Probability-Weighted Ensembles of US County-Level Climate Projections for Climate Risk Analysis
DJ Rasmussen, Malte Meinshausen, Robert E Kopp
Journal of Applied Meteorology and Climatology | AMER METEOROLOGICAL SOC | Published : 2016
Quantitative assessment of climate change risk requires a method for constructing probabilistic time series of changes in physical climate parameters. Here, two such methods, surrogate/model mixed ensemble (SMME) and Monte Carlo pattern/residual (MCPR), are developed and then are applied to construct joint probability density functions (PDFs) of temperature and precipitation change over the twenty-first century for every county in the United States. Both methods produce likely (67% probability) temperature and precipitation projections that are consistent with the Intergovernmental Panel on Climate Change's interpretation of an equal-weighted Coupled Model Intercomparison Project phase 5 (CM..View full abstract
We thank M. Oppenheimer for helpful discussion and two anonymous reviewers for their comments. DMR and REK were supported by the Risky Business Project and by the Climate Impact Lab through the University of Chicago 1896 Fund. We acknowledge the World Climate Research Programme's Working Group on Coupled Modeling, which is responsible for CMIP, and we thank the climate modeling groups (listed in Table A2 of the online supplemental material) for producing and making available their model output. For CMIP the U.S. Department of Energy's Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals.