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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Published in:Geoscientific Model Development
Main Authors: Guarino, Maria Vittoria, Sime, Louise, Schroeder, David, Lister, Grenville M.S., Hatcher, Rosalyn
Format: Article in Journal/Newspaper
Language:English
Published: European Geosciences Union 2020
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Online Access: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/
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spelling 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
institution Open Polar
collection Natural Environment Research Council: NERC Open Research Archive
op_collection_id 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
container_issue 1
container_start_page 139
op_container_end_page 154
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