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Radar Signal Interpretation in Warm Season Rainstorms
Author(s) -
Nicolas R. Dalezios,
N. Kouwen
Publication year - 1990
Publication title -
hydrology research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.665
H-Index - 48
eISSN - 1996-9694
pISSN - 0029-1277
DOI - 10.2166/nh.1990.0004
Subject(s) - radar , bivariate analysis , environmental science , meteorology , weather radar , signal (programming language) , preprocessor , computer science , remote sensing , algorithm , geology , machine learning , telecommunications , geography , artificial intelligence , programming language
There are several sources of error affecting the returned power of weather radar signals with an impact on the accuracy of radar rainfall measurements. In this study, several factors and sources of error are considered at the preprocessing stage of the raw radar reflectivities for surface rainfall estimation. In particular, deterministic corrective algorithms are developed and alternatively used for non-rainfall echoes, wind effect, signal attenuation and the Z-R relationship. These techniques are applied to a number of warm season rainstorms. A bivariate statistical objective analysis is used as a basis for comparing the different algorithms. Two error statistics are computed in order to assess the performance of each algorithm. The results indicate that the deterministic techniques constitute a necessary step in the ultimate improvement of surface rainfall estimates by weather radar.

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