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| Titel |
The impact of near-surface soil moisture assimilation at subseasonal, seasonal, and inter-annual timescales |
| VerfasserIn |
C. Draper, R. Reichle |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1027-5606
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| Digitales Dokument |
URL |
| Erschienen |
In: Hydrology and Earth System Sciences ; 19, no. 12 ; Nr. 19, no. 12 (2015-12-18), S.4831-4844 |
| Datensatznummer |
250120866
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| Publikation (Nr.) |
 copernicus.org/hess-19-4831-2015.pdf |
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| Zusammenfassung |
| A 9 year record of Advanced Microwave Scanning Radiometer – Earth Observing System (AMSR-E) soil moisture retrievals are assimilated
into the Catchment land surface model at four locations in the US. The
assimilation is evaluated using the unbiased mean square error (ubMSE)
relative to watershed-scale in situ observations, with the ubMSE
separated into contributions from the subseasonal
(SMshort), mean seasonal (SMseas), and
inter-annual (SMlong) soil moisture dynamics. For
near-surface soil moisture, the average ubMSE for Catchment without
assimilation was (1.8 × 10−3 m3 m−3)2, of
which 19 % was in SMlong, 26 % in
SMseas, and 55 % in SMshort. The AMSR-E
assimilation significantly reduced the total ubMSE at every site, with
an average reduction of 33 %. Of this ubMSE reduction, 37 %
occurred in SMlong, 24 % in SMseas, and
38 % in SMshort. For root-zone soil moisture, in situ
observations were available at one site only, and the near-surface and
root-zone results were very similar at this site. These results
suggest that, in addition to the well-reported improvements in
SMshort, assimilating a sufficiently long soil moisture
data record can also improve the model representation of important
long-term events, such as droughts. The improved agreement between the
modeled and in situ SMseas is harder to interpret, given
that mean seasonal cycle errors are systematic, and systematic errors
are not typically targeted by (bias-blind) data assimilation.
Finally, the use of 1-year subsets of the AMSR-E and Catchment soil
moisture for estimating the observation-bias correction (rescaling)
parameters is investigated. It is concluded that when only 1 year of
data are available, the associated uncertainty in the rescaling
parameters should not greatly reduce the average benefit gained from
data assimilation, although locally and in extreme years there is a risk of
increased errors. |
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