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| Titel |
Calibration of aerodynamic roughness over the Tibetan Plateau with Ensemble Kalman Filter analysed heat flux |
| VerfasserIn |
J. H. Lee, J. Timmermans, Z. Su, M. Mancini |
| 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 ; 16, no. 11 ; Nr. 16, no. 11 (2012-11-20), S.4291-4302 |
| Datensatznummer |
250013575
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| Publikation (Nr.) |
 copernicus.org/hess-16-4291-2012.pdf |
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| Zusammenfassung |
| Aerodynamic roughness height (Zom) is a key parameter required in
several land surface hydrological models, since errors in heat flux
estimation are largely dependent on optimization of this input.
Despite its significance, it remains an uncertain parameter which is not
readily determined. This is mostly because of non-linear relationship in
Monin-Obukhov similarity (MOS) equations and uncertainty of vertical characteristic of
vegetation in a large scale. Previous studies often determined aerodynamic
roughness using a minimization of cost function over MOS
relationship or linear regression over it, traditional wind profile method,
or remotely sensed vegetation index. However, these are complicated procedures that require a high
accuracy for several other related parameters embedded in serveral equations including MOS. In
order to simplify this procedure and reduce the number of parameters in need,
this study suggests a new approach to extract aerodynamic roughness parameter
from single or two heat flux measurements analyzed via Ensemble Kalman Filter (EnKF)
that affords non-linearity. So far, to our knowledge, no previous study has
applied EnKF to aerodynamic roughness estimation, while the majority of data
assimilation study have paid attention to updates of other land surface state
variables such as soil moisture or land surface temperature. The approach of
this study was applied to grassland in semi-arid Tibetan Plateau and maize on
moderately wet condition in Italy. It was demonstrated that aerodynamic
roughness parameter can be inversely tracked from heat flux EnKF final
analysis. The aerodynamic roughness height estimated in this approach was
consistent with eddy covariance method and literature value. Through
a calibration of this parameter, this adjusted the sensible heat previously
overestimated and latent heat flux previously underestimated by the original
Surface Energy Balance System (SEBS) model. It was considered that this
improved heat flux estimation especially during the summer Monsoon period,
based upon a comparison with precipitation and soil moisture field measurement. For an
advantage of this approach over other previous methodologies,
this approach is useful even when eddy
covariance data are absent at a large scale and is time-variant over vegetation growth, as
well as is not directly affected by saturation problem of remotely sensed
vegetation index. |
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