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SMOS卫星盐度数据在中国近岸海域的准确度评估
引用本文:王新新,杨建洪,赵冬至,王祥,孙广轮.SMOS卫星盐度数据在中国近岸海域的准确度评估[J].海洋学报,2013,35(5):169-176.
作者姓名:王新新  杨建洪  赵冬至  王祥  孙广轮
作者单位:大连海事大学 环境科学与工程学院, 辽宁 大连 116026;国家海洋局 国家海洋环境监测中心, 辽宁 大连 116023;国家海洋局 国家海洋环境监测中心, 辽宁 大连 116023;国家海洋局 国家海洋环境监测中心, 辽宁 大连 116023;大连海事大学 环境科学与工程学院, 辽宁 大连 116026;国家海洋局 国家海洋环境监测中心, 辽宁 大连 116023;大连海事大学 环境科学与工程学院, 辽宁 大连 116026;国家海洋局 国家海洋环境监测中心, 辽宁 大连 116023
基金项目:海洋公益性行业科研专项经费项目(20090592)。
摘    要:盐度是描述海洋的关键变量,对海表面盐度进行观测可以推进对全球水循环的理解。本文的主要目的是在中国近海海域对SMOS卫星盐度数据进行准确度评估。主要方法是将SMOS卫星L2海洋盐度数据产品(V317)与实测ARGO数据和走航数据进行匹配,并采用统计学的方法对SMOS卫星数据准确度进行评估。结果表明:匹配数据的线性关系不显著,SMOS卫星盐度数据(V317)在南海和东海的均方根误差分别约为1.2和0.7,应用海表面粗糙度修正模型得到的3组海表盐度数据准确度都相对较低,尤其在近岸强风场区域,海表盐度卫星数据相对于实测数据偏高,这可能是由于海表粗糙度和陆地射频干扰(RFI)作用影响的结果;SMOS卫星数据在东海的均方根误差比南海高0.5左右,这可能是由于东海海域为相对开阔海域,受陆地RFI影响相对南海较小;在中国近岸海域,应用SSS1和SSS3模型得到的盐度数据准确度相对较高,可以对模型进行地球物理参数修正,进行局地化改进,预计可以提高近岸海域盐度反演的准确度。

关 键 词:卫星遥感  海表盐度  ARGO  粗糙度修正模型  近岸影响

SMOS satellite salinity data accuracy assessment in the China coastal areas
WANG Xinxin,YANG Jianhong,ZHAO Dongzhi,WANG Xiang and SUN Guanglun.SMOS satellite salinity data accuracy assessment in the China coastal areas[J].Acta Oceanologica Sinica (in Chinese),2013,35(5):169-176.
Authors:WANG Xinxin  YANG Jianhong  ZHAO Dongzhi  WANG Xiang and SUN Guanglun
Institution:College of Environmental Science and Engineering, Dalian Maritime University, Dalian 116026, China;National Marine Environmental Monitoring Center, State Oceanic Administration, Dalian 116023, China;National Marine Environmental Monitoring Center, State Oceanic Administration, Dalian 116023, China;National Marine Environmental Monitoring Center, State Oceanic Administration, Dalian 116023, China;College of Environmental Science and Engineering, Dalian Maritime University, Dalian 116026, China;National Marine Environmental Monitoring Center, State Oceanic Administration, Dalian 116023, China;College of Environmental Science and Engineering, Dalian Maritime University, Dalian 116026, China;National Marine Environmental Monitoring Center, State Oceanic Administration, Dalian 116023, China
Abstract:The ocean salinity is a key variable to describe the ocean. Observing sea surface salinity (SSS) can promote the understanding of global water cycle. This paper main aims to carry out the accuracy assessment of SMOS satellite SSS data in the coastal waters of China. The main methods of this paper is that matching SMOS satellite L2 ocean salinity data products (V317) with the in-situ ARGO data and navigation data, evaluating SMOS satellite data using statistics method. The results show that the linear relationship of the matched data is not significant, and the RMSE of the SMOS SSS in South China Sea and East China Sea are 1.2 and 0.7 respectively. The three sets of SSS data, which are acquired applying three models in correcting the sea surface roughness are all with relatively low accuracy, especially in coastal strong wind areas,the SSS value observed by satellite is overestimated, and SMOS SSS retrieve may be seriously influenced by the sea surface roughness and land radio frequency. The RMSE of SMOS SSS data in South China Sea is higher than the East China Sea around 0.5.the degree of accuracy of salinity data using SSS1 and SSS3 are relatively high in the China seas. In further application, higher accuracy can be purchased by amending geophysical parametersand applying local improvement in China seas.
Keywords:satellite remote sensing  sea surface salinity  ARGO  roughness correction model  coastal effect
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