TITLE:
Evaluation on Radar Reflectivity-Rainfall Rate (Z-R) Relationships for Guyana
AUTHORS:
Komalchand Dhiram, Zhenhui Wang
KEYWORDS:
Radar Reflectivity, Rain Gauges, Rainfall Rate, Z-R Relationships, Correlation
JOURNAL NAME:
Atmospheric and Climate Sciences,
Vol.6 No.4,
October
11,
2016
ABSTRACT: The
constant development of science and technology in weather radar results in
high-resolution spatial and temporal rainfall estimates and improved early
warnings of meteorological phenomena such as flood [1]. Weather radars do not measure the rainfall
amount directly, so a relationship between the reflectivity (Z) and
rainfall rate (R), called the Z-R relationship (Z = aRb),
where a and b are empirical constants, can be used to estimate the rainfall
amount. In this research, mathematical techniques were used to find the best
climatological Z-R relationships for the Low Coastal Plain of Guyana.
The reflectivity data from the S-Band Doppler Weather Radar for February 17 and
21, 2011 and May 8, 2012 together with the daily rainfall depths at 29 rainfall
stations located within a 150 km radius were investigated. A climatological Z-R relationship type Z = 200R1.6 (Marshall-Palmer)
configured by default into the radar system was used to investigate the
correlation between the radar reflectivity and the rainfall by gauges. The same
data sets were used with two distinct experimental Z-R relationships, Z = 300R1.4 (WSR-88D Convective) and Z = 250R1.2 (Rosenfeld Tropical) to determine if any could be
applicable for area of study. By comprehensive regression analysis, New Z-R and R-Z relationships for each of the three events aforementioned were
developed. In addition, a combination of all the samples for all three events
were used to produce another relationship called “All in One”. Statistical
measures were then applied to detect BIAS and Error STD in order to produce more
evidence-based results. It is proven that different Z-R relationships could be calibrated into the radar system to
provide more accurate rainfall estimation.