A global monthly climatology of total alkalinity: a neural network approach (2019) [Dataset]
The 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 networ...
Main Authors: | , , , , , , , , , , , |
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Format: | Dataset |
Language: | English |
Published: |
Digital.CSIC
2019
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Subjects: | |
Online Access: | https://dx.doi.org/10.20350/digitalcsic/8644 https://digital.csic.es/handle/10261/184460 |
Summary: | The 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 |
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