linked in logo | IS-ENES | Contact

Exploring climate model data

Which GCM is best/how to select one?

Many climate change experiments have been performed with GCMs. Four criteria for selection of which GCM(s)' output to use for an impact study have been suggested: vintage, resolution, validity and representativeness of results.

In general, recent model simulations are likely (though by no means certain) to be more reliable than those of an earlier vintage. They are based on recent knowledge, incorporate more processes and feedbacks and are usually of a higher spatial resolution than earlier models.

As climate models have evolved and computing power has increased, there has been a tendency towards increased resolution. Some of the early GCMs operated on a horizontal resolution of some 1000 km with between 2 and 10 levels in the vertical. More recent models are run at nearer 250 km spatial resolution with perhaps 20 vertical levels. However, although higher resolution models contain more spatial detail this does not necessarily guarantee a superior model performance.

A more persuasive criterion for model selection is to adopt the GCMs that simulate the present-day climate most faithfully, on the premise that these GCMs would also yield the most reliable representation of future climate. The approach involves comparing GCM simulations that represent present-day conditions with the observed climate. The modelled and observed data are projected to the same grid, and statistical methods employed to compare, for example, mean values, variability and climatic patterns. Some model-observed comparisons are possible using the Data Visualisation Pages of the DDC.

If results from more than one GCM are to be applied in an impact assessment (and given the known uncertainties of GCMs, this is strongly recommended), another criterion for selection is to examine the representativeness of the results. Not all GCMs have been independly developed, in fact a family tree may be constructed (see link). Where several GCMs are to be selected, it might be prudent to choose models that show a range of changes in a key variable in the study region (for example, models showing little change in precipitation, models showing an increase and models showing a decrease). The selections may not necessarily be the best validated models (see above), although some combination of models satisfying both criteria couldbe agreed upon.


Related links

Global models

GCM Genealogy



The IS-ENES project has received funding from the European Union's Seventh Framework Programme for research, technological development and demonstration.