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Erschienen in:
2015 | OriginalPaper | Buchkapitel
Downscaling of Regional Climate Scenarios within Agricultural Areas Across Canada with a Multivariate, Multisite Model
verfasst von : Nathaniel K. Newlands, Weixun Lu, Tracy A. Porcelli
Erschienen in: Interdisciplinary Topics in Applied Mathematics, Modeling and Computational Science
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Abstract
Better methods are needed to statistically downscale climate variability to agricultural ecosystem impact scales and to reduce uncertainty in regional climate model (RCM) predictions. We present a multivariate, multisite model for downscaling climate to the 10 km scale for agricultural areas across Canada. Scenario data was obtained from NARCCAP (North American Regional Climate Change Assessment Program). This method employs variable-selection for a multivariate set of regional climate model predictors, and may offer a rapid (automated) and reliable (cross-validated) way to generate high-resolution climate surfaces for use in agricultural decision-making. We provide selected results that show the model can significantly reduce bias in mean precipitation.