Relationships between Interdecadal and Interannual Climatic Variations and Their Effect on Pennsylvania Climate

Abstract

The variability of Pennsylvania winter climate is shown to b e t h e result of mechanisms working on two distinctly different time scales: interdecadal and interannual. lnterdecadal variability is associated with hemispheric changes in large-scale atmospheric circulation regimes. During periods of zonal flow, Pennsylvania temperatures are above normal, while meridional flow is associated with below-normal temperatures. Precipitation is near normal during zonal regimes, but can b e either very dry (as it was in the 1960s) or abnormally wet (like the 1970s) with meridional flow, depending on t h e exact placement of the deepened trough over t h e eastern United States. imbedded in the interdecadal fluctuations is interannual variability which is related t o two important Northern Hemisphere teleconnection patterns: t h e Pacific/North American (PNA) and North Atlantic Oscillation (NAO) patterns. Interannual changes in t h e atmospheric circulation, as expressed by indices of the two teleconnections, explain 50 percent of the variance in Pennsylvania winter temperature, but only ;4 percent of the precipitation variance. It is argued that knowledge of such relationships provides a basis for refining and better interpreting models of greenhouse gas-induced climatic change.EDlA attention t o such news items as t h e 1982-83 El Nirioi'Southern Oscillation (ENSO) event and t h e possibility of greenhouse gas-induced warming has alerted many observers t o t h e fact that climate does have a considerable impact o n society. In turn, this knowledge has spawned an increased interest in t h e study of climatic variability ( e g , Brinkmann 1985;Karl 1985).It is now apparent that climate varies o n many temporal and spatial scales. The two examples used above, ENSO and greenhouse warming, operate at very different time scales: ENSO denotes interannual variations in climate (Yarnal 1985; Yarnal and Kiladis 1985), while t h e greenhouse gas-induced warming might have climatic effects that would last o n t h e scale of at least decades t o centuries (National Research Council 1982). Spatially, climates can vary from local scale, such as urban-rural effects (Kukla e t al. 1986), t o regional scale (Karl and Riebsame 1984) t o global scale (Jones e t al. 1986).Relationships between longer and shorter time scales (e.g., decadal versus interannual) and between larger and smaller spatial scales (e.g., global versus regiona1)are of particular concern t o scientists investigating greenhouse gas-induced warming (Clark 1985). The numerous general circulation models (GCMs) used t o predict t h e results of increased CO, and trace gas concentrations (Schlesinger 1984) have relatively coarse resolutions, providing little interannual and regional detail within t h e predicted decadal and global scale changes (Dickinson 1986). Yet t h e modelers are aware that much of t h e real human impact of t h e greenhouse warming will result from t h e smaller scale temporal and spatial changes (Lamb 1987). Within t h e context of t h e wintertime circ...

Impact of climate variation and change on Mid-Atlantic Region hydrology and water resources

“…For instance, the rain-on-snow flood of March 1936(Lichtenwalner 1936 and the Hurricane Agnes flood of June 1972(Bailey et al 1975 are evident in the unsmoothed data. Similarly, the decadelong drought of the 1960s (Cook & Jacoby 1983) and the very wet decade of the 1970s (Yarnal & Leathers 1988) appear in the smoothed curve. Despite the record snowfalls of the 1990s and the record wet year of 1996, from this perspective the 1990s were not outstandingly wet in the SRB.…”

An evaluation of two GCMs: simulation of North American teleconnection indices and synoptic phenomena

“…Several atmospheric GCMs have been shown to underestimate the amplitude of the PNA pattern associated with the 1997-1998 El Niño event (Kang et al, 2002), although Renshaw et al (1998) showed that HadAM3, the atmospheric component of HadCM3, correctly reproduces the changes in the frequency distribution of the PNA index associated with the phases of ENSO. As with the NAO, most studies of the PNA have focused on interannual and longer timescales, although the PNA varies on all timescales from days to decades (Blackmon et al, 1984;Yarnal and Leathers, 1988).…”

A synoptic climatology of stream flow and acidity

“…The distinction between the 2 approaches is in the way the atmospheric classification and the surface environment relate to one another (Yarnal 1993).…”

“…If he or she first complles a classification of weather types over the region and then relates the classes to days with high precipitation acidities, the investigator is employing a circulation-to-environment scheme. Yarnal (1993) identified 5 categories of circulation-to-environment schemes: manual synoptic typing (e.g. Lamb 1972); correlation-based map-pattern classification (Lund 1963 In contrast, with the environment-to-circulation approdch the investigator identifies the atmospheric circulation associated with particular environmental conditions at the surface.…”