DOI for 'input4MIPs.CMIP6.OMIP.MRI.MRI-JRA55-do-1-5-0'
doi:10.22033/ESGF/input4MIPs.15017
Name
input4MIPs.CMIP6.OMIP.MRI.MRI-JRA55-do-1-5-0
Abstract
CMIP6 Forcing Datasets (input4MIPs). These data include all datasets published for 'input4MIPs.CMIP6.OMIP.MRI.MRI-JRA55-do-1-5-0' with the full Data Reference Syntax following the template 'activity_id.mip_era.target_mip.institution_id.source_id.realm.frequency.variable_id.grid_label'. The MRI JRA55-do 1.5.0: Atmospheric state generated for OMIP based on the JRA-55 reanalysis (Based on JRA-55 reanalysis (1958-01 to 2020-07)) climate model, released in 2020, includes the following components: . The model was run by the Meteorological Research Institute, Tsukuba, Ibaraki 305-0052, Japan (MRI) in native nominal resolutions: none. Project: The forcing datasets (and boundary conditions) needed for CMIP6 experiments are being prepared by a number of different experts. Initially many of these datasets may only be available from those experts, but over time as part of the 'input4MIPs' activity most of them will be archived by PCMDI and served by the Earth System Grid Federation (https://esgf-node.llnl.gov/search/input4mips/ ). More information is available in the living document: http://goo.gl/r8up31 .
Subjects
input4MIPs.CMIP6.OMIP.MRI.MRI-JRA55-do-1-5-0 forcing data climate CMIP6
input4MIPs forcing data for CMIP6 is evolving, new versions are added when datasets are changed or additions are made. Cite this data collection according to the Data Citation Guidelines (http://bit.ly/2gBCuqM) and be sure to include the version number (e.g. v20210101).
Individuals using the data must abide by the terms of use for CMIP6 data (https://pcmdi.llnl.gov/CMIP6/TermsOfUse). Details on any license restrictions are recorded as global attributes in the files. (More information: http://climate.mri-jma.go.jp/~htsujino/jra55do.html).
Centro Euro-Mediterraneo sui Cambiamenti Climatici
28
Scheinert, Markus
-
GEOMAR Helmholtz Centre for Ocean Research Kiel
29
Tomita, Hiroyuki
-
Nagoya University
30
Valdivieso, Maria
-
University of Reading
31
Yamazaki, Dai
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Institute of Industrial Science, the University of Tokyo
IsReferencedByNext generation of Bluelink ocean reanalysis with multiscale data assimilation: BRAN2020. Chamberlain, Matthew A.; Oke, Peter R.; Fiedler, Russell A. S.; Beggs, Helen M.; Brassington, Gary B.; Divakaran, Prasanth. DOI:10.5194/essd-2021-194
IsCitedByZooplankton grazing is the largest source of uncertainty for marine carbon cycling in CMIP6 models. Rohr, Tyler; Richardson, Anthony J.; Lenton, Andrew; Chamberlain, Matthew A.; Shadwick, Elizabeth H.. DOI:10.1038/s43247-023-00871-w
IsCitedByNext generation of Bluelink ocean reanalysis with multiscale data assimilation: BRAN2020. Chamberlain, Matthew A.; Oke, Peter R.; Fiedler, Russell A. S.; Beggs, Helen M.; Brassington, Gary B.; Divakaran, Prasanth. DOI:10.5194/essd-13-5663-2021
IsCitedByData from: Evaluating the trustworthiness of explainable artificial intelligence (XAI) methods applied to regression predictions of Arctic sea-ice motion. Hoffman, Lauren A.; Mazloff, Matthew R.; Gille, Sarah T.; Giglio, Donata; Heimbach, Patrick. DOI:10.6075/j0s182q6