海表面温度的变分同化预报模式:初始场的全局优化

高艳秋; 苏洁; 李磊; 吕咸青

doi:10.3969/j.issn.1001-909X.2015.01.001

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海洋学研究 ›› 2015, Vol. 33 ›› Issue (1) : 1-8. DOI: 10.3969/j.issn.1001-909X.2015.01.001

研究论文

海表面温度的变分同化预报模式:初始场的全局优化

高艳秋^1,2, 苏洁³, 李磊³, 吕咸青³

作者信息 +

Application of adjoint assimilation method in a sea surface temperature prediction model:global optimization of the initial field

GAO Yan-qiu¹, SU Jie², LI Lei², LV Xian-qing²

Author information +

文章历史 +

摘要

利用变分同化技术,将船舶报资料与海表面温度短期数值预报模式有机结合,实现了渤、黄、东海的海表面温度短期数值预报。本预报模式利用伴随方法实现了预报模式的全局优化,不但最大限度地利用了船舶报资料,而且初始温度场的调整由自动的数值迭代过程来实现。在渤、黄、东海海域,4个季节的典型月份的SST连续1个月的24 h后报结果与船舶报资料均方差均降至0.8 ℃以下。同化后海表面温度初始场的绝均差较同化前有显著下降。与以前所用的客观分析方法比较的结果表明,伴随同化的预报精度明显高于客观分析方法。

Abstract

Variational assimilation technique, in conjunction with the ship reported data, is applied to a short term numerical prediction model in order to realize automatic short term SST forecast in the Bohai, the Yellow and the East China Seas. The prediction model, using the adjoint assimilation method, achieves a global optimization of the initial SST field. Corresponding to the four typical months (February, May, August and November) of four quarters respectively in 2002, we do forecast for a month continuously. The results indicate that the root mean square error between the hindcasts of 24 successive hours and the ship reported data is reduced to below 0.8 ℃. The mean absolute errors of SST are reduced markedly, compared with the values before assimilation. The forecast accuracy is improved with the adjoint assimilation method compared with the results from the objective analysis method.

导出引用

高艳秋, 苏洁, 李磊, 吕咸青. 海表面温度的变分同化预报模式:初始场的全局优化[J]. 海洋学研究. 2015, 33(1): 1-8 https://doi.org/10.3969/j.issn.1001-909X.2015.01.001

GAO Yan-qiu, SU Jie, LI Lei, LV Xian-qing. Application of adjoint assimilation method in a sea surface temperature prediction model:global optimization of the initial field[J]. Journal of Marine Sciences. 2015, 33(1): 1-8 https://doi.org/10.3969/j.issn.1001-909X.2015.01.001

中图分类号： P731.31

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