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Long-term Forecast of Seasonal Precipitation in Korea using the Large-scale Predictors  

Kim, Hwa-Su (Department of Atmospheric Science, Kongju National University)
Kwak, Chong-Heum (Department of Atmospheric Science, Kongju National University)
So, Seon-Sup (Department of Atmospheric Science, Kongju National University)
Suh, Myoung-Seok (Department of Atmospheric Science, Kongju National University)
Park, Chung-Kyu (Climate Prediction Division, Climate Bureau, Korea Meteorological Administration)
Kim, Maeng-Ki (Department of Atmospheric Science, Kongju National University)
Publication Information
Journal of the Korean earth science society / v.23, no.7, 2002 , pp. 587-596 More about this Journal
Abstract
A super ensemble model was developed for the seasonal prediction of regional precipitation in Korea using the lag correlated large scale predictors, based on the empirical orthogonal function (EOF) analysis and multiple linear regression model. The predictability of this model was also evaluated by cross-validation. Correlation between the predicted and the observed value obtained from the super ensemble model showed 0.73 in spring, 0.61 in summer, 0.69 in autumn and 0.75 in winter. The predictability of categorical forecasting was also evaluated based on the three classes such as above normal, near normal and below normal that are clearly defined in terms of a priori specified by threshold values. Categorical forecasting by the super ensemble model has a hit rate with a range from 0.42 to 0.74 in seasonal precipitation.
Keywords
seasonal prediction; super ensemble model; predictors; long range forecast;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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