Global couplled ocean-atmosphere reanalysis and forecast with pelagic ecosystem


GCMD Science Keywords
[Oceans ] [Ocean Circulation ] [Biosphere ] [Aquatic Ecosystems ] [Plankton ]

IDENTIFICATION INFORMATION

Name Global couplled ocean-atmosphere reanalysis and forecast with pelagic ecosystem
Abbreviation K‚VCDA
Metadata Identifier RECCA_JAMSTEC_K7_CDA20181218144550-DIAS20180903143952-en

CONTACT

CONTACT on DATASET

Name Shiro Nishikawa
Organization Japan Agency for Marine-Earth Science and Technology
Address 3175-25, Showa-cho, Kanazawa-ku, Yokohama, Kanagawa, 236-0001, Japan
TEL +81-45-778-5738
E-mail snishika@jamstec.go.jp

CONTACT on PROJECT

Data Integration and Analysis System

Name DIAS Office
Organization Remote Sensing Technology Center of Japan
Address TOKYU REIT Toranomon Building 2F 3-17-1 Toranomon, Minato-ku, Tokyo, 105-0001, Japan
E-mail dias-office@diasjp.net

DOCUMENT AUTHOR

Name JAMSTEC-CEIST

DATASET CREATOR

Name JAMSTEC-CEIST

DATE OF THIS DOCUMENT

2018-12-18

DATE OF DATASET

  • creation : 2014-08-26

DATASET OVERVIEW

Abstract

The system used to produce the data set is the 4-dimensional variational (4D-VAR) coupled data assimilation system based on a

coupled ocean-atmosphere global model, which was developed by Sugiura et al. (2008) and the JAMSTEC-K7 consortium. It also

incorporates a biogeochemical model (NPZDC model), which is the pelagic ecosystem model based on nitrogen cycle (Masuda et al. 2013). (See the references for details of the system and models.)

In the 4D-VAR approach, optimized 4-dimensional analysis fields are sought by minimizing a cost function on the basis of adjoint method for physical parameters and Green's function approach (Menemenlis et al. 2005) for biogeochemical ones. The assimilated observations for the atmospheric component are the PREPBUFR data set (air temperature, specific humidity, and wind vectors) and 10 m scalar wind stress from SSMIS satellite observations. The assimilated observations for the oceanic physical component are OISST, and temperature and salinity profile data from the Argo and GTSPP. The assimilated data for the biogeochemical

component are climatological mean monthly nitrate from WOA05, chlorophyll-a from SeaWiFS, and chlorophyll-a from WOA98 which is converted to detritus.

The procedure of the production of the data set is as follows: using the assimilation window of 3 months, the assimilation experiment was conducted for every 3-months period from January-March 2010. Using the optimized control variables and parameters within the assimilation windows, the forecast experiments were performed for 3 years from the beginning of the assimilation windows (thus, the first 3 months correspond to the state estimation and the remaining 2 years and 9 months correspond to the pure forecast). In the forecast experiments, 10 ensemble forecast runs were also conducted using the atmospheric initial conditions shifted to 1-5 days before/after.

Topic Category(ISO19139)

  • climatologyMeteorologyAtmosphere

  • oceans

Temporal Extent

Begin Date 2014-01-01
End Date Under Continuation
Temporal Characteristics 10day

Geographic Bounding Box

North bound latitude 90
West bound longitude 360
Eastbound longitude 0
South bound latitude -90

Grid

Dimension Name Dimension Size (slice number of the dimension) Resolution Unit
row 360 1 (deg)
column 180 1 (deg)
vertical 45 (m)

Keywords

Keywords on Dataset

Keyword Type Keyword Keyword thesaurus Name
theme OCEANOGRAPHY GENERAL > Physical and biogeochemical interactions, OCEANOGRAPHY GENERAL > Climate and interannual variability, OCEANOGRAPHY GENERAL > Ocean data assimilation and reanalysis, OCEANOGRAPHY GENERAL > Ocean predictability and prediction, OCEANOGRAPHY BIOLOGICAL AND CHEMICAL > Nutrients and nutrient cycling AGU
theme Models > GCMD_platform
theme [Oceans ] > [Ocean Circulation ], [Biosphere ] > [Aquatic Ecosystems ] > [Plankton ] GCMD_science

Keywords on Project

Data Integration and Analysis System
Keyword Type Keyword Keyword thesaurus Name
theme DIAS > Data Integration and Analysis System No_Dictionary

Online Resource

Distribution Information

name version specification
Raw binary (GrADSŚ`Ž®) 1.0

USE CONSTRAINTS

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Data Integration and Analysis System

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1. Users shall prioritize and abide by terms of use stipulated by a data provider in the event such exist

2. The use of DIAS data sets is limited to research and educational purposes [*1]

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[*1] Data sets whose commercial usage are allowed under the data policy by data provider will be also allowed to be used commercially as DIAS data sets, after ongoing preparation works have been completed. Please contact the DIAS Office for more details.

[DIAS Office]

E-mail: dias-office@diasjp.net

Remote Sensing Technology Center of Japan

TOKYU REIT Toranomon Building 2F 3-17-1 Toranomon, Minato-ku, Tokyo, 105-0001

Disclaimer for Project

Data Integration and Analysis System

1. DIAS data provider is not liable for any losses or any damage when DIAS data sets are used.

2. DIAS data and related information are subject to change without any prior notice.

3. DIAS data sets provided are not supported for any additional processing or analysis.

ACKNOWLEDGEMENT

Project Acknowledgement

Data Integration and Analysis System

Whenever DIAS dataset is used for any academic presentations, and any publication of scientific results, the author(s) shall specify the following acknowledgement and if the data provider has their own acknowledgement quotation, the author(s) shall use both acknowledgements.

"The DIAS dataset is archived and provided under the framework of the Data Integration and Analysis System (DIAS) funded by Ministry of Education, Culture, Sports, Science and Technology (MEXT)."

REFERENCES

Sugiura, N., T. Awaji, S. Masuda, T. Mochizuki, T. Toyoda, T. Miyama, H. Igarashi, and Y. Ishikawa (2008), Development of a four-dimensional variational coupled data assimilation system for enhanced analysis and prediction of seasonal to interannual climate variations. J. Geophys. Res., 113, C10017, doi:10.1029/2008JC004741.

Masuda, S., T. Doi, N. Sugiura, S. Osafune, and Y. Ishikawa (2014), Data synthesis for biogeochemical variables by using a 4 dimensional variational approach.

Ann. Rep. ESC., April 2012 - March 2013, 67-70.

Menemenlis, D. I. Fukumori, and T. Lee (2005), Using Green's functions to calibrate an ocean general circulation model. Mon. Wes. Rev., 133, 1224-1240.


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