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Correction of Gust Estimation in the Yellow and Bohai Seas and Adjacent Areas
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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。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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图 1 黄渤海及其邻近地区364个代表站分布
(数字为基准观测站序号)
Fig. 1 Distribution of 364 representative stations in the Yellow and Bohai Seas and adjacent areas
(the number denotes the order of benchmark observation stations)
图 2 2021年1月—2022年12月阵风系数方法拟合结果与小时内最大阵风散点图
Fig. 2 Scatter plots of gust factor fitting results and hourly maximum gust from Jan 2021 to Dec 2022
图 3 2021年1月—2022年12月12个基准观测站在不同风速级别下平均误差与接近时刻阵风比例散点图
Fig. 3 Scatter plot of mean error and the ratio of closer to instantaneous gust at different wind speed magnitudes for 12 benchmark observation stations from Jan 2021 to Dec 2022
图 4 2021年1月—2022年12月不同观测站差异系数、阵风系数拟合结果与小时内最大阵风间的拟合度散点图
Fig. 4 Scatter plot of the difference coefficient and goodness of fit between gust factor fitting results and hourly maximum gust at different observation stations from Jan 2021 to Dec 2022
图 5 2021年1月—2022年12月12个基准观测站的C在0~1之间以0.01步长增加时D的分布
Fig. 5 Distribution of D values for C values ranging from 0 to 1 with a step size of 0.01 for 12 benchmark observation stations from Jan 2021 to Dec 2022
图 6 2021年1月—2022年12月12个基准观测站经自然对数处理后的累计频率分布(a)及差值对比(b)
Fig. 6 Cumulative frequency distribution(a) and error comparison(b) after natural logarithm transformation for 12 benchmark observation stations from Jan 2021 to Dec 2022
图 7 2021年1月—2022年12月364个观测站经自然对数处理后的累计频率分布(a)及差值对比(b)
Fig. 7 Cumulative frequency distribution(a) and error comparison(b) after natural logarithm transformation for 364 observation stations from Jan 2021 to Dec 2022
图 9 2022年9月14日20:00—16日20:00台风梅花(2022)影响期间小时内最大阵风极大值(a)、阵风系数方法(b)及经GECO方法订正后(c)拟合结果为正偏差的观测站分布
Fig. 9 Maximum hourly gust during the impact of Typhoon Muifa from 2000 BT 14 Sep to 2000 BT 16 Sep in 2022(a), the distribution of stations with positive bias in fitting results of gusts by applying the gust factor method(b) and GECO method(c)
表 1 基准观测站信息
Table 1 Benchmark observation station information
序号 区站号 位置 海拔/m 1 54337 41.1°N，121.1°E 65 2 54497 40.1°N，124.3°E 13 3 54511 39.8°N，116.5°E 33 4 54539 39.4°N，118.9°E 8 5 54662 38.9°N，121.6°E 90 6 54727 36.7°N，117.6°E 122 7 54857 36.1°N，120.3°E 75 8 54778 37.2°N，122.5°E 61 9 58027 34.3°N，117.2°E 42 10 58150 33.8°N，120.3°E 1 11 58238 31.9°N，118.9°E 36 12 58362 31.4°N，121.5°E 6 
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表 2 2021年1月—2022年12月订正前后12个基准观测站对于风速为12 m·s-1及以上阵风拟合误差对比
Table 2 Comparison of fitting errors before and after correction for 12 benchmark observation stations with gusts no less than 12 m·s-1 from Jan 2021 to Dec 2022
序号 订正前平均误差/(m·s-1) 订正后平均误差/(m·s-1) 均方根误差减少率/% 1 -2.69 -1.40 19.14 2 -1.76 -0.66 12.72 3 -2.69 -1.43 16.44 4 -2.42 -1.24 17.33 5 -2.01 -0.70 12.78 6 -1.25 0.40 6.01 7 -1.45 -0.32 7.27 8 -1.97 -0.78 13.27 9 -3.56 -2.36 14.69 10 -1.80 -0.84 12.32 11 -2.90 -1.90 14.78 12 -3.00 -1.82 14.18
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表 3 2021年1月—2022年12月阵风系数方法对陆地及浮标观测站拟合误差对比
Table 3 Comparison of fitting errors of gust factor method for land and buoy observation stations from Jan 2021 to Dec 2022
统计量 风速范围/(m·s-1) 10.8~13.8 13.9~17.1 17.2~20.7 陆地样本量 48706 10374 1483 浮标样本量 4433 1866 544 陆地拟合误差标准差/(m·s-1) 2.705 3.516 4.979 浮标拟合误差标准差/(m·s-1) 1.830 2.082 2.236 陆地拟合误差平均值/(m·s-1) -2.47 -3.66 -5.54 浮标拟合误差平均值/(m·s-1) -0.60 -0.83 -1.21
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