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...

Full description

Bibliographic Details
Published in:Geoscientific Model Development
Main Authors: Guarino, Maria-Vittoria, Sime, Louise C., Schroeder, David, Lister, Grenville M. S., Hatcher, Rosalyn
Format: Article in Journal/Newspaper
Language:English
Published: European Geosciences Union 2020
Subjects:
Online Access: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/
id ftunivreading:oai:centaur.reading.ac.uk:90792
record_format openpolar
spelling 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
institution Open Polar
collection CentAUR: Central Archive at the University of Reading
op_collection_id ftunivreading
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 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
container_issue 1
container_start_page 139
op_container_end_page 154
_version_ 1802650020928815104