Preprints
https://doi.org/10.5194/gmd-2020-331
https://doi.org/10.5194/gmd-2020-331

Submitted as: development and technical paper 14 Dec 2020

Submitted as: development and technical paper | 14 Dec 2020

Review status: this preprint is currently under review for the journal GMD.

Benefits of sea ice thickness initialization for the Arctic decadal climate prediction skill in EC-Earth3

Tian Tian1, Shuting Yang1, Mehdi Pasha Karami2, François Massonnet3, Tim Kruschke2, and Torben Koenigk2,4 Tian Tian et al.
  • 1Danish Meteorological Institute, Denmark
  • 2Swedish Meteorological and Hydrological Institute, Sweden
  • 3Georges Lemaitre Centre for Earth and Climate Research, Earth and Life Institute, Université Catholique de Louvain, Louvain-la-Neuve, Belgium
  • 4Bolin Centre for Climate Research, Stockholm University, Sweden

Abstract. A substantial part of Arctic climate predictability at interannual time scales stems from the knowledge of the initial sea ice conditions. Among all the variables characterizing sea ice, sea ice volume, being a product of sea ice area/concentration (SIC) and thickness (SIT), is the most sensitive parameter for climate change. However, the majority of climate prediction systems are only assimilating the observed SIC due to lack of long-term reliable global observation of SIT. In this study the EC-Earth3 Climate Prediction System with anomaly initialization to ocean, SIC and SIT states is developed. In order to evaluate the benefits of specific initialized variables at regional scales, three sets of retrospective ensemble prediction experiments are performed with different initialization strategies: ocean-only; ocean plus SIC; and ocean plus SIC and SIT initialization. The increased skill from ocean plus SIC initialization is small in most regions, compared to ocean-only initialization. In the marginal ice zone covered by seasonal ice, skills regarding winter SIC are mainly gained from the initial ocean temperature anomalies. Consistent with previous studies, the Arctic sea ice volume anomalies are found to play a dominant role for the prediction skill of September Arctic sea ice extent. Winter preconditioning of SIT for the perennial ice in the central Arctic Ocean results in increased skill of SIC in the adjacent Arctic coastal waters (e.g. the Laptev/East Siberian/Chukchi Seas) for lead time up to a decade. This highlights the importance of initializing SIT for predictions of decadal time scale in regional Arctic sea ice. Our results suggest that as the climate warming continues and the central Arctic Ocean might become seasonal ice free in the future, the controlling mechanism for decadal predictability may thus shift from being the sea ice volume playing the major role to a more ocean-related processes.

Tian Tian et al.

 
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Data sets

Benefits of sea ice thickness initialization for the Arctic decadal climate prediction skill in EC-Earth3: data Tian Tian https://doi.org/10.5281/zenodo.4297926

Model code and software

Benefits of sea ice thickness initialization for the Arctic decadal climate prediction skill in EC-Earth3: scripts and routines Tian Tian, Mehdi Pasha Karami, and François Massonnet https://doi.org/10.5281/zenodo.4297603

Tian Tian et al.

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Short summary
Three decadal prediction experiments with EC-Earth3 are performed to investigate the impact of ocean, sea ice concentration and thickness initialization, respectively. We find that the persistence of perennial thick ice in the central Arctic can affect the sea ice predictability in its adjacent waters via advection process or wind, despite those regions can be seasonally ice free during recent two decades. This has implication for the coming decades as the thinning of Arctic sea ice continues.