Climate models are our major source of knowledge about climate change. The impacts of
climate change are often quantified by impact models. Whereas impact models typically …

Understanding and modelling future risks from natural hazards is becoming increasingly
crucial as the climate changes, human population grows, asset wealth accumulates, and …

Statistical downscaling and bias correction are becoming standard tools in climate impact
studies. This book provides a comprehensive reference to widely-used approaches, and …

Realizing the error characteristics of regional climate models (RCMs) and the consequent
limitations in their direct utilization in climate change impact research, this study analyzes a …

There is now a large published literature on the strengths and weaknesses of downscaling
methods for different climatic variables, in different regions and seasons. However, little …

Climate models used in the Intergovernmental Panel on Climate Change (IPCC) Fourth
Assessment Report (AR4) on the whole reproduce the observed seasonal cycle and …

Downscaling of climate model data is essential to local and regional impact analysis. We
compare two methods of statistical downscaling to produce continuous, gridded time series …

Coho salmon (Oncorhynchus kisutch) populations that spawn in the coastal rivers of
Oregon, USA, formerly supported robust fisheries but are now listed as a “threatened …

Advances in the understanding of physical, chemical, and biological processes influencing
water quality, coupled with improvements in the collection and analysis of hydrologic data …

Empirical-statistical downscaling (ESD) is a method for estimating how local climatic
variables are affected by large-scale climatic conditions. ESD has been applied to local …