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We used the most recent downscaled data for current and future climate, created by Hayhoe et al. (2006) from three general circulation model outputs: the HadleyCM3 model (Pope 2000), the Geophysical Fluid Dynamics Laboratory (GFDL CM2.1) model (Delworth et al. 2005), and the Parallel Climate Model (PCM) (Washington et al,. 2000). These three are the latest generation of numerical models that couple atmospheric, ocean, sea-ice, and land-surface components to represent historical climate variability and estimate projected long-term increases in global temperatures due to human induced emissions. Atmospheric processes are simulated in these models at a horizontal resolution of 2.5 by 2 degrees (GFDL), 3.75 by 2.5 degrees (HadCM3) and T42 or ~2.8 by 2.8 degrees (PCM).
Monthly temperature and precipitation fields were statistically downscaled by Hayhoe et al. to daily values for regions with a resolution of 1/8° (Wood et al. 2002). Downscaling entailed the use of an empirical statistical technique that maps the probability density functions for modeled monthly and daily precipitation and temperature for the climatological period (1961–90) onto those of gridded historical observed data such that the mean and variability of both monthly and daily observations are reproduced by the climate model data .
We used the data for two emission scenarios: the A1fi (high emissions - which assume that the current emission trends continue into the future without modification) and the B1 (significant conservation and reduction of CO2 emissions). These two emissions scenarios bracket most of the emission futures as outlined by the Intergovernmental Panel on Climate Change’s evaluation of emission scenarios (Nakicenovic et al. 2000), and end the 21st century at roughly double (550 ppm-B1) and triple (970 ppm-A1fi) the pre-industrial levels for CO2.
We also averaged the three models for each emission scenario to yield an average high and average low emission set of climate predictors. We used these two averages plus the PCM B1 (coolest scenario) and HadleyCM3 A1fi (warmest scenario) to represent the averages and extremes of possible outcomes from the climate analysis.
To compare current vs future GCM scenarios (boxplots and statistical summaries), see: Compare Climates
Delworth, TL, Broccoli, AJ, Rosati, A, Stouffer RJ, et al, 2006. GFDL’s CM2 global coupled climate models Part 1 formulation and simulation characteristics. Journal of Climate 19, 643-674.
Hayhoe, K. Hellman, J., Lesht, B., Nadelhoffer, K., Wuebbles, D., and others (contributing authors Iverson, Prasad, Matthews, Peters). 2008. Climate change and Chicago: projections and potential impacts. An Assessment Prepared for the City of Chicago. http://www.chicagoclimateaction.org/filebin/pdf/report/Chicago_climate_impacts_report_Chapter_Five_Ecosystems.pdf
Pope, V. D., 2000. The impact of new physical parametrizations in the Hadley Centre climate model -- HadCM3. Climate Dynamics 16, 123-46. 16, 123-146.
Washington, W. M., Weatherly, J. W., Meehl, G. A., Semtner Jr., A. J., Bettge, T.W., Craig, A. P., Strand Jr., W. G., Arblaster, J. M., Wayland, V. B., James, R., Zhang, Y., 2000. Parallel climate model (PCM) control and transient simulations. Climate Dynamics 16, 755-74. 16, 755-774.