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| Titel |
Evaluation of TRMM rainfall estimates over a large Indian river basin (Mahanadi) |
| VerfasserIn |
D. Kneis, C. Chatterjee, R. Singh |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1027-5606
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| Digitales Dokument |
URL |
| Erschienen |
In: Hydrology and Earth System Sciences ; 18, no. 7 ; Nr. 18, no. 7 (2014-07-04), S.2493-2502 |
| Datensatznummer |
250120403
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| Publikation (Nr.) |
 copernicus.org/hess-18-2493-2014.pdf |
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| Zusammenfassung |
The paper examines the quality of satellite-based precipitation
estimates for the lower Mahanadi River basin (eastern India). The
considered data sets known as 3B42 and 3B42-RT (version 7/7A) are
routinely produced by the tropical rainfall measuring mission (TRMM)
from passive microwave and infrared recordings. While the 3B42-RT
data are disseminated in real time, the gauge-adjusted 3B42 data set
is published with a delay of some months. The quality of the two
products was assessed in a two-step procedure. First, the
correspondence between the remotely sensed precipitation rates and
rain gauge data was evaluated at the sub-basin scale. Second, the
quality of the rainfall estimates was assessed by analysing their
performance in the context of rainfall–runoff simulation.
At sub-basin level (4000 to 16 000 km2) the
satellite-based areal precipitation estimates were found to be
moderately correlated with the gauge-based counterparts (R2 of
0.64–0.74 for 3B42 and 0.59–0.72 for 3B42-RT). Significant
discrepancies between TRMM data and ground observations were
identified at high-intensity levels. The rainfall depth derived from
rain gauge data is often not reflected by the TRMM estimates (hit
rate < 0.6 for ground-based intensities > 80 mm day-1). At the same time, the remotely sensed
rainfall rates frequently exceed the gauge-based equivalents (false
alarm ratios of 0.2–0.6). In addition, the real-time product
3B42-RT was found to suffer from a spatially consistent negative bias.
Since the regionalisation of rain gauge data is potentially
associated with a number of errors, the above results are subject to
uncertainty. Hence, a validation against independent information,
such as stream flow, was essential. In this case study, the outcome
of rainfall–runoff simulation experiments was consistent with the
above-mentioned findings. The best fit between observed and
simulated stream flow was obtained if rain gauge data were used as
model input (Nash–Sutcliffe index of 0.76–0.88 at gauges not
affected by reservoir operation). This compares to the values of
0.71–0.78 for the gauge-adjusted TRMM 3B42 data and 0.65–0.77 for
the 3B42-RT real-time data. Whether the 3B42-RT data are useful in
the context of operational runoff prediction in spite of the
identified problems remains a question for further research. |
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