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Title: The impact of Arctic sea ice change on midlatitude climate
Author: Holmes, Caroline Ruth
ISNI:       0000 0004 5921 9349
Awarding Body: University of Reading
Current Institution: University of Reading
Date of Award: 2016
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Arctic sea ice loss is a robust feature of observations and of climate model projections. Amplified winter lower tropospheric warming in the Arctic relative to the global mean is associated with this ice loss. Many recent studies have addressed the possible effects of these changes on the midlatitude atmospheric circulation, particularly in the North Atlantic. These studies suggest responses including an equatorward jet shift, a negative annular mode response and changes in Rossby wave behaviour. However, there is disagreement on the magnitude, significance and even sign of these responses. Previous studies have shown the advantages of model hierarchies for understanding the atmosphere. In this thesis, experiments are conducted in HadGAM1 with simplified lower boundary conditions. Two sets of experiments are conducted, one in a zonally symmetric aquaplanet and the other in a configuration with representative northern hemisphere land masses. A wide range of sea ice profiles are imposed. The dominant response to ice removal in an aquaplanet is an equatorward jet shift, consistent with previous work. This response is moderate in magnitude for ice which does not exceed 65◦ latitude, but strongly nonlinear for greater ice extents. The zonal mean response is qualitatively similar in the asymmetric configuration, but the nature of the asymmetric response shows sensitivity to the exact ice edge location. These results have implications for understanding the impact of sea ice anomalies in past as well as present climates. Changes in surface temperature gradients, including from Arctic amplification, could affect midlatitude climate even if circulation changes are small. In particular, changes in thermal advection could alter midlatitude temperature variability and extremes. In this thesis a multiple regression model is used to investigate projected monthly temperature variance changes in a recent single model ensemble. Many robust changes, including reduced winter temperature variance in Europe, are consistent with the effect of changes in the seasonal mean temperature gradient alone.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available