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, 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.

Details

Publication status:
Published
Author(s):
Authors: Guarino, Maria Vittoria ORCIDORCID record for Maria Vittoria Guarino, Sime, Louise ORCIDORCID record for Louise Sime, Schroeder, David, Lister, Grenville M.S., Hatcher, Rosalyn

On this site: Louise Sime, Maria Vittoria Guarino
Date:
16 January, 2020
Journal/Source:
Geoscientific Model Development / 13
Page(s):
139-154
Digital Object Identifier (DOI):
https://doi.org/10.5194/gmd-13-139-2020