H'/> PCA determination of the radiometric noise of high spectral resolution infrared observations from spectral residuals: Application to IASI
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PCA determination of the radiometric noise of high spectral resolution infrared observations from spectral residuals: Application to IASI

机译：PCA从光谱残留的高频分辨率红外观测的辐射噪声测定：对IASI的应用

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Highlights?Characterization of IASI radiometric noise based on direct Earth observations from space.?Characterization of the full non-diagonal observational covariance matrix.?Case study based on one year long record of IASI soundings.?Comparison with blackbody in flight calibrations.AbstractThe problem of characterizing and estimating the instrumental or radiometric noise of satellite high spectral resolution infrared spectrometers directly from Earth observations is addressed in this paper. An approach has been developed, which relies on the Principal Component Analysis (PCA) with a suitable criterion to select the optimal number of PC scores. Different selection criteria have been set up and analysed, which is based on the estimation theory of Least Squares and/or Maximum Likelihood Principle. The approach is independent of any forward model and/or radiative
机译：<！[cdata [ 亮点 ？ 基于从空间直接接地观测的IASI辐射噪声的表征。 ？ 全面非对角观测协方差矩阵的表征。 ？ 案例研究基于一年的IASI探测记录。 ？ compa与飞行校准中的黑体的rison。 < CE：抽象XMLNS：CE =“http://www.elsevier.com/xml/common/dtd”xmlns =“http://www.elsevier.com/xml/ja/dtd”id =“abs0001”class = “作者”查看=“全部”> 抽象 本文解决了直接从地球观测的表征和估计卫星高光谱分辨率红外光谱仪的仪器或辐射噪声的问题。已经开发了一种方法，它依赖于具有合适标准的主成分分析（PCA）来选择最佳的PC分数。已经建立和分析了不同的选择标准，其基于最小二乘和/或最大似然原理的估计理论。该方法独立于任何前进模型和/或辐射

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