Evaluation of a radar-based storm nowcasting method in the Three Gorges
YANG Wenyu1, LI Zhe1, NI Guangheng1, HONG Yang1, Ali Zahraei2
1. State Key Laboratory of Hydroscience and Engineering, Tsinghua University, Beijing 100084, China;
2. Cooperative Remote Sensing Science and Technology Center, National Oceanic and Atmospheric Administration, New York NY 10031, USA
Abstract：A pixel-based nowcasting algorithm (PBN) was applied at the Three Gorges Region to forecast the rainfall in the short-term. During the 2010 summer, 11 rainfall events gathered with radar were used to evaluate the algorithm performance with four performance statistics including the correlation coefficient, probability of detection, false alarm ratio and critical success indes. The correlation coefficient of the one-hour forecast results is close to 0.6, which suggests that the PBN algorithm effectively tracks and predicts rainfall events within an hour of their occurrence. An analysis of four rainfall events using these performance statistics suggested that the PBN algorithm is a promising nowcasting platform for typical stratiform rainfall events over a large area. However, the algorithm still cannot accurately forecast rainfall with several convective centers.
杨文宇, 李哲, 倪广恒, 洪阳, Ali Zahraei. 基于天气雷达的长江三峡暴雨临近预报方法及其精度评估[J]. 清华大学学报（自然科学版）, 2015, 55(6): 604-611.
YANG Wenyu, LI Zhe, NI Guangheng, HONG Yang, Ali Zahraei. Evaluation of a radar-based storm nowcasting method in the Three Gorges. Journal of Tsinghua University(Science and Technology), 2015, 55(6): 604-611.
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