基于梯度依赖OI的全球多参数Argo数据集的构建与验证  

Construction and validation of global multi-parameter Argo dataset based on gradient-dependent OI

作　　者：王丹阳 张春玲 卢少磊 李兆钦[3,4] 刘增宏 WANG Danyang;ZHANG Chunling;LU Shaolei;LI Zhaoqin;LIU Zenghong(College of marine sciences,Shanghai Ocean University,Shanghai 201306,China;Key Laboratory of Marine Ecological Monitoring and Restoration Technologies,Ministry of Natural Resources,Shanghai 201306,China;Second Institute of Oceanography,Ministry of Natural Resources,Hangzhou 310012,China;State Key Laboratory of Satellite Ocean Environment Dynamics,Ministry of Natural Resources,Hangzhou 310012,China)

机构地区：[1]上海海洋大学海洋科学学院,上海201306 [2]自然资源部海洋生态监测与修复技术重点实验室,上海201306 [3]自然资源部第二海洋研究所,浙江杭州310012 [4]卫星海洋环境动力学国家重点实验室,浙江杭州310012

出　　处：《海洋预报》2023年第2期77-88,共12页Marine Forecasts

基　　金：国家自然科学基金项目(42106090、U1811464)。

摘　　要：利用Argo资料,基于梯度依赖最优插值客观分析系统,重构2004—2020年空间分辨率为1°×1°的全球多参数Argo网格化数据集,并通过置信区间估计、实测数据检验、与其他数据集对比等方式,对该数据集进行一系列的验证。结果表明:重构的Argo数据集在95%的统计概率下,90%以上的温度、盐度重构结果可信,且与实测数据的温度、盐度最大偏差不超过±1.0℃、±0.02。该数据集所反映的大尺度信号与现有数据集一致,并且可以保留较多中小尺度信号,分析结果与实际观测更接近。Based on the gradient-dependent optimal interpolation objective analysis system,only,a global multiparameter Argo gridded dataset with a spatial resolution of 1°×1°from 2004 to 2020 is constructed using the Argo observation in this paper.A series of validations are made for this dataset including confidence interval estimation,observation inspection and comparison with other datasets.The results show that more than 90%of the reconstructed temperature and salinity are reliable under the statistical probability of 95%with the maximum bias from observations are less than±1.0℃and±0.02,respectively.The large-scale signals reflected in this dataset are consistent with the existing datasets,and more small and medium-scale signals can be retained.The analysis results are closer to the observations.

关 键 词：梯度依赖最优插值 ARGO 多参数 网格化数据集 客观分析 

分 类 号：P715.2[天文地球—海洋科学]