CMIP5 Statistically Downscaled for Western USA
The Multivariate Adaptive Constructed Analogs(MACA)(Abatzoglou, Brown, 2011)
method is a statistical downscaling method which utilizes a training dataset ( the meteorological observation dataset (Abatzoglou, 2012)) to remove historical biases and match spatial patterns in climate model output.
Most recently, MACA has been used to downscale the model output from 14 global climate models (GCMs) of the Coupled Intermodel Comparison Project 5 (CMIP5) to 4-km resolution for the historical GCM forcings (1950-2005) and the future Representative Concentration Pathways (rcp's) rcp 45/85 scenarios (2006-2100).
This Dataset has the following features: