Quality control for community-based sea-ice model development
Abstract
A new collaborative organization for sea-ice model development, the CICE Consortium, has devised quality control procedures to maintain the integrity of its numerical codes' physical representations, enabling broad participation from the scientific community in the Consortium's open software development environment. Using output from five coupled and uncoupled configurations of the Los Alamos Sea Ice Model, CICE, we formulate quality control methods that exploit common statistical properties of sea-ice thickness, and test for significant changes in model results in a computationally efficient manner. New additions and changes to CICE are graded into four categories, ranging from bit-for-bit amendments to significant, answer-changing upgrades. These modifications are assessed using criteria that account for the high level of autocorrelation in sea-ice time series, along with a quadratic skill metric that searches for hemispheric changes in model answers across an array of different CICE configurations. These metrics also provide objective guidance for assessing new physical representations and code functionality.
- Authors:
-
[1];
[2];
- Naval Postgraduate School, Monterey, CA (United States)
- Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
- Naval Research Laboratory, Stennis Space Center, MS (United States)
- National Center for Atmospheric Research, Boulder, CO (United States)
- NOAA Earth System Research Laboratory, Washington, DC (United States)
- Recherche en Prévision Numérique Environnementale, Environnement et Changement Climatique Canada Dorval, QC (Canada)
- DoD HPCMP PETTT, Engility Corp., Stennis Space Center, MS (United States)
- Publication Date:
- Research Org.:
- Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC). Biological and Environmental Research (BER) (SC-23)
- OSTI Identifier:
- 1467338
- Report Number(s):
- LA-UR-18-22855
Journal ID: ISSN 1364-503X
- Grant/Contract Number:
- AC52-06NA25396; SC0005522; SC0005783
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Philosophical Transactions of the Royal Society. A, Mathematical, Physical and Engineering Sciences
- Additional Journal Information:
- Journal Volume: 376; Journal Issue: 2129; Journal ID: ISSN 1364-503X
- Publisher:
- The Royal Society Publishing
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 58 GEOSCIENCES; Earth Sciences; sea ice, Icepack, earth system modeling, sea ice forecasting
Citation Formats
Roberts, Andrew F., Hunke, Elizabeth C., Allard, Richard, Bailey, David A., Craig, Anthony P., Lemieux, Jean-François, and Turner, Matthew D. Quality control for community-based sea-ice model development. United States: N. p., 2018.
Web. doi:10.1098/rsta.2017.0344.
Roberts, Andrew F., Hunke, Elizabeth C., Allard, Richard, Bailey, David A., Craig, Anthony P., Lemieux, Jean-François, & Turner, Matthew D. Quality control for community-based sea-ice model development. United States. https://doi.org/10.1098/rsta.2017.0344
Roberts, Andrew F., Hunke, Elizabeth C., Allard, Richard, Bailey, David A., Craig, Anthony P., Lemieux, Jean-François, and Turner, Matthew D. Mon .
"Quality control for community-based sea-ice model development". United States. https://doi.org/10.1098/rsta.2017.0344. https://www.osti.gov/servlets/purl/1467338.
@article{osti_1467338,
title = {Quality control for community-based sea-ice model development},
author = {Roberts, Andrew F. and Hunke, Elizabeth C. and Allard, Richard and Bailey, David A. and Craig, Anthony P. and Lemieux, Jean-François and Turner, Matthew D.},
abstractNote = {A new collaborative organization for sea-ice model development, the CICE Consortium, has devised quality control procedures to maintain the integrity of its numerical codes' physical representations, enabling broad participation from the scientific community in the Consortium's open software development environment. Using output from five coupled and uncoupled configurations of the Los Alamos Sea Ice Model, CICE, we formulate quality control methods that exploit common statistical properties of sea-ice thickness, and test for significant changes in model results in a computationally efficient manner. New additions and changes to CICE are graded into four categories, ranging from bit-for-bit amendments to significant, answer-changing upgrades. These modifications are assessed using criteria that account for the high level of autocorrelation in sea-ice time series, along with a quadratic skill metric that searches for hemispheric changes in model answers across an array of different CICE configurations. These metrics also provide objective guidance for assessing new physical representations and code functionality.},
doi = {10.1098/rsta.2017.0344},
journal = {Philosophical Transactions of the Royal Society. A, Mathematical, Physical and Engineering Sciences},
number = 2129,
volume = 376,
place = {United States},
year = {Mon Aug 20 00:00:00 EDT 2018},
month = {Mon Aug 20 00:00:00 EDT 2018}
}
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Cited by: 8 works
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Figures / Tables:
Table 1: Summary of sea ice models used in this study.
