TY - JOUR
T1 - Quality control for community-based sea-ice model development
AU - Roberts, Andrew F.
AU - Hunke, Elizabeth C.
AU - Allard, Richard
AU - Bailey, David A.
AU - Craig, Anthony P.
AU - Lemieux, Jean François
AU - Turner, Matthew D.
N1 - Publisher Copyright:
© 2018 The Authors.
PY - 2018/9/28
Y1 - 2018/9/28
N2 - 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.
AB - 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.
KW - CICE
KW - Earth system modelling
KW - Icepack
KW - Sea-ice forecasting
UR - https://www.scopus.com/pages/publications/85052538943
U2 - 10.1098/rsta.2017.0344
DO - 10.1098/rsta.2017.0344
M3 - Article
C2 - 30126915
AN - SCOPUS:85052538943
SN - 1364-503X
VL - 376
JO - Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
JF - Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
IS - 2129
M1 - 20170344
ER -