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  5. JRA-55 based surface dataset for driving ocean–sea-ice models (JRA55-do)
 
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JRA-55 based surface dataset for driving ocean–sea-ice models (JRA55-do)

Author(s)
Tsujino, Hiroyuki  
Urakawa, Shogo  
Nakano, Hideyuki  
Small, R. Justin  
Kim, Who  
Yeager, Stephen  
Danabasoglu, Gokhan  
Suzuki, Tatsuo  
Bamber, Jonathan L.  
Bentsen, Mats  
Böning, Claus W.  
Bozec, Alexandra  
Chassignet, Eric  
Curchitser, Enrique  
Boeira Dias, Fabio  
Durack, Paul James  
Griffies, Stephen  
Harada, Yayoi  
Ilicak, Mehmet  
Josey, Simon  
Kobayashi, Chiaki  
Kobayashi, Shinya  
Komuro, Yoshiki  
Large, William  
Le Sommer, Julien  
Marsland, Simon  
Masina, Simona  
Istituto Nazionale di Geofisica e Vulcanologia (INGV), Sezione Bologna, Bologna, Italia  
Scheinert, Markus  
Tomita, Hiroyuki  
Valdivieso, Maria  
Yamazaki, Dai  
Language
English
Obiettivo Specifico
4A. Oceanografia e clima
Status
Published
JCR Journal
JCR Journal
Journal
Ocean Modelling  
Issue/vol(year)
/130 (2018)
Pages (printed)
79-139
Date Issued
2018
DOI
10.1016/j.ocemod.2018.07.002
URI
https://www.earth-prints.org/handle/2122/12523
Abstract
We present a new surface-atmospheric dataset for driving ocean–sea-ice models based on Japanese 55-year atmospheric reanalysis (JRA-55), referred to here as JRA55-do. The JRA55-do dataset aims to replace the CORE interannual forcing version 2 (hereafter called the CORE dataset), which is currently used in the framework of the Coordinated Ocean-ice Reference Experiments (COREs) and the Ocean Model Intercomparison Project (OMIP). A major improvement in JRA55-do is the refined horizontal grid spacing (∼ 55 km) and temporal interval (3 hr). The data production method for JRA55-do essentially follows that of the CORE dataset, whereby the surface fields from an atmospheric reanalysis are adjusted relative to reference datasets. To improve the adjustment method, we use high-quality products derived from satellites and from several other atmospheric reanalysis projects, as well as feedback on the CORE dataset from the ocean modelling community. Notably, the surface air temperature and specific humidity are adjusted using multi-reanalysis ensemble means. In JRA55-do, the downwelling radiative fluxes and precipitation, which are affected by an ambiguous cloud parameterisation employed in the atmospheric model used for the reanalysis, are based on the reanalysis products. This approach represents a notable change from the CORE dataset, which imported independent observational products. Consequently, the JRA55-do dataset is more self-contained than the CORE dataset, and thus can be continually updated in near real-time. The JRA55-do dataset extends from 1958 to the present, with updates expected at least annually. This paper details the adjustments to the original JRA-55 fields, the scientific rationale for these adjustments, and the evaluation of JRA55-do. The adjustments successfully corrected the biases in the original JRA-55 fields. The globally averaged features are similar between the JRA55-do and CORE datasets, implying that JRA55-do can suitably replace the CORE dataset for use in driving global ocean–sea-ice models.
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