| 一个集合海浪预报系统及其初步试验 |
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| 引用本文： | 孙明华.一个集合海浪预报系统及其初步试验[J].应用气象学报,2011,22(6):673-680. |
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| 作者姓名： | 孙明华 |
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| 作者单位： | 国家气象中心，北京 100081 |
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| 基金项目： | 国家973计划项目“台风登陆前后异常变化及机理研究”（2009CB421500） |
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| 摘 要： | 使用集合天气预报系统的多个成员的风场预报来驱动海浪模式WAVEWATCH Ⅲ, 计算出含多个成员的海浪预报场，并相应开发出各海浪要素的集合预报产品，如集合平均、离散度、集合概率等，建立了一个集合海浪数值预报系统。使用该系统进行了2007年9—10月为期两个月的预报试验，利用太平洋和大西洋海域范围的浮标观测资料对系统的预报水平的初步检验分析显示，该集合海浪预报方法能够有效地将传统的确定性预报扩展到概率预报领域，且集合平均的预报水平要优于单一的确定性预报，采用集合预报方法可以提供单纯确定性预报所不能够提供的额外信息，具有较好的应用潜力。
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| 关 键 词： | 集合预报 海浪数值预报 WAVEWATCH Ⅲ 概率 |
| 收稿时间： | 3/9/2011 12:00:00 AM |
| 修稿时间： | 8/3/2011 12:00:00 AM |
An Ensemble Ocean Wave Forecast System and Preliminary Experiment |
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| Sun Minghua.An Ensemble Ocean Wave Forecast System and Preliminary Experiment[J].Quarterly Journal of Applied Meteorology,2011,22(6):673-680. |
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| Authors: | Sun Minghua |
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| Affiliation: | National Meteorological Center, Beijing 100081 |
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| Abstract: | The basic methods of ensemble wave prediction at home and abroad and an ensemble wave numerical forecast system are introduced. The system is established by running the operational wave model WAVEWATCH Ⅲ using wind data from the 15 members' ensemble weather forecast system, which is based on the T213L31 model and operational running in China National Meteorological Center. The ensemble model calculates 15 members wave field, including one control forecast and 14 perturbation members forecast. The model computes the waves over all the oceans up to 10 days at 12:00 with 1° by 1° resolution. Based on hot initialization, the model uses the 12 h wave hindcast as its initial field. Through the information extraction and processing from the 15 member's wave fields, the system produces the ensemble wave products such as ensemble mean and spread, spaghetti charts and probability charts. Forecast experiment for the period from 1 Sep to 31 Oct in 2007 is done using the system and buoys data in the Pacific and Atlantic at the same period. The main verifying indexes are bias and root mean square error. For the mean monthly bias of 10 m wind speed and significant wave height, the performance of the ensemble mean is better than the control forecast, however both of them have a relatively low system deviation and one cause is that the spin up time of the system may not be long enough. For the monthly root mean square error, the ensemble mean of 10 m wind speed is lower than the control forecast by 3—12 percentage for the different forecast periods, meanwhile the ensemble mean of significant wave height is lower than the control forecast by 3—17 percentage with consistent variation trend. Comparing 15 ensemble members' forecast to the Buoy_46006 data, it shows that the ensemble members can follow the changes of the observation well and cover the variation range of the observation other than the deterministic forecast. In summary, the verification results show that the ensemble technique can provide a successful method of extending the standard deterministic forecasts to the probabilistic domain and the prediction skill of the ensemble mean is better than that of one single deterministic forecast. The ensemble method could provide additional information that could not be gleaned from a purely deterministic approach and has a good prospect of application in the field of wave forecast. |
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