4.7 Article

Using mean flow change as a proxy to infer interdecadal storm track variability

Journal

JOURNAL OF CLIMATE
Volume 16, Issue 13, Pages 2178-2196

Publisher

AMER METEOROLOGICAL SOC
DOI: 10.1175/2773.1

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Several recent studies, based mainly on analyses of reanalysis data, have suggested that the Northern Hemisphere storm tracks have intensified during the second half of the twentieth century. However, comparisons with rawinsonde observations over land areas suggest that eddy, variance/covariance. statistics may contain spurious jumps that had led to an exaggeration of the storm track secular trend. In this study, storm track variations are inferred from mean flow anomalies using canonical correlation analysis (CCA). A CCA model relating storm track anomalies to mean flow anomalies is derived using recent, more reliable data. The model is then applied to infer storm track anamalies using mean flow anomalies for earlier periods, when storm track analyses are deemed more suspect (or even nonexistent). Results of the CCA analyses suggest that the strong secular trend observed over the Atlantic basin and Europe is consistent with mean flow anomalies, while CCA predictions based on mean flow changes suggest only a much weaker trend:in the Pacific storm track activity than that present in the reanalysis data. Over the regions where comparisons with rawinsonde data can be made, the interdecadal trends inferred by the CCA model are quite consistent with rawinsonde data over the Pacific storm track entrance and exit regions, as well as the Atlantic storm track exit regions, but are inconsistent with rawinsonde observations and reanalysis data over northeastern North America where CCA predictions are generally poor. A CCA hindcast based on Trenberth and Paolino mean sea level pressure data as a predictor shows no indication that the secular increase in storm track intensity extends further back prior to 1960, suggesting that during the entire twentieth century, storm track activity was weakest during the 1960s.

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