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| Titel |
A regional carbon data assimilation system and its preliminary evaluation in East Asia |
| VerfasserIn |
Z. Peng, M. Zhang, X. Kou, X. Tian, X. Ma |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1680-7316
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| Digitales Dokument |
URL |
| Erschienen |
In: Atmospheric Chemistry and Physics ; 15, no. 2 ; Nr. 15, no. 2 (2015-01-30), S.1087-1104 |
| Datensatznummer |
250119355
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| Publikation (Nr.) |
 copernicus.org/acp-15-1087-2015.pdf |
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| Zusammenfassung |
| In order to optimize surface CO2 fluxes at grid scales, a regional
surface CO2 flux inversion system (Carbon Flux Inversion system and
Community Multi-scale Air Quality, CFI-CMAQ) has been developed by applying
the ensemble Kalman filter (EnKF) to constrain the CO2 concentrations
and applying the ensemble Kalman smoother (EnKS) to optimize the surface
CO2 fluxes. The smoothing operator is associated with the atmospheric
transport model to constitute a persistence dynamical model to forecast the
surface CO2 flux scaling factors. In this implementation, the
"signal-to-noise" problem can be avoided; plus, any useful observed
information achieved by the current assimilation cycle can be transferred
into the next assimilation cycle. Thus, the surface CO2 fluxes can be
optimized as a whole at the grid scale in CFI-CMAQ. The performance of
CFI-CMAQ was quantitatively evaluated through a set of Observing System
Simulation Experiments (OSSEs) by assimilating CO2 retrievals from
GOSAT (Greenhouse Gases Observing Satellite). The results showed that the
CO2 concentration assimilation using EnKF could constrain the CO2
concentration effectively, illustrating that the simultaneous assimilation
of CO2 concentrations can provide convincing CO2 initial analysis
fields for CO2 flux inversion. In addition, the CO2 flux
optimization using EnKS demonstrated that CFI-CMAQ could, in general,
reproduce true fluxes at grid scales with acceptable bias. Two further sets
of numerical experiments were conducted to investigate the sensitivities of
the inflation factor of scaling factors and the smoother window. The results
showed that the ability of CFI-CMAQ to optimize CO2 fluxes greatly
relied on the choice of the inflation factor. However, the smoother window
had a slight influence on the optimized results. CFI-CMAQ performed very
well even with a short lag-window (e.g. 3 days). |
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