| 黄渤海及其邻近地区阵风估测改进 |
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| 引用本文： | 胡海川, 钱传海, 渠鸿宇. 黄渤海及其邻近地区阵风估测改进. 应用气象学报, 2023, 34(6): 668-680. DOI: 10.11898/1001-7313.20230603. |
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| 作者姓名： | 胡海川 钱传海 渠鸿宇 |
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| 作者单位： | 1.国家气象中心, 北京 100081;2.中国气象局气象发展与规划院, 北京 100081 |
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| 基金项目： | 国家重点研发计划(2022YFC3004200)； |
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| 摘 要： | 为定量化下垫面等局地性因素对阵风拟合效果的影响, 利用2021年1月—2022年12月风速观测数据, 分析阵风系数方法在黄渤海及其邻近地区不同观测站拟合能力差异的原因, 并基于差异系数及频率匹配构建阵风估测改进(gust estimation correction, GECO)方法, 对阵风系数方法拟合结果进行订正。结果表明:阵风系数方法的拟合结果随风速增加更倾向于整点观测时刻阵风, 使用小时内最大阵风与整点观测时刻阵风计算得到的差异系数可以定量表征观测站局地特性对阵风系数拟合结果的影响。对差异系数大的观测站, 阵风系数方法对其强阵风拟合结果的负偏差也较大, 需对其进行更大幅度订正。基于12个基准观测站构建的GECO方法同样适用于黄渤海及其邻近地区的364个观测站。对于风速为12 m·s-1及以上和16 m·s-1及以上的阵风, 经GECO方法订正后的均方根误差较阵风系数方法分别减少12.3%和11.5%。对台风梅花(2212)的检验显示, GECO方法能够有效提升大级别阵风的估测能力, 可为阵风客观预报方法改进提供参考。
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| 关 键 词： | 阵风系数 阵风估测 阵风预报 差异系数 频率匹配 |
| 收稿时间： | 2023-08-08 |
| 修稿时间： | 2023-10-17 |
Correction of Gust Estimation in the Yellow and Bohai Seas and Adjacent Areas |
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| Hu Haichuan, Qian Chuanhai, Qu Hongyu. Correction of gust estimation in the Yellow and Bohai Seas and adjacent areas. J Appl Meteor Sci, 2023, 34(6): 668-680. DOI: 10.11898/1001-7313.20230603. |
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| Authors: | Hu Haichuan Qian Chuanhai Qu Hongyu |
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| Affiliation: | 1. National Meteorological Center, Beijing 100081;2. CMA Institute for Development and Programme Design, Beijing 100081 |
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| Abstract: | Due to the influence of local factors such as underlying surface, the fitting performance of the gust factor method can vary among different observation stations in the Yellow and Bohai Seas and adjacent areas. Therefore, based on observations from January 2021 to December 2022, causes for different performances are analyzed, and a gust estimation correction (GECO) method is proposed based on the coefficient of difference and frequency matching to correct fitting results of the gust factor method. It's concluded that, as the gust wind speed increases, the fitting results tend to be biased towards the gust at the whole observation time rather than the maximum gust within the hour. The difference coefficient calculated from the maximum gust within the hour and the gust at the whole hour observation time can quantitatively characterize the influence of local characteristics of the observation station on fitting results. For stations with large difference coefficients, the gust factor method has a larger negative bias in fitting the strong gusts, so it needs to be corrected to a greater extent. Conversely, for stations with small differences, the gust factor method has a smaller negative bias in fitting the strong gusts, so it only needs to be corrected to a smaller extent. GECO method constructed based on statistical results of 12 benchmark observation stations can also be applied to 364 stations in the Yellow and Bohai Seas and adjacent areas, demonstrating the feasibility of quantitatively characterizing the influence of local factors such as underlying surface on fitting results of gusts, as well as the stability of GECO method. In the comparative test of fitting errors for 364 stations in the Yellow and Bohai Seas and adjacent areas, after correction by GECO method, the root mean square error of gusts above 12 m·s-1 and 16 m·s-1 is reduced by 12.3% and 11.5%, respectively, compared to the gust factor method. Although GECO method may slightly increase the fitting error of weak gusts, it can significantly improve the fitting performance of strong gusts. In the verification during the impact of Typhoon Muifa from 14 September to 16 September in 2022, the fitting performance of strong gusts is also significantly improved after correction by GECO method. The improvement of fitting performance is the basis for improving forecasting skill. Combining GECO method with other objective gust forecasting methods can further enhance the forecasting service capability of gusts. |
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| Keywords: | gust factor gust estimation gust forecast difference coefficient frequency matching |
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