摘要
本文将AMSR-E卫星微波遥感海表温资料运用到渤黄东海海表面温度短期数值预报模式当中。数值预报模式利用伴随方法实现了预报模式的初值场优化。微波遥感海表温资料与海表面温度短期数值预报模式有机结合后的试验结果表明:将预报结果和船舶报资料进行比对时,将遥感资料引入到数据同化的结果要明显优于仅同化船舶报资料的结果,且均方差大部分都小于0.8℃;将预报结果和旬平均场资料进行比对时,将遥感资料引入到数据同化的结果和仅同化船舶报资料的结果在整体上一致,个别月份优于仅同化船舶报资料的结果,且均方差大部分都小于0.5℃,最小的部分甚至可以达到0.2℃。在本文研究中发现将AMSR-E卫星微波遥感资料引入到数据同化中,在将预报结果和船舶报资料进行比对时,可以提高海表温度的预报精度。
The AMSR-E satellite microwave remote sensing data are used to the sea surface temperature（SST） numerical prediction model in the Bohai sea,the Yellow sea,and the East China Sea.The model is used for the optimization of initial condition with the adjoint method of assimilation.The experiment of assimilating microwave remote sensing SST data shows the following results.When comparing the predicting results with the hourly ships-report data,the predicting results of assimilating both the remote sensing SST data and the hourly ships-report data are better than those of only assimilating the hourly ships-report data in general.And most of the mean square errors are smaller than 0.8℃ with assimilating two kinds of data.However,when comparing the predicting results with the ten-days averaged SST field,the predicting results of assimilating both the remote sensing SST data and the hourly ships-report data are consistent with those of only assimilating the hourly ships-report data,and are better in few months.And the most of the mean square errors are smaller than 0.5℃ and the minimum value even can reach 0.2℃.So the assimilation of remote sensing SST data can improve the predicting precision of SST.
出处
《海洋湖沼通报》
CSCD
北大核心
2011年第4期25-31,共7页
Transactions of Oceanology and Limnology
基金
国家重点基础研究发展计划项目(2007CB411807)
卫星海洋环境动力学国家重点实验室开放研究基金(SOED0708)
国家科技支撑计划项目(2007BAC03A0606)资助
关键词
数据同化
伴随方法
遥感海表温资料
海表温度数值预报
渤黄东海
data assimilation
adjoint method
remote sensing SST data
SST Numerical forecast model
Bohai sea
Yellow sea and East China Sea
