The North American Regional Climate-Change Assessment Program
Kim, J., Waliser, D.E., Mattmann, C.A., Mearns, L.O., Goodale, C.E., Hart, A.F., Crichton, D.J., McGinnis, S., Lee, H., Loikith, P.C. and Boustani, M. 2013. Evaluation of the surface climatology over the conterminous United States in the North American regional climate change assessment program hindcast experiment using a regional climate model evaluation system. Journal of Climate 26: 5698-5715.
Based on their evaluation, the eleven U.S. researchers report that (1) "the most noticeable systematic errors in the annual-mean surface air temperatures are the warm biases in the Great Plains and the cold bias in the Atlantic and Gulf of Mexico coasts," that (2) "for the winter, the most outstanding RCM errors include the warm bias in the Atlantic coast and Florida regions and cold bias in northern California and Arizona-western New Mexico," that (3) "the most notable common errors in simulating the annual precipitation [are] the wet bias in the mountainous northwestern United States and dry bias in the Gulf Coast region and the southern Great Plains," that (4) "in the summer, most RCMs underestimate precipitation in Southern California, Arizona, New Mexico, the Great Plains, and western Texas," while they "overestimate in all three coastal regions," that (5) "all RCMs show especially poor performance in simulating the summer monsoon rainfall in the Arizona-western new Mexico region," and that (6) "the model bias in surface insolation varies widely according to RCMs."
Once again, it is a clear fact that as complex and powerful as today's GCMs and RCMs are, they are still in their infancy when it comes to trying to not only replicate, but to accurately predict real-world climate, not only in the near-term, but far into the future. For the present, the models' reach vastly exceeds their grasp.