2013: Behaviour of the winter North Atlantic eddy-driven jet stream in the CMIP3 integrations

Abstract A systematic analysis of the winter North Atlantic eddy-driven jet stream latitude andwind speed from 52 model integrations, taken from the coupled model intercomparison project phase 3, is carried out and compared to results obtained from the ERA-40 reanalyses. We con-sider here a control...

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Bibliographic Details
Main Authors: Abdel Hannachi, Elizabeth A. Barnes, Tim Woollings
Other Authors: The Pennsylvania State University CiteSeerX Archives
Format: Text
Language:English
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Online Access:http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.656.6571
http://barnes.atmos.colostate.edu/FILES/MANUSCRIPTS/Hannachi_Barnes_etal_2012_CDYN.pdf
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Summary:Abstract A systematic analysis of the winter North Atlantic eddy-driven jet stream latitude andwind speed from 52 model integrations, taken from the coupled model intercomparison project phase 3, is carried out and compared to results obtained from the ERA-40 reanalyses. We con-sider here a control simulation, twentieth century simula-tion, and two time periods (2046–2065 and 2081–2100) from a twenty-first century, high-emission A2 forced sim-ulation. The jet wind speed seasonality is found to be similar between the twentieth century simulations and the ERA-40 reanalyses and also between the control and forced simula-tions although nearly half of the models overestimate the amplitude of the seasonal cycle. A systematic equatorward bias of the models jet latitude seasonality, by up to 7", is observed, andmodels additionally overestimate the seasonal cycle of jet latitude about the mean, with the majority of the models showing equatorward and poleward biases during the cold and warm seasons respectively. A main finding of this work is that no GCM under any forcing scenario con-sidered here is able to simulate the trimodal behaviour of the observed jet latitude distribution. The models suffer from serious problems in the structure of jet variability, rather than just quantitiative errors in the statistical moments. 1