Programme Prioritaire de Recherche Make Our Planet Great Again

Risks and Uncertainties under Climate Change

RISCCi

Mots-clés : Climate Change; Uncertainty; Perturbed Physics; Scenarios; Risk;

Résumé

The RISCCI project began in September 2018, and its core development has been the creation of an ensemble platform to explore parametric uncertainty in the MeteoFrance climate model, CNRM-CM6.  Two initial ensemble experiments have been completed, iterating on parameter sampling strategies and experimental configurations to explore both climatological performance and greenhouse gas response uncertainty.  In parallel with these efforts, the project has conducted a number of simple climate modeling studies to address fundamental questions of how climate sensitivity metrics relate to future climate projection uncertainty and long term projection risk, work which has played a key part in two successfully funded supporting H2020 projects: ESM2025 and PROVIDE.  

 

The CNRM-CM6 ensemble project

 

the CNRM-CM6 PPE project explores parametric uncertainty in the atmospheric component of the model (ARPEGE), taking a set of 35 uncertain parameters in the model and exploring the climatic sensitivity of the model to univariate and multivariate perturbations.  Initial parameter choices, default values and plausible maximum and minimum values were obtained through extended consultation with MeteoFrance developers, and by consideration of output from internal calibration simulations for the beta versions leading up to the release model of CNRM-CM6.

 

 Perturbation experiments were then conducted for each of the parameter combinations to produce estimates of net climate feedback and climate sensitivity for each member of the parameter distribution.  The resulting ensemble resulted in a significant spread in climate sensitivity, such that model configurations spanned the range of climate sensitivity present in the multi-model archive of climate models contriubting to the CMIP project.  A second stage experiment is in process, using a set of optimal model candidates which span a range of global and regional response to greenhouse gas forcing.  These configurations will produce a set of coupled future simulations which can sample potentially high-risk, low probability futures which are not generally considered in climate risk assessments.

 

Long Term climate projection risk

 

The PI has written two studies this year on metrics of climate senstivity and how they relate to near term and long term climate risk.  This work has developed a simple climate model capable of exploring climate feedbacks on different timescales and this work is the foundation of the ESM2025 project, where the key developments will be incorporated into an open-source simple climate model OS-MAGICC.  A suite of ESM experiments under ESM2025 will examinespatial sea surface warming patterns which correspond to warming at different timescales of equilibration response as boundary conditions for an additional set of AMIP experiments which will provide a significantly improved understanding of coupled system equilibration and transient response.

 

Carbon cycle response uncertainty

 

The PI is collaborating with CERFACS colleagues and an international team exploring a novel approach for carbon cycle feedbacks which addresses a key issue in the simulation of perturbed parameter sensitivity in land surface models.   This research has developed a reduced-form “sparse” configuration of the Community Land Model in order to explore parameteric senstivity of carbon cycle feedbacks to parameter perturbations.

 

 

 

L'auteur de ce résumé est le coordinateur du projet, qui est responsable du contenu de ce résumé. L'ANR décline par conséquent toute responsabilité quant à son contenu.

Informations générales

Acronyme projet : RISCCi
Référence projet : 17-MPGA-0016
Région du projet : Occitanie
Discipline : 3 - STUE
Aide PIA : 499 716 €
Début projet : août 2018
Fin projet : août 2023

Coordinateur du projet : Benjamin Mark SANDERSON
Email : sanderson@cerfacs.fr

Consortium du projet

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