How biased are our models? – a case study of the alpine region

<p>Geophysical process simulations play a crucial role in the understanding of the subsurface. This understanding is required to provide, for instance, clean energy sources such as geothermal energy. However, the calibration and validation of the physical models heavily rely on state measureme...

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Autores principales:	D. Degen, C. Spooner, M. Scheck-Wenderoth, M. Cacace
Formato:	article
Lenguaje:	EN
Publicado:	Copernicus Publications 2021
Materias:	Geology QE1-996.5
Acceso en línea:	https://doaj.org/article/08a4ce0f37364f83ab3db5fa4ac25494
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id	oai:doaj.org-article:08a4ce0f37364f83ab3db5fa4ac25494
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spelling	oai:doaj.org-article:08a4ce0f37364f83ab3db5fa4ac254942021-11-24T08:41:14ZHow biased are our models? – a case study of the alpine region10.5194/gmd-14-7133-20211991-959X1991-9603https://doaj.org/article/08a4ce0f37364f83ab3db5fa4ac254942021-11-01T00:00:00Zhttps://gmd.copernicus.org/articles/14/7133/2021/gmd-14-7133-2021.pdfhttps://doaj.org/toc/1991-959Xhttps://doaj.org/toc/1991-9603<p>Geophysical process simulations play a crucial role in the understanding of the subsurface. This understanding is required to provide, for instance, clean energy sources such as geothermal energy. However, the calibration and validation of the physical models heavily rely on state measurements such as temperature. In this work, we demonstrate that focusing analyses purely on measurements introduces a high bias. This is illustrated through global sensitivity studies. The extensive exploration of the parameter space becomes feasible through the construction of suitable surrogate models via the reduced basis method, where the bias is found to result from very unequal data distribution. We propose schemes to compensate for parts of this bias. However, the bias cannot be entirely compensated. Therefore, we demonstrate the consequences of this bias with the example of a model calibration.</p>D. DegenC. SpoonerC. SpoonerM. Scheck-WenderothM. Scheck-WenderothM. CacaceCopernicus PublicationsarticleGeologyQE1-996.5ENGeoscientific Model Development, Vol 14, Pp 7133-7153 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Geology QE1-996.5
spellingShingle	Geology QE1-996.5 D. Degen C. Spooner C. Spooner M. Scheck-Wenderoth M. Scheck-Wenderoth M. Cacace How biased are our models? – a case study of the alpine region
description	<p>Geophysical process simulations play a crucial role in the understanding of the subsurface. This understanding is required to provide, for instance, clean energy sources such as geothermal energy. However, the calibration and validation of the physical models heavily rely on state measurements such as temperature. In this work, we demonstrate that focusing analyses purely on measurements introduces a high bias. This is illustrated through global sensitivity studies. The extensive exploration of the parameter space becomes feasible through the construction of suitable surrogate models via the reduced basis method, where the bias is found to result from very unequal data distribution. We propose schemes to compensate for parts of this bias. However, the bias cannot be entirely compensated. Therefore, we demonstrate the consequences of this bias with the example of a model calibration.</p>
format	article
author	D. Degen C. Spooner C. Spooner M. Scheck-Wenderoth M. Scheck-Wenderoth M. Cacace
author_facet	D. Degen C. Spooner C. Spooner M. Scheck-Wenderoth M. Scheck-Wenderoth M. Cacace
author_sort	D. Degen
title	How biased are our models? – a case study of the alpine region
title_short	How biased are our models? – a case study of the alpine region
title_full	How biased are our models? – a case study of the alpine region
title_fullStr	How biased are our models? – a case study of the alpine region
title_full_unstemmed	How biased are our models? – a case study of the alpine region
title_sort	how biased are our models? – a case study of the alpine region
publisher	Copernicus Publications
publishDate	2021
url	https://doaj.org/article/08a4ce0f37364f83ab3db5fa4ac25494
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How biased are our models? – a case study of the alpine region

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