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Works referenced in this record:
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Level-ice melt ponds in the Los Alamos sea ice model, CICE
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Influence of the Sea Ice Thickness Distribution on Polar Climate in CCSM3
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Impacts of a mushy-layer thermodynamic approach in global sea-ice simulations using the CICE sea-ice model
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Improving the simulation of landfast ice by combining tensile strength and a parameterization for grounded ridges: MODELING LANDFAST ICE
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Development of the Regional Arctic System Model (RASM): Near-Surface Atmospheric Climate Sensitivity
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Summarizing multiple aspects of model performance in a single diagram
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A global ocean mesh to overcome the North Pole singularity
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- Madec, Gurvan; Imbard, Maurice
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Arctic Sea Ice Freeboard and Thickness, Version 1
dataset, January 2009
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Cice6 Simulations: Quality Control For Community Based Sea Ice Model Development
dataset, January 2018
- Hunke, Elizabeth
- Zenodo
Gofs Simulations: Quality Control For Community Based Sea Ice Model Development
dataset, January 2018
- Allard, Richard
- Zenodo
2Spt Test Time Series: Quality Control For Community Based Sea Ice Model Development
dataset, January 2018
- Roberts, Andrew
- Zenodo
The Coastal Streamflow Flux In The Regional Arctic System Model [Supplementary Data]
dataset, February 2017
- Hamman, J.; Nijssen, B.; Roberts, A.
- Zenodo-Supplementary information for journal article at DOI: 10.1002/2016JC012323, 1 gz file (738.6 MB)
Rasm Simulations: Quality Control For Community Based Sea Ice Model Development
dataset, January 2018
- Roberts, Andrew
- Zenodo
2Spt Test Time Series: Quality Control For Community Based Sea Ice Model Development
dataset, January 2018
- Roberts, Andrew
- Zenodo
Two modes of sea-ice gravity drainage: A parameterization for large-scale modeling: GRAVITY DRAINAGE
journal, May 2013
- Turner, Adrian K.; Hunke, Elizabeth C.; Bitz, Cecilia M.
- Journal of Geophysical Research: Oceans, Vol. 118, Issue 5
A new atmospheric dataset for forcing ice-ocean models: Evaluation of reforecasts using the Canadian global deterministic prediction system: CGRF Dataset for Forcing Ice-Ocean Models
journal, July 2013
- Smith, Gregory C.; Roy, François; Mann, Philip
- Quarterly Journal of the Royal Meteorological Society, Vol. 140, Issue 680
Viscous–Plastic Sea Ice Dynamics with the EVP Model: Linearization Issues
journal, June 2001
- Hunke, Elizabeth C.
- Journal of Computational Physics, Vol. 170, Issue 1
A treatise on frequency spectrum of drift ice velocity
journal, June 2012
- Leppäranta, Matti; Oikkonen, Annu; Shirasawa, Kunio
- Cold Regions Science and Technology, Vol. 76-77
Level-ice melt ponds in the Los Alamos sea ice model, CICE
journal, November 2013
- Hunke, Elizabeth C.; Hebert, David A.; Lecomte, Olivier
- Ocean Modelling, Vol. 71
The elastic–viscous–plastic method revisited
journal, November 2013
- Bouillon, Sylvain; Fichefet, Thierry; Legat, Vincent
- Ocean Modelling, Vol. 71
A continuum model of melt pond evolution on Arctic sea ice
journal, January 2007
- Flocco, Daniela; Feltham, Daniel L.
- Journal of Geophysical Research, Vol. 112, Issue C8
Arctic Sea Ice Freeboard and Thickness, Version 1
dataset, January 2009
- Yi, Donghui; Zwally, H. Jay
- NASA National Snow and Ice Data Center DAAC
A high-resolution ocean and sea-ice modelling system for the Arctic and North Atlantic oceans
journal, January 2015
- Dupont, F.; Higginson, S.; Bourdallé-Badie, R.
- Geoscientific Model Development, Vol. 8, Issue 5
Cice6 Simulations: Quality Control For Community Based Sea Ice Model Development
dataset, January 2018
- Hunke, Elizabeth
- Zenodo
Rasm Simulations: Quality Control For Community Based Sea Ice Model Development
dataset, January 2018
- Roberts, Andrew
- Zenodo
Gofs Simulations: Quality Control For Community Based Sea Ice Model Development
dataset, January 2018
- Allard, Richard
- Zenodo
Eccc Simulations: Quality Control For Community Based Sea Ice Model Development
dataset, January 2018
- Lemieux, Jean-François
- Zenodo
2Spt Test Time Series: Quality Control For Community Based Sea Ice Model Development
dataset, January 2018
- Roberts, Andrew
- Zenodo
US Navy Operational Global Ocean and Arctic Ice Prediction Systems
journal, September 2014
- Metzger, E. Joseph; Smedstad, Ole Martin; Thoppil, Prasad
- Oceanography, Vol. 27, Issue 3
Cice6 Simulations: Quality Control For Community Based Sea Ice Model Development
dataset, January 2018
- Hunke, Elizabeth
- Zenodo
Eccc Simulations: Quality Control For Community Based Sea Ice Model Development
dataset, January 2018
- Lemieux, Jean-François
- Zenodo
Figures/Tables have been extracted from DOE-funded journal article accepted manuscripts.