This paper, just published with co-authors from the PRIMAVERA project, on model-observation comparison offers researchers important guidance on objective selection of observational data.

Using climate models to estimate the quality of global observational data sets 

Massonnet, F. et al., 2016. Science doi: 10.1126/science.aaf6369

Observational estimates of the climate system are essential to monitor and understand ongoing climate change and to assess the quality of climate models used to produce near- and long-term climate information. This study poses the dual and unconventional question: can climate models be used to assess the quality of observational references? We show that this question not only rests on solid theoretical grounds but also offers insightful applications in practice. By comparing four observational products of sea surface temperature with a large multi-model climate forecast ensemble, we find compelling evidence that models systematically score better against the most recent, advanced, but also most independent product. These results call for generalized procedures of model-observation comparison and provide guidance for a more objective observational data set selection.

Download the paper from Science here.