Error Characteristics of Rainfall Measurements by Collocated Joss–Waldvogel Disdrometers

Abstract

Error characteristics of rainfall measurements were studied using six collocated Joss–Waldvogel (JW) disdrometers that are located at NASA’s Wallops Flight Facility. The six disdrometer means of rain rate R, reflectivity Z, and differential reflectivity ZDR, for a given minute were considered as a reference. The maximum deviations of R, Z, and ZDR from the mean in a rain event were 0.6 mm h−1, 1.3 dB, and 0.05 dB, respectively. Rainfall statistics were then examined between disdrometer pairs. The root-mean-square (rms) difference of R, Z, and ZDR between paired disdrometers in a rain event were as high as 3.2 mm h−1, 3.7 dB, and 0.3 dB, respectively. The rms difference of R and ZDR were even higher when the disdrometer observations were stratified based on reflectivity intervals. The differences in disdrometer rainfall measurements have a potential impact when the disdrometers are considered as calibration tools for vertically pointing and scanning radars. The differences between the disdrometer measurements also result in differences in coefficients and exponents of the derived relations between radar parameters and rain rate. Among the four different relations between radar parameters and rain rate, the absolute difference in rain rate |ΔR| from two different JW disdrometers was highest in R(ZH, ZDR) and lowest in R(KDP, ZDR). The other two relations were R(Z) and R(KDP). The |ΔR| increases with increasing horizontally polarized reflectivity ZH, and differential specific phase KDP in both single- and dual-parameter rainfall estimators, while the |ΔR| increases with decreasing ZDR in dual-parameter rainfall estimators. Several sources of JW disdrometer malfunctions were also presented. The hardware problems were the leading cause for the malfunction of the JW disdrometers, as identified by the manufacturer. A single JW disdrometer could have inherent measurement errors that can only be identified in the presence of collocated (preferably two) rain-measuring instruments.

Estimating Rain Rates from Tipping-Bucket Rain Gauge Measurements

“…These differences might result from the rainfall variability, instrument precisions or environmental effects. According to the JW disdrometer manufacturer, the difference of event rain totals measured by the rain gauge and eo-located JW disdrometer should be within 15% for a rain event with total rainfall of 5 to 10 mm or more (Tokay et al 2005).…”

“…Many factors could affect the TB gauge measurements and rain rate estimation (Humphrey et al 1997;Nespor and Sevruk 1999;Habib et al 2001;Wolff et al 2005). As a precision instrument, the TB gauge suffers the systematic problem due to inadequate calibration before and after its deployment.…”

“…Many rain products and their quality evaluations have been produced by TSVO. Rain gauges have played a crucial role in this validation effort (Wolff et al 2005).…”

“…The 7-minute averages of 2A-56 rain rates are used in the Window Probability Matching Method (WPMM) to derive radar reflectivity-rainrate (ZeR) relations (Rosenfeld et al 1994;Amitai 2000), and then rainfall estimations. The 2A-56 is also widely used for the calibration of the ground-based radar estimates, the validation of monthly satellite rainfall estimates, as well as being disseminated as data files to the scientific community in general (Habib and Krajewski 2002;Datta et al 2003;Tokay et al 2003a;Fisher 2004;Wolff et al 2005). …”

Errors and Uncertainties in Microwave Link Rainfall Estimation Explored Using Drop Size Measurements and High-Resolution Radar Data

“…We have used two separate datasets for this to ensure that the retrieval relations used are independent of the data to which they are applied. Because of the (usually) limited sampling area or volume, obtaining statistically robust measurements of DSDs is a challenge (e.g., Tokay et al 2005;Uijlenhoet et al 2006). Despite these limitations, measurements made by disdrometers are still valuable and will be used here.…”