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Problems Modeling Air-Sea Fluxes and Sea Surface Temperatures

Bates, S.C., Fox-Kemper, B., Jayne, S.R., Large, W.G., Stevenson, S. and Yeager, S.G. 2012. Mean biases, variability, and trends in air-sea fluxes and sea surface temperature in the CCSM4. Journal of Climate 25: 7781-7801.
According to the Bates et al. (2012), "eliminating the mean bias in climate models continues to be a principal motivating goal in climate science." And, therefore, 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. In doing so, Bates et al. report the following:

(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."

One can only hope that the errors listed above can be corrected, that these wrongs can ultimately be righted. But until then ...

Additional References
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.

Archived 7 May 2013