How well must climate models agree with observations?

The usefulness of a climate-model simulation cannot be inferred solely from its degree of agreement with observations. Instead, one has to consider additional factors such as internal variability, the tuning of the model, observational uncertainty, the temporal change in dominant processes or the un...

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Published in:Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
Main Author: Notz, Dirk
Format: Article in Journal/Newspaper
Language:English
Published: The Royal Society 2015
Subjects:
Online Access:http://dx.doi.org/10.1098/rsta.2014.0164
https://royalsocietypublishing.org/doi/pdf/10.1098/rsta.2014.0164
https://royalsocietypublishing.org/doi/full-xml/10.1098/rsta.2014.0164
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spelling crroyalsociety:10.1098/rsta.2014.0164 2024-09-30T14:42:57+00:00 How well must climate models agree with observations? Notz, Dirk 2015 http://dx.doi.org/10.1098/rsta.2014.0164 https://royalsocietypublishing.org/doi/pdf/10.1098/rsta.2014.0164 https://royalsocietypublishing.org/doi/full-xml/10.1098/rsta.2014.0164 en eng The Royal Society https://royalsociety.org/journals/ethics-policies/data-sharing-mining/ Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences volume 373, issue 2052, page 20140164 ISSN 1364-503X 1471-2962 journal-article 2015 crroyalsociety https://doi.org/10.1098/rsta.2014.0164 2024-09-02T04:21:06Z The usefulness of a climate-model simulation cannot be inferred solely from its degree of agreement with observations. Instead, one has to consider additional factors such as internal variability, the tuning of the model, observational uncertainty, the temporal change in dominant processes or the uncertainty in the forcing. In any model-evaluation study, the impact of these limiting factors on the suitability of specific metrics must hence be examined. This can only meaningfully be done relative to a given purpose for using a model. I here generally discuss these points and substantiate their impact on model evaluation using the example of sea ice. For this example, I find that many standard metrics such as sea-ice area or volume only permit limited inferences about the shortcomings of individual models. Article in Journal/Newspaper Sea ice The Royal Society Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 373 2052 20140164
institution Open Polar
collection The Royal Society
op_collection_id crroyalsociety
language English
description The usefulness of a climate-model simulation cannot be inferred solely from its degree of agreement with observations. Instead, one has to consider additional factors such as internal variability, the tuning of the model, observational uncertainty, the temporal change in dominant processes or the uncertainty in the forcing. In any model-evaluation study, the impact of these limiting factors on the suitability of specific metrics must hence be examined. This can only meaningfully be done relative to a given purpose for using a model. I here generally discuss these points and substantiate their impact on model evaluation using the example of sea ice. For this example, I find that many standard metrics such as sea-ice area or volume only permit limited inferences about the shortcomings of individual models.
format Article in Journal/Newspaper
author Notz, Dirk
spellingShingle Notz, Dirk
How well must climate models agree with observations?
author_facet Notz, Dirk
author_sort Notz, Dirk
title How well must climate models agree with observations?
title_short How well must climate models agree with observations?
title_full How well must climate models agree with observations?
title_fullStr How well must climate models agree with observations?
title_full_unstemmed How well must climate models agree with observations?
title_sort how well must climate models agree with observations?
publisher The Royal Society
publishDate 2015
url http://dx.doi.org/10.1098/rsta.2014.0164
https://royalsocietypublishing.org/doi/pdf/10.1098/rsta.2014.0164
https://royalsocietypublishing.org/doi/full-xml/10.1098/rsta.2014.0164
genre Sea ice
genre_facet Sea ice
op_source Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
volume 373, issue 2052, page 20140164
ISSN 1364-503X 1471-2962
op_rights https://royalsociety.org/journals/ethics-policies/data-sharing-mining/
op_doi https://doi.org/10.1098/rsta.2014.0164
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