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气象:2022,48(1):84-95
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集合百分位融合法在广东台风降水预报中的改进
张华龙,程正泉,肖柳斯,吴乃庚,罗聪
(广东省气象台,广州 510640;广州市气象台,广州 511430;广东省生态气象中心,广州 510640)
Improvement of the Optimal Percentile Fusion Method Based on Ensemble Forecast of Typhoon Rainfall in Guangdong Province
ZHANG Hualong,CHENG Zhengquan,XIAO Liusi,WU Naigeng,LUO Cong
(Guangdong Meteorological Observatory, Guangzhou 510640;Guangzhou Meteorological Observatory, Guangzhou 511430;Guangdong Ecological Meteorology Center, Guangzhou 510640)
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投稿时间:2020-11-10    修订日期:2021-10-08
中文摘要: 基于欧洲中期天气预报中心(ECMWF)集合预报的客观检验结果,构建了针对广东台风降水的最优百分位融合产品,检验表明强降水风险评分(TS)较集合平均产品提升显著,预报时效越长,提升幅度越大,但预报偏差(Bias)与虚警率(FAR)也相应增大。最优百分位融合产品的强降水预报范围偏大与台风路径预报的发散度有较大关联,因融合产品在较大降水量级采用高百分位进行映射,强降水的融合结果与各成员强降水落区的并集接近,台风路径越发散,各成员强降水落区的空间位置通常也更发散,造成融合产品预报的强降水落区范围偏大。为克服这一缺陷,引入集合预报对某一降水阈值的概率预报指标,通过该指标判识可能存在明显空报的强降水预报,从而改进最优百分位融合产品,在测试期,改进后的融合产品暴雨TS在维持的情况下,Bias从1.27下降至1.03,FAR从0.51下降至0.43;预报时效越长,融合产品Bias的改进效果越显著,TS的提升幅度也越大。上述改进可为业务中提供强降水范围更合适、落区更准确的网格定量降水客观产品。
Abstract:Based on ECMWF ensemble forecast, the optimal percentile fusion product of typhoon rainfall in Guangdong Province is developed by using customized fusion parameters. Verification indicates that threat score (TS) of severe precipitation is significantly improved than the ensemble average product. The longer the forecast lead time, the greater the increment, but Bias and false alarm ratio (FAR) also become greater accordingly. The over-estimation of severe precipitation forecast is related to the divergence of typhoon path forecast. Since the fusion product uses high percentile field for mapping in large rainfall grades, the fusion result of severe precipitation is close to the union of severe rainfall locations of each member. When the typhoon paths are more dispersed, the spatial location of the severe precipitation area of each member is generally more divergent, resulting in the large range error of the severe rainfall area predicted by the fusion product. In order to solve this problem, a forecast index describing the probability of forecasting a certain precipitation threshold is introduced, which can effectively identify the heavy rainfall forecast samples with large false alarms but few hit alarms. Using the index, we are likely able to improve the optimal percentile fusion product. Under the condition of maintaining TS, the improved fusion products have Bias decreasing from 1.27 to 1.03 and FAR from 0.51 to 0.43 during the test period. Meanwhile, the longer the forecast time, the greater the improvement effect of Bias and TS of the fusion products. Therefore, the revised products can provide grid quantitative precipitation forecast with more appropriate severe precipitation scope and more accurate rainfall location in forecasting operation.
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基金项目:广东省科技计划项目(2018B020208004)、广东省气象局科技创新团队(GRMCTD202102、GRMCTD202004)、广东省重点领域研发计划项目(2019B111101002)、中国气象局气象预报业务关键技术发展专项[YBGJXM(2020)5A-04]和广东省气象局科学技术研究项目(GRMC2018Z05)共同资助
引用文本:
张华龙,程正泉,肖柳斯,吴乃庚,罗聪,2022.集合百分位融合法在广东台风降水预报中的改进[J].气象,48(1):84-95.
ZHANG Hualong,CHENG Zhengquan,XIAO Liusi,WU Naigeng,LUO Cong,2022.Improvement of the Optimal Percentile Fusion Method Based on Ensemble Forecast of Typhoon Rainfall in Guangdong Province[J].Meteor Mon,48(1):84-95.