Open AccessSampling Issues in Estimating Radar Variables from Disdrometer Data
Author(s) -
Paul L. Smith
Publication year - 2016
Publication title -
journal of atmospheric and oceanic technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.774
H-Index - 124
eISSN - 1520-0426
pISSN - 0739-0572
DOI - 10.1175/jtech-d-16-0040.1
Subject(s) - disdrometer , differential phase , estimator , radar , polarimetry , remote sensing , sampling (signal processing) , environmental science , statistics , population , meteorology , computer science , phase (matter) , mathematics , physics , geography , optics , rain gauge , scattering , telecommunications , demography , detector , sociology , quantum mechanics
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 Z dr can occur with samples of even a few hundred drops; significant biases and errors also occur in estimates of reflectivity Z H or specific differential phase K dp . 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.