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...

Full description

Bibliographic Details
Main Authors: Broullón, 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, Steven M. A. C.
Format: Dataset
Language:English
Published: Digital.CSIC 2018
Subjects:
Total alkalinity
Monthly climatology
Neural network
Ocean acidification
Pacific
Online Access:https://dx.doi.org/10.20350/digitalcsic/8564
https://digital.csic.es/handle/10261/169529
Description
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)

Similar Items