Paper Reviewed
Grose, M.R., Brown, J.N., Narsey, S., Brown, J.R., Murphy, B.F., Langlais, C., Gupta, A.S., Moise, A.F. and Irving, D.B. 2014. Assessment of the CMIP5 global climate model simulations of the western tropical Pacific climate system and comparison to CMIP3. International Journal of Climatology 34: 3382-3399.

In introducing their publication in the Royal Meteorological Society's International Journal of Climatology, Grose et al. (2014) write that "an important influence on confidence in model projections is the realism with which the models simulate the current climate mean and variability." And they note, in this regard, that "while models are now sufficiently reliable to provide useful insights into many aspects of the climate system in the region, systematic biases in the simulation of some important features in the Pacific region persist." So what are these still-unresolvable biases? And how significant are they?

Quoting the nine Australian researchers, "there is evidence to reject one model as unsuitable for making climate projections in the region, and another two models unsuitable for analysis of the South Pacific Convergence Zone (SPCZ)." And they add that "many of the systematic model biases in the mean climate in CMIP3 are also present in the CMIP5 models," specifically identifying "biases in the position and orientation of the SPCZ and Inter-Tropical Convergence Zone, as well as the spatial pattern, variability and teleconnections of the West Pacific monsoon, and the simulation of El Niño Southern Oscillation." In addition, they indicate that unresolved problems also prohibit successful modeling of the region's cold tongue and the West Pacific monsoon, further adding that there are still "several regions in the world where CMIP5 models show significant differences to observed trends in temperature and mean sea level pressure."

As for the significance of these many biases in the current crop of CMIP5 models, one can get a sense of their importance in Grose et al.'s concluding opinion that "all projections must account for the uncertainty introduced by the presence of these biases."