During the boreal cool season, regional climate in the United States is strongly impacted by extreme temperature regimes (ETRs), including both cold air outbreaks (CAOs) and warm waves (WWs), which have significant impacts on energy consumption, agriculture, as well as the human population. Using NCEP/NCAR and MERRA reanalysis data, the statistical characteristics of ETRs over three distinct geographical regions are studied: the Midwest (MW), Northeast Megalopolis (NE), and Deep South (SE). The regional long-term variability in the frequency and amplitude of ETRs is examined, and the modulation of these ETRs by low frequency modes is quantified.
ETR behavior is characterized using three different metrics applied to both T and Twc: 1) the number of extreme cold/warm days, 2) a seasonal cumulative "impact factor", and 3) a peak normalized anomaly value. A trend analysis reveals a significant downward trend in SE WW events from 1949-2011. Otherwise, no significant trends are found for ETRs in any of the other regions. Thus, these results indicate that there has not been any significant reduction in either the amplitude or frequency of CAOs over the United States during the period of analysis. In fact, for the SE region, the recent winters of 2009/2010 and 2010/2011 both rank among the top 5 in terms of CAO metrics. In addition, strong interannual variability in ETRs is evident from 1949-2011 in each region. Linear regression analysis is then used to determine the associations between ETR metrics and the seasonal mean state of several low frequency modes, and it is found that ETRs tend to be modulated by certain low frequency modes. For instance, in the SE region, there is a significant association between ETRs and the phase of the North Atlantic (or Arctic) Oscillation (NAO/AO), the Pacific North American (PNA) pattern (for WWs only), the Pacific Decadal Oscillation (PDO) and the El Niño-Southern Oscillation (for WWs only). Over the MW region, WWs are modulated by the NAO/AO and PNA patterns, while in the NE region, the AO, NAO (for WWs only) and PDO (for WWs only) are implicated. In addition, it is found that there is an asymmetry between the low frequency mode modulation of CAOs and WWs. Multiple linear regression analysis is then used to quantify the relative roles of the various low frequency modes in explaining interannual variability in ETR metrics, and reveals that various combinations of low frequency modes can explain anywhere between 10% and 50% of the variance in the ETR metrics.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/42889 |
| Date | 18 November 2011 |
| Creators | Westby, Rebecca Marie |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Detected Language | English |
| Type | Thesis |
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