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http://dx.doi.org/10.3741/JKWRA.2017.50.8.563

Assessment of predictability of categorical probabilistic long-term forecasts and its quantification for efficient water resources management  

Son, Chanyoung (Hydrometeorological Cooperation Center)
Jeong, Yerim (Hydrometeorological Cooperation Center)
Han, Soohee (Hydrometeorological Cooperation Center)
Cho, Younghyun (Korea Water Resources Corporation (K-water))
Publication Information
Journal of Korea Water Resources Association / v.50, no.8, 2017 , pp. 563-577 More about this Journal
Abstract
As the uncertainty of precipitation increases due to climate change, seasonal forecasting and the use of weather forecasts become essential for efficient water resources management. In this study, the categorical probabilistic long-term forecasts implemented by KMA (Korea Meteorological Administration) since June 2014 was evaluated using assessment indicators of Hit Rate, Reliability Diagram, and Relative Operating Curve (ROC) and a technique for obtaining quantitative precipitation estimates based on probabilistic forecasts was proposed. The probabilistic long-term forecasts showed its maximum predictability of 48% and the quantified precipitation estimates were closely matched with actual observations; maximum correlation coefficient (R) in predictability evaluation for 100% accurate and actual weather forecasts were 0.98 and 0.71, respectively. A precipitation quantification approach utilizing probabilistic forecasts proposed in this study is expected to enable water management considering the uncertainty of precipitation. This method is also expected to be a useful tool for supporting decision-making in the long-term planning for water resources management and reservoir operations.
Keywords
Categorical probabilistic long-term forecasts; Quantification; Precipitation;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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