Document Type

Article

Publication Date

December 2014

Publication Title

Journal of Climate

Volume

27

First Page

9006

Last Page

9026

DOI

10.1175/JCLI-D-14-00040.1

Keywords

Climate Classification/regimes, Data mining, Pattern detection, Ranking methods, Time Series, Multidecadal Variability

Disciplines

Atmospheric Sciences | Climate | Meteorology

Abstract

The optimal ranking regime (ORR) method was used to identify intradecadal to multidecadal (IMD) time windows containing significant ranking sequences in U.S. climate division temperature data. The simplicity of the ORR procedure’s output—a time series’ most significant nonoverlapping periods of high or low rankings—makes it possible to graphically identify common temporal breakpoints and spatial patterns of IMD variability in the analyses of 102 climate division temperature series. This approach is also applied to annual Atlantic multidecadal oscillation (AMO) and Pacific decadal oscillation (PDO) climate indices, a Northern Hemisphere annual temperature (NHT) series, and divisional annual and seasonal temperature data during 1896–2012. In addition, Pearson correlations are calculated between PDO, AMO, and NHT series and the divisional temperature series. Although PDO phase seems to be an important influence on spring temperatures in the northwestern United States, eastern temperature regimes in annual, winter, summer, and fall temperatures are more coincident with cool and warm phase AMO regimes. Annual AMO values also correlate significantly with summer temperatures along the Eastern Seaboard and fall temperatures in the U.S. Southwest. Given evidence of the abrupt onset of cold winter temperatures in the eastern United States during 1957/58, possible climate mechanisms associated with the cause and duration of the eastern U.S. warming hole period—identified here as a cool temperature regime occurring between the late 1950s and late 1980s—are discussed.

Comments

This article originally appeared in Journal of Climate in Volume 27 and can be found online at this link

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