Advances in Atmospheric Sciences

, Volume 33, Issue 8, pp 905–918 | Cite as

Scale-dependent regional climate predictability over North America inferred from CMIP3 and CMIP5 ensemble simulations



Through the analysis of ensembles of coupled model simulations and projections collected from CMIP3 and CMIP5, we demonstrate that a fundamental spatial scale limit might exist below which useful additional refinement of climate model predictions and projections may not be possible. That limit varies among climate variables and from region to region. We show that the uncertainty (noise) in surface temperature predictions (represented by the spread among an ensemble of global climate model simulations) generally exceeds the ensemble mean (signal) at horizontal scales below 1000 km throughout North America, implying poor predictability at those scales. More limited skill is shown for the predictability of regional precipitation. The ensemble spread in this case tends to exceed or equal the ensemble mean for scales below 2000 km. These findings highlight the challenges in predicting regionally specific future climate anomalies, especially for hydroclimatic impacts such as drought and wetness.


regional climate predictability CMIP5 ensemble North America climate change 


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Copyright information

© Chinese National Committee for International Association of Meteorology and Atmospheric Sciences, Institute of Atmospheric Physics, Science Press and Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.Department of Meteorology and Center for Advanced Data Assimilation and Predictability TechniquesThe Pennsylvania State UniversityUniversity ParkUSA
  2. 2.IMSG at NOAA/NWS/NCEP/Environmental Modeling CenterUniversity ParkUSA

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