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| Titel |
Sensitivity tests for an ensemble Kalman filter for aerosol assimilation |
| VerfasserIn |
N. A. J. Schutgens, T. Miyoshi, T. Takemura, T. Nakajima |
| 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 ; 10, no. 14 ; Nr. 10, no. 14 (2010-07-16), S.6583-6600 |
| Datensatznummer |
250008638
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| Publikation (Nr.) |
 copernicus.org/acp-10-6583-2010.pdf |
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| Zusammenfassung |
We present sensitivity tests for a global aerosol assimilation system
utilizing AERONET observations of AOT (aerosol optical thickness) and
AAE (aerosol Ångström exponent). The assimilation system employs an
ensemble Kalman filter which requires tuning of three numerical
parameters: ensemble size nens, local patch size npatch and inflation
factor ρ. In addition, experiments are performed to test the impact of
various implementations of the system. For instance, we use a different
prescription of the emission ensemble or a different combination of
observations.
The various experiments are compared against one-another and against
independent AERONET and MODIS/Aqua observations. The assimilation leads
to significant improvements in modelled AOT and AAE fields. Moreover
remaining errors are mostly random while they are mostly systematic for an
experiment without assimilation. In addition, these results do not depend
much on our parameter or design choices.
It appears that the value of the local patch size has by far the biggest
impact on the assimilation, which has sufficiently converged for an ensemble
size of nens=20. Assimilating AOT and AAE is clearly preferential to
assimilating AOT at two different wavelengths. In contrast, initial
conditions or a description of aerosol beyond two modes (coarse and fine)
have only little effect.
We also discuss the use of the ensemble spread as an error estimate of the
analysed AOT and AAE fields. We show that a very common prescription of
the emission ensemble (independent random modification in each grid cell) can
have trouble generating sufficient spread in the forecast ensemble. |
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