| 黄、渤海冷空气海浪场的集合预报试验 |
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| 引用本文： | 王亚男,王庆元,刘彬贤. 黄、渤海冷空气海浪场的集合预报试验[J]. 海洋学报, 2015, 37(9): 10-16 |
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| 作者姓名： | 王亚男 王庆元 刘彬贤 |
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| 作者单位： | 天津市气象台, 天津 300074 |
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| 基金项目： | 国家公益行业(气象)科研专项(GYHY201006034)。 |
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| 摘 要： | 利用欧洲集合天气预报系统51个预报风场驱动SWAN海浪模式,对黄、渤海2013年12月-2014年2月期间受冷空气影响的海浪场进行数值模拟试验,并利用浮标观测资料对海浪集合预报结果进行初步检验分析,结果显示:从逐时平均偏差结果可知,24h预报时效内集合平均与控制预报性能相近,48~72h预报时效内,集合平均明显优于控制预报,但均比实况偏小;集合分位值(75、90百分位值和极端值)明显优于集合平均,且预报时效越长,优势越明显,集合预报极端值与实况相当或略偏大;从逐24h平均偏差结果可知,集合分位值(75、90百分位值和极端值)比集合平均和控制预报更接近实况。总的分析表明:集合分位值(75、90百分位值和极端值)对受冷空气影响的海浪场具有较强的分辨能力,可以提高对海浪场的预报水平,且有较好的应用潜力。
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| 关 键 词： | 集合海浪预报 SWAN海浪模式 冷空气 |
| 收稿时间： | 2014-09-12 |
| 修稿时间： | 2015-06-10 |
The ensemble wave forecast and test of cold air wave by using SWAN model in the Bohai Sea and the Yellow Sea |
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| Wang Y,Wang Qingyuan and Liu Binxian. The ensemble wave forecast and test of cold air wave by using SWAN model in the Bohai Sea and the Yellow Sea[J]. Acta Oceanologica Sinica (in Chinese), 2015, 37(9): 10-16 |
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| Authors: | Wang Y Wang Qingyuan Liu Binxian |
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| Affiliation: | Tianjin Meteorological Observatory, Tianjin 300074, China |
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| Abstract: | In the paper,a wave forecast system is established by running the wave model SWAN (Simulating Waves Nearshore). The forcing wind field in this system is reconstructed by the 51 members of EC ensemble weather forecast system. Then,a case study of the cold air during December 2013 to February 2014 is conducted to analysis the features of wave effected by the cold air using this system. Furthermore,using buoys data,the system forecasts are verified and compared. The main results are as follows: for the view of hourly mean bias,in 24 h forecast period the performance of ensemble mean is similar to control forecast,in 48 to 72 h forecast period the performance of ensemble mean is better than control forecast. The forecast of ensemble mean and control forecast are smaller than the reality. In both periods,the performance of ensemble statistics (75%,90% and extreme value) is better than control forecast and especially better in the long period of validity. Meanwhile,the forecast of ensemble extreme value is equal to or slightly larger than the reality; for the view of 24 hourly mean bias,the products of ensemble statistics (75%,90% and extreme value) are closer to the reality than the ensemble mean and control forecast value. To sum up,the products of ensemble statistics (75%,90% and extreme value) have higher accuracy of cold wave field. Conclusions show this system can improve the forecast level of wave influenced on cold air and have a good prospect of application. |
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| Keywords: | ensemble wave prediction SWAN cold air |
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