8.6.4 How to Assess Our Relative Confidence in Feedbacks Simulated by Different Models?
Assessments of our relative confidence in climate projections from different models should ideally be based on a comprehensive set of observational tests that would allow us to quantify model errors in simulating a wide variety of climate statistics, including simulations of the mean climate and variability and of particular climate processes. The collection of measures that quantify how well a model performs in an ensemble of tests of this kind are referred to as ‘climate metrics’. To have the ability to constrain future climate projections, they would ideally have strong connections with one or several aspects of climate change: climate sensitivity, large-scale patterns of climate change (inter-hemispheric symmetry, polar amplification, vertical patterns of temperature change, land-sea contrasts), regional patterns or transient aspects of climate change. For example, to assess confidence in model projections of the Australian climate, the metrics would need to include some measures of the quality of ENSO simulation because the Australian climate depends much on this variability (see Section 11. 7).
To better assess confidence in the different model estimates of climate sensitivity, two kinds of observational tests are available: tests related to the global climate response associated with specified external forcings (discussed in Chapters 6, 9 and 10; Box 10.2) and tests focused on the simulation of key feedback processes.
Based on the understanding of both the physical processes that control key climate feedbacks (see Section 8.6.3), and also the origin of inter-model differences in the simulation of feedbacks (see Section 8.6.2), the following climate characteristics appear to be particularly important: (i) for the water vapour and lapse rate feedbacks, the response of upper-tropospheric RH and lapse rate to interannual or decadal changes in climate; (ii) for cloud feedbacks, the response of boundary-layer clouds and anvil clouds to a change in surface or atmospheric conditions and the change in cloud radiative properties associated with a change in extratropical synoptic weather systems; (iii) for snow albedo feedbacks, the relationship between surface air temperature and snow melt over northern land areas during spring and (iv) for sea ice feedbacks, the simulation of sea ice thickness.
A number of diagnostic tests have been proposed since the TAR (see Section 8.6.3), but few of them have been applied to a majority of the models currently in use. Moreover, it is not yet clear which tests are critical for constraining future projections. Consequently, a set of model metrics that might be used to narrow the range of plausible climate change feedbacks and climate sensitivity has yet to be developed.