通过现场测量验证SMAP SSS

W. Tang, A. Fore, S. Yueh, Tong Lee, A. Hayashi, A. Sanchez‐Franks, D. Baranowski
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引用次数: 77

摘要

从SMAP辐射计测量数据中获取的海面盐度(SSS)与从Argo浮标、热带系泊浮标和船载热盐度记录仪(TSG)数据收集的原位盐度测量数据进行验证。与Argo网格数据相比,SMAP SSS在热带和中纬度地区的月精度达到0.2 PSU。在热带海洋中,对系泊浮标在1米处测得的盐度进行时间序列比较表明,SMAP可以跟踪一个月内发生的较大盐度变化。对SMAP、SMOS和Argo数据的协同分析使我们能够从卫星检索评估中识别和排除一些实时浮标数据中的错误跳跃或漂移。在周尺度上,SMAP-buoy配对分析的平均标准差为0.22 PSU,相关系数为0.73;月平均标准差降至0.17 PSU,相关性提高至0.8。SMAP L3每日地图显示,在印度夏季风期间,咸水从阿拉伯海侵入孟加拉湾,与孟加拉湾边界层实验(BoBBLE)项目现场活动期间部署的浮标收集的每日测量结果一致。在地中海,SMAP的SSS空间格局被船载TSG数据证实。
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Validating SMAP SSS with in situ measurements
Sea surface salinity (SSS) retrieved from SMAP radiometer measurements is validated with in situ salinity measurements collected from Argo floats, tropical moored buoys and ship-based thermosalinograph (TSG) data. SMAP SSS achieved accuracy of 0.2 PSU on a monthly basis in comparison with Argo gridded data in the tropics and mid-latitudes. In tropical oceans, time series comparison of salinity measured at 1 m by moored buoys indicates that SMAP can track large salinity changes occurred within a month. Synergetic analysis of SMAP, SMOS and Argo data allows us to identify and exclude erroneous jumps or drift in some real-time buoy data from assessment of satellite retrieval. The resulting SMAP-buoy matchup analysis leads to an average standard deviation of 0.22 PSU and correlation coefficient of 0.73 on weekly scale; the average standard deviation reduced to 0.17 PSU and the correlation improved to 0.8 on monthly scale. SMAP L3 daily maps reveals salty water intrusion from the Arabian Sea into the Bay of Bengal during the Indian summer monsoon, consistent with the daily measurements collected from floats deployed during the Bay of Bengal Boundary Layer Experiment (BoBBLE) project field campaign. In the Mediterranean Sea, the spatial pattern of SSS from SMAP is confirmed by the ship-based TSG data.
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