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| Titel |
Comparing the CarbonTracker and TM5-4DVar data assimilation systems for CO2 surface flux inversions |
| VerfasserIn |
A. Babenhauserheide, S. Basu, S. Houweling, W. Peters, A. Butz |
| 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. 17 ; Nr. 15, no. 17 (2015-09-01), S.9747-9763 |
| Datensatznummer |
250120005
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| Publikation (Nr.) |
 copernicus.org/acp-15-9747-2015.pdf |
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| Zusammenfassung |
Data assimilation systems allow for estimating surface fluxes of
greenhouse gases from atmospheric concentration measurements. Good
knowledge about fluxes is essential to understand how climate change
affects ecosystems and to characterize feedback mechanisms. Based
on the assimilation of more than 1 year of atmospheric in situ
concentration measurements, we compare the performance of two
established data assimilation models, CarbonTracker and TM5-4DVar (Transport Model 5 – Four-Dimensional Variational model),
for CO2 flux estimation. CarbonTracker uses an ensemble
Kalman filter method to optimize fluxes on ecoregions. TM5-4DVar
employs a 4-D variational method and optimizes fluxes on
a 6° × 4° longitude–latitude grid. Harmonizing
the input data allows for analyzing the strengths and weaknesses of
the two approaches by direct comparison of the modeled
concentrations and the estimated fluxes. We further assess the
sensitivity of the two approaches to the density of observations and
operational parameters such as the length of the assimilation time window.
Our results show that both models provide optimized CO2
concentration fields of similar quality. In Antarctica CarbonTracker
underestimates the wintertime CO2 concentrations, since its
5-week assimilation window does not allow for adjusting the distant
surface fluxes in response to the detected concentration
mismatch. Flux estimates by CarbonTracker and TM5-4DVar are
consistent and robust for regions with good observation coverage,
regions with low observation coverage reveal significant
differences. In South America, the fluxes estimated by TM5-4DVar
suffer from limited representativeness of the few observations. For
the North American continent, mimicking the historical increase of
the measurement network density shows improving agreement between
CarbonTracker and TM5-4DVar flux estimates for increasing
observation density. |
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