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| Titel |
Comparing Ensemble Kalman filter and 4DVar data assimilation systems for CO2 flux inversions |
| VerfasserIn |
Arne Babenhauserheide, Sourish Basu, Sander Houweling, Wouter Peters, André Butz |
| Konferenz |
EGU General Assembly 2014
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 16 (2014) |
| Datensatznummer |
250097394
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| Publikation (Nr.) |
 EGU/EGU2014-12970.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 biosystems and to characterize natural feedback
mechanisms - one of the big unknown factors of climate change.
Based on more than one year of atmospheric in-situ concentration measurements, we
compare the performance of two established data assimilation techniques, Carbontracker and
TM5-4DVar, for CO2 flux estimation. Carbontracker is an Ensemble Kalman Filter method,
TM5-4DVar a 4D variational method. Harmonizing the input data allows for analyzing the
strengths and weaknesses of the two approaches by direct comparison of the modeled
concentrations and estimated fluxes.
We further assess the sensitivity of the two approaches to the density of observations and
operational parameters such as correlation lengths. This allows for investigating potential
improvements to the flux estimates from adding more measurement sites or observations with
a different correlation structure. The next step will be assimilating remote-sensing
total-column data from satellite or ground-based soundings. |
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