Relationships between the North Atlantic Oscillation index and temperatures in Europe in global climate models
The study evaluates relationships between the North Atlantic Oscillation (NAO) index and winter temperatures (including indices of extremes) over Europe in an ensemble of transient simulations of current global climate models (GCMs). We focus on identification of areas in which the NAO index is link...
| Published in: | Studia Geophysica et Geodaetica |
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| Main Authors: | , |
| Format: | Article in Journal/Newspaper |
| Language: | unknown |
| Subjects: | |
| Online Access: | https://kramerius.lib.cas.cz/view/uuid:5ca4c581-34cb-49c9-b8e8-eb7f1074c872 https://doi.org/10.1007/s11200-012-0824-0 |
| Summary: | The study evaluates relationships between the North Atlantic Oscillation (NAO) index and winter temperatures (including indices of extremes) over Europe in an ensemble of transient simulations of current global climate models (GCMs). We focus on identification of areas in which the NAO index is linked to winter temperatures and temperature extremes in simulations of the recent climate (1961–2000), and evaluate how these relationships change in climate change scenarios for the late 21st century (2071–2100). Most GCMs are able to reproduce main features of the observed links. The NAO index is more important for cold than warm extremes, which is also reproduced by the GCMs. However, all GCMs underestimate the magnitude of the NAO influence on cold extremes when averaged over northern and western Europe. For future scenarios, the links between the NAO and temperatures are mostly analogous to those in the recent climate, except for one GCM (CM3) in which the influence of the NAO on temperature almost disappears over whole Europe. This suggests that future scenarios from this particular GCM should be evaluated with caution. The NAO index is found to represent a useful covariate that explains an important fraction of variability of cold extremes in winter, and its incorporation into extreme value models for daily temperatures (and their possible changes under climate change) may improve performance of these models and reliability of estimates of extremes and their uncertainty. Romana Beranová, Jan Kyselý. Obsahuje seznam literatury |
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