A global monthly climatology of total alkalinity: a neural network approach [Dataset]
The item is made of 4 files: 1) Readme_Global_monthly_dataset.txt; 2) ATNNWOA13.nc is the climatological data of total alkalinity computed with NN; 3) NN 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...
Main Authors: | , , , , , , , , , , , |
---|---|
Format: | Dataset |
Language: | English |
Published: |
Digital.CSIC
2018
|
Subjects: | |
Online Access: | https://dx.doi.org/10.20350/digitalcsic/8564 https://digital.csic.es/handle/10261/169529 |
Summary: | The item is made of 4 files: 1) Readme_Global_monthly_dataset.txt; 2) ATNNWOA13.nc is the climatological data of total alkalinity computed with NN; 3) NN 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) |
---|