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毛旭, 刘鑫华, 杨波. 2023. 一种优化的基于对流可分辨模式的飞机积冰潜势概率预报方法[J]. 大气科学, 47(5): 1525−1540. doi: 10.3878/j.issn.1006-9895.2207.21235
引用本文: 毛旭, 刘鑫华, 杨波. 2023. 一种优化的基于对流可分辨模式的飞机积冰潜势概率预报方法[J]. 大气科学, 47(5): 1525−1540. doi: 10.3878/j.issn.1006-9895.2207.21235
MAO Xu, LIU Xinhua, YANG Bo. 2023. An Optimized Probabilistic Prediction Method for Aircraft Icing Potential Based on a Convection-Allowing Model [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 47(5): 1525−1540. doi: 10.3878/j.issn.1006-9895.2207.21235
Citation: MAO Xu, LIU Xinhua, YANG Bo. 2023. An Optimized Probabilistic Prediction Method for Aircraft Icing Potential Based on a Convection-Allowing Model [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 47(5): 1525−1540. doi: 10.3878/j.issn.1006-9895.2207.21235

一种优化的基于对流可分辨模式的飞机积冰潜势概率预报方法

An Optimized Probabilistic Prediction Method for Aircraft Icing Potential Based on a Convection-Allowing Model

  • 摘要: 本文对飞机积冰概率预报方法进行了优化,该算法主要基于对流可分辨率数值模式输出的温湿层结结构进行计算,可输出高时空分辨率,且符合中国积冰情况的积冰潜势。相较于原始算法,从云层判断、对流云积冰、隶属函数三方面进行了优化。首先,优化后算法采用了更切合中国积冰分布的隶属函数。其次,使用随高度变化而变化的相对湿度阈值来判断云层,可以有效减少低层云和高层云的空报、中层云的漏报。第三,增加对流云中积冰条件的预报,进一步提高积冰潜势算法的预报准确率。通过对近600份国内飞机积冰报告的系统性检验评估,结果表明优化后的潜势预报方法在高阈值与低阈值区间预报效果均优于原始预报方法及传统IC算法。通过2020年3月陕西中南部的三次飞机飞机积冰场外探测个例检验,不仅对积冰条件的有无预报准确,而且在积冰强度方面也符合实际观测结果。

     

    Abstract: In this paper, a model-based aircraft icing potential probability prediction method is optimized. The algorithm is mainly based on the temperature and humidity output from a convection-allowing model, which can output the aircraft icing potential with high temporal and spatial resolution fitting the aircraft icing situation in China. Compared with the original algorithm, it is optimized from three aspects: cloud layer judgment, convective cloud aircraft icing, and the membership functions. First, the optimized algorithm adopts membership functions that are more suitable for aircraft icing accumulation in China. Second, the variation in the relative humidity threshold with height is used to judge cloud layers, which effectively decreases the missing reports of low- and high-level clouds and the false alarms of middle-level clouds. Third, the prediction of icing conditions in convective clouds is established separately to further improve the prediction accuracy of the icing potential algorithm. Systematically verifying nearly 600 pilot reports of domestic aircraft icing shows that the prediction effect of the optimized aircraft icing potential prediction method is better than that of the original prediction method and the traditional IC algorithm in the high and low threshold ranges. Verified by three cases of aircraft icing detection in central and southern Shanxi Province in March 2020, it is accurate in predicting the presence of icing conditions and consistent with the actual observation results in terms of icing intensity.

     

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