Machine dependence and reproducibility for coupled climate simulations: the HadGEM3-GC3.1 CMIP Preindustrial simulation
When the same weather or climate simulation is run on different high-performance computing (HPC) platforms, model outputs may not be identical for a given initial condition. While the role of HPC platforms in delivering better climate projections is to some extent discussed in the literature, attent...
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ftunivreading:oai:centaur.reading.ac.uk:90792 2024-06-23T07:56:43+00:00 Machine dependence and reproducibility for coupled climate simulations: the HadGEM3-GC3.1 CMIP Preindustrial simulation Guarino, Maria-Vittoria Sime, Louise C. Schroeder, David Lister, Grenville M. S. Hatcher, Rosalyn 2020-01-16 text https://centaur.reading.ac.uk/90792/ https://centaur.reading.ac.uk/90792/1/gmd-13-139-2020.pdf https://www.geosci-model-dev.net/13/139/2020/ en eng European Geosciences Union https://centaur.reading.ac.uk/90792/1/gmd-13-139-2020.pdf Guarino, M.-V., Sime, L. C., Schroeder, D. <https://centaur.reading.ac.uk/view/creators/90005031.html> orcid:0000-0003-2351-4306 , Lister, G. M. S. <https://centaur.reading.ac.uk/view/creators/90000726.html> and Hatcher, R. <https://centaur.reading.ac.uk/view/creators/90000930.html> (2020) Machine dependence and reproducibility for coupled climate simulations: the HadGEM3-GC3.1 CMIP Preindustrial simulation. Geoscientific Model Development, 13 (1). pp. 139-154. ISSN 1991-9603 doi: https://doi.org/10.5194/gmd-13-139-2020 <https://doi.org/10.5194/gmd-13-139-2020> cc_by_4 Article PeerReviewed 2020 ftunivreading https://doi.org/10.5194/gmd-13-139-2020 2024-06-11T15:10:14Z When the same weather or climate simulation is run on different high-performance computing (HPC) platforms, model outputs may not be identical for a given initial condition. While the role of HPC platforms in delivering better climate projections is to some extent discussed in the literature, attention is mainly focused on scalability and performance rather than on the impact of machine-dependent processes on the numerical solution. Here we investigate the behaviour of the Preindustrial (PI) simulation prepared by the UK Met Office for the forthcoming CMIP6 (Coupled Model Intercomparison Project Phase 6) under different computing environments. Discrepancies between the means of key climate variables were analysed at different timescales, from decadal to centennial. We found that for the two simulations to be statistically indistinguishable, a 200-year averaging period must be used for the analysis of the results. Thus, constant-forcing climate simulations using the HadGEM3-GC3.1 model are reproducible on different HPC platforms provided that a sufficiently long duration of simulation is used. In regions where El Niño–Southern Oscillation (ENSO) teleconnection patterns were detected, we found large sea surface temperature and sea ice concentration differences on centennial timescales. This indicates that a 100-year constant-forcing climate simulation may not be long enough to adequately capture the internal variability of the HadGEM3-GC3.1 model, despite this being the minimum simulation length recommended by CMIP6 protocols for many MIP (Model Intercomparison Project) experiments. On the basis of our findings, we recommend a minimum simulation length of 200 years whenever possible. Article in Journal/Newspaper Sea ice CentAUR: Central Archive at the University of Reading Geoscientific Model Development 13 1 139 154 |
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Open Polar |
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CentAUR: Central Archive at the University of Reading |
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ftunivreading |
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English |
description |
