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Spatial, temporal and frequency based climate change assessment in Columbia River Basin using multi downscaled-scenarios

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Abstract

Uncertainties in climate modelling are well documented in literature. Global Climate Models (GCMs) are often used to downscale the climatic parameters on a regional scale. In the present work, we have analyzed the changes in precipitation and temperature for future scenario period of 2070–2099 with respect to historical period of 1970–2000 from statistically downscaled GCM projections in Columbia River Basin (CRB). Analysis is performed using two different statistically downscaled climate projections (with ten GCMs downscaled products each, for RCP 4.5 and RCP 8.5, from CMIP5 dataset) namely, those from the Bias Correction and Spatial Downscaling (BCSD) technique generated at Portland State University and from the Multivariate Adaptive Constructed Analogs (MACA) technique, generated at University of Idaho, totaling to 40 different scenarios. The two datasets for BCSD and MACA are downscaled from observed data for both scenarios projections i.e. RCP4.5 and RCP8.5. Analysis is performed using spatial change (yearly scale), temporal change (monthly scale), percentile change (seasonal scale), quantile change (yearly scale), and wavelet analysis (yearly scale) in the future period from the historical period, respectively, at a scale of 1/16th of degree for entire CRB region. Results have indicated in varied degree of spatial change pattern for the entire Columbia River Basin, especially western part of the basin. At temporal scales, winter precipitation has higher variability than summer and vice versa for temperature. Most of the models have indicated considerate positive change in quantiles and percentiles for both precipitation and temperature. Wavelet analysis provided insights into possible explanation to changes in precipitation.

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Acknowledgments

Partial financial support for this study was provided by the DOE-BPA (cooperative agreement 00063182) and institute for sustainable solution at Portland State University. The authors would also like to acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modeling groups for producing and making available their model outputs. For CMIP, the US Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and leads development of software infrastructure in partnership with the Global Organization for Earth System Science Portals.

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  1. Department of Civil and Environmental Engineering, Portland State University, 1930 S.W. 4th Avenue, Suite 200, Portland, OR, 97201, USA

    Arun Rana & Hamid Moradkhani

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  1. Arun Rana
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  2. Hamid Moradkhani
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Correspondence to Hamid Moradkhani.

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Rana, A., Moradkhani, H. Spatial, temporal and frequency based climate change assessment in Columbia River Basin using multi downscaled-scenarios. Clim Dyn 47, 579–600 (2016). https://doi.org/10.1007/s00382-015-2857-x

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