FN Archimer Export Format
PT J
TI Surface ocean CO2 in 1990–2011 modelled using a feed-forward neural network
BT 
AF ZENG, Jiye
   NOJIRI, Yukihiro
   NAKAOKA, Shin-ichiro
   NAKAJIMA, Hideaki
   SHIRAI, Tomoko
AS 1:1;2:1;3:1;4:1;5:1;
FF 1:;2:;3:;4:;5:;
C1 Natl Inst Environm Studies, Ctr Global Environm Res, Tsukuba, Ibaraki 3058506, Japan.
C2 NIES, JAPAN
IN DOAJ
IF 1.562
TC 12
UR https://archimer.ifremer.fr/doc/00293/40400/38957.pdf
LA English
DT Article
CR OISO 8
   OISO1
   OISO2
   OISO3-NIVMER98
   OISO4 (VT 46)
   OISO5 (VT 49)
   VT 105 / OISO 17
   VT 108 / OISO-18
   VT 114 / OISO-19
   VT 117 / OISO-20
   VT 120 / OISO-21
   VT 127 / OISO-22
   VT 136 / OISO-23
   VT 51 / OISO 6
   VT 57 / OISO 9
   VT 60 / CARAUS - OISO 10
   VT 62 / CARAUS - OISO 11
   VT 79 / OISO 12
   VT 80 / OISO 13
   VT 81 / OISO 14
   VT 85 / OISO 15
   VT 94 / OISO 16
BO Marion Dufresne
DE ;ocean;CO2;neural network;model
AB 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.
PY 2015
PD JUN
SO Geoscience Data Journal
SN 2049-6060
PU Wiley-blackwell
VL 2
IS 1
UT 000364220100005
BP 47
EP 51
DI 10.1002/gdj3.26
ID 40400
ER

EF