Model Mean State Sea Ice Thickness Reflects Dynamic Effect Biases: A Process Based Evaluation
Abstract Global climate models account for sea ice thickness by summing thermodynamic processes that affect thickness through phase change and dynamic processes that affect thicknesses through relative motion. Comparison of these individual processes with observations is essential for model interpre...
| Published in: | Geophysical Research Letters |
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| Main Authors: | , , |
| Format: | Article in Journal/Newspaper |
| Language: | English |
| Published: |
Wiley
2024
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| Subjects: | |
| Online Access: | https://doi.org/10.1029/2023GL106963 https://doaj.org/article/cf40d26cae7141d59adbe13fdf275379 |
| Summary: | Abstract Global climate models account for sea ice thickness by summing thermodynamic processes that affect thickness through phase change and dynamic processes that affect thicknesses through relative motion. Comparison of these individual processes with observations is essential for model interpretation and development. We utilized observational estimates of basal thermodynamic growth, overall thickness changes and their residual difference (including dynamics) to evaluate these processes in the National Center for Atmospheric Research (NCAR) Community Earth System Model 2 (CESM2) submission to the World Climate Research Program (WCRP) Ocean Model Comparison Project Phase 2 (OMIP2) and Pan‐Arctic Ice–Ocean Modeling and Assimilation System (PIOMAS). Both models exhibit a similar pattern of higher basal thermodynamic growth and lower residual effects and wintertime thickness in the central Arctic than observational estimates for 2010–2018, and vice versa in the peripheral seas. Correcting residual effect biases would ameliorate the biases in both mean thickness and basal thermodynamic growth. |
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