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Evaluation of methods for selecting climate models to simulate future hydrological change

  • Andrew C. RossEmail author
  • Raymond G. Najjar
Article

Abstract

A challenge for climate impact studies is the selection of a limited number of climate model projections among the dozens that are typically available. Here, we examine the impacts of methods for climate model selection on projections of runoff change for five different watersheds across the conterminous USA. The results from an ensemble of 29 global climate models and 29 corresponding hydrological model simulations are compared with the results that would have been obtained by applying six different selection methods to the climate model data and using only the selected models to drive the hydrological model. We evaluate each selection method based on whether the runoff projections produced by the method meet the method’s objective and on whether the results are sensitive to the number of models chosen. The Katsavounidis–Kuo–Zhang (KKZ) method, which is intended to maximize the spread in the projected climate change, was the only method that met both criteria for suitability. Although the KKZ method generally performed well, the results from both it and the other methods varied somewhat unpredictably based on region and number of models chosen. This study shows that the methods and models used in similar top–down studies should be carefully chosen and that the results obtained should be interpreted with caution.

Keywords

Climate model ensembles Hydrological change Model selection Model uncertainty 

Notes

Acknowledgments

We thank the anonymous reviewers and editor for comments that improved this manuscript.We also thank the World Climate Research Programme’s Working Group on Coupled Modelling, the U.S. Department of Energy’s Program for Climate Model Diagnosis and Intercomparison, the Global Organization for Earth System Science Portals, and the climate modeling groups (Table S1) for their roles in CMIP, as well as the providers of the downscaled hydrology projections.

Funding information

Funding was provided by the National Science Foundation (CBET-1360286), Pennsylvania Sea Grant (NA10OAR4170063), and National Oceanic and Atmospheric Administration’s National Centers for Coastal Ocean Science (NA16NOS4780207 to Virginia Institute of Marine Science).

Supplementary material

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Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Department of Meteorology and Atmospheric ScienceThe Pennsylvania State UniversityPennsylvaniaUSA
  2. 2.Princeton University Program in Atmospheric and Oceanic SciencesPrincetonUSA

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