English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  Global high-resolution monthly pCO(2) climatology for the coastal ocean derived from neural network interpolation

Laruelle, G. G., Landschützer, P., Gruber, N., Tison, J.-L., Delille, B., & Regnier, P. (2017). Global high-resolution monthly pCO(2) climatology for the coastal ocean derived from neural network interpolation. Biogeosciences, 14, 4545-4561. doi:10.5194/bg-14-4545-2017.

Item is

Files

show Files
hide Files
:
bg-14-4545-2017.pdf (Publisher version), 4MB
Name:
bg-14-4545-2017.pdf
Description:
-
OA-Status:
Visibility:
Public
MIME-Type / Checksum:
application/pdf / [MD5]
Technical Metadata:
Copyright Date:
-
Copyright Info:
-
:
bg-14-4545-2017-supplement.zip (Supplementary material), 49MB
Name:
bg-14-4545-2017-supplement.zip
Description:
-
OA-Status:
Visibility:
Public
MIME-Type / Checksum:
application/zip / [MD5]
Technical Metadata:
Copyright Date:
-
Copyright Info:
-
License:
-

Locators

show

Creators

show
hide
 Creators:
Laruelle, Goulven G., Author
Landschützer, Peter1, Author           
Gruber, Nicolas, Author
Tison, Jean-Louis, Author
Delille, Bruno, Author
Regnier, Pierre, Author
Affiliations:
1Director’s Research Group OES, The Ocean in the Earth System, MPI for Meteorology, Max Planck Society, ou_913553              

Content

show
hide
Free keywords: CO2 ATLAS SOCAT; CARBON SINK; SURFACE PCO(2); INTERANNUAL VARIABILITY; CONTINENTAL-SHELF; ARCTIC-OCEAN; SEA; FLUXES; EXCHANGE; CYCLE
 Abstract: In spite of the recent strong increase in the number of measurements of the partial pressure of CO2 in the surface ocean (pCO(2)), the air-sea CO2 balance of the continental shelf seas remains poorly quantified. This is a consequence of these regions remaining strongly under-sampled in both time and space and of surface p CO2 exhibiting much higher temporal and spatial variability in these regions compared to the open ocean. Here, we use a modified version of a two-step artificial neural network method (SOM-FFN; Landschutzer et al., 2013) to interpolate the p CO2 data along the continental margins with a spatial resolution of 0.25 ffi and with monthly resolution from 1998 to 2015. The most important modifications compared to the original SOM-FFN method are (i) the much higher spatial resolution and (ii) the inclusion of sea ice and wind speed as predictors of p CO2. The SOM-FFN is first trained with p CO2 measurements extracted from the SO-CATv4 database. Then, the validity of our interpolation, in both space and time, is assessed by comparing the generated pCO(2) field with independent data extracted from the LD-VEO2015 database. The new coastal pCO(2) product confirms a previously suggested general meridional trend of the annual mean pCO(2) in all the continental shelves with high values in the tropics and dropping to values beneath those of the atmosphere at higher latitudes. The monthly resolution of our data product permits us to reveal significant differences in the seasonality of pCO(2) across the ocean basins. The shelves of the western and northern Pacific, as well as the shelves in the temperate northern Atlantic, display particularly pronounced seasonal variations in pCO(2); while the shelves in the south-eastern Atlantic and in the southern Pacific reveal a much smaller seasonality. The calculation of temperature normalized pCO(2) for several latitudes in different oceanic basins confirms that the seasonality in shelf pCO(2) cannot solely be explained by temperature-induced changes in solubility but are also the result of seasonal changes in circulation, mixing and biological productivity. Our results also reveal that the amplitudes of both thermal and nonthermal seasonal variations in pCO(2) are significantly larger at high latitudes. Finally, because this product's spatial extent includes parts of the open ocean as well, it can be readily merged with existing global open-ocean products to produce a true global perspective of the spatial and temporal variability of surface ocean pCO(2).

Details

show
hide
Language(s): eng - English
 Dates: 20172017
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: ISI: 000412902300002
DOI: 10.5194/bg-14-4545-2017
 Degree: -

Event

show

Legal Case

show

Project information

show hide
Project name : C-CASCADES
Grant ID : 643052 744
Funding program : Horizon 2020 (H2020)
Funding organization : European Commission (EC)

Source 1

show
hide
Title: Biogeosciences
  Other : Biogeosciences
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: Katlenburg-Lindau, Germany : Copernicus GmbH on behalf of the European Geosciences Union
Pages: - Volume / Issue: 14 Sequence Number: - Start / End Page: 4545 - 4561 Identifier: ISSN: 1726-4170
CoNE: https://pure.mpg.de/cone/journals/resource/111087929276006