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Climate modelling: computing and data challenges

Authors: Joussaume, Sylvie;

Climate modelling: computing and data challenges

Abstract

Climate models are extensively used to assess mitigation and adaptation strategies for climate change, as shown by the Intergovernmental Panel on Climate Change Assessment Reports. The international climate modelling community supports these assessments through internationally coordinated experiments, the latest one in support to the 6th Assessment Report (to come out August 2021) being the 6th phase of the Coupled modeling intercomparison project, CMIP6. These experiments provide climate projections for future climate scenarios but also enhance the scientific basis for model evaluation and for understanding of climate processes. They represent an important investment in both computing and data shared openly through the Earth System Grid Federation, supported by the European Network for Earth System modelling (ENES) infrastructure project, IS-ENES. The future of climate modeling highly depends on available computing power: ensemble of prediction experiments to better estimate uncertainties, increase of resolution to better represent small scale processes, enhanced complexity of the Earth’s climate system to include biogeochemical cycles, capacity to run long experiments to investigate climate stability. Preparing for next generation climate models, enabling efficient high-resolution simulations, is addressed by the European Center of Excellence in HPC, ESiWACE. It gathers the climate and weather modelling communities with the object to enhance synergies between the two communities to address the new computing architectures, a challenge for these communities relying on legacy codes. Presented at the eScience 2021 Conference on September 21st, 2021.

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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