Kumar, S., Merwade, V., Kinter III, J.L. and Niyogi, D. 2013. Evaluation of temperature and precipitation trends and long-term persistence in CMIP5 twentieth-century climate simulations. Journal of Climate 26: 4168-4185.
Authors Kumar et al. (2013) "analyzed twentieth-century temperature and precipitation trends and long-term persistence from 19 climate models participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5)," focusing "on continental areas (60°S-60°N) during 1930-2004 to ensure higher reliability in the observations." This they did via a "nonparametric trend detection method," while "long-term persistence was quantified using the Hurst coefficient, taken from the hydrology literature." An what did that analysis reveal?
Although some things were done well by the participating models, others were not. Kumar et al. report, for example, that "the models capture the long-term persistence in temperature reasonably well," but they say that "the models have limited capability to capture the long-term persistence in precipitation." They also state that "most climate models underestimate the spatial variability in temperature trends," and they say there were "large uncertainties in the simulation of regional-/local-scale temperature and precipitation trends." In addition, they report that "Sakaguchi et al. (2012a,b) have evaluated the simulation skill for temperature trends from selected CMIP3 and CMIP5 climate models," finding "limited skill in the simulation of temperature trends at regional scales in these climate models."
Finally, "from a regional natural resource planning perspective," the four scientists write that the multimodel-ensemble averages provide what they kindly call "conservative value for planning or design." As an example, they note that "the India and West Africa regions are drying much faster (-20 mm/decade) in the observations than simulations by the multimodel-ensemble average (-5 mm/decade)," while similarly noting that "north-central Asia is warming twice as fast as the global-average warming," which is something "not found in the multimodel-ensemble average."
Clearly, the best climate models of the present day are still not up to doing what we really need them to do to be of much service. In fact, they could potentially be leading us in a direction we may soon find to actually be detrimental to the well-being of the biosphere, including ourselves.
Sakaguchi, K., Zeng, X. and Brunke, M.A. 2012a. Temporal- and spatial-scale dependence of three CMIP3 climate models in simulating surface temperature trends in the twentieth century. Journal of Climate 25: 2456-2470.
Sakaguchi, K., Zeng, X. and Brunke, M.A. 2012b. The hindcast skill of the CMIP ensembles for the surface air temperature trend. Journal of Geophysical Research 117: 10.1029/2012JD017765.