Climatic Change

, Volume 87, Supplement 1, pp 21-42

First online:

Climate change scenarios for the California region

  • Daniel R. CayanAffiliated withScripps Institution of Oceanography, University of California, San DiegoU.S. Geological Survey Email author 
  • , Edwin P. MaurerAffiliated withSanta Clara University
  • , Michael D. DettingerAffiliated withScripps Institution of Oceanography, University of California, San DiegoU.S. Geological Survey
  • , Mary TyreeAffiliated withScripps Institution of Oceanography, University of California, San Diego
  • , Katharine HayhoeAffiliated withDepartment of Geosciences, Texas Tech University

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To investigate possible future climate changes in California, a set of climate change model simulations was selected and evaluated. From the IPCC Fourth Assessment, simulations of twenty-first century climates under a B1 (low emissions) and an A2 (a medium-high emissions) emissions scenarios were evaluated, along with occasional comparisons to the A1fi (high emissions) scenario. The climate models whose simulations were the focus of the present study were from the Parallel Climate Model (PCM1) from NCAR and DOE, and the NOAA Geophysical Fluid Dynamics Laboratory CM2.1 model (GFDL). These emission scenarios and attendant climate simulations are not “predictions,” but rather are a purposely diverse set of examples from among the many plausible climate sequences that might affect California in the next century. Temperatures over California warm significantly during the twenty-first century in each simulation, with end-of-century temperature increases from approximately +1.5°C under the lower emissions B1 scenario in the less responsive PCM1 to +4.5°C in the higher emissions A2 scenario within the more responsive GFDL model. Three of the simulations (all except the B1 scenario in PCM1) exhibit more warming in summer than in winter. In all of the simulations, most precipitation continues to occur in winter. Relatively small (less than ~10%) changes in overall precipitation are projected. The California landscape is complex and requires that model information be parsed out onto finer scales than GCMs presently offer. When downscaled to its mountainous terrain, warming has a profound influence on California snow accumulations, with snow losses that increase with warming. Consequently, snow losses are most severe in projections by the more responsive model in response to the highest emissions.