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| Titel |
Ensemble filter based estimation of spatially distributed parameters in a mesoscale dust model: experiments with simulated and real data |
| VerfasserIn |
V. M. Khade, J. A. Hansen, J. S. Reid, D. L. Westphal |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1680-7316
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| Digitales Dokument |
URL |
| Erschienen |
In: Atmospheric Chemistry and Physics ; 13, no. 6 ; Nr. 13, no. 6 (2013-03-27), S.3481-3500 |
| Datensatznummer |
250018544
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| Publikation (Nr.) |
 copernicus.org/acp-13-3481-2013.pdf |
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| Zusammenfassung |
| The ensemble adjustment Kalman filter (EAKF) is used to estimate the
erodibility fraction parameter field in a coupled meteorology and dust
aerosol model (Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS))
over the Sahara desert. Erodibility is often employed as the key
parameter to map dust source. It is used along with surface winds (or surface
wind stress) to calculate dust emissions. Using the Saharan desert as a test
bed, a perfect model Observation System Simulation Experiments (OSSEs) with
40 ensemble members, and observations of aerosol optical depth (AOD), the
EAKF is shown to recover correct values of erodibility at about 80% of the
points in the domain. It is found that dust advected from upstream grid
points acts as noise and complicates erodibility estimation. It is also found
that the rate of convergence is significantly impacted by the structure of
the initial distribution of erodibility estimates; isotropic initial
distributions exhibit slow convergence, while initial distributions with
geographically localized structure converge more quickly. Experiments using
observations of Deep Blue AOD retrievals from the MODIS satellite sensor
result in erodibility estimates that are considerably lower than the values
used operationally. Verification shows that the use of the tuned erodibility
field results in better predictions of AOD over the west Sahara
and the Arabian Peninsula. |
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