Three modes of recent pan-Arctic multivariate change

We investigate the recent large changes in the Arctic for 1965-1995 through examination of 86 regionally-distributed time series representing seven data types: climate indices, atmosphere, ocean, terrestrial, sea ice, fisheries, and other biological data. To our knowledge, this is the first semi-quantitative analysis of Arctic data that spans multiple disciplines and geographic regions. Although visual inspection of the data collection indicates that Arctic change is complex, three patterns are evident. The pattern based upon the first Principal Component(PC1), representing 23% of the variance, has a single regime-like shift near 1989 based on a large number of time series, which include projections from a strong stratospheric vortex in spring, the Arctic Oscillation, sea ice declines in several regions, and changes in selected mammal, bird, and fish populations. The pattern based on the second Principal Component(PC2) shows interdecadal variability over the Arctic Ocean Basin north of 70N; this variability is observed in surface wind fields, sea ice, and ocean circulation. Contributions to PC1 cover a larger geographic area than PC2, and are consistent with a recent amplification of the interdecadal mode due to polar processes such as increased incidence of cold stratospheric temperature anomalies or internal feedbacks. Most land processes-such as snow cover, greenness, Siberian runoff, permafrost temperatures-and certain subarctic sea ice records show a third pattern of a linear trend over the 30-year interval, qualitatively different than either PC1 or PC2. These variables are from lower latitudes and often integrate the atmospheric or oceanographic influence over several seasons or years including summer. That more than half of the data collection projects strongly onto one of the three patterns, suggests that the Arctic is responding as a coherent system over the previous three decades. However, no single index or class of observations exclusively track change in the Arctic, a conclusion that emerges from a multivariate analysis.