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| Titel |
Satellite-driven downscaling of global reanalysis precipitation products for hydrological applications |
| VerfasserIn |
H. Seyyedi, E. N. Anagnostou, E. Beighley, J. McCollum |
| 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. 12 ; Nr. 18, no. 12 (2014-12-11), S.5077-5091 |
| Datensatznummer |
250120558
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| Publikation (Nr.) |
 copernicus.org/hess-18-5077-2014.pdf |
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| Zusammenfassung |
| Deriving flood hazard maps for ungauged basins typically requires simulating
a long record of annual maximum discharges. To improve this approach,
precipitation from global reanalysis systems must be downscaled to a spatial
and temporal resolution applicable for flood modeling. This study evaluates
such downscaling and error correction approaches for improving hydrologic
applications using a combination of NASA's Global Land Data Assimilation
System (GLDAS) precipitation data set and a higher resolution multi-satellite
precipitation product (TRMM). The study focuses on 437 flood-inducing storm
events that occurred over a period of ten years (2002–2011) in the
Susquehanna River basin located in the northeastern United States. A
validation strategy was devised for assessing error metrics in rainfall and
simulated runoff as function of basin area, storm severity, and season. The
WSR-88D gauge-adjusted radar-rainfall (stage IV) product was used as the
reference rainfall data set, while runoff simulations forced with the stage
IV precipitation data set were considered as the runoff reference. Results
show that the generated rainfall ensembles from the downscaled reanalysis
product encapsulate the reference rainfall. The statistical analysis consists
of frequency and quantile plots plus mean relative error and root-mean-square
error statistics. The results demonstrated improvements in the precipitation
and runoff simulation error statistics of the satellite-driven downscaled
reanalysis data set compared to the original reanalysis precipitation
product. Results vary by season and less by basin scale. In the fall season
specifically, the downscaled product has 3 times lower mean relative error
than the original product; this ratio increases to 4 times for the simulated
runoff values. The proposed downscaling scheme is modular in design and can
be applied on any gridded satellite and reanalysis data set. |
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