Background
According to the authors, "eliminating the mean bias in climate models continues to be a principal motivating goal in climate science." And, therefore ...

What was done
... they "investigated mean biases in air-sea heat and freshwater flux components in the Community Climate System Model version 4 [CCSM4]." This they did by comparing present-day mean biases, variability errors, and late twentieth-century trend differences derived from the CCSM4 with real-world information obtained from the Coordinated Ocean-Ice Reference Experiment (CORE) data set.

What was learned
Bates et al. report that: (1) "although regional biases in some components are improved, others are still present and some are made worse [italics added]," (2) "the largest degradation in the transition from CCSM3 to CCSM4 in mean flux bias is found in the greater shortwave radiation reaching the ocean's surface," (3) "this degradation is a global, nearly uniform increase with many regional averages falling outside the range of observation-based estimates," (4) "enhanced evaporation leads to net air-sea freshwater fluxes that can be outside the range of observation-based estimates, and thus lead to erroneous ocean salinity and density," (5) "enhanced evaporation can also lead to an enhanced hydrological cycle with more precipitation over both the ocean and land," (6) "annual variability [in air-sea flux fields] is substantially in error in virtually all regions with the likelihood of robust CCSM4-CORE disagreement - based on the wavelet probability analysis of Stevenson et al. (2010) - almost always above 90%," (7) "the net shortwave radiation has the largest errors on all time scales (mean, annual, and interannual)," and (8) "the pattern of errors is different for each time scale, suggesting that cloud activity at each time scale may be flawed with different patterns."

What it means
In the words of the six scientists who conducted the analyses, "substantial improvements in annual variance fidelity may be possible in future model versions." One can only hope they are correct, and that the wrongs of the models can ultimately be righted. But until then ...

Reference
Stevenson, S., Fox-Kemper, B., Jochum, M., Rajagopalan, B. and Yeager, S.G. 2010. ENSO model validation using wavelet probability analysis. Journal of Climate 23: 5540-5547.