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BER Research Highlights


Quality Control for Community Based Sea Ice Model Development
Published: July 17, 2018
Posted: May 08, 2019

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.

The Science
Using output from five coupled and uncoupled configurations of the Los Alamos Sea Ice Model, CICE, the authors formulated quality control methods that exploit common statistical properties of sea ice thickness, which are used to efficiently test for significant changes in model results when the code is altered.  Modifications to the code are assessed using criteria that account for the high level of autocorrelation in sea ice time series, along with a skill metric that searches for hemispheric changes in model answers across an array of different CICE configurations.

The Impact
Quality control of community sea ice codes has, until now, been somewhat subjective.  These statistical tests grade new additions and changes to CICE into four categories, ranging from bit-for-bit amendments to significant, answer-changing upgrades. In addition to providing a classification procedure for modifications to existing code, these metrics also provide objective guidance for assessing new physical representations and code functionality.

Summary
Understanding whether or not changes in CICE code may also alter the climate of the model can be nontrivial.  A large team of scientists, led by DOE’s Los Alamos National Laboratory, known as “the CICE Consortium” has developed an efficient and automated acceptance testing method for controlling the quality of new contributions to CICE, thereby guarding against inadvertent bugs or numerical inaccuracies.  The method exploits statistical properties of sea ice thickness evolution common across a range of sea ice models and is demonstrated in both stand-alone and coupled model settings. The CICE software and data are publicly available through an open-source repository and data portal to facilitate community involvement and improvement.

Contacts (BER PM)
Dorothy Koch
Earth and Environmental System Modeling
Dorothy.Koch@science.doe.gov

Renu Joseph
Earth and Environmental System Modeling
Renu.Joseph@science.doe.gov

(PI Contact)
Andrew F. Roberts and Elizabeth C. Hunke
Los Alamos National Laboratory
eclare@lanl.gov

Funding
This research was based on work supported by the U.S. Department of Energy Office of Science, Biological and Environmental Research as part of the Earth and Environmental System Modeling program. The Office of Naval Research (ONR, award N0001417WX00563), National ESPC Committee Support Project, National Science Foundation, and the Canadian Operational Network of coupled Environmental Prediction Systems (CONCEPTS) programs provided additional support for the work.

Publication
Roberts, A. F., E. C. Hunke, R. Allard, D. A. Bailey, A. P. Craig, J-F. Lemieux, M. D. Turner. “Quality Control for Community Based Sea Ice Model Development.” Philos. Trans. Royal Soc. A A376:2017.0344 (2018). [DOI:10.1098/rsta.2017.0344]

Related Links
CICE Consortium
https://zenodo.org/communities/cice-consortium/

Topic Areas:

  • Research Area: Earth and Environmental Systems Modeling

Division: SC-33.1 Earth and Environmental Sciences Division, BER

 

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