Eddy Rich Earth System Models (EERIE) will develop a new generation of Earth System Models (ESMs) that are capable of explicitly representing a crucially important, yet unexplored regime of the Earth system, the ocean mesoscale. L...
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Información proyecto EERIE
Duración del proyecto: 47 meses
Fecha Inicio: 2023-01-01
Fecha Fin: 2026-12-31
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Descripción del proyecto
Eddy Rich Earth System Models (EERIE) will develop a new generation of Earth System Models (ESMs) that are capable of explicitly representing a crucially important, yet unexplored regime of the Earth system, the ocean mesoscale. Leveraging the latest advances in science and technology, EERIE will substantially improve the ability of such ESMs to faithfully represent the centennial-scale evolution of the global climate, especially its variability, extremes and how tipping points may unfold under the influence of the ocean mesoscale. Model improvements include new dynamical cores, new components (particularly sea ice), scale-aware parametrization and the complementary use of Machine Learning (ML) The technological challenge associated with this ambition is very high. EERIE’s goal is to achieve a simulation speed of up to 5 simulated years per day (5 SYPDs) and to make efficient use (reduction in power consumption by 50%) of the pre-exascale supercomputers now available in Europe. The technological solutions that are to be leveraged in EERIE are the use of reduced precision, GPUs, ML and reduced I/O. Alongside model improvements, EERIE will develop innovative experimental simulation protocols that are suitable for the mesoscale, to be pioneered on behalf of the global climate modelling community, in preparation for the next IPCC. EERIE will produce useful and usable climate information that will contribute to national and international climate change assessments such as IPCC; it will incorporate model variability and extremes within an Integrated Assessment Model (IAM) via a MLemulato;, and it will deliver storyline approaches to the consequences of climate tipping points and disease outbreaks.