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Problems of CMIP5 Climate Models with Tropical Low Clouds

Reference
Nam, C., Bony, S., Dufresne, J.-L. and Chepfer, H. 2012. The 'too few, too bright' tropical low-cloud problem in CMIP5 models. Geophysical Research Letters 39: 10.1029/2012GL053421.
In the words of authors Nam et al. (2012), the response of low-level clouds has long been identified as "a key source of uncertainty for model cloud feedbacks under climate change," citing the work of Bony and Dufresne (2005), Webb et al. (2006), Wyant et al. (2006) and Medeiros et al. (2008). And they state that "the ability of climate models to simulate low-clouds and their radiative properties" plays a huge role in assessing "our confidence in climate projections."

In studying this unresolved dilemma, Nam et al. analyzed "outputs from multiple climate models participating in the Fifth phase of the Coupled Model Intercomparison Project (CMIP5) using the Cloud Feedback Model Intercomparison Project Observations Simulator Package (COSP), and compared them with different satellite data sets," including "CALIPSO lidar observations, PARASOL mono-directional reflectances, and CERES radiative fluxes at the top of the atmosphere." So what did their comparison reveal?

In the words of the four French researchers, "the current generation of climate models still experiences difficulties in predicting the low-cloud cover and its radiative effects." In particular, they report that the models: (1) "under-estimate low-cloud cover in the tropics," (2) "over-estimate optical thickness of low-clouds, particularly in shallow cumulus regimes," (3) "poorly represent the dependence of the low-cloud vertical structure on large-scale environmental conditions," and (4) "predict stratocumulus-type of clouds in regimes where shallow cumulus cloud-types should prevail." However, they say that "the impact of these biases on the Earth's radiation budget ... is reduced by compensating errors [italics added]," including "the tendency of models to under-estimate the low-cloud cover and to over-estimate the occurrence of mid- and high-clouds above low-clouds."

Given such findings, it seems more than odd that leaders of numerous nations are forging ahead with energy policy prescriptions for halting global warming - which has been non-existent for close to two decades now - based on climate change projections derived from mathematical models harboring acknowledged problems that are supposedly overcome by compensating errors.

Additional References
Bony, S. and Dufresne, J. 2005. Marine boundary layer clouds at the heart of tropical cloud feedback uncertainties in climate models. Geophysical Research Letters 32: 10.1029/2005GL023851.

Medeiros, B., Stevens, B., Held, I., Zhao, M., Williamson, D., Olson, J. and Bretherton, C. 2008. Aquaplanets, climate sensitivity, and low clouds. Journal of Climate 21: 4974-4991.

Webb, M.J., Senior, C.A., Sexton, D.M.H., Ingram, W.J., Williams, K.D., Ringer, M.A., McAvaney, B.J., Colman, R., Soden, B.J., Gudgel, R., Knutson, T., Emori, S., Ogura, T., Tsushima, Y., Andronova, N., Li, B., Musat, I., Bony, S. and Taylor, K.E. 2006. On the contribution of local feedback mechanisms to the range of climate sensitivity in two GCM ensembles. Climate Dynamics 27: 17-38.

Wyant, M., Khairoutdinov, M. and Bretherton, C. 2006. Climate sensitivity and cloud response of a GCM with a superparameterization. Geophysical Research Letters 33: 10.1029/2005GL025464.

Archived 19 March 2013