Modeling Climate Feedbacks Based on Short-Term Climate Variations
Koumoutsaris, S. 2013. What can we learn about climate feedbacks from short-term climate variations? Tellus A 65: 10.3402/tellusa.v65i0.18887.
In the words of the Swiss scientist, "the CMIP3 models show a much larger interdecile range for all short-term feedbacks in comparison to the long-term ones," which he says "is also the case for the three models with the most realistic ENSO representation," citing van Oldenborgh et al. (2005)." He also indicates that the models have difficulty capturing "the position and magnitude of ENSO teleconnection patterns." In addition, he reports that "the uncertainty in the cloud feedback, using a combination of reanalysis and satellite data, is still very large."
Koumoutsaris concludes that his several analyses indicate that "important aspects of the ENSO variability are still poorly understood and/or simulated." And in the case of cloud feedback, he says that it is difficult to come to "any firm conclusion" ... even on the sign of the feedback. And when these phenomena are so poorly simulated - even to the point where the direction of change of one of them remains unknown - it should be clear to all that the climate-modeling enterprise still has a long, long way to go before it can be considered good enough to serve as a basis for energy policy decisions that are already dictating various aspects of human behavior.
Bony, S., Colman, R., Kattsov, V.M., Allan, R.P., Bretherton, C.S., Dufresne, J., Hall, A., Hallegatte, S., Ingram, W., Randall, D.A., Soden, B.J., Tselioudis, G. and Webb, M.J. 2006. How well do we understand and evaluate climate change feedback processes? Journal of Climate 19: 3445-3482.
Van Oldenborgh, G.J., Philip, S.Y. and Collins, M. 2005. El Niņo in a changing climate: a multi-model study. Ocean Science 1: 81-95.