Introductory Overview

• Main Author: Goodin, Douglas G.
• Format: Book Part
• Language: unknown
• Published: Oxford University Press 2003
• Subjects: Pacific; North Atlantic; North Atlantic oscillation
• Online Access: http://dx.doi.org/10.1093/oso/9780195150599.003.0022

Timescale is the organizing framework of this volume. In various sections, we consider the effects of climate variability on ecosystems at timescales ranging from weeks or months to centuries. In part III, we turn our attention to interdecadal-scale events. The timescales we consider are not absolutely defined, but for our purposes we define the interdecadal scale to encompass effects occurring with recurring cycles generally ranging from 10 to 50 years. A recurring theme in many of the chapters in this section is the effect on ecosystem response of teleconnection patterns associated with recognized quasi-periodic atmospheric circulation modes. These circulation modes include the well-known El Niño– Southern Oscillation (ENSO) phenomenon, which is generally thought to recur at shorter, interdecadal timescales but also includes some longer-term periodicities. Several other climate variability modes, including the Pacific North American index (PNA), North Atlantic Oscillation (NAO), Pacific Decadal Oscillation (PDO), and North Pacific index (NP) also show strong interdecadal scale signatures and figure prominently in the chapters of part III. McHugh and Goodin begin the section by examining the climate record at several North American LTER sites for evidence of interdecadal-scale fluctuation. They note that interdecadal-scale contributions to climate variability can best be described in terms of two types of variation: (1) discontinuities in mean value, and (2) the presence of trends in the data. Evaluation of interdecadal periodicities in LTER data is complicated by the relatively short time series of observations available. McHugh and Goodin approach the problem mainly through the use of power spectrum analysis, a widely used tool for evaluating the periodicity in a time series of data. Principal components analysis is used to decompose the time series of growing-season climate data for each of the LTER sites into their principal modes of variability. These modes are then subjected to power spectrum analysis to ...