Model Mean State Sea Ice Thickness Reflects Dynamic Effect Biases: A Process Based Evaluation

Anheuser, James; Liu, Yinghui; Key, Jeff

doi:10.1029/2023gl106963

i

Model Mean State Sea Ice Thickness Reflects Dynamic Effect Biases: A Process Based Evaluation

2024
By Anheuser, James ; Liu, Yinghui ; Key, Jeff

Select the Download button to view the document

Please click the download button to view the document.

Details

Journal Title:

Geophysical Research Letters
Personal Author:

Anheuser, James ; Liu, Yinghui ; Key, Jeff
NOAA Program & Office:

NESDIS (National Environmental Satellite, Data, and Information Service) ; CIMSS (Cooperative Institute for Meteorological Satellite Studies) ; STAR (Center for Satellite Applications and Research)
Description:

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.
Source:

Geophysical Research Letters, 51(5)
DOI:

https://doi.org/10.1029/2023gl106963
ISSN:

0094-8276 ; 1944-8007
Format:

pdf
Publisher:

American Geophysical Union (AGU)
Document Type:

Journal Article
Funding:

Grant no. NA20NES4320003
License:

https://creativecommons.org/licenses/by/4.0/
Rights Information:

CC BY
Compliance:

Library
Main Document Checksum:

urn:sha-512:0ade47b7bfcf6c7ac0cc171030d76169b35495d64f78e3f906ea0dc6e4b2111be29d210b4e8db4d942fe2b3b62aa76971f40783167a2f9a739f4388c46e0ef4b
Download URL:

https://repository.library.noaa.gov/view/noaa/67865/noaa_67865_DS1.pdf
File Type:

[PDF - 8.34 MB ]

ON THIS PAGE

Details

The NOAA IR serves as an archival repository of NOAA-published products including scientific findings, journal articles, guidelines, recommendations, or other information authored or co-authored by NOAA or funded partners. As a repository, the NOAA IR retains documents in their original published format to ensure public access to scientific information.

BACK TO TOP