English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  A statistical gap-filling method to interpolate global monthly surface ocean carbon dioxide data

Jones, S. D., Le Quere, C., Rödenbeck, C., Manning, A. C., & Olsen, A. (2016). A statistical gap-filling method to interpolate global monthly surface ocean carbon dioxide data. Journal of Advances in Modeling Earth Systems, 7(4), 1554 -1575. doi:10.1002/2014MS000416.

Item is

Files

show Files
hide Files
:
BGC2419.pdf (Publisher version), 3MB
Name:
BGC2419.pdf
Description:
-
OA-Status:
Visibility:
Public
MIME-Type / Checksum:
application/pdf / [MD5]
Technical Metadata:
Copyright Date:
-
Copyright Info:
-
License:
-

Locators

show
hide
Locator:
http://dx.doi.org/10.1002/2014MS000416 (Publisher version)
Description:
OA
OA-Status:

Creators

show
hide
 Creators:
Jones, Steve D., Author
Le Quere, Corinne, Author
Rödenbeck, Christian1, Author           
Manning, Andrew C., Author
Olsen, Are, Author
Affiliations:
1Inverse Data-driven Estimation, Dr. C. Rödenbeck, Department Biogeochemical Systems, Prof. M. Heimann, Max Planck Institute for Biogeochemistry, Max Planck Society, ou_1497785              

Content

show
hide
Free keywords: -
 Abstract: We have developed a statistical gap-filling method adapted to the specific coverage and properties of observed fugacity of surface ocean CO2 (fCO2). We have used this method to interpolate the Surface Ocean CO2 Atlas (SOCAT) v2 database on a 2.5°×2.5° global grid (south of 70°N) for 1985–2011 at monthly resolution. The method combines a spatial interpolation based on a “radius of influence” to determine nearby similar fCO2 values with temporal harmonic and cubic spline curve-fitting, and also fits long-term trends and seasonal cycles. Interannual variability is established using deviations of observations from the fitted trends and seasonal cycles. An uncertainty is computed for all interpolated values based on the spatial and temporal range of the interpolation. Tests of the method using model data show that it performs as well as or better than previous regional interpolation methods, but in addition it provides a near-global and interannual coverage.

Details

show
hide
Language(s):
 Dates: 2015-09-212015-10-242016-01-21
 Publication Status: Issued
 Pages: 22
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1002/2014MS000416
Other: BGC2419
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: Journal of Advances in Modeling Earth Systems
  Other : JAMES
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: Washington, D.C. : American Geophysical Union
Pages: 22 Volume / Issue: 7 (4) Sequence Number: - Start / End Page: 1554 - 1575 Identifier: Other: 1942-2466
CoNE: https://pure.mpg.de/cone/journals/resource/19422466