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Possible causes of data model discrepancy in the temperature history of the last Millennium

Model simulations and proxy-based reconstructions are the main tools for quantifying pre-instrumental climate variations. For some metrics such as Northern Hemisphere mean temperatures, there is remarkable agreement between models and reconstructions. For other diagnostics, such as the regional resp...

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Autores principales: Neukom, Raphael, Schurer, Andrew P., Steiger, Nathan. J., Hegerl, Gabriele C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5953951/
https://www.ncbi.nlm.nih.gov/pubmed/29765075
http://dx.doi.org/10.1038/s41598-018-25862-2
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author Neukom, Raphael
Schurer, Andrew P.
Steiger, Nathan. J.
Hegerl, Gabriele C.
author_facet Neukom, Raphael
Schurer, Andrew P.
Steiger, Nathan. J.
Hegerl, Gabriele C.
author_sort Neukom, Raphael
collection PubMed
description Model simulations and proxy-based reconstructions are the main tools for quantifying pre-instrumental climate variations. For some metrics such as Northern Hemisphere mean temperatures, there is remarkable agreement between models and reconstructions. For other diagnostics, such as the regional response to volcanic eruptions, or hemispheric temperature differences, substantial disagreements between data and models have been reported. Here, we assess the potential sources of these discrepancies by comparing 1000-year hemispheric temperature reconstructions based on real-world paleoclimate proxies with climate-model-based pseudoproxies. These pseudoproxy experiments (PPE) indicate that noise inherent in proxy records and the unequal spatial distribution of proxy data are the key factors in explaining the data-model differences. For example, lower inter-hemispheric correlations in reconstructions can be fully accounted for by these factors in the PPE. Noise and data sampling also partly explain the reduced amplitude of the response to external forcing in reconstructions compared to models. For other metrics, such as inter-hemispheric differences, some, although reduced, discrepancy remains. Our results suggest that improving proxy data quality and spatial coverage is the key factor to increase the quality of future climate reconstructions, while the total number of proxy records and reconstruction methodology play a smaller role.
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spelling pubmed-59539512018-05-21 Possible causes of data model discrepancy in the temperature history of the last Millennium Neukom, Raphael Schurer, Andrew P. Steiger, Nathan. J. Hegerl, Gabriele C. Sci Rep Article Model simulations and proxy-based reconstructions are the main tools for quantifying pre-instrumental climate variations. For some metrics such as Northern Hemisphere mean temperatures, there is remarkable agreement between models and reconstructions. For other diagnostics, such as the regional response to volcanic eruptions, or hemispheric temperature differences, substantial disagreements between data and models have been reported. Here, we assess the potential sources of these discrepancies by comparing 1000-year hemispheric temperature reconstructions based on real-world paleoclimate proxies with climate-model-based pseudoproxies. These pseudoproxy experiments (PPE) indicate that noise inherent in proxy records and the unequal spatial distribution of proxy data are the key factors in explaining the data-model differences. For example, lower inter-hemispheric correlations in reconstructions can be fully accounted for by these factors in the PPE. Noise and data sampling also partly explain the reduced amplitude of the response to external forcing in reconstructions compared to models. For other metrics, such as inter-hemispheric differences, some, although reduced, discrepancy remains. Our results suggest that improving proxy data quality and spatial coverage is the key factor to increase the quality of future climate reconstructions, while the total number of proxy records and reconstruction methodology play a smaller role. Nature Publishing Group UK 2018-05-15 /pmc/articles/PMC5953951/ /pubmed/29765075 http://dx.doi.org/10.1038/s41598-018-25862-2 Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Neukom, Raphael
Schurer, Andrew P.
Steiger, Nathan. J.
Hegerl, Gabriele C.
Possible causes of data model discrepancy in the temperature history of the last Millennium
title Possible causes of data model discrepancy in the temperature history of the last Millennium
title_full Possible causes of data model discrepancy in the temperature history of the last Millennium
title_fullStr Possible causes of data model discrepancy in the temperature history of the last Millennium
title_full_unstemmed Possible causes of data model discrepancy in the temperature history of the last Millennium
title_short Possible causes of data model discrepancy in the temperature history of the last Millennium
title_sort possible causes of data model discrepancy in the temperature history of the last millennium
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5953951/
https://www.ncbi.nlm.nih.gov/pubmed/29765075
http://dx.doi.org/10.1038/s41598-018-25862-2
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