Abstract

Vertically integrated liquid (VIL) water content is a parameter obtained from a radar performing voluminal scanning. This parameter has proven useful in the detection of severe storms and may be a worthwhile indicator for very short-term rainfall forecasting methods. Unfortunately, no information is available on the accuracy of VIL radar measurements. The present paper addresses this issue by means of simulation. Reference VILs are defined from vertical profiles of drop size distributions (DSD). These profiles make it possible to simulate the corresponding vertical profiles of reflectivity as well as the radar measurements used to deduce the VIL, as estimated classically (i.e., application of a classical relationship between equivalent radar reflectivity factor Ze and liquid water content M adapted to raindrops). A comparison of the reference VIL to the corresponding estimate then allows estimating radar measurement error. The VIL measurement error is first studied from two hypothetical, yet realistic, vertical profiles of DSD: one typical of stratiform rain and the other typical of a convective situation. A sensitivity analysis with respect to both meteorological conditions and radar operating conditions is also performed on these two profiles. For the convective case, use of a classical Ze–M relationship adapted to liquid water results in a significant underestimation of the reference VIL value. The same effect applies to the stratiform profile, even though brightband phenomena can compensate for this underestimation and lend the impression of smaller measurement error. A simple alternative method is proposed in order to reduce measurement errors. Both conventional and alternative VIL measurement methods are tested on the two theoretical profiles as well as on a series of actual vertical profiles of reflectivity. Better measurements are obtained with the alternative method, provided the altitude of the 0°C isotherm and the density of ice particles can be determined with reasonable precision. This alternative method for estimating VIL from radar data could serve to improve VIL measurement accuracy and would be worth applying to a longer series of observed data.

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