Publications in Scientific Journals:

C. Draper, J. Mahfouf, J.C. Calvet, E. Martin, W. Wagner:
"Assimilation of ASCAT near-surface soil moisture into the SIM hydrological model over France";
Hydrology and Earth System Sciences, 15 (2011), 3829 - 3841.

English abstract:
This study examines whether the assimilation
of remotely sensed near-surface soil moisture observations
might benefit an operational hydrological model, specifically
M´et´eo-France´s SAFRAN-ISBA-MODCOU (SIM) model.
Soil moisture data derived from ASCAT backscatter observations
are assimilated into SIM using a Simplified Extended
Kalman Filter (SEKF) over 3.5 years. The benefit of the assimilation
is tested by comparison to a delayed cut-off version
of SIM, in which the land surface is forced with more
accurate atmospheric analyses, due to the availability of additional
atmospheric observations after the near-real time
data cut-off. However, comparing the near-real time and
delayed cut-off SIM models revealed that the main difference
between them is a dry bias in the near-real time precipitation
forcing, which resulted in a dry bias in the rootzone
soil moisture and associated surface moisture flux forecasts.
While assimilating the ASCAT data did reduce the
root-zone soil moisture dry bias (by nearly 50 %), this was
more likely due to a bias within the SEKF, than due to the
assimilation having accurately responded to the precipitation
errors. Several improvements to the assimilation are identified
to address this, and a bias-aware strategy is suggested
for explicitly correcting the model bias. However, in this experiment
the moisture added by the SEKF was quickly lost
from the model surface due to the enhanced surface fluxes
(particularly drainage) induced by the wetter soil moisture
states. Consequently, by the end of each winter, during which
frozen conditions prevent the ASCAT data from being assimilated,
the model land surface had returned to its original
(dry-biased) climate. This highlights that it would be more
effective to address the precipitation bias directly, than to correct
it by constraining the model soil moisture through data

"Official" electronic version of the publication (accessed through its Digital Object Identifier - DOI)

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