| ZHANG Chunling,XU Jianping,BAO Xianwen,WANG Zhenfeng. 2013. An effectivemethod for improving the accuracy of Argo objective analysis. Acta Oceanologica Sinica, 32(7):66－77 |
| An effectivemethod for improving the accuracy of Argo objective analysis |
| An effectivemethod for improving the accuracy of Argo objective analysis |
| Received:April 11, 2012 Revised:October 15, 2012 |
| DOI：10.1007/s13131-013-0333-1 |
| Key words:gradient-dependent correlation scale background error covariance optimal interpolation spectrumanalysis Argo data |
| 中文关键词: gradient-dependent correlation scale background error covariance optimal interpolation spectrumanalysis Argo data |
| 基金项目:The Marine Public Welfare Special Funds, the State Oceanic Administration of China under contract No. 200705022; the Technology Special Basic Work, the Ministry of Science and Technology under contract No. 2012FY112300; the Basic Scientific Research Special Funds of the Second Institute of Oceanography, the State Oceanic Administration of China under contract No. JT0904. |
| Author Name | Affiliation | E-mail | | ZHANG Chunling | Institute ofMarine Environment, Ocean University of China, Qingdao 266003, China
Second Institute of Oceanography, State Oceanic Administration, Hangzhou 310012, China | zhangchunling81@163.com | | XU Jianping | Institute ofMarine Environment, Ocean University of China, Qingdao 266003, China
Second Institute of Oceanography, State Oceanic Administration, Hangzhou 310012, China
State Key Laboratory of Satellite Oceanography EnvironmentDynamics, Second Institute of Oceanography, State Oceanic Administration, Hangzhou 310012, China | | | BAO Xianwen | Institute ofMarine Environment, Ocean University of China, Qingdao 266003, China | | | WANG Zhenfeng | Marine HydrologicMeteorological Center, Command of Navy East China Sea Fleet, Ningbo 312122, China | |
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| Abstract: |
| Based on the optimal interpolation objective analysis of the Argo data, improvements are made to the empirical formula of a background error covariancematrixwidely used in data assimilation and objective analysis systems. Specifically, an estimation of correlation scales that can improve effectively the accuracy of Argo objective analysis has been developed. Thismethod can automatically adapt to the gradient change of a variable and is referred to as “gradient-dependent correlation scalemethod”. Its effect on the Argo objective analysis is verified theoretically with Gaussian pulse and spectrumanalysis. The results of one-dimensional simulation experiment show that the gradient-dependent correlation scales can improve the adaptability of the objective analysis system, making it possible for the analysis scheme to fully absorb the shortwave information of observation in areas with larger oceanographic gradients. The new scheme is applied to the Argo data objective analysis systemin the Pacific Ocean. The results are obviously improved. |
| 中文摘要: |
| Based on the optimal interpolation objective analysis of the Argo data, improvements are made to the empirical formula of a background error covariancematrixwidely used in data assimilation and objective analysis systems. Specifically, an estimation of correlation scales that can improve effectively the accuracy of Argo objective analysis has been developed. Thismethod can automatically adapt to the gradient change of a variable and is referred to as “gradient-dependent correlation scalemethod”. Its effect on the Argo objective analysis is verified theoretically with Gaussian pulse and spectrumanalysis. The results of one-dimensional simulation experiment show that the gradient-dependent correlation scales can improve the adaptability of the objective analysis system, making it possible for the analysis scheme to fully absorb the shortwave information of observation in areas with larger oceanographic gradients. The new scheme is applied to the Argo data objective analysis systemin the Pacific Ocean. The results are obviously improved. |
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