ;
  • Jo, Seong-Il (Department of Statistics, Seoul National University) ;
  • Lee, Jae-Yong (Department of Statistics, Seoul National University) ;
  • Oh, Hee-Seok (Department of Statistics, Seoul National University) ;
  • Kang, Hyun-Suk (National Institute of Meteorological Research Korea Meteorological Administration)
  • 투고 : 20090700
  • 심사 : 20090900
  • 발행 : 2009.12.31

초록

A canonical correlation analysis(CCA)-based method is proposed for prediction of future climate change which combines information from ensembles of atmosphere-ocean general circulation models(AOGCMs) and observed climate values. This paper focuses on predictions of future climate on a regional scale which are of potential economic values. The proposed method is obtained by coupling the classical CCA with empirical orthogonal functions(EOF) for dimension reduction. Furthermore, we generate a distribution of climate responses, so that extreme events as well as a general feature such as long tails and unimodality can be revealed through the distribution. Results from real data examples demonstrate the promising empirical properties of the proposed approaches.

키워드

참고문헌

  1. Glahn, H. (1963). Canonical correlation and its relationship to discriminate analysis and multiple regression, Journal of the Atmospheric Sciences, 25, 23-31
  2. Greene, A. M., Goddard, L. and Lall, U. (2006). Probabilistic multimodel regional temperature change projections, Journal of Climate, 19, 4326-4343 https://doi.org/10.1175/JCLI3864.1
  3. Landman, W. A. and Goddard, L. (2002). Statistical recalibration of GCM forecasts over southern Africa using model output statistics, Journal of Climate, 15, 2038-2055 https://doi.org/10.1175/1520-0442(2002)015<2038:SROGFO>2.0.CO;2
  4. Parzen, E. (1962). On estimation of a probability density function and mode, The Annals of Mathematical Statistics, 33, 1065-1076 https://doi.org/10.1214/aoms/1177704472
  5. Storch, H. V. and Zwiers, F. W. (1999). Statistical Analysis in Climate Research, Cambridge
  6. Wilks, D. S. (2006). Statistical Methods in the Atmospheric Sciences, Academic Press

피인용 문헌

  1. Multimodel ensemble forecasting of rainfall over East Asia: regularized regression approach vol.34, pp.14, 2014, https://doi.org/10.1002/joc.3938