Abstract

Four types (2D-video disdrometer: 2DVD; precipitation occurrence sensor system: POSS; micro-rain radar: MRR; and Joss–Waldvogel disdrometer: JWD) of sixteen instruments were collocated within a square area of 400 m2 from 16 April to 8 May 2008 for intercomparison of drop size distribution (DSD) of rain. This unique dataset was used to study the inherent measurement uncertainty due to the diversity of the measuring principles and sampling sizes of the four types of instruments. The DSD intercomparison shows generally good agreement among them, except that the POSS and MRR had higher concentrations of small raindrops (<1.0 mm) and offered a better chance to observe big raindrops (>5.2 mm). The measurement uncertainty (
 
 
 σ
 
 
 ) was obtained quantitatively after considering the zero or non-zero measurement error covariance between two instruments of the same type. The results indicate the measurement uncertainties were found to be neither independent nor identical among the same type of instruments. The MRR is relatively accurate (lower 
 
 
 σ
 
 
 ) due to large sampling volumes and accurate measurement of the Doppler power spectrum. The JWD is the least accurate due to the small sampling volumes. The 
 
 
 σ
 
 
 decreases rapidly with increasing time-averaging window. The 2DVD shows the best accuracy of R in longer averaging time, but this is not true for Z due to the small sampling volume. The MRR outperformed other instruments for Z for entire averaging time due to its measuring principle.

Highlights

  • The drop size distribution (DSD) of rain collected by various types of disdrometer has been broadly used for numerous studies and applications

  • The underestimation from POSS and micro rain radar (MRR) may be attributed to wet radome, the path attenuation effect, and calibration issues

  • 2DVD exhibited inherent measuring issues, it directly measured raindrop sizes and concentration with digital images. 2DVD was selected as the reference disdrometer

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Summary

Introduction

The drop size distribution (DSD) of rain collected by various types of disdrometer has been broadly used for numerous studies and applications. The radar-based quantitative precipitation estimation (QPE) can be significantly improved by understanding the natural variability of the DSD [1,2,3,4,5,6,7]. The uncertainty in the radar-based QPE can be greatly reduced by utilizing suitable DSDs and corresponding rainfall estimators [1,7,8,9,10]. DSDs obtained from a small domain were studied regarding sampling variability and investigating the 2D spatial correlation functions [18,19,20,21]. Tapiador et al [3], Jaffrain and Berne [4,5], and Jaffrain et al [6] used several PARSIVELs to investigate the sampling uncertainty, the small-scale variability of DSD, and the influence on radar QPE

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