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Robustness of Euro-Mediterranean Synoptic Circulation Types and Sensitivity to Member Selection in CMIP6 Models.

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Title: Robustness of Euro-Mediterranean Synoptic Circulation Types and Sensitivity to Member Selection in CMIP6 Models.
Authors: Olmo, Matías Ezequiel1 (AUTHOR) matias.olmo@bsc.es, Cos, Pep1 (AUTHOR), Campos, Diego1 (AUTHOR), Muñoz, Ángel G.1 (AUTHOR), Samso, Margarida1 (AUTHOR), Soret, Albert1 (AUTHOR), Doblas-Reyes, Francisco1,2 (AUTHOR)
Source: Journal of Climate. Feb2026, Vol. 39 Issue 4, p1053-1064. 12p.
Subjects: Climate change models, Atmospheric circulation, Atmospheric models, Climate change
Abstract: To assess the influence of internal variability (IV) on a classification of atmospheric circulation types (CTs) in the Euro-Mediterranean (EM) region, 262 simulations by eight global climate models (GCMs) from the Coupled Model Intercomparison Project phase 6 (CMIP6) historical experiment are studied. A reanalysis-based daily classification of CTs is considered as a reference (1950–2014), discriminating the main sea level pressure types associated with specific temperature and rainfall patterns. The reanalysis centroids are projected into each GCM member. Results are explored through specific metrics characterizing the temporal and spatial variability of CTs. While the seasonality of CTs is generally well captured, considerable spread exists among model members across the different evaluated attributes. CTs typical of transition seasons and rainfall related are more challenging to reproduce. The multimember ensemble mean is notably better than the individual members in capturing the CT variability, which is represented differently among members from the same GCM and for each CT. EC-Earth3 and MIROC6 simulations presented the best performances, indicating a consensus toward better physical modeling. Our results demonstrate that the selection of individual ensemble members is a nonnegligible factor when analyzing CT classifications. It should be considered an additional source of uncertainty when generating tailored climate information and when assessing long-term surface trends at the regional scale. This is particularly challenging for hotspot regions like the EM. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Climate is the property of American Meteorological Society and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Robustness of Euro-Mediterranean Synoptic Circulation Types and Sensitivity to Member Selection in CMIP6 Models.
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Climate%22">Journal of Climate</searchLink>. Feb2026, Vol. 39 Issue 4, p1053-1064. 12p.
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– Name: Abstract
  Label: Abstract
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  Data: To assess the influence of internal variability (IV) on a classification of atmospheric circulation types (CTs) in the Euro-Mediterranean (EM) region, 262 simulations by eight global climate models (GCMs) from the Coupled Model Intercomparison Project phase 6 (CMIP6) historical experiment are studied. A reanalysis-based daily classification of CTs is considered as a reference (1950–2014), discriminating the main sea level pressure types associated with specific temperature and rainfall patterns. The reanalysis centroids are projected into each GCM member. Results are explored through specific metrics characterizing the temporal and spatial variability of CTs. While the seasonality of CTs is generally well captured, considerable spread exists among model members across the different evaluated attributes. CTs typical of transition seasons and rainfall related are more challenging to reproduce. The multimember ensemble mean is notably better than the individual members in capturing the CT variability, which is represented differently among members from the same GCM and for each CT. EC-Earth3 and MIROC6 simulations presented the best performances, indicating a consensus toward better physical modeling. Our results demonstrate that the selection of individual ensemble members is a nonnegligible factor when analyzing CT classifications. It should be considered an additional source of uncertainty when generating tailored climate information and when assessing long-term surface trends at the regional scale. This is particularly challenging for hotspot regions like the EM. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Journal of Climate is the property of American Meteorological Society and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Text: English
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              Text: Feb2026
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