Intercomparison and validation of the mixed layer depth fields of global ocean syntheses

Intercomparison and evaluation of the global ocean surface mixed layer depth (MLD) fields estimated from a suite of major ocean syntheses are conducted. Compared with the reference MLDs calculated from individual profiles, MLDs calculated from monthly mean and gridded profiles show negative biases o...

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Bibliographic Details
Main Authors: Toyoda, Takahiro, Fujii, Yosuke, Kuragano, Tsurane, Kamachi, Masafumi, Ishikawa, Yoichi, Masuda, Shuhei, Sato, Kanako, Awaji, Toshiyuki, Hernandez, Fabrice, Ferry, Nicolas, Guinehut, Stéphanie, Martin, Matthew J., Peterson, K. Andrew, Good, Simon A., Valdivieso, Maria, Haines, Keith, Storto, Andrea, Masina, Simona, Köhl, Armin, Zuo, Hao, Balmaseda, Magdalena, Yin, Yonghong, Shi, Li, Alves, Oscar, Smith, Gregory, Chang, You-Soon, Vernieres, Guillaume, Wang, Xiaochun, Forget, Gael, Heimbach, Patrick, Wang, Ou, Fukumori, Ichiro, Lee, Tong
Other Authors: Massachusetts Institute of Technology. Department of Earth, Atmospheric, and Planetary Sciences
Format: Article
Language:English
Published: Springer Berlin Heidelberg 2016
Online Access:http://hdl.handle.net/1721.1/104620
https://orcid.org/0000-0003-3925-6161
Description
Summary:Intercomparison and evaluation of the global ocean surface mixed layer depth (MLD) fields estimated from a suite of major ocean syntheses are conducted. Compared with the reference MLDs calculated from individual profiles, MLDs calculated from monthly mean and gridded profiles show negative biases of 10–20 m in early spring related to the re-stratification process of relatively deep mixed layers. Vertical resolution of profiles also influences the MLD estimation. MLDs are underestimated by approximately 5–7 (14–16) m with the vertical resolution of 25 (50) m when the criterion of potential density exceeding the 10-m value by 0.03 kg m[superscript −3] is used for the MLD estimation. Using the larger criterion (0.125 kg m[superscript −3]) generally reduces the underestimations. In addition, positive biases greater than 100 m are found in wintertime subpolar regions when MLD criteria based on temperature are used. Biases of the reanalyses are due to both model errors and errors related to differences between the assimilation methods. The result shows that these errors are partially cancelled out through the ensemble averaging. Moreover, the bias in the ensemble mean field of the reanalyses is smaller than in the observation-only analyses. This is largely attributed to comparably higher resolutions of the reanalyses. The robust reproduction of both the seasonal cycle and interannual variability by the ensemble mean of the reanalyses indicates a great potential of the ensemble mean MLD field for investigating and monitoring upper ocean processes.