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Autori principali: Sgheri, Luca, Sgattoni, Cristina, Zugarini, Chiara
Natura: Preprint
Pubblicazione: 2024
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Accesso online:https://arxiv.org/abs/2407.07113
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author Sgheri, Luca
Sgattoni, Cristina
Zugarini, Chiara
author_facet Sgheri, Luca
Sgattoni, Cristina
Zugarini, Chiara
contents 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 a land cover map. 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.
format Preprint
id arxiv_https___arxiv_org_abs_2407_07113
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Determination of emissivity profiles using a Bayesian data-driven approach
Sgheri, Luca
Sgattoni, Cristina
Zugarini, Chiara
Applications
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 a land cover map. 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.
title Determination of emissivity profiles using a Bayesian data-driven approach
topic Applications
url https://arxiv.org/abs/2407.07113