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| Titel |
Stochastic repercussion of land-surface energy budget noise onto a coupled land-atmosphere model |
| VerfasserIn |
P. Gentine, D. Entekhabi, E. Schertzer, J. Polcher |
| Konferenz |
EGU General Assembly 2009
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 11 (2009) |
| Datensatznummer |
250021322
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| Zusammenfassung |
| The present study is based on the work first introduced by Lettau (1951): in this paper
Lettau analytically studied the response of a linearized land-atmosphere model
to a sinusoidal forcing of net radiation at the land-surface. The model has been
first improved to obtain the analytical solution of the temperature and heat flux
profiles in the soil and in the Atmospheric Boundary Layer (ABL) in response to
any daily forcing of incoming radiation at the land-surface. With this model, the
profiles of temperature and heat are expressed in terms of temporal Fourier series.
Moreover the surface variables (temperature, specific humidity, surface fluxes) are also
derived analytically and their diurnal course is expressed as a function of both surface
parameters (friction velocity, vegetation height, aerodynamic resistance, stomatal
conductance).
In this presentation, we further extend the application of this theoretical model to the
study of the error in the land-surface energy budget closure. This closure error could result
form either modeling or experimental inaccuracies, leading to incorrect energy partitioning at
the land-surface. In particular, the response of the coupled land-atmosphere model to the
land-surface energy error is investigated. This noise in the energy budget is introduced in the
form of a stochastic Brownian Bridge, which is a Brownian Motion conditioned to vanish at
0h and 24h.
First the impact of land-surface noise on the partitioning of land-surface energy
partitioning is examined. Moreover the influence of the land-surface noise on Land Surface
Temperature and air temperature is carefully analyzed, as it is fundamental for the use of data
assimilation in conjunction with land-surface models.
Finally, the repercussion of the surface noise in the ABL and the soil is analytically found
and its temporal and spatial dependency is studied. In particular, the correlation between the
land-surface state and the ABL state is further investigated. These results emphasize the
impact of accurate land-surface modeling on both the atmosphere and the soil representation,
leading to strong impact on meteorological and hydrological predictions as well as for data
assimilation of land-surface temperature. |
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