基于遥感数据的温度剖面预报研究

作者：笪良龙  李韦华  韩梅  濮兴啸

单位：海军潜艇学院, 山东青岛266071

关键词：温度剖面 SST SSHA 最小二乘

分类号：P732

出版年·卷·期（页码）：2011·28·第六期（51-54）

摘要：

为了提高温度剖面的预报精度,提出了一种基于遥感数据的温度剖面预报方法。文中使用27个实测温度剖面和遥感SST、SSHA数据实现了对温度剖面的预报,并用该点的ARGO数据进行了检验。实验结果表明,将遥感数据同化到温度剖面的预报中是可行的,并能有效的提高温度剖面的预报精度。

In order to improve the predition accuracy of the temperature profile,a method for forecasting ocean temperature profile based on the satellite data is developed.By using 27 in situ temperature profiles data,remote sensing SST(Sea Surface Temperature) and SSHA(Sea Surface Height Anomaly) data,the prediction of the tem-perature profile is achieved.The predition result of the temperature profile has been validated with the ARGO(Array for Real-time Geostrophic Oceanography) data.The experiment result shows that it is feasible by assim-ilating the remote data into the forecasting of temperature profile,and it improves the forecasting accuracy of ocean temperature profile effectively.

参考文献：

[1] DeWitt P W.Modal decomposition of the monthly Gulf Stream/Kuroshio temperature fields[R].Naval Oceanographic Office Tech.1987:265-297. [2] Fox D N,Teague W J,Barron C N,et al.The Modular Ocean Data Assimilation System (MODAS)[J].Journal of Atmospheric and Oceanic Technology,2002,19(2):240-252. [3] Bruno D N,Rosalia S.Reconstructing Sythetic Profiles from surface data.American Meteorological Society[J].2004,21(2):693-703. [4] Eugenia Kalnay著,蒲朝霞等译.大气模式、资料同化和可预报性[M].北京气象出版社,2005. [5] 韩梅,魏亮.最优插值法在海温数据同化中的应用研究[J].海洋技术,2008,27(4):90-92.

服务与反馈：

【文章下载】【发表评论】【查看评论】【加入收藏】