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| Titel |
Streamflow data assimilation for soil moisture analysis |
| VerfasserIn |
K. Warrach-Sagi, V. Wulfmeyer |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1991-959X
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| Digitales Dokument |
URL |
| Erschienen |
In: Geoscientific Model Development ; 3, no. 1 ; Nr. 3, no. 1 (2010-01-07), S.1-12 |
| Datensatznummer |
250000792
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| Publikation (Nr.) |
 copernicus.org/gmd-3-1-2010.pdf |
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| Zusammenfassung |
| Streamflow depends on the soil moisture of a river catchment and can
be measured with relatively high accuracy. The soil moisture in the
root zone influences the latent heat flux and, hence, the quantity
and spatial distribution of atmospheric water vapour and
precipitation. As numerical weather forecast and climate models
require a proper soil moisture initialization for their land surface
models, we enhanced an Ensemble Kalman Filter to assimilate
streamflow time series into the multi-layer land surface model
TERRA-ML of the regional weather forecast model COSMO. The impact of
streamflow assimilation was studied by an observing system
simulation experiment in the Enz River catchment (located at the
downwind side of the northern Black Forest in Germany). The results
demonstrate a clear improvement of the soil moisture field in the
catchment. We illustrate the potential of streamflow data
assimilation for weather forecasting and discuss its spatial and
temporal requirements for a corresponding, automated river gauging
network. |
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