Background
Climate modelers have long struggled to adequately represent the sensitivity of convective cloud systems to tropospheric humidity in their mathematical representations of earth's climate system.

What was done
Del Genio reviews the rate of progress in this important endeavor in the journal Surveys in Geophysics.

What was learned
The U.S. National Aeronautics and Space Administration scientist - stationed at the Goddard Institute for Space Studies in New York - finds a number of important problems related to this particular field of endeavor that have yet to be adequately resolved. He notes, for example, that many parameterizations of convective cloud variability "are not sufficiently sensitive to variations in tropospheric humidity," which "lack of sensitivity," as he describes it, "can be traced in part to underestimated entrainment of environmental air into rising convective clouds and insufficient evaporation of rain into the environment." And as a result of these deficiencies, he notes that "the parameterizations produce deep convection too easily while stabilizing the environment too quickly to allow the effects of convective mesoscale organization to occur."

To be fair, Del Genio does note that "recent versions of some models have increased their sensitivity to tropospheric humidity and improved some aspects of their variability," but he says that "a parameterization of mesoscale organization is still absent from most models," while stating that "adequately portraying convection in all its realizations remains a difficult problem [italics added]."

On another note, Del Genio writes that "to date, metrics for model evaluation have focused almost exclusively on time mean two-dimensional spatial distributions of easily observed parameters," and he indicates that "it has become clear that such metrics have no predictive value for climate feedbacks and climate sensitivity (e.g., Collins et al., 2011)," while adding that those metrics "are also probably not helpful for assessing most other important features of future climate projections, because temporal variability gives greater insight into the physical processes at work."

What it means
Success in adequately dealing with clouds of all types in general circulation models would appear to be a long way off. In fact, Del Genio opines that "given the insensitivity of these models to tropospheric humidity and their failure to simulate the Madden-Julian Oscillation and diurnal cycle, ... it seems unlikely that it will ever be possible to establish a general set of metrics that can be used to anoint one subset of models as our most reliable indicators of all aspects of climate change."

Reference
Collins, M., Booth, B.B.B., Bhaskaran, B., Harris, G.R., Murphy, J.M., Sexton, D.M.H. and Webb, M.J. 2011. Climate model errors, feedbacks and forcings: a comparison of perturbed physics and multi-model ensembles. Climate Dynamics 36: 1737-1766.