Multivariate Adaptive Constructed Analogs(MACA) Statistical Downscaling Method

The Multivariate Adaptive Constructed Analogs(MACA)(Abatzoglou, Brown, 2011) method is a statistical downscaling method which utilizes a training dataset (i.e. a meteorological observation dataset) to remove historical biases and match spatial patterns in climate model output. The following products are available: MACAv1-METDATA is available for the Western USA, while MACAv2-LIVNEH/MACAv2-METDATA are available over the entire conterminous USA. MACAv2-LIVNEH/MACAv2-METDATA both use the newest version of the MACA method (version 2), while MACAv1-METDATA uses version 1. Both methods are very similar to that described by Abatzoglou and Brown, 2011. MACAv2-METDATA

Categories: Data; Tags: Data Visualization & Tools, Northwest CASC, Science Tools for Managers, multivariate adaptive constructed analogs, statistical downscaling