Paper Reviewed
Takahashi, H., Su, H. and Jiang, J.H. 2016. Error analysis of upper tropospheric water vapor in CMIP5 models using "A-Train" satellite observations and reanalysis data. Climate Dynamics 46: 2787-2803.

Introducing their study, Takahashi et al. (2016) note that "upper tropospheric water vapor (UTWV) plays a critical role in amplifying global warming caused by increasing greenhouse gases," yet they say "it is one of the most poorly simulated quantities in climate models." And in light of this fact, they go on to "diagnose the UTWV simulation errors from AMIP models submitted to the CMIP5 project by using 'A-Train' satellite observation and reanalysis data." And what did this undertaking reveal?

The three U.S. researchers report that the models "generally have [1] positive biases in UTWV, except over the continental convective regions where [2] negative biases predominate." And they also note, in this regard, that (3,4) "the errors in the patterns and amplitudes of climatological UTWV are highly correlated with those in relative humidity [RH] and vertical pressure velocity [hPa/day]." And they thus conclude their paper by saying "we find that large errors in UTWV in CMIP5 models are primarily driven by the errors in RH, which are closely related to the errors in large-scale circulation, rather than the errors in temperature."

And so it would appear that all kinds of errors continue to torment the world's climate modelers.