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Comparative analysis of atmospheric radiative transfer models using the Atmospheric Look-up table Generator (ALG) toolbox (version 2.0)

Atmospheric radiative transfer models (RTMs) are software tools that help researchers in understanding the radiative processes occurring in the Earth’s atmosphere. Given their importance in remote sensing applications, the intercomparison of atmospheric RTMs is therefore one of the main tasks used t...

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Autores principales: Vicent, Jorge, Verrelst, Jochem, Sabater, Neus, Alonso, Luis, Rivera-Caicedo, Juan Pablo, Martino, Luca, Muñoz-Marí, Jordi, Moreno, José
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7613350/
https://www.ncbi.nlm.nih.gov/pubmed/36082005
http://dx.doi.org/10.5194/gmd-13-1945-2020
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author Vicent, Jorge
Verrelst, Jochem
Sabater, Neus
Alonso, Luis
Rivera-Caicedo, Juan Pablo
Martino, Luca
Muñoz-Marí, Jordi
Moreno, José
author_facet Vicent, Jorge
Verrelst, Jochem
Sabater, Neus
Alonso, Luis
Rivera-Caicedo, Juan Pablo
Martino, Luca
Muñoz-Marí, Jordi
Moreno, José
author_sort Vicent, Jorge
collection PubMed
description Atmospheric radiative transfer models (RTMs) are software tools that help researchers in understanding the radiative processes occurring in the Earth’s atmosphere. Given their importance in remote sensing applications, the intercomparison of atmospheric RTMs is therefore one of the main tasks used to evaluate model performance and identify the characteristics that differ between models. This can be a tedious tasks that requires good knowledge of the model inputs/outputs and the generation of large databases of consistent simulations. With the evolution of these software tools, their increase in complexity bears implications for their use in practical applications and model intercomparison. Existing RTM-specific graphical user interfaces are not optimized for performing intercomparison studies of a wide variety of atmospheric RTMs. In this paper, we present the Atmospheric Look-up table Generator (ALG) version 2.0, a new software tool that facilitates generating large databases for a variety of atmospheric RTMs. ALG facilitates consistent and intuitive user interaction to enable the running of model executions and storing of RTM data for any spectral configuration in the optical domain. We demonstrate the utility of ALG in performing intercomparison studies of radiance simulations from broadly used atmospheric RTMs (6SV, MODTRAN, and libRadtran) through global sensitivity analysis. We expect that providing ALG to the research community will facilitate the usage of atmospheric RTMs to a wide range of applications in Earth observation.
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spelling pubmed-76133502022-09-07 Comparative analysis of atmospheric radiative transfer models using the Atmospheric Look-up table Generator (ALG) toolbox (version 2.0) Vicent, Jorge Verrelst, Jochem Sabater, Neus Alonso, Luis Rivera-Caicedo, Juan Pablo Martino, Luca Muñoz-Marí, Jordi Moreno, José Geosci Model Dev Article Atmospheric radiative transfer models (RTMs) are software tools that help researchers in understanding the radiative processes occurring in the Earth’s atmosphere. Given their importance in remote sensing applications, the intercomparison of atmospheric RTMs is therefore one of the main tasks used to evaluate model performance and identify the characteristics that differ between models. This can be a tedious tasks that requires good knowledge of the model inputs/outputs and the generation of large databases of consistent simulations. With the evolution of these software tools, their increase in complexity bears implications for their use in practical applications and model intercomparison. Existing RTM-specific graphical user interfaces are not optimized for performing intercomparison studies of a wide variety of atmospheric RTMs. In this paper, we present the Atmospheric Look-up table Generator (ALG) version 2.0, a new software tool that facilitates generating large databases for a variety of atmospheric RTMs. ALG facilitates consistent and intuitive user interaction to enable the running of model executions and storing of RTM data for any spectral configuration in the optical domain. We demonstrate the utility of ALG in performing intercomparison studies of radiance simulations from broadly used atmospheric RTMs (6SV, MODTRAN, and libRadtran) through global sensitivity analysis. We expect that providing ALG to the research community will facilitate the usage of atmospheric RTMs to a wide range of applications in Earth observation. 2020-04-20 /pmc/articles/PMC7613350/ /pubmed/36082005 http://dx.doi.org/10.5194/gmd-13-1945-2020 Text en https://creativecommons.org/licenses/by/4.0/This work is distributed under the Creative Commons Attribution 4.0 License https://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Vicent, Jorge
Verrelst, Jochem
Sabater, Neus
Alonso, Luis
Rivera-Caicedo, Juan Pablo
Martino, Luca
Muñoz-Marí, Jordi
Moreno, José
Comparative analysis of atmospheric radiative transfer models using the Atmospheric Look-up table Generator (ALG) toolbox (version 2.0)
title Comparative analysis of atmospheric radiative transfer models using the Atmospheric Look-up table Generator (ALG) toolbox (version 2.0)
title_full Comparative analysis of atmospheric radiative transfer models using the Atmospheric Look-up table Generator (ALG) toolbox (version 2.0)
title_fullStr Comparative analysis of atmospheric radiative transfer models using the Atmospheric Look-up table Generator (ALG) toolbox (version 2.0)
title_full_unstemmed Comparative analysis of atmospheric radiative transfer models using the Atmospheric Look-up table Generator (ALG) toolbox (version 2.0)
title_short Comparative analysis of atmospheric radiative transfer models using the Atmospheric Look-up table Generator (ALG) toolbox (version 2.0)
title_sort comparative analysis of atmospheric radiative transfer models using the atmospheric look-up table generator (alg) toolbox (version 2.0)
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7613350/
https://www.ncbi.nlm.nih.gov/pubmed/36082005
http://dx.doi.org/10.5194/gmd-13-1945-2020
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