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王丽芳, 漆梁波, 周伟, 王璐璐, 王轲. 2021: 频率匹配技术在暴雨预报中的应用及改进分析. 暴雨灾害, 40(4): 352-361. DOI: 10.3969/j.issn.1004-9045.2021.04.003
引用本文: 王丽芳, 漆梁波, 周伟, 王璐璐, 王轲. 2021: 频率匹配技术在暴雨预报中的应用及改进分析. 暴雨灾害, 40(4): 352-361. DOI: 10.3969/j.issn.1004-9045.2021.04.003
WANG Lifang, QI Liangbo, ZHOU Wei, WANG lulu, WANG ke. 2021: On the application and improvement of the frequency matching method to rainstorm forecasts. Torrential Rain and Disasters, 40(4): 352-361. DOI: 10.3969/j.issn.1004-9045.2021.04.003
Citation: WANG Lifang, QI Liangbo, ZHOU Wei, WANG lulu, WANG ke. 2021: On the application and improvement of the frequency matching method to rainstorm forecasts. Torrential Rain and Disasters, 40(4): 352-361. DOI: 10.3969/j.issn.1004-9045.2021.04.003

频率匹配技术在暴雨预报中的应用及改进分析

On the application and improvement of the frequency matching method to rainstorm forecasts

  • 摘要: 利用欧洲中期天气预报中心和美国国家环境预报中心2017年5—8月逐日降水预报资料及同时段MICAPS降水观测资料,采用频率匹配技术对江淮流域夏季降水预报进行模式偏差订正及改进技术探讨。结果表明:(1)模式对小雨预报偏多,存在大量空报;对大雨及以上降水预报偏少,存在较大漏报。(2)偏差订正通过下调小量级降水、上调大量级降水,使各量级降水的强度和面积偏差均得到一定程度改善,降水量级两端订正效果明显,订正后小雨和暴雨准确率显著提升。(3)偏差订正对暴雨落区预报的改进效果与过程相关,个例分析表明:对于雨带位置预报较准确的大范围梅雨锋暴雨,偏差订正后暴雨TS评分明显提升;对于副高边缘的小范围暴雨以及雨带位置预报失误的梅雨锋暴雨或台风暴雨,偏差订正后暴雨TS评分改善不明显甚至降低。(4)针对上述问题,提出了系数动态调整和模式集成的改进思路,即对于平均雨量5 mm以下的小范围暴雨,适当上调订正系数;平均雨量在15 mm以上的大范围暴雨,适当下调订正系数。模式集成订正可有效提高暴雨TS评分。

     

    Abstract: Based on the daily precipitation forecast data of European Centre for Medium Range Weather Forecasts and National Center for Environmental Forecasting from May to August in 2017, combining with observation data during the same time period, the frequency matching technique is used to correct the model bias of summer precipitation forecast in Jianghuai River basin, and improvement to the scheme is also discussed. The following four conclusions are drawn from this study. (1) The model has significant false alarm forecast of light rain and missed forecast for heavy rain and above. (2) By lowering the precipitation with low intensity and raising the precipitation with high intensity, the intensity and area forecast skills in different precipitation magnitudes are improved to some extent. The correction effect is more obvious at both ends of precipitation magnitude, the accuracy of light rain and torrential rain forecast is significantly improved after the bias correction. (3) The improvement effect of rainstorm area forecast depends on the precipitation type. Typical case analysis shows that: for the large area Meiyu front rainstorms with more accurate forecast of rain belt location, the rainstorm TS score is significantly improved after bias correction. For rainstorms in a small area at the periphery of the subtropical high and the Meiyu front rainstorm or typhoon rainstorm with inaccurate forecast of rain belt location, the improvement of rainstorm TS score is not obvious or even lower after the bias correction. (4) To solve the above problems, the improvement ideas of dynamic coefficient adjustment and model integration are put forward, i.e., for small area rainstorm with average rainfall of 5 mm or less, the coefficient should be appropriately increased, while for large area rainstorm with average rainfall of 15 mm or above, the coefficient should be lowered appropriately. Model integration can effectively improve the rainstorm TS score.

     

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