| Registro completo |
| Provedor de dados: |
ArchiMer
|
| País: |
France
|
| Título: |
Surface ocean CO2 in 1990–2011 modelled using a feed-forward neural network
|
| Autores: |
Zeng, Jiye
Nojiri, Yukihiro
Nakaoka, Shin-ichiro
Nakajima, Hideaki
Shirai, Tomoko
|
| Data: |
2015-07
|
| Ano: |
2015
|
| Palavras-chave: |
Ocean
CO2
Neural network
Model
|
| Resumo: |
This dataset includes the monthly distributions of CO2 fugacity in the world surface oceans reconstructed using a feed-forward neural network model and the CO2 measurements of the Surface Ocean CO2 Atlas version 2.0. It has a spatial resolution of 1 9 1° and spans a period of 22 years, from January 1990 to December 2011. The dataset also includes necessary parameters for the reconstruction and an estimate of the CO2 fluxes between the ocean and the atmosphere. The aim of this work is to provide a dataset for estimating the oceans’ contribution to the global carbon budget.
|
| Tipo: |
Text
|
| Idioma: |
Inglês
|
| Identificador: |
https://archimer.ifremer.fr/doc/00293/40400/38957.pdf
DOI:10.1002/gdj3.26
https://archimer.ifremer.fr/doc/00293/40400/
|
| Editor: |
Wiley-blackwell
|
| Formato: |
application/pdf
|
| Fonte: |
Geoscience Data Journal (2049-6060) (Wiley-blackwell), 2015-07 , Vol. 2 , N. 1 , P. 47-51
|
| Direitos: |
2015 The Authors. Geoscience Data Journal published by Royal Meteorological Society and John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
info:eu-repo/semantics/openAccess
restricted use
|
