Toward machine-assisted tuning avoiding the underestimation of uncertainty in climate change projections.

Documenting the uncertainty of climate change projections is a fundamental objective of the inter-comparison exercises organized to feed into the Intergovernmental Panel on Climate Change (IPCC) reports. Usually, each modeling center contributes to these exercises with one or two configurations of its climate model, corresponding to a particular choice of "free parameter" values, resulting from a long and often tedious "model tuning" phase. How much uncertainty is omitted by this selection and how might readers of IPCC reports and users of climate projections be misled by its omission? We show here how recent machine learning approaches can transform the way climate model tuning is approached, opening the way to a simultaneous acceleration of model improvement and parametric uncertainty quantification. We show how an automatic selection of model configurations defined by different values of free parameters can produce different "warming worlds," all consistent with present-day observations of the climate system.

Are general circulation models obsolete?

Traditional general circulation models, or GCMs-that is, three-dimensional dynamical models with unresolved terms represented in equations with tunable parameters-have been a mainstay of climate research for several decades, and some of the pioneering studies have recently been recognized by a Nobel prize in Physics. Yet, there is considerable debate around their continuing role in the future. Frequently mentioned as limitations of GCMs are the structural error and uncertainty across models with different representations of unresolved scales and the fact that the models are tuned to reproduce certain aspects of the observed Earth. We consider these shortcomings in the context of a future generation of models that may address these issues through substantially higher resolution and detail, or through the use of machine learning techniques to match them better to observations, theory, and process models. It is our contention that calibration, far from being a weakness of models, is an essential element in the simulation of complex systems, and contributes to our understanding of their inner workings. Models can be calibrated to reveal both fine-scale detail and the global response to external perturbations. New methods enable us to articulate and improve the connections between the different levels of abstract representation of climate processes, and our understanding resides in an entire hierarchy of models where GCMs will continue to play a central role for the foreseeable future.

Increased risk of near term global warming due to a recent AMOC weakening.

Some of the new generation CMIP6 models are characterised by a strong temperature increase in response to increasing greenhouse gases concentration1. At first glance, these models seem less consistent with the temperature warming observed over the last decades. Here, we investigate this issue through the prism of low-frequency internal variability by comparing with observations an ensemble of 32 historical simulations performed with the IPSL-CM6A-LR model, characterized by a rather large climate sensitivity. We show that members with the smallest rates of global warming over the past 6-7 decades are also those with a large internally-driven weakening of the Atlantic Meridional Overturning Circulation (AMOC). This subset of members also matches several AMOC observational fingerprints, which are in line with such a weakening. This suggests that internal variability from the Atlantic Ocean may have dampened the magnitude of global warming over the historical era. Taking into account this AMOC weakening over the past decades means that it will be harder to avoid crossing the 2 °C warming threshold.

[A Study of the relationship between craniofacial morphology and the occlusion in lacteal dentition: occipital remodeling specificities and basicranial individual features that play an occlusal key role]. / Étude des relations entre la morphologie cranio-faciale et l'occlusion en denture temporaire : remodelages occipitaux et singularités basicrâniennes déterminantes pour l'occlusion.

Before performing any procedure or initiating early intervention on children in lacteal dentition, it is crucial to closely investigate a few key elements of the cranial base of the child. A first step of diagnostics is needed - the classification of the dysharmony ie its squelettal and/or functional element - before we prescribe a major orthopedic treatment or just stop dysfunctions using simple functional appliances. To confront these constraints of diagnostic, a set of 243 children in the lacteal dentition was examined. Our clinical expertise made it possible to select cephalometric measurements that would be supposedly linked with the type of skeletal dysharmony (based on cranial and facial osseous landmarks located on the profile-view of a digital tele-X-ray). The occlusal classification takes into account occlusal criteria and the design of the masticatory function. Statistical analysis (namely linear discriminant analysis of cephalometric variables) indicates that in lacteal dentition, some cranial architectural features have preferred links with specific occlusions. We noticed that the amplitude of basicranial "flexure" (hence the sphenoidal angle) is influenced by the occipital remodeling: the ontogenic process of flexion of the base and the amplitude of closure of the sphenoid angle are under controlled by the remodeling of the occipital bone in three main modalities. Correlations exist between these groups and the facial equilibrium, like a forward or backward position of the chin. The important clinical deduction is that the masticatory function in lacteal dentition is organized by architectural constraints that arise from the remodeling of the cranial base; the squelettal effect of dysfunctions is certainly specific to each type of dysfunction, nonetheless it also depends on the architectural uniqueness of the cranial base.