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Quantitative precipitation estimation with weather radar using a data- and information-based approach

Neuper, M.; Ehret, U.

Abstract (englisch):
In this study we propose and demonstrate a data-driven approach in an “information-theoretic” framework to quantitatively estimate precipitation. In this context, predictive relations are expressed by empirical discrete probability distributions directly derived from data instead of fitting and applying deterministic functions, as is standard operational practice. Applying a probabilistic relation has the benefit of providing joint statements about rain rate and the related estimation uncertainty. The information-theoretic framework furthermore allows for the integration of any kind of data considered useful and explicitly considers the uncertain nature of quantitative precipitation estimation (QPE). With this framework we investigate the information gains and losses associated with various data and practices typically applied in QPE. To this end, we conduct six experiments using 4 years of data from six laser optical disdrometers, two micro rain radars (MRRs), regular rain gauges, weather radar reflectivity and other operationally available meteorological data from existing stations. Each experiment addresses a typical question related to QPE. ... mehr

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Verlagsausgabe §
DOI: 10.5445/IR/1000098756
Veröffentlicht am 09.10.2019
Originalveröffentlichung
DOI: 10.5194/hess-23-3711-2019
Coverbild
Zugehörige Institution(en) am KIT Institut für Wasser und Gewässerentwicklung (IWG)
Publikationstyp Zeitschriftenaufsatz
Jahr 2019
Sprache Englisch
Identifikator ISSN: 1027-5606, 1607-7938
KITopen-ID: 1000098756
Erschienen in Hydrology and earth system sciences
Band 23
Heft 9
Seiten 3711-3733
Vorab online veröffentlicht am 16.09.2019
Nachgewiesen in Scopus
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