利用贝叶斯数据驱动法确定发射率曲线

IF 5.4 3区材料科学 Q2 CHEMISTRY, PHYSICAL

ACS Applied Energy Materials Pub Date : 2024-10-18 DOI:10.1016/j.matcom.2024.10.015

Luca Sgheri , Cristina Sgattoni , Chiara Zugarini

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引用次数: 0

摘要

在本文中，我们探讨了如何确定与真实数据密切匹配的光谱发射率曲线，以用作检索代码中的初始猜测和/或先验信息。我们的方法采用贝叶斯方法，将 CAMEL（Combined ASTER MODIS Emissivity over Land）发射率数据库与 MODIS/Terra＋Aqua Annually Land Cover Type 数据库整合在一起。利用贝叶斯框架，以高分辨率黄剖面凸组合的形式得出解决方案。我们在 IASI（红外大气探测干涉仪）数据上测试了我们的方法，发现它优于 CAMEL 数据的线性样条插值法和黄发射率数据库本身。

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Determination of emissivity profiles using a Bayesian data-driven approach

In this paper, we explore the determination of a spectral emissivity profile that closely matches real data, intended for use as an initial guess and/or a priori information in a retrieval code. Our approach employs a Bayesian method that integrates the CAMEL (Combined ASTER MODIS Emissivity over Land) emissivity database with the MODIS/Terra＋Aqua Yearly Land Cover Type database. The solution is derived as a convex combination of high-resolution Huang profiles using the Bayesian framework. We test our method on IASI (Infrared Atmospheric Sounding Interferometer) data and find that it outperforms the linear spline interpolation of the CAMEL data and the Huang emissivity database itself.

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来源期刊

ACS Applied Energy Materials Materials Science-Materials Chemistry

CiteScore

10.30

自引率

6.20%

发文量

1368

期刊介绍： ACS Applied Energy Materials is an interdisciplinary journal publishing original research covering all aspects of materials, engineering, chemistry, physics and biology relevant to energy conversion and storage. The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrate knowledge in the areas of materials, engineering, physics, bioscience, and chemistry into important energy applications.