Abstract

This paper reviews methods that have been used to evaluate global climate simulations and to downscale global climate scenarios for the assessment of climate impacts on hydrologic systems in the Pacific Northwest, USA. The approach described has been developed to facilitate integrated assessment research in support of regional resource management. Global climate model scenarios are evaluated and selected based on historic 20th century simulations. A statistical downscaling method is then applied to produce a regional data set. To facilitate the use of climate projections in hydrologic assessment, additional statistical mapping may be applied to generate synthetic station time series. Finally, results are presented from a regional climate model that indicate important differences in the regional climate response from what is captured by global models and statistical downscaling.

Introduction

Some of the most important anticipated impacts of climate change are expressed through hydrologic processes such as streamflow, snowpack, and flooding. Modelling these impacts requires high-resolution regional data for future scenarios of temperature and precipitation. The science of climate change at global and regional scales is quite advanced, and climate simulations are typically downscaled to as fine as 10–۵۰ km grids or to station locations. While there remains significant research to be done to fully understand climate dynamics at these scales and to bolster confidence in future scenarios, the current climate modeling is adequate for many applications in hydrology.