摘要

A statistical downscaling technique is employed to link atmospheric circulation produced by an ensemble of global climate model (GCM) simulations over the twenty-first century to precipitation recorded at weather stations on Vancouver Island. Relationships between the different spatial scales are established with synoptic typing, coupled with non-homogeneous Markov models to simulate precipitation intensity and occurrence. Types are generated from daily precipitation observations spanning 1971 to 2000. Atmospheric predictors used to influence the Markov models are derived from two versions of GCM output: averages of GCM grid cells selected by correlation maps of circulation and precipitation data and an approach involving common Empirical Orthogonal Functions (EOFs) calculated from GCM output over the northeast Pacific Ocean. Projections for 2081 to 2100 made using averaged grid cells find that winter (November-February) precipitation anomalies produce modestly positive values, with gains of 7.5% in average precipitation, typical increases of 9.0% rising to 20% in the case of high-intensity precipitation, and little spatial dependence. In contrast, average and high-intensity summer precipitation (June-September) decline negligibly at most island weather stations with the exception of those in the southwestern sections, which experience reductions of 15% relative to 1971 to 2000. Projections made using common EOFs display a strong spatial dependence. Future winter precipitation is expected to increase only on the west coast of the island by 11%, on average, while the southeastern coast will experience decreases of 5% to 10%. The same pattern repeats in summer, though with negligible increases on the west coast and declines of 12% to 16% on the southeastern coast. The reliability of this novel EOF method remains to be confirmed definitively, however. In both seasons precipitation occurrence decreases slightly at all stations with declines in the total days with measurable precipitation ranging from 2% to 8%.

  • 出版日期2012