Accessibility navigation


An assessment of ten ocean reanalyses in the polar regions

Uotila, P., Goosse, H., Haines, K. ORCID: https://orcid.org/0000-0003-2768-2374, Chevallier, M., Barthelemy, A., Bricaud, C., Carton, J., Fuckar, N., Garric, G., Iovino, D., Kauker, F., Korhonen, M., Lien, V. S., Marnela, M., Massonnet, F., Mignac, D., Peterson, K. A., Sadikni, R., Shi, L., Tietsche, S. , Toyoda, T., Xie, J. and Zhang, Z. (2019) An assessment of ten ocean reanalyses in the polar regions. Climate Dynamics, 52 (3-4). pp. 1613-1650. ISSN 0930-7575

[img]
Preview
Text (Open access) - Published Version
· Available under License Creative Commons Attribution.
· Please see our End User Agreement before downloading.

12MB
[img] Text - Accepted Version
· Restricted to Repository staff only

7MB

It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

To link to this item DOI: 10.1007/s00382-018-4242-z

Abstract/Summary

Global and regional ocean and sea ice reanalysis products (ORAs) are increasingly used in polar research, but their quality remains to be systematically assessed. To address this, the Polar ORA Intercomparison Project (Polar ORA-IP) has been established following on from the ORA-IP project. Several aspects of ten selected ORAs in the Arctic and Antarctic were addressed by concentrating on comparing their mean states in terms of snow, sea ice, ocean transports and hydrography. Most polar diagnostics were carried out for the first time in such an extensive set of ORAs. For the multi-ORA mean state, we found that deviations from observations were typically smaller than individual ORA anomalies, often attributed to offsetting biases of individual ORAs. The ORA ensemble mean therefore appears to be a useful product and while knowing its main deficiencies and recognizing its restrictions, it can be used to gain useful information on the physical state of the polar marine environment.

Item Type:Article
Refereed:Yes
Divisions:Science > School of Mathematical, Physical and Computational Sciences > National Centre for Earth Observation (NCEO)
Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:76764
Publisher:Springer

Downloads

Downloads per month over past year

University Staff: Request a correction | Centaur Editors: Update this record

Page navigation