Comparing climate time series – Part 2: A multivariate test
This paper proposes a criterion for deciding whether climate model simulations are consistent with observations. Importantly, the criterion accounts for correlations in both space and time. The basic idea is to fit each multivariate time series to a vector autoregressive (VAR) model and then test th...
Published in: | Advances in Statistical Climatology, Meteorology and Oceanography |
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ftnonlinearchiv:oai:noa.gwlb.de:cop_mods_00058997 2024-09-15T18:21:46+00:00 Comparing climate time series – Part 2: A multivariate test DelSole, Timothy Tippett, Michael K. 2021-12 electronic https://doi.org/10.5194/ascmo-7-73-2021 https://noa.gwlb.de/receive/cop_mods_00058997 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00058605/ascmo-7-73-2021.pdf https://ascmo.copernicus.org/articles/7/73/2021/ascmo-7-73-2021.pdf eng eng Copernicus Publications Advances in Statistical Climatology, Meteorology and Oceanography -- http://advances-statistical-climatology-meteorology-oceanography.net/ -- https://www.adv-stat-clim-meteorol-oceanogr.net/volumes_and_issues.html -- http://www.bibliothek.uni-regensburg.de/ezeit/?2840620 -- 2364-3587 https://doi.org/10.5194/ascmo-7-73-2021 https://noa.gwlb.de/receive/cop_mods_00058997 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00058605/ascmo-7-73-2021.pdf https://ascmo.copernicus.org/articles/7/73/2021/ascmo-7-73-2021.pdf https://creativecommons.org/licenses/by/4.0/ uneingeschränkt info:eu-repo/semantics/openAccess article Verlagsveröffentlichung article Text doc-type:article 2021 ftnonlinearchiv https://doi.org/10.5194/ascmo-7-73-2021 2024-06-26T04:36:34Z This paper proposes a criterion for deciding whether climate model simulations are consistent with observations. Importantly, the criterion accounts for correlations in both space and time. The basic idea is to fit each multivariate time series to a vector autoregressive (VAR) model and then test the hypothesis that the parameters of the two models are equal. In the special case of a first-order VAR model, the model is a linear inverse model (LIM) and the test constitutes a difference-in-LIM test. This test is applied to decide whether climate models generate realistic internal variability of annual mean North Atlantic sea surface temperature. Given the disputed origin of multidecadal variability in the North Atlantic (e.g., some studies argue it is forced by anthropogenic aerosols, while others argue it arises naturally from internal variability), the time series are filtered in two different ways appropriate to the two driving mechanisms. In either case, only a few climate models out of three dozen are found to generate internal variability consistent with observations. In fact, it is shown that climate models differ not only from observations, but also from each other, unless they come from the same modeling center. In addition to these discrepancies in internal variability, other studies show that models exhibit significant discrepancies with observations in terms of the response to external forcing. Taken together, these discrepancies imply that, at the present time, climate models do not provide a satisfactory explanation of observed variability in the North Atlantic. Article in Journal/Newspaper North Atlantic Niedersächsisches Online-Archiv NOA Advances in Statistical Climatology, Meteorology and Oceanography 7 2 73 85 |
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article Verlagsveröffentlichung |
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article Verlagsveröffentlichung DelSole, Timothy Tippett, Michael K. Comparing climate time series – Part 2: A multivariate test |
topic_facet |
article Verlagsveröffentlichung |
description |
This paper proposes a criterion for deciding whether climate model simulations are consistent with observations. Importantly, the criterion accounts for correlations in both space and time. The basic idea is to fit each multivariate time series to a vector autoregressive (VAR) model and then test the hypothesis that the parameters of the two models are equal. In the special case of a first-order VAR model, the model is a linear inverse model (LIM) and the test constitutes a difference-in-LIM test. This test is applied to decide whether climate models generate realistic internal variability of annual mean North Atlantic sea surface temperature. Given the disputed origin of multidecadal variability in the North Atlantic (e.g., some studies argue it is forced by anthropogenic aerosols, while others argue it arises naturally from internal variability), the time series are filtered in two different ways appropriate to the two driving mechanisms. In either case, only a few climate models out of three dozen are found to generate internal variability consistent with observations. In fact, it is shown that climate models differ not only from observations, but also from each other, unless they come from the same modeling center. In addition to these discrepancies in internal variability, other studies show that models exhibit significant discrepancies with observations in terms of the response to external forcing. Taken together, these discrepancies imply that, at the present time, climate models do not provide a satisfactory explanation of observed variability in the North Atlantic. |
format |
Article in Journal/Newspaper |
author |
DelSole, Timothy Tippett, Michael K. |
author_facet |
DelSole, Timothy Tippett, Michael K. |
author_sort |
DelSole, Timothy |
title |
Comparing climate time series – Part 2: A multivariate test |
title_short |
Comparing climate time series – Part 2: A multivariate test |
title_full |
Comparing climate time series – Part 2: A multivariate test |
title_fullStr |
Comparing climate time series – Part 2: A multivariate test |
title_full_unstemmed |
Comparing climate time series – Part 2: A multivariate test |
title_sort |
comparing climate time series – part 2: a multivariate test |
publisher |
Copernicus Publications |
publishDate |
2021 |
url |
https://doi.org/10.5194/ascmo-7-73-2021 https://noa.gwlb.de/receive/cop_mods_00058997 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00058605/ascmo-7-73-2021.pdf https://ascmo.copernicus.org/articles/7/73/2021/ascmo-7-73-2021.pdf |
genre |
North Atlantic |
genre_facet |
North Atlantic |
op_relation |
Advances in Statistical Climatology, Meteorology and Oceanography -- http://advances-statistical-climatology-meteorology-oceanography.net/ -- https://www.adv-stat-clim-meteorol-oceanogr.net/volumes_and_issues.html -- http://www.bibliothek.uni-regensburg.de/ezeit/?2840620 -- 2364-3587 https://doi.org/10.5194/ascmo-7-73-2021 https://noa.gwlb.de/receive/cop_mods_00058997 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00058605/ascmo-7-73-2021.pdf https://ascmo.copernicus.org/articles/7/73/2021/ascmo-7-73-2021.pdf |
op_rights |
https://creativecommons.org/licenses/by/4.0/ uneingeschränkt info:eu-repo/semantics/openAccess |
op_doi |
https://doi.org/10.5194/ascmo-7-73-2021 |
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Advances in Statistical Climatology, Meteorology and Oceanography |
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