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Keywords:

  • climate prediction;
  • climate sensitivity;
  • model calibration;
  • transient climate response

[1] Surface temperature, upper-air temperature, and ocean heat content data are used to constrain the distributions of the parameters that define three climate system properties in the MIT Integrated Global Systems Model: effective climate sensitivity, the rate of ocean heat uptake into the deep ocean, and net anthropogenic aerosol forcing. Five different surface temperature data records are used to show that the resulting parameter distribution functions are sensitive to the dataset used to estimate the likelihood of model output given the observed climate records. Estimates of effective climate sensitivity mode and mean differ by as much as 1 K between the datasets, with an overall range of 1.2 to 5.3 K. Ocean effective diffusivity distributions are poorly constrained by any dataset. The overall range of net aerosol forcing values, −0.19 to −0.83 Wm−2, is small compared to other uncertainties in climate forcings. Transient climate response (TCR) estimates derived from these distributions range between 0.87 and 2.41 K and the shapes of individual TCR distributions depend on the surface dataset. Understanding the differences in parameter distributions and climate system properties derived from them is critical for understanding the full range of uncertainty involved in climate model calibration and prediction results.