The phrase
"emergent constraints" refers to relationships or patterns that scientists observe in complex systems or models. These relationships help scientists predict certain outcomes or variables without directly measuring or observing them. In simpler terms,
emergent constraints are ways scientists use existing information to make predictions about things they can't directly study.
Full definition
Bracegirdle, T. J. & Stephenson, D. B. On the robustness
of emergent constraints used in multimodel climate change projections of Arctic warming.
My Google search
with emergent constraints referred most often to emergency restraints for patients reacting in psychotic episodes.
It is interesting that Tapio Schneider, the joint author of the Brient Alb paper, with considerable mathematical / statistical abilities, advocates caution
regarding emergent constraint studies.
The main implication of the Brient
Alb emergent constraint is that the relationship between deseasonalized tropical low - cloud SW reflection and SST in the low - sensitivity inmcm4 and GISS - E2 models is far from that observed.
Borodina, A., Fischer, E. M. & Knutti,
R. Emergent constraints in climate projections: a case study of changes in high - latitude temperature variability.
The usefulness of
emergent constraints consists mostly in finding leads that help us understand and improve the physical processes in climate models that control the inter-model spread in future projections.
Since the AR4, there are a few examples of
emergent constraints where observations are used to constrain multi-model ensemble projections.
But do we really believe this to be the case, e.g., for low - cloud and turbulence parameterizations, on which the relationship in the above example (and probably in many
other emergent constraints) depends?
It needs to be a collective approach to
emergent constraints rather than a singling out one, so this whole piece went in the wrong direction by trying to find a single magic bullet.
The dependence of sensitivity on the SST warming pattern, in GCMs at least, implies that even if a valid,
strong emergent constraint on ECS in coupled GCMs were found, and there were no shortcomings in the atmospheric models of GCMs that satisfied the constraint, that would be insufficient to constrain real - world ECS.
The Zhai methods have more shortcomings than those used by Brient & Schneider for their very
similar emergent constraint, and the radical difference for four CMIP5 models in the two studies» assessment of consistency with the observational constraint from seasonal variations is a major concern.
It is fairly clear that all potentially
credible emergent constraints on ECS in climate models that have been investigated really constrain SW low cloud feedback (Qu et al. 2018).
The Brient Alb and
Zhai emergent constraints are very similar; they both involve the variation of low cloud SW reflection with SST.
There is another serious problem
with emergent constraints that do not involve the response of the climate system to increasing greenhouse gas concentrations over multidecadal or longer periods.
All but one of the models from NCAR, GFDL, GISS, UKMO and MPI, perhaps the best - known modelling centres, are ruled out by the Brient
Alb emergent constraint.
This in turn means that the observed increase in the CO2 amplitude can be converted into a much improved estimate of the CO2 - fertilization, which the authors call
an Emergent Constraint.
There have been quite a number of papers published in recent years concerning «
emergent constraints» on equilibrium climate sensitivity (ECS) in comprehensive global climate models (GCMs), of both the current (CMIP5) and previous (CMIP3) generations.