Estimation of global CO2 fluxes at regional scale using the maximum likelihood ensemble filter

Ravi S. Lokupitiya, D. Zupanski, A. S. Denning, S. R. Kawa, Kevin Gurney, M. Zupanski

Research output: Contribution to journalArticle

31 Citations (Scopus)

Abstract

We use an ensemble-based data assimilation method, known as the maximum likelihood ensemble filter (MLEF), which has been coupled with a global atmospheric transport model to estimate slowly varying biases of carbon surface fluxes. Carbon fluxes for this test consist of hourly gross primary production and ecosystem, respiration over land, and air-sea gas exchange. Persistent multiplicative biases intended to represent incorrectly simulated biogeochemical or land-management processes such as stand age, soil fertility, or coarse woody debris were estimated for 1 year at 10° longitude by 6° latitude spatial resolution and with an 8-week time window. We tested the model using a pseudodata experiment with an existing observation network that includes flasks, aircraft profiles, and continuous measurements. Because of the underconstrained nature of the problem, strong covariance smoothing was applied in the first data assimilation cycle, and localization schemes have been introduced. Error covariance was propagated in subsequent cycles. The coupled model satisfactorily recovered the land biases in densely observed areas. Ocean biases, however, were poorly constrained by the atmospheric observations. Unlike in batch mode inversions, the MLEF has a capability of assimilating large observation vectors and hence is suitable for assimilating hourly continuous observations and satellite observations in the future. Uncertainty was reduced further in our pseudodata experiment than by previous batch methods because of the ability to assimilate a large observation vector. Propagation of spatial covariance and dynamic localization avoid the need for prescribed spatial patterns of error covariance centered at observation sites as in previous grid-scale methods.

Original languageEnglish (US)
Article numberD20110
JournalJournal of Geophysical Research: Atmospheres
Volume113
Issue number20
DOIs
StatePublished - Oct 27 2008
Externally publishedYes

Fingerprint

Maximum likelihood
Fluxes
filter
filters
data assimilation
Carbon
coarse woody debris
atmospheric transport
surface flux
carbon flux
gas exchange
smoothing
Debris
soil fertility
land management
assimilation
Ecosystems
primary production
aircraft
respiration

ASJC Scopus subject areas

  • Atmospheric Science
  • Geophysics
  • Earth and Planetary Sciences (miscellaneous)
  • Space and Planetary Science

Cite this

Lokupitiya, R. S., Zupanski, D., Denning, A. S., Kawa, S. R., Gurney, K., & Zupanski, M. (2008). Estimation of global CO2 fluxes at regional scale using the maximum likelihood ensemble filter. Journal of Geophysical Research: Atmospheres, 113(20), [D20110]. https://doi.org/10.1029/2007JD009679

Estimation of global CO2 fluxes at regional scale using the maximum likelihood ensemble filter. / Lokupitiya, Ravi S.; Zupanski, D.; Denning, A. S.; Kawa, S. R.; Gurney, Kevin; Zupanski, M.

In: Journal of Geophysical Research: Atmospheres, Vol. 113, No. 20, D20110, 27.10.2008.

Research output: Contribution to journalArticle

Lokupitiya, Ravi S. ; Zupanski, D. ; Denning, A. S. ; Kawa, S. R. ; Gurney, Kevin ; Zupanski, M. / Estimation of global CO2 fluxes at regional scale using the maximum likelihood ensemble filter. In: Journal of Geophysical Research: Atmospheres. 2008 ; Vol. 113, No. 20.
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