Quantifying the sensitivity of simulated climate change to model configuration

Author Posting. © The Author(s), 2009. This is the author's version of the work. It is posted here by permission of Springer for personal use, not for redistribution. The definitive version was published in Climatic Change 3-4 (2009): 275-298, doi:10.1007/s10584-008-9494-x.This study used “factor separation” to quantify the sensitivity of simulated present and future surface temperatures and precipitation to alternative regional climate model physics components. The method enables a quantitative isolation of the effects of using each physical component as well as the combined effect of two or more components. Simulation results are presented from eight versions of the Mesoscale Modeling System Version 5 (MM5), one-way nested within one version of the Goddard Institute for Space Studies Atmosphere-Ocean Global Climate Model (GISS AOGCM). The MM5 simulations were made at 108 km grid spacing over the continental United States for five summers in the 1990s and 2050s. Results show that the choice of cumulus convection parameterization is the most important “factor” in the simulation of contemporary surface summer temperatures and precipitation over both the western and eastern United States. The choice of boundary layer scheme and radiation package also increases the range of model simulation results. Moreover, the alternative configurations give quite different results for surface temperature and precipitation in the 2050s. For example, simulated 2050s surface temperatures by the scheme with the coolest 1990s surface temperatures are comparable to 1990s temperatures produced by other schemes. The study analyzes the spatial distribution of 1990s to 2050s projected changes in the surface temperature for the eight MM5 versions. The predicted surface temperature change at a given grid point, averaged over all eight model configurations, is generally about twice the standard deviation of the eight predicted changes, indicating relative consensus among the different model projections. Factor separation analysis indicates that the choice of cumulus parameterization is the most important modeling factor amongst the three tested contributing to the computed 1990s to 2050s surface temperature change, although enhanced warming over many areas is also attributable to synergistic effects of changing all three model components. Simulated ensemble mean precipitation changes, however, are very small and generally smaller than the inter-model standard deviations. The MM5 versions therefore offer little consensus regarding 1990s to 2050s changes in precipitation rates.This research was supported by Grant R828733 from the U.S. Environmental Protection Agency's Science to Achieve Results (STAR) program, NSF Grant ATM-0652518, NASA Grant NNX07AI93G and the NASA Climate Variability and Climate Change Programs