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dc.contributor.authorBroullón, Danieles_ES
dc.contributor.authorPérez, Fiz F.es_ES
dc.contributor.authorVelo, A.es_ES
dc.contributor.authorHoppema, Marioes_ES
dc.contributor.authorOlsen, Arees_ES
dc.contributor.authorTakahashi, Taroes_ES
dc.contributor.authorKey, Robert M.es_ES
dc.contributor.authorGonzález-Dávila, Melchores_ES
dc.contributor.authorTanhua, Tostees_ES
dc.contributor.authorJeansson, Emiles_ES
dc.contributor.authorKozyr, Alexes_ES
dc.contributor.authorvan Heuven, Stevenes_ES
dc.coverage.spatialOcean, globales_ES
dc.date.accessioned2018-09-10T12:16:36Z-
dc.date.available2018-09-10T12:16:36Z-
dc.date.issued2018-
dc.identifier.citationBroullón, Daniel; Pérez, Fiz F.; Velo, A.; Hoppema, M.; Olsen, Are; Takahashi, Taro; Key, Robert M.; González-Dávila, Melchor; Tanhua, T.; Jeansson, Emil; Kozyr, Alex; Van Heuven, S.; 2018; “A global monthly climatology of total alkalinity: a neural network approach (Discussions version) [Dataset]”; Digital.CSIC; http://dx.doi.org/10.20350/digitalCSIC/8564es_ES
dc.identifier.urihttp://hdl.handle.net/10261/169529-
dc.descriptionThe item is made of 6 files: 1) Readme_Global_monthly_dataset.txt; 2) ATNNWOA13.nc is the climatological data of total alkalinity computed with NNGv2; 3) NNGv2 is the neural network object used to create the climatology; 4) NNw3RMSE is a neural network object used to evaluate the error of the network when it is trained without data beyond +-3RMSE; 5)ATNNWOA13.mp4 is a video of the surface climatology, 3 vertical sections in the Pacific Ocean, Atlantic Ocean and Indean Ocean and, the variation in depth of one month (April); 6) Example.rar contains an example matrix of inputs to the neural network, the NNGv2.mat and a MATLAB script to compute AT with NNGv2.-- The final version is in http://dx.doi.org/10.20350/digitalCSIC/8644-
dc.description.sponsorshipThis research was supported by Ministerio de Educación, Cultura y Deporte (FPU grant FPU15/06026), Ministerio de Economía y Competitividad through the ARIOS (CTM2016-76146-C3-1-R) project co-funded by the Fondo Europeo de Desarrollo Regional 2014-2020 (FEDER) and EU Horizon 2020 through the AtlantOS project (grant agreement 633211)es_ES
dc.language.isoenges_ES
dc.relationinfo:eu-repo/grantAgreement/EC/H2020/633211es_ES
dc.relationinfo:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/CTM2016-76146-C3-1-Res_ES
dc.relation.isbasedonWORLD OCEAN ATLAS 2013 (WOA13) https://www.nodc.noaa.gov/OC5/woa13/es_ES
dc.relation.isbasedonGlobal Ocean Data Analysis Project version 2 (GLODAPv2) https://www.nodc.noaa.gov/ocads/oceans/GLODAPv2/es_ES
dc.relation.requiresThe climatology file can be easily opened with any netcdf reader. For a quick map viewing the Panoply NASA GISS software is strongly recommended (https://www.giss.nasa.gov/tools/panoply/download/).es_ES
dc.rightsopenAccesses_ES
dc.subjectTotal alkalinityes_ES
dc.subjectMonthly climatologyes_ES
dc.subjectNeural networkses_ES
dc.subjectOcean acidificationes_ES
dc.titleA global monthly climatology of total alkalinity: a neural network approach (Discussions version) [Dataset]es_ES
dc.typedatasetes_ES
dc.identifier.doi10.20350/digitalCSIC/8564-
dc.description.peerreviewedNoes_ES
dc.contributor.funderMinisterio de Economía y Competitividad (España)es_ES
dc.relation.csicSíes_ES
oprm.item.hasRevisionno ko 0 false*
dc.identifier.funderhttp://dx.doi.org/10.13039/501100003329es_ES
dc.subject.urihttp://aims.fao.org/aos/agrovoc/c_8721-
dc.subject.urihttp://aims.fao.org/aos/agrovoc/c_90 -
dc.subject.urihttp://aims.fao.org/aos/agrovoc/c_29553 -
dc.type.coarhttp://purl.org/coar/resource_type/c_ddb1es_ES
dc.subject.agrovocalkalinity -
dc.subject.agrovocacidification-
dc.subject.agrovocclimatic data-
item.openairecristypehttp://purl.org/coar/resource_type/c_ddb1-
item.fulltextWith Fulltext-
item.cerifentitytypeProducts-
item.openairetypedataset-
item.languageiso639-1en-
item.grantfulltextopen-
Aparece en las colecciones: (IIM) Conjuntos de datos
Ficheros en este ítem:
Fichero Descripción Tamaño Formato
ATNNWOA13.mp434,12 MBUnknownVisualizar/Abrir
NNw3RMSE.mat26,1 kBUnknownVisualizar/Abrir
ATNNWOA13.nc589,73 MBUnknownVisualizar/Abrir
README_Global_monthly_dataset2.txt1,37 kBTextVisualizar/Abrir
Example.rar54,81 kBUnknownVisualizar/Abrir
NNGv2.mat26,18 kBUnknownVisualizar/Abrir
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