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| Titel |
The TAMORA algorithm: satellite rainfall estimates over West Africa using multi-spectral SEVIRI data |
| VerfasserIn |
R. S. Chadwick, D. I. F. Grimes, R. W. Saunders, P. N. Francis, T. A. Blackmore |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1680-7340
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| Digitales Dokument |
URL |
| Erschienen |
In: Precipitation: Measurement, Climatology, Remote Sensing, and Modeling (EGU Session 2009) ; Nr. 25 (2010-03-08), S.3-9 |
| Datensatznummer |
250015729
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| Publikation (Nr.) |
 copernicus.org/adgeo-25-3-2010.pdf |
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| Zusammenfassung |
| A multi-spectral rainfall estimation algorithm has been developed for the
Sahel region of West Africa with the purpose of producing accumulated
rainfall estimates for drought monitoring and food security. Radar data were
used to calibrate multi-channel SEVIRI data from MSG, and a probability of
rainfall at several different rain-rates was established for each combination
of SEVIRI radiances. Radar calibrations from both Europe (the SatPrecip
algorithm) and Niger (TAMORA algorithm) were used. 10 day estimates were
accumulated from SatPrecip and TAMORA and compared with kriged gauge data and
TAMSAT satellite rainfall estimates over West Africa. SatPrecip was found to
produce large overestimates for the region, probably because of its non-local
calibration. TAMORA was negatively biased for areas of West Africa with
relatively high rainfall, but its skill was comparable to TAMSAT for the
low-rainfall region climatologically similar to its calibration area around
Niamey. These results confirm the high importance of local calibration for
satellite-derived rainfall estimates. As TAMORA shows no improvement in skill
over TAMSAT for dekadal estimates, the extra cloud-microphysical information
provided by multi-spectral data may not be useful in determining rainfall
accumulations at a ten day timescale. Work is ongoing to determine whether it
shows improved accuracy at shorter timescales. |
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