Preprints
https://doi.org/10.5194/gmd-2021-99
https://doi.org/10.5194/gmd-2021-99

Submitted as: methods for assessment of models 14 Jun 2021

Submitted as: methods for assessment of models | 14 Jun 2021

Review status: a revised version of this preprint was accepted for the journal GMD.

SITool (v1.0) – a new evaluation tool for large-scale sea ice simulations: application to CMIP6 OMIP

Xia Lin1,2, François Massonnet1, Thierry Fichefet1, and Martin Vancoppenolle3 Xia Lin et al.
  • 1Georges Lemaître Centre for Earth and Climate Research, Earth and Life Institute, Université catholique de Louvain, Louvain-la-Neuve, 1348, Belgium
  • 2Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, 519000, China
  • 3Laboratoire d'Océanographie et du Climat, CNRS/IRD/MNHN, Sorbonne Université, 75252, Paris, France

Abstract. The Sea Ice Evaluation Tool (SITool) described in this paper is a performance metrics and diagnostics tool developed to evaluate the skill of bi-polar model reconstructions of sea ice concentration, extent, edge location, drift, thickness, and snow depth. It is a Python-based software and consists of well-documented functions used to derive various sea ice metrics and diagnostics. Here, the SITool version 1.0 (v1.0) is introduced and documented, and is then used to evaluate the performance of global sea ice reconstructions from nine models that provided sea ice output under the experimental protocols of the Coupled Model Intercomparison Project 6 (CMIP6) Ocean Model Intercomparison Project with two different atmospheric forcing datasets: the Coordinated Ocean-ice Reference Experiments version 2 (CORE-II) and the updated Japanese 55-year atmospheric reanalysis (JRA55-do). Two sets of observational references for sea ice concentration, thickness, snow depth, and ice drift are systematically used to reflect the impact of observational uncertainty on model performance. Based on available model outputs and observational references, the ice concentration, extent, and edge location during 1980–2007, as well as the ice thickness, snow depth, and ice drift during 2003–2007 are evaluated. It is found that (1) in general, model biases are larger than observational uncertainties and model performances are primarily consistent compared to different observational references, (2) By changing the atmospheric forcing from CORE-II to JRA55-do reanalysis data, the overall performance (mean state, interannual variability and trend) of the simulated sea ice areal properties in both hemispheres, as well as the mean ice thickness simulation in the Antarctic, the mean snow depth and ice drift simulations in both hemispheres are improved, (3) the simulated sea ice areal properties are also improved in the model with increased spatial resolution, (4) for the cross-metric analysis, there is no link between the performance in one variable and the performance in another. The SITool is an open-access version-controlled software that can run on a wide range of CMIP6 compliant sea ice outputs. The current version of SITool (v1.0) is primarily developed to evaluate atmosphere-forced simulations and it could be eventually extended to fully coupled models.

Xia Lin et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on gmd-2021-99', Anonymous Referee #1, 20 Jul 2021
    • AC1: 'Comment on gmd-2021-99', Xia Lin, 06 Sep 2021
  • RC2: 'Comment on gmd-2021-99', Anonymous Referee #2, 21 Jul 2021
    • AC1: 'Comment on gmd-2021-99', Xia Lin, 06 Sep 2021
  • RC3: 'Comment on gmd-2021-99', Anonymous Referee #3, 22 Jul 2021
    • AC1: 'Comment on gmd-2021-99', Xia Lin, 06 Sep 2021
  • AC1: 'Comment on gmd-2021-99', Xia Lin, 06 Sep 2021

Xia Lin et al.

Xia Lin et al.

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Short summary
This study introduces a new Sea Ice Evaluation Tool (SITool) to quantify the performance of global sea ice simulations by providing systematic and meaningful ice metrics and diagnostics. The SITool is applied to evaluate atmosphere-forced simulations and it could be eventually extended to fully coupled models. The SITool will be useful to describe inter-model differences and to help teams managing various versions of a sea ice model or tracking the time-evolution of model performance.