Editorial Type:
Article
Article Type:
Research Article

Radar–Rain Gauge Comparisons under Observational Uncertainties

Grzegorz J. Ciach Iowa Institute of Hydraulic Research, University of Iowa, Iowa City, Iowa

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Witold F. Krajewski Iowa Institute of Hydraulic Research, University of Iowa, Iowa City, Iowa

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Print Publication:
01 Oct 1999
DOI:
https://doi.org/10.1175/1520-0450(1999)038<1519:RRGCUO>2.0.CO;2
Page(s):
1519–1525
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Abstract

A simple, analytically tractable model of the radar–rain gauge rainfall observational process, including measurement errors, is presented. The model is applied to study properties of different reflectivity–rainfall (Z–R) relationships estimated from radar and rain gauge data. Three common Z–R adjustment schemes are considered: direct and reverse nonlinear regression, and the probability matching method. The three techniques result in quite different formulas for the estimated Z–R relationships. All three also are different from the intrinsic Z–R of the model and depend strongly on the assumed observational uncertainties. The results explain, to a degree, the diversity of Z–R relationships encountered in the literature. They also suggest that development of new tools that account for the uncertainties is necessary to separate the observational and natural causes of the Z–R variability.

Corresponding author address: Prof. Witold F. Krajewski, Iowa Institute of Hydraulic Research, University of Iowa, 404 Hydraulics Laboratory, Iowa City, IA 52242-1585.

Abstract

A simple, analytically tractable model of the radar–rain gauge rainfall observational process, including measurement errors, is presented. The model is applied to study properties of different reflectivity–rainfall (Z–R) relationships estimated from radar and rain gauge data. Three common Z–R adjustment schemes are considered: direct and reverse nonlinear regression, and the probability matching method. The three techniques result in quite different formulas for the estimated Z–R relationships. All three also are different from the intrinsic Z–R of the model and depend strongly on the assumed observational uncertainties. The results explain, to a degree, the diversity of Z–R relationships encountered in the literature. They also suggest that development of new tools that account for the uncertainties is necessary to separate the observational and natural causes of the Z–R variability.

Corresponding author address: Prof. Witold F. Krajewski, Iowa Institute of Hydraulic Research, University of Iowa, 404 Hydraulics Laboratory, Iowa City, IA 52242-1585.

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Journal of Applied Meteorology and Climatology

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