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| Titel |
Assimilation of Soil Wetness Index and Leaf Area Index into the ISBA-A-gs land surface model: grassland case study |
| VerfasserIn |
A. L. Barbu, J.-C. Calvet, J.-F. Mahfouf, C. Albergel, S. Lafont |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1726-4170
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| Digitales Dokument |
URL |
| Erschienen |
In: Biogeosciences ; 8, no. 7 ; Nr. 8, no. 7 (2011-07-22), S.1971-1986 |
| Datensatznummer |
250006054
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| Publikation (Nr.) |
 copernicus.org/bg-8-1971-2011.pdf |
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| Zusammenfassung |
| The performance of the joint assimilation in a land surface model of a Soil
Wetness Index (SWI) product provided by an exponential filter together with
Leaf Area Index (LAI) is investigated. The data assimilation is evaluated
with different setups using the SURFEX modeling platform, for a period of
seven years (2001–2007), at the SMOSREX grassland site in southwestern
France. The results obtained with a Simplified Extended Kalman Filter
demonstrate the effectiveness of a joint data assimilation scheme when both
SWI and Leaf Area Index are merged into the ISBA-A-gs land surface model.
The assimilation of a retrieved Soil Wetness Index product presents several
challenges that are investigated in this study. A significant improvement of
around 13 % of the root-zone soil water content is obtained by assimilating
dimensionless root-zone SWI data. For comparison, the assimilation of in
situ surface soil moisture is considered as well. A lower impact on the root
zone is noticed. Under specific conditions, the transfer of the information
from the surface to the root zone was found not accurate. Also, our results
indicate that the assimilation of in situ LAI data may correct a number of
deficiencies in the model, such as low LAI values in the senescence phase
by using a seasonal-dependent error definition for background and
observations. In order to verify the specification of the errors for SWI
and LAI products, a posteriori diagnostics are employed. This approach
highlights the importance of the assimilation design on the quality of the
analysis. The impact of data assimilation scheme on CO2 fluxes is also
quantified by using measurements of net CO2 fluxes gathered at the SMOSREX
site from 2005 to 2007. An improvement of about 5 % in terms of rms error is
obtained. |
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