Climatic Change

, Volume 118, Issue 2, pp 469–485 | Cite as

Future projections and uncertainty assessment of extreme rainfall intensity in the United States from an ensemble of climate models

  • Jianting Zhu
  • William Forsee
  • Rina Schumer
  • Mahesh Gautam


Changes in climate are expected to lead to changes in the characteristics extreme rainfall frequency and intensity. In this study, we propose an integrated approach to explore potential changes in intensity-duration-frequency (IDF) relationships. The approach incorporates uncertainties due to both the short simulation periods of regional climate models (RCMs) and the differences in IDF curves derived from multiple RCMs in the North American Regional Climate Change Assessment Program (NARCCAP). The approach combines the likelihood of individual RCMs according to the goodness of fit between the extreme rainfall intensities from the RCMs’ historic runs and those from the National Centers for Environmental Prediction (NCEP) North American Regional Reanalysis (NARR) data set and Bayesian model averaging (BMA) to assess uncertainty in IDF predictions. We also partition overall uncertainties into within-model uncertainty and among-model uncertainty. Results illustrate that among-model uncertainty is the dominant source of the overall uncertainty in simulating extreme rainfall for multiple locations in the U.S., pointing to the difficulty of predicting future climate, especially extreme rainfall regimes. For all locations a more intense extreme rainfall occurs in future climate; however the rate of increase varies among locations.


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Copyright information

© Springer Science+Business Media Dordrecht 2012

Authors and Affiliations

  • Jianting Zhu
    • 1
  • William Forsee
    • 2
  • Rina Schumer
    • 3
  • Mahesh Gautam
    • 4
  1. 1.Department of Civil and Architectural EngineeringUniversity of WyomingLaramieUSA
  2. 2.Desert Research InstituteLas VegasUSA
  3. 3.Desert Research InstituteRenoUSA
  4. 4.California Department of Water ResourcesSacramentoUSA

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