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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European Geosciences Union
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ftnerc:oai:nora.nerc.ac.uk:523411 2023-05-15T18:18:39+02:00 Machine dependence and reproducibility for coupled climate simulations: the HadGEM3-GC3.1 CMIP Preindustrial simulation Guarino, Maria Vittoria Sime, Louise Schroeder, David Lister, Grenville M.S. Hatcher, Rosalyn 2020-01-16 text http://nora.nerc.ac.uk/id/eprint/523411/ https://nora.nerc.ac.uk/id/eprint/523411/1/gmd-13-139-2020.pdf https://www.geosci-model-dev.net/13/139/2020/ en eng European Geosciences Union https://nora.nerc.ac.uk/id/eprint/523411/1/gmd-13-139-2020.pdf Guarino, Maria Vittoria orcid:0000-0002-7531-4560 Sime, Louise orcid:0000-0002-9093-7926 Schroeder, David; Lister, Grenville M.S.; Hatcher, Rosalyn. 2020 Machine dependence and reproducibility for coupled climate simulations: the HadGEM3-GC3.1 CMIP Preindustrial simulation. Geoscientific Model Development, 13 (1). 139-154. https://doi.org/10.5194/gmd-13-139-2020 <https://doi.org/10.5194/gmd-13-139-2020> cc_by_4 CC-BY Publication - Article PeerReviewed 2020 ftnerc https://doi.org/10.5194/gmd-13-139-2020 2023-02-04T19:48:25Z 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 Natural Environment Research Council: NERC Open Research Archive Geoscientific Model Development 13 1 139 154 |
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Open Polar |
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Natural Environment Research Council: NERC Open Research Archive |
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ftnerc |
language |
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 Schroeder, David Lister, Grenville M.S. Hatcher, Rosalyn |
spellingShingle |
Guarino, Maria Vittoria Sime, Louise 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 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 |
http://nora.nerc.ac.uk/id/eprint/523411/ https://nora.nerc.ac.uk/id/eprint/523411/1/gmd-13-139-2020.pdf https://www.geosci-model-dev.net/13/139/2020/ |
genre |
Sea ice |
genre_facet |
Sea ice |
op_relation |
https://nora.nerc.ac.uk/id/eprint/523411/1/gmd-13-139-2020.pdf Guarino, Maria Vittoria orcid:0000-0002-7531-4560 Sime, Louise orcid:0000-0002-9093-7926 Schroeder, David; Lister, Grenville M.S.; Hatcher, Rosalyn. 2020 Machine dependence and reproducibility for coupled climate simulations: the HadGEM3-GC3.1 CMIP Preindustrial simulation. Geoscientific Model Development, 13 (1). 139-154. https://doi.org/10.5194/gmd-13-139-2020 <https://doi.org/10.5194/gmd-13-139-2020> |
op_rights |
cc_by_4 |
op_rightsnorm |
CC-BY |
op_doi |
https://doi.org/10.5194/gmd-13-139-2020 |
container_title |
Geoscientific Model Development |
container_volume |
13 |
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1 |
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139 |
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154 |
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1766195287433412608 |