When the same weather or climate simulation is run on different high-performance computing (HPC) platforms, model outputs may not be identical for a given initial condition. While the role of HPC platforms in delivering better climate projections is to some extent discussed in the literature, attention is mainly focused on scalability and performance rather than on the impact of machine-dependent processes on the numerical solution. Here we investigate the behaviour of the Preindustrial (PI) simulation prepared by the UK Met Office for the forthcoming CMIP6 (Coupled Model Intercomparison Project Phase 6) under different computing environments. Discrepancies between the means of key climate variables were analysed at different timescales, from decadal to centennial. We found that for the two simulations to be statistically indistinguishable, a 200-year averaging period must be used for the analysis of the results. Thus, constant-forcing climate simulations using the HadGEM3-GC3.1 model are reproducible on different HPC platforms provided that a sufficiently long duration of simulation is used. In regions where El Niño–Southern Oscillation (ENSO) teleconnection patterns were detected, we found large sea surface temperature and sea ice concentration differences on centennial timescales. This indicates that a 100-year constant-forcing climate simulation may not be long enough to adequately capture the internal variability of the HadGEM3-GC3.1 model, despite this being the minimum simulation length recommended by CMIP6 protocols for many MIP (Model Intercomparison Project) experiments. On the basis of our findings, we recommend a minimum simulation length of 200 years whenever possible. |
format |
Article in Journal/Newspaper |
author |
Guarino, Maria-Vittoria Sime, Louise C. Schroeder, David Lister, Grenville M. S. Hatcher, Rosalyn |
spellingShingle |
Guarino, Maria-Vittoria Sime, Louise C. Schroeder, David Lister, Grenville M. S. Hatcher, Rosalyn Machine dependence and reproducibility for coupled climate simulations: the HadGEM3-GC3.1 CMIP Preindustrial simulation |
author_facet |
Guarino, Maria-Vittoria Sime, Louise C. Schroeder, David Lister, Grenville M. S. Hatcher, Rosalyn |
author_sort |
Guarino, Maria-Vittoria |
title |
Machine dependence and reproducibility for coupled climate simulations: the HadGEM3-GC3.1 CMIP Preindustrial simulation |
title_short |
Machine dependence and reproducibility for coupled climate simulations: the HadGEM3-GC3.1 CMIP Preindustrial simulation |
title_full |
Machine dependence and reproducibility for coupled climate simulations: the HadGEM3-GC3.1 CMIP Preindustrial simulation |
title_fullStr |
Machine dependence and reproducibility for coupled climate simulations: the HadGEM3-GC3.1 CMIP Preindustrial simulation |
title_full_unstemmed |
Machine dependence and reproducibility for coupled climate simulations: the HadGEM3-GC3.1 CMIP Preindustrial simulation |
title_sort |
machine dependence and reproducibility for coupled climate simulations: the hadgem3-gc3.1 cmip preindustrial simulation |
publisher |
European Geosciences Union |
publishDate |
2020 |
url |
https://centaur.reading.ac.uk/90792/ https://centaur.reading.ac.uk/90792/1/gmd-13-139-2020.pdf https://www.geosci-model-dev.net/13/139/2020/ |
genre |
Sea ice |
genre_facet |
Sea ice |
op_relation |
https://centaur.reading.ac.uk/90792/1/gmd-13-139-2020.pdf Guarino, M.-V., Sime, L. C., Schroeder, D. <https://centaur.reading.ac.uk/view/creators/90005031.html> orcid:0000-0003-2351-4306 , Lister, G. M. S. <https://centaur.reading.ac.uk/view/creators/90000726.html> and Hatcher, R. <https://centaur.reading.ac.uk/view/creators/90000930.html> (2020) Machine dependence and reproducibility for coupled climate simulations: the HadGEM3-GC3.1 CMIP Preindustrial simulation. Geoscientific Model Development, 13 (1). pp. 139-154. ISSN 1991-9603 doi: https://doi.org/10.5194/gmd-13-139-2020 <https://doi.org/10.5194/gmd-13-139-2020> |
op_rights |
cc_by_4 |
op_doi |
https://doi.org/10.5194/gmd-13-139-2020 |
container_title |
Geoscientific Model Development |
container_volume |
13 |
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1 |
container_start_page |
139 |
op_container_end_page |
154 |
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1802650020928815104 |