A discussion of some aspects of statistical downscaling in climate impacts assessment

作者：Liu Chang Ming; Liu Wen Bin^*; Fu Guo Bin; Ouyang Ru Lin

来源：Advances in Water Science, 2012, 23(3): 427-437.

DOI：CNKI: 32.1309.P.20120501.1616.002

• Climate impact assessment
• Climate impacts
• Down-scaling
• Dynamic downscaling
• Extreme events
• Global climate model
• Global climates
• Regression method
• Spatial resolution
• Statistical downscaling
• Stochastic weather generator
• Uncertainty
• Weather types

Global Climate Models (GCMs) are the primary tools for understanding how the global climate might change in the future. However, the relatively low spatial resolution of GCMs outputs is unsatisfactory for the local-scale climate impact assessments. Compared to dynamic downscaling, the statistical downscaling approach is widely used to bridge this gap. In this review paper, recent advances in three fundamental statistical downscaling approaches (regression methods, weather type approaches and stochastic weather generators) were presented firstly. Furthermore, uncertainties in statistical downscaling were discussed. The developments and applications of statistical downscaling in China were then summarized. The review study concludes that the comparisons and combinations of statistical downscaling and dynamic downscaling approaches, downscaling of extreme events and uncertainty analysis in statistical downscaling will become the mainstream of future related studies.

• 出版日期2012