English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  Study of the footprints of short-term variation in XCO2 observed by TCCON sites using NIES and FLEXPART atmospheric transport models

Belikov, D. A., Maksyutov, S., Ganshin, A., Zhuravlev, R., Deutscher, N. M., Wunch, D., et al. (2017). Study of the footprints of short-term variation in XCO2 observed by TCCON sites using NIES and FLEXPART atmospheric transport models. Atmospheric Chemistry and Physics, 17(1), 143-157. doi:10.5194/acp-17-143-2017.

Item is

Files

show Files
hide Files
:
BGC2454D.pdf (Postprint), 3MB
Name:
BGC2454D.pdf
Description:
-
OA-Status:
Visibility:
Public
MIME-Type / Checksum:
application/pdf / [MD5]
Technical Metadata:
Copyright Date:
-
Copyright Info:
-
License:
-
:
BGC2454.pdf (Publisher version), 11MB
Name:
BGC2454.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/10.5194/acp-17-143-2017 (Publisher version)
Description:
OA
OA-Status:

Creators

show
hide
 Creators:
Belikov, D. A., Author
Maksyutov, S., Author
Ganshin, A., Author
Zhuravlev, R., Author
Deutscher, N. M., Author
Wunch, D., Author
Feist, Dietrich G.1, Author           
Morino, I., Author
Parker, R. J., Author
Strong, K., Author
Yoshida, Y., Author
Bril, A., Author
Oshchepkov, S., Author
Boesch, H., Author
Dubey, M. K., Author
Griffith, D., Author
Hewson, W., Author
Kivi, R., Author
Mendonca, J., Author
Notholt, J., Author
Schneider, M., AuthorSussmann, R., AuthorVelazco, V., AuthorAoki, S., Author more..
Affiliations:
1Atmospheric Remote Sensing Group, Dr. D. Feist, Department Biogeochemical Systems, Prof. M. Heimann, Max Planck Institute for Biogeochemistry, Max Planck Society, ou_1497783              

Content

show
hide
Free keywords: -
 Abstract: The Total Carbon Column Observing Network (TCCON) is a network of ground-based Fourier Transform Spectrometers (FTS) that record near-infrared (NIR) spectra of the Sun. From these spectra, accurate and precise observations of CO2 column-averaged dry-air mole fraction (denoted XCO2) are retrieved. TCCON FTS observations have previously been used to validate satellite estimations of XCO2; however, our knowledge of the short-term spatial and temporal variations in XCO2 surrounding the TCCON sites is limited. In this work, we use the National Institute for Environmental Studies (NIES) Eulerian three-dimensional transport model and the FLEXPART (FLEXible PARTicle) Lagrangian Particle Dispersion Model (LPDM) to determine the footprints of short-term variations in XCO2 observed by operational, past, future, and possible TCCON sites. We propose a footprint-based method for the colocation of satellite and TCCON XCO2 observations, and estimate the performance of the method using the NIES model and five GOSAT XCO2 product datasets. Comparison of the proposed approach with a standard geographic method shows higher number of colocation points and average bias reduction up to 0.15 ppm for a subset of 16 stations for the period from January 2010 to January 2014. Case studies of the Darwin and La Réunion sites reveal that when the footprint area is rather curved, non-uniform and significantly different from a geographical rectangular area, the differences between these approaches are more noticeable. This emphasizes that the colocation is sensitive to local meteorological conditions and flux distributions.

Details

show
hide
Language(s):
 Dates: 2016-12-012017-01-032017
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: Other: BGC2454
DOI: 10.5194/acp-17-143-2017
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: Atmospheric Chemistry and Physics
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: Katlenburg-Lindau, Germany : European Geosciences Union
Pages: - Volume / Issue: 17 (1) Sequence Number: - Start / End Page: 143 - 157 Identifier: ISSN: 1680-7316
CoNE: https://pure.mpg.de/cone/journals/resource/111030403014016