| 飞机积冰预报算法对比及其集成预报模型研究 |
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| 引用本文： | 卞双双,何宏让,安豪,潘晓滨,张云.飞机积冰预报算法对比及其集成预报模型研究[J].气象,2019,45(10):1352-1362. |
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| 作者姓名： | 卞双双 何宏让 安豪 潘晓滨 张云 |
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| 作者单位： | 山东省临沂市气象台，临沂 276000; 国防科技大学气象海洋学院，南京 211101; 北京应用气象研究所，北京 100029,国防科技大学气象海洋学院，南京 211101,北京应用气象研究所，北京 100029,国防科技大学气象海洋学院，南京 211101,国防科技大学气象海洋学院，南京 211101 |
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| 基金项目： | 国家自然科学基金项目（41375106）资助 |
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| 摘 要： | 以人工增雨作业获取的飞机积冰实例资料为基础,利用WRF模式对51次飞机积冰过程进行数值模拟,对比分析了常用七种积冰预报算法对积冰潜势区和强度的预报效果,进而采用评分权重集成法建立了飞机积冰强度集成预报模型,并检验了其预报效果。结果表明:(1)假霜点温度经验法对2002年4月4日积冰个例的预报效果与实况一致,而其他积冰算法预报效果均与实况相差较大;(2)对51次飞机积冰预报效果进行统计检验发现,假霜点温度经验法的预报效果最好,积冰强度预报准确率为72.55%,其次是RAOB法,IC指数法和I积冰指数法次之,改进的IC指数法预报准确率最差,只有19.61%;(3)对比不同积冰算法建立的集成预报模型的预报效果发现,选用IC指数法、假霜点温度经验法、RAOB法进行集成预报时,预报准确率最高,且漏报率、偏弱率及偏强率均能控制在10%以内,比单一预报算法中的最高预报准确率提高了8%,且漏报率降低了4%,偏强率降低了8%。
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| 关 键 词： | 飞机积冰，数值模拟，积冰预报算法，评分权重法，集成预报模型 |
| 收稿时间： | 2018/6/6 0:00:00 |
| 修稿时间： | 2019/8/5 0:00:00 |
Comparative Analysis of Aircraft Icing Forecasting Algorithms and Research on Ensemble Prediction Model |
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| BIAN Shuangshuang,HE Hongrang,AN Hao,PAN Xiaobin and ZHANG Yun.Comparative Analysis of Aircraft Icing Forecasting Algorithms and Research on Ensemble Prediction Model[J].Meteorological Monthly,2019,45(10):1352-1362. |
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| Authors: | BIAN Shuangshuang HE Hongrang AN Hao PAN Xiaobin and ZHANG Yun |
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| Institution: | Linyi Meteorological Observatory of Shandong Province, Linyi 276000; College of Meteorology and Oceanography, National University of Defense Technology, Nanjing 211101; Beijing Institute of Applied Meteorology, Beijing 100029,College of Meteorology and Oceanography, National University of Defense Technology, Nanjing 211101,Beijing Institute of Applied Meteorology, Beijing 100029,College of Meteorology and Oceanography, National University of Defense Technology, Nanjing 211101 and College of Meteorology and Oceanography, National University of Defense Technology, Nanjing 211101 |
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| Abstract: | Based on the aircraft icing data which were obtained from the artificial rainfall enhancement, this paper uses the Weather Research and Forecasting Model to simulate 51 aircraft icing processes, contrasts and analyses the prediction results of icing potential area and intensity forecasted by seven kinds of commonly-used icing forecasting algorithms, then utilizes the score weight integration method to establish the ensemble forecasting model of aircraft icing intensity, and tests its forecasting effect. The results show that (1) in forecasting an icing case that occurred in 4 April 2002, the forecasting effect of the false frost point temperature empirical method is consistent with the actual condition but there are great differences between the effect forecasted by the other icing algorithms and the observed condition. (2) After the statistical test for the 51 aircraft icing forecast effects, the prediction effect of the false frost point temperature empirical method is the best, whose accurate rate of icing intensity forecast is up to 72.55%, followed by the RAOB method, IC index method and I icing index method, but that of improved IC index method is the poorest, only 19.61%. (3) By comparing the forecasting effects of the ensemble forecasting models established by different icing algorithms, we find that when using IC index method, the false frost point temperature empirical method, and RAOB method to forecast, the forecast accuracy rate is the highest, which is 8% higher than the best forecast accuracy by a single forecasting algorithm and the false negative rate, weak rate and strong rate can all be controlled within 10%, and the false negative rate is reduced by 4%, the strong rate is reduced by 8%. |
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| Keywords: | aircraft icing numerical simulation icing forecasting algorithms score weighting method ensemble prediction model |
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