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Title

A global monthly climatology of total alkalinity: a neural network approach (2019) [Dataset]

AuthorsBroullón, 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.
KeywordsTotal alkalinity
Monthly climatology
Neural network
Ocean acidification
Issue Date2019
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.; 2019; “A global monthly climatology of total alkalinity: a neural network approach (2019) [Dataset]”; Digital.CSIC; http://dx.doi.org/10.20350/digitalCSIC/8644
DescriptionThe item is made of 5 files: 1) README.txt; 2) AT_NNGv2_climatology.nc contains the climatology of AT computed with NNGv2 in netcdf4 format and the climatologies of oxygen (median filtered from WOA13), phosphate, nitrate and silicate (these three derived from CANYON-B); 3) NNGv2 is the neural network object used to create the climatology; 4)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); 5) Example.rar contains an example matrix of inputs to the neural network, the NNGv2.mat and a MATLAB script to compute AT with NNGv2
URIhttp://hdl.handle.net/10261/184460
DOIhttp://dx.doi.org/10.20350/digitalCSIC/8644
Appears in Collections:(IIM) Conjuntos de datos

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File Description SizeFormat 
README_Global_monthly_2019.txt1,62 kBTextView/Open
NNGv2.mat26,15 kBUnknownView/Open
Example.rar54,74 kBUnknownView/Open
AT_NNGv2_climatology.nc2,95 GBUnknownView/Open
ATNNWOA13.mp466,4 MBUnknownView/Open
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