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One-Lag Estimators for Cross-Polarization Measurements

One-Lag Estimators for Cross-Polarization Measurements Estimators of the linear depolarization ratio (LDR) and cross-polarization correlation coefficients ( ρ xh ) free from noise biases are devised. The estimators are based on the 1-lag correlation functions. The 1-lag estimators can be implemented with radar with simultaneous reception of copolar and cross-polar returns. Absence of noise biases makes the 1-lag estimators useful in eliminating variations of the system gain and in observations of heavy precipitation with enhanced thermal radiation. The 1-lag estimators allow for measurements at lower signal-to-noise ratios than the conventional algorithms. The statistical biases and standard deviations of 1-lag estimates are obtained via the perturbation analysis. It is found that both the 1-lag and conventional estimates of ρ xh experience strong statistical biases at ρ xh less than 0.3 (i.e., at low canting angles of oblate hydrometeors), and a procedure to correct for this bias is proposed. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Atmospheric and Oceanic Technology American Meteorological Society

One-Lag Estimators for Cross-Polarization Measurements

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Publisher
American Meteorological Society
Copyright
Copyright © 2005 American Meteorological Society
ISSN
1520-0426
DOI
10.1175/JTECH1919.1
Publisher site
See Article on Publisher Site

Abstract

Estimators of the linear depolarization ratio (LDR) and cross-polarization correlation coefficients ( ρ xh ) free from noise biases are devised. The estimators are based on the 1-lag correlation functions. The 1-lag estimators can be implemented with radar with simultaneous reception of copolar and cross-polar returns. Absence of noise biases makes the 1-lag estimators useful in eliminating variations of the system gain and in observations of heavy precipitation with enhanced thermal radiation. The 1-lag estimators allow for measurements at lower signal-to-noise ratios than the conventional algorithms. The statistical biases and standard deviations of 1-lag estimates are obtained via the perturbation analysis. It is found that both the 1-lag and conventional estimates of ρ xh experience strong statistical biases at ρ xh less than 0.3 (i.e., at low canting angles of oblate hydrometeors), and a procedure to correct for this bias is proposed.

Journal

Journal of Atmospheric and Oceanic TechnologyAmerican Meteorological Society

Published: Feb 17, 2005

References