Editorial Type:
Article
Article Type:
Research Article

Sampling Issues in Estimating Radar Variables from Disdrometer Data

Paul L. Smith South Dakota School of Mines and Technology, Rapid City, South Dakota

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Print Publication:
01 Nov 2016
DOI:
https://doi.org/10.1175/JTECH-D-16-0040.1
Page(s):
2305–2313
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Abstract

Simulation of sampling from gamma-distributed raindrop populations demonstrates that significant biases and substantial errors can occur in estimates of polarimetric radar variables based on samples of raindrop populations obtained with disdrometers. Biases and RMS errors of 0.5 dB or more in estimates of differential reflectivity Zdr can occur with samples of even a few hundred drops; significant biases and errors also occur in estimates of reflectivity ZH or specific differential phase Kdp. The results indicate that very large samples would be required to obtain adequate representation of the population characteristics for many radar applications. They also suggest that greater attention is needed to the sample sizes in the disdrometer data used in developing polarimetric rainfall-rate estimators or hydrometeor classification algorithms.

Corresponding author address: Paul L. Smith, South Dakota School of Mines and Technology, 501 E. St. Joseph St., Rapid City, SD 57701. E-mail: paul.smith@sdsmt.edu

Abstract

Simulation of sampling from gamma-distributed raindrop populations demonstrates that significant biases and substantial errors can occur in estimates of polarimetric radar variables based on samples of raindrop populations obtained with disdrometers. Biases and RMS errors of 0.5 dB or more in estimates of differential reflectivity Zdr can occur with samples of even a few hundred drops; significant biases and errors also occur in estimates of reflectivity ZH or specific differential phase Kdp. The results indicate that very large samples would be required to obtain adequate representation of the population characteristics for many radar applications. They also suggest that greater attention is needed to the sample sizes in the disdrometer data used in developing polarimetric rainfall-rate estimators or hydrometeor classification algorithms.

Corresponding author address: Paul L. Smith, South Dakota School of Mines and Technology, 501 E. St. Joseph St., Rapid City, SD 57701. E-mail: paul.smith@sdsmt.edu
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Journal of Atmospheric and Oceanic Technology

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