基于演化算符的南海海面高度异常中长期统计预报

李美莲; 金慕君; 纪增华; 李威; 梁康壮

doi:10.12284/hyxb2021185

基于演化算符的南海海面高度异常中长期统计预报

doi: 10.12284/hyxb2021185

李美莲^1,,
金慕君¹,
纪增华¹,
李威^{1, 2, ,},
梁康壮¹

1.
天津大学海洋科学与技术学院，天津 300072
2.
天津市海洋气象重点实验室，天津 300074

基金项目: 国家自然科学基金（41876014）

详细信息

作者简介:
李美莲（1999-），女，广东省江门市人，主要从事海洋预报等方向研究。E-mail:limeilian@tju.edu.cn

通讯作者:
李威，男，教授，主要从事海洋数值预报、海洋数值模拟等方向研究。E-mail:liwei1978@tju.edu.cn

中图分类号: P731.3
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- 文章访问数: 145
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- PDF下载量: 33
- 被引次数: 0
出版历程
- 收稿日期: 2020-10-31
- 修回日期: 2021-01-28
- 网络出版日期: 2021-12-10
- 刊出日期: 2021-12-30

Medium and long term statistical prediction of sea surface height anomaly in the South China Sea based on evolutionary operator

1.
School of Marine Science and Technology, Tianjin University, Tianjin 300072, China
2.
Tianjin Key Laboratory for Oceanic Meteorology, Tianjin 300074, China

摘要

摘要: 水下移动平台行动时需要1～3个月左右海洋数值预测预报结果，但是当前数值预报技术受对应的气象驱动场预报时效的限制，难以提供10 d以上的数值预报产品。鉴于海水在动力热力上具有较大的惯性，海洋内区有其自身的演化规律，本研究设计了一种基于演化算符的统计预测方法，利用历史卫星遥感资料构建海洋状态变量中长期演化矩阵，并结合惯性预报模型，构建了最终的南海海洋中长期统计预报模型，能够提供1～60 d逐日的南海海面高度异常预测结果，开展数值试验验证了该方法的有效性，结果表明，在起报后15 d内，预报结果与卫星资料的相关系数均大于0.8，在起报60 d内，相关系数仍高于0.6。
- 海洋预报 /
- 演化算符 /
- 中长期时效
Abstract: When performing work, underwater platforms usually need about 1-month to 3-months ocean numerical forecasts results. However, the current numerical forecasting technology is limited to the corresponding weather-driven field forecasting, and it is difficult to provide numerical forecast products for more than 10 days. Considering that the seawater itself has large inertia physically, and the inner ocean area has its own evolutionary principles, a statistical prediction method based on evolutionary operator is proposed. The method uses historical satellite remote sensing data to construct a long-term evolution matrix of ocean state variables, and then combines with the inertial prediction model. The final medium- and long-term statistical prediction model of the South China Sea is constructed, which can provide the prediction results for 1 d to 60 d of daily sea surface height anomaly in the South China Sea. We carry out the numerical experiments to show the effectiveness of the method. The results show that the correlation coefficients between the forecast results and the satellite data are all higher than 0.8 within 15 days and higher than 0.6 within 60 days after the start date of forecast.
- ocean forecast /
- evolution operator /
- medium- and long-range

HTML全文

图 1 3种预报方法与真实值的相关系数

Fig. 1 Correlation coefficients between three forecasting methods and real values

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图 2 3种预报方法与真实值的均方根误差

Fig. 2 Root mean square error between three forecasting methods and real values

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图 3 海面高度异常统计预报结果与卫星观测结果

Fig. 3 Statistical prediction results and satellite observation results of sea surface height anomalies

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图 4 海面高度异常预测结果与卫星观测结果相对于预测起始点的增量

Fig. 4 The increment of prediction results and satellite observation results relative to the predicted starting point of sea surface height anomaly

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图 5 演化算符预报与惯性预报方差的曲线拟合

Fig. 5 Curve fitting of evolutionary operator prediction and inertial prediction error

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图 6 综合模型与3种模型的均方根误差与相关系数对比

a. 4种预报方法与真实值的均方根误差；b. 4种预报方法与真实值的相关系数

Fig. 6 Comparison of root mean square error and correlation coefficients between the comprehensive model and the three models

a. Four forecasting methods with real values root mean square error; b. correlation coefficients between four forecasting methods and real values

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图 7 选取的截面

Fig. 7 Selected sections

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图 8 综合模型与3种模型的时间−站点图

Fig. 8 Time-to-site diagram of the synthesis model and the three models

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