卫星亚像元的盐度变化:对卫星原位比较的影响。

C. Thouvenin-Masson, J. Boutin, J. Vergely, D. Khvorostyanov, X. Perrot, G. Reverdin
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摘要

海面盐度(SSS)是由SMOS和SMAP l波段辐射计反演的,空间分辨率约为50km。传统上,卫星SSS产品的验证是基于与现场近地表盐度测量值的比较。在系泊处、货船浮筒和船舶轨道沿线进行现场测量[JB1],可提供准时或一维(沿船舶轨道)的SSS估计。一维或准时原位测量与二维卫星产品之间的采样差异导致采样误差,必须将采样误差与卫星产品验证的测量误差分开。我们使用小尺度分辨率场(1/12°墨卡托全球海洋物理分析和预报),通过比较准时、[JB2]一维和二维SSS变化来估计每种原位测量的期望采样误差。更好地理解采样误差可以更准确地验证卫星SSS和卫星检索算法估计的误差。通过考虑卫星减去经采样和检索误差归一化的原位盐度差的标准差来量化改进。如果正确考虑所有误差贡献,这个量应该等于1。该方法将应用于SMOS SSS以及合并的SMOS和SMAP SSS产品。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Salinity variability in satellite subpixels: impact on satellite in-situ comparisons.
Sea Surface Salinity (SSS) are retrieved from SMOS and SMAP L-band radiometers at a spatial resolution of about 50km. Traditionally, satellite SSS products validation is based on comparisons with in-situ near surface salinity measurements. In-situ measurements are performed on moorings, argo floats and along ship tracks[JB1] , which provide punctual or one-dimensional (along ship tracks) estimations of the SSS. The sampling difference between one-dimensional or punctual in-situ measurements and two-dimensional satellite products results in a sampling error that must be separated from measurement errors for the validation of satellite products. We use a small-scale resolution field (1/12° Mercator Global Ocean Physics Analysis and Forecast) to estimate the expected sampling error of each kind of in-situ measurements, by comparing punctual, [JB2] one-dimensional and two-dimensional SSS variability. The better understanding of sampling errors allows a more accurate validation of satellite SSS and of the errors estimated by satellite retrieval algorithms. The improvement is quantified by considering the standard deviation of satellite minus in-situ salinities differences normalized by the sampling and retrieval errors. This quantity should be equal to one if all the error contributions are correctly considered. This methodology will be applied to SMOS SSS and to merged SMOS and SMAP SSS products.
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