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| Titel |
A practical demonstration on AMSU retrieval precision for upper tropospheric humidity by a non-linear multi-channel regression method |
| VerfasserIn |
C. Jimenez, P. Eriksson, V. O. John, S. A. Buehler |
| 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 ; 5, no. 2 ; Nr. 5, no. 2 (2005-02-11), S.451-459 |
| Datensatznummer |
250002355
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| Publikation (Nr.) |
 copernicus.org/acp-5-451-2005.pdf |
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| Zusammenfassung |
| A neural network algorithm inverting selected channels from the
Advance Microwave Sounding Unit instruments AMSU-A and AMSU-B was
applied to retrieve layer averaged relative humidity. The neural
network was trained with a global synthetic dataset representing
clear-sky conditions. A precision of around 6% was obtained when
retrieving global simulated radiances, the precision deteriorated
less than 1% when real mid-latitude AMSU radiances were inverted
and compared with co-located data from a radiosonde station. The 6%
precision outperforms by 1% the reported precision estimate
from a linear single-channel regression between radiance and
weighting function averaged relative humidity, the more traditional
approach to exploit AMSU data. Added advantages are not only a
better precision; the AMSU-B humidity information is more optimally
exploited by including temperature information from AMSU-A channels;
and the layer averaged humidity is a more physical quantity than the
weighted humidity, for comparison with other datasets. The training
dataset proved adequate for inverting real radiances from a
mid-latitude site, but it is limited by not considering the impact
of clouds or surface emissivity changes, and further work is needed
in this direction for further validation of the precision estimates. |
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