Documenting numerical experiments in support of the Coupled Model Intercomparison Project Phase 6 (CMIP6)

<p>Numerical simulation, and in particular simulation of the earth system, relies on contributions from diverse communities, from those who develop models to those involved in devising, executing, and analysing numerical experiments. Often these people work in different institutions and may be...

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Main Authors: C. Pascoe, B. N. Lawrence, E. Guilyardi, M. Juckes, K. E. Taylor
Format: Article
Language:English
Published: Copernicus Publications 2020-05-01
Series:Geoscientific Model Development
Online Access:https://www.geosci-model-dev.net/13/2149/2020/gmd-13-2149-2020.pdf
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spelling doaj-4c67150afe54493cb3b5083fa1dc28582020-11-25T02:02:36ZengCopernicus PublicationsGeoscientific Model Development1991-959X1991-96032020-05-01132149216710.5194/gmd-13-2149-2020Documenting numerical experiments in support of the Coupled Model Intercomparison Project Phase 6 (CMIP6)C. Pascoe0C. Pascoe1B. N. Lawrence2B. N. Lawrence3E. Guilyardi4E. Guilyardi5M. Juckes6M. Juckes7K. E. Taylor8STFC Rutherford Appleton Laboratory, Harwell, UKNational Centre of Atmospheric Science, Leeds, UKNational Centre of Atmospheric Science, Leeds, UKDepartments of Meteorology and Computer Science, University of Reading, Reading, UKNational Centre of Atmospheric Science, Leeds, UKLOCEAN/IPSL, Sorbonne Université/CNRS/IRD/MNHN, Paris, FranceSTFC Rutherford Appleton Laboratory, Harwell, UKNational Centre of Atmospheric Science, Leeds, UKPCMDI, Lawrence Livermore National Laboratory, Livermore, CA, USA<p>Numerical simulation, and in particular simulation of the earth system, relies on contributions from diverse communities, from those who develop models to those involved in devising, executing, and analysing numerical experiments. Often these people work in different institutions and may be working with significant separation in time (particularly analysts, who may be working on data produced years earlier), and they typically communicate via published information (whether journal papers, technical notes, or websites). The complexity of the models, experiments, and methodologies, along with the diversity (and sometimes inexact nature) of information sources, can easily lead to misinterpretation of what was actually intended or done. In this paper we introduce a taxonomy of terms for more clearly defining numerical experiments, put it in the context of previous work on experimental ontologies, and describe how we have used it to document the experiments of the sixth phase for the Coupled Model Intercomparison Project (CMIP6). We describe how, through iteration with a range of CMIP6 stakeholders, we rationalized multiple sources of information and improved the clarity of experimental definitions. We demonstrate how this process has added value to CMIP6 itself by (a) helping those devising experiments to be clear about their goals and their implementation, (b) making it easier for those executing experiments to know what is intended, (c) exposing interrelationships between experiments, and (d) making it clearer for third parties (data users) to understand the CMIP6 experiments. We conclude with some lessons learnt and how these may be applied to future CMIP phases as well as other modelling campaigns.</p>https://www.geosci-model-dev.net/13/2149/2020/gmd-13-2149-2020.pdf
collection DOAJ
language English
format Article
sources DOAJ
author C. Pascoe
C. Pascoe
B. N. Lawrence
B. N. Lawrence
E. Guilyardi
E. Guilyardi
M. Juckes
M. Juckes
K. E. Taylor
spellingShingle C. Pascoe
C. Pascoe
B. N. Lawrence
B. N. Lawrence
E. Guilyardi
E. Guilyardi
M. Juckes
M. Juckes
K. E. Taylor
Documenting numerical experiments in support of the Coupled Model Intercomparison Project Phase 6 (CMIP6)
Geoscientific Model Development
author_facet C. Pascoe
C. Pascoe
B. N. Lawrence
B. N. Lawrence
E. Guilyardi
E. Guilyardi
M. Juckes
M. Juckes
K. E. Taylor
author_sort C. Pascoe
title Documenting numerical experiments in support of the Coupled Model Intercomparison Project Phase 6 (CMIP6)
title_short Documenting numerical experiments in support of the Coupled Model Intercomparison Project Phase 6 (CMIP6)
title_full Documenting numerical experiments in support of the Coupled Model Intercomparison Project Phase 6 (CMIP6)
title_fullStr Documenting numerical experiments in support of the Coupled Model Intercomparison Project Phase 6 (CMIP6)
title_full_unstemmed Documenting numerical experiments in support of the Coupled Model Intercomparison Project Phase 6 (CMIP6)
title_sort documenting numerical experiments in support of the coupled model intercomparison project phase 6 (cmip6)
publisher Copernicus Publications
series Geoscientific Model Development
issn 1991-959X
1991-9603
publishDate 2020-05-01
description <p>Numerical simulation, and in particular simulation of the earth system, relies on contributions from diverse communities, from those who develop models to those involved in devising, executing, and analysing numerical experiments. Often these people work in different institutions and may be working with significant separation in time (particularly analysts, who may be working on data produced years earlier), and they typically communicate via published information (whether journal papers, technical notes, or websites). The complexity of the models, experiments, and methodologies, along with the diversity (and sometimes inexact nature) of information sources, can easily lead to misinterpretation of what was actually intended or done. In this paper we introduce a taxonomy of terms for more clearly defining numerical experiments, put it in the context of previous work on experimental ontologies, and describe how we have used it to document the experiments of the sixth phase for the Coupled Model Intercomparison Project (CMIP6). We describe how, through iteration with a range of CMIP6 stakeholders, we rationalized multiple sources of information and improved the clarity of experimental definitions. We demonstrate how this process has added value to CMIP6 itself by (a) helping those devising experiments to be clear about their goals and their implementation, (b) making it easier for those executing experiments to know what is intended, (c) exposing interrelationships between experiments, and (d) making it clearer for third parties (data users) to understand the CMIP6 experiments. We conclude with some lessons learnt and how these may be applied to future CMIP phases as well as other modelling campaigns.</p>
url https://www.geosci-model-dev.net/13/2149/2020/gmd-13-2149-2020.pdf
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