Prospective tools for climate modelling
Most of the future climate studies hereby described are based on climate simulation results,
performed with coupled (CGCM) or forced global climate models.
Since several years, numerous tools have been developed to ease processing and analysis of
numerical simulations. In the near future, our team will prepare the next generation of CGCMs
to be used for various studies such as medium-range predictions and climate scenarios.
The permanent collaboration between us and researchers and engineers of Centre National
de Recherches Météorologiques (CNRM) and Laboratoire d’Océanographie et du Climat-
Exp´erimentation et Analyse Num´erique (LOCEAN, CNRS) should be further fostered. In this
way, the behaviour of a state-of-the-art medium resolution coupled model will fit the researcher
needs and allow an iterative validation of each technical improvement.
Moreover, standard interfaces wll be set up to facilitate future releases, verification procedures
and information exchanges between laboratories.
Performing simulations as demanding as, for example, IPCC AR5 decadal predictions requires
an infrastructure consisting of high-end capability and capacity computing.
Today’s emergence of Petascale architectures and evolution of computing technologies increase
a lot the number of potential ressources. To be able to use our state-of-the-art model on such
platforms, a complete transformation of its programming structure will soon be required.
A deep analysis of the performance of each component of a climate model on massively parallel
infrastructure is a prerequisite for improving the global performance of the system. The
information obtained will directly improve the decision on whether and where to apply effort
to optimize our code.
To be able to face unknown problems of one of the numerous ressources used on Petascale
environnement is another challenge we plan to assess. It will be important to estimate
vulnerability of our code and anticipate possible problems never encountered before.
Climate modelers will also need to better identify each individual step of a coupled simulation
workflow (model compilation, input data preprocessing, monitoring, output post-processing
and archiving) to harvest heterogeneous computational ressources and match the most suitable
architecture to process each task.
Simultaneously, the Grid compliant version of the low resolution CERFACS coupled model,
included in the Grid-related project called Leage for Efficient Grid Operations (LEGO), will be
evaluated. Its performances will be measured on a realistic multi-parametric study. Previous
enhancements realized on simulation tasks scheduling should be transposed to massively parallel
architectures.
performed with coupled (CGCM) or forced global climate models.
Since several years, numerous tools have been developed to ease processing and analysis of
numerical simulations. In the near future, our team will prepare the next generation of CGCMs
to be used for various studies such as medium-range predictions and climate scenarios.
The permanent collaboration between us and researchers and engineers of Centre National
de Recherches Météorologiques (CNRM) and Laboratoire d’Océanographie et du Climat-
Exp´erimentation et Analyse Num´erique (LOCEAN, CNRS) should be further fostered. In this
way, the behaviour of a state-of-the-art medium resolution coupled model will fit the researcher
needs and allow an iterative validation of each technical improvement.
Moreover, standard interfaces wll be set up to facilitate future releases, verification procedures
and information exchanges between laboratories.
Performing simulations as demanding as, for example, IPCC AR5 decadal predictions requires
an infrastructure consisting of high-end capability and capacity computing.
Today’s emergence of Petascale architectures and evolution of computing technologies increase
a lot the number of potential ressources. To be able to use our state-of-the-art model on such
platforms, a complete transformation of its programming structure will soon be required.
A deep analysis of the performance of each component of a climate model on massively parallel
infrastructure is a prerequisite for improving the global performance of the system. The
information obtained will directly improve the decision on whether and where to apply effort
to optimize our code.
To be able to face unknown problems of one of the numerous ressources used on Petascale
environnement is another challenge we plan to assess. It will be important to estimate
vulnerability of our code and anticipate possible problems never encountered before.
Climate modelers will also need to better identify each individual step of a coupled simulation
workflow (model compilation, input data preprocessing, monitoring, output post-processing
and archiving) to harvest heterogeneous computational ressources and match the most suitable
architecture to process each task.
Simultaneously, the Grid compliant version of the low resolution CERFACS coupled model,
included in the Grid-related project called Leage for Efficient Grid Operations (LEGO), will be
evaluated. Its performances will be measured on a realistic multi-parametric study. Previous
enhancements realized on simulation tasks scheduling should be transposed to massively parallel
architectures.
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