On structural errors in emergent constraints

Abstract

Abstract. Studies of emergent constraints have frequently proposed that a single metric alone can constrain future responses of the Earth system to anthropogenic emissions. The prevalence of this thinking has led to literature and messaging which is sometimes confusing to policymakers, with a series of studies over the last decade making confident, yet contradictory, claims on the probability bounds of key climate variables. Here, we illustrate that emergent constraints are more likely to occur where the variance across an ensemble of climate models of both observable and future climate arises from common structural assumptions and few degrees of freedom. Such cases are likely to occur when processes are represented in a common, oversimplified fashion throughout the ensemble, about which we have the least confidence in performance out of sample. We consider these issues in the context of a number of published constraints, and argue that the application of emergent constraints alone to estimate uncertainties in unknown climate responses can potentially lead to bias and overconfidence in constrained projections. Together with statistical robustness and plausibility of mechanism, assessments of climate responses must include multiple lines of evidence to identify biases that arise from common oversimplified modeling assumptions which impact both present and future climate simulations in order to mitigate against the influence of common structural biases.

 RETRACTED ARTICLE: A constraint on historic growth in global photosynthesis due to increasing CO2

“…For example, if all models in the ensemble had the same missing or biased process representation, which led to systematic bias in the modeled relationship between the sensitivity of photosynthesis to CO2 and the land sink across models, that could bias the emergent constraint reported here. Systematic cross-model biases with shared structural similarity could also lead to an underestimation of the uncertainty associated with the values derived from the emergent constraint 46,47 . The models we examine represent the state-ofthe-science for land surface modeling, and have substantial diversity of process representations and responses to forcings 48 , even for well-studied processes such as photosynthesis.…”

Toward Consistent Observational Constraints in Climate Predictions and Projections

“…Efforts to identify consensus or consolidate constraints from multiple, often conflicting, emergent constraints have started to take place within the climate sensitivity context (Bretherton andCaldwell, 2020, Sherwood et al, 2020). However, these frameworks do not yet account for common model structural errors that will likely lead such assessments to an overly confident constraint (Sanderson et al, 2021). The reliability of emergent constraints for general climate projections is even less clear at this time (e.g., Brient, 2020), and therefore, we do not discuss such constraints further here as it is not clear how complete and reliable such constraints are.…”