Influence of drizzle on Z–M relationships in warm clouds

Abstract

This paper addresses the sensitivity of the relationships between radar reflectivity (Z) and liquid water content (M) for liquid water clouds to microphysical drizzle parameters by means of simulated radar observation at a frequency of 3 GHz of modeled cumulus clouds. A power law relationship for non drizzling clouds with water content as high as 3 gm − 3 : Z c = 0.026 M c 1.61 is numerically derived and agreed with previous empirical relationships relative to cumulus and stratocumulus. This relationship is then used to explore the influence of drizzle on the correlation between radar reflectively and water content. Due to their large diameters with respect to cloud droplets, drizzle sized drops dominate radar reflectivity but do not carry the cloud water content so that reflectivity and liquid water content are expected to be not correlated in clouds containing drizzle. It is shown that for congestus or extreme congestus cumuli, microphysical conditions for which the Z c -M c relationship can be used with a tolerance of 5 and 10% are provided whereas for humilis or mediocris cumuli, the presence of drizzle breaks down the Z c -M c relationship whatever the situations.

Revisiting Liquid Water Content Retrievals in Warm Stratified Clouds: The Modified Frisch

“…The most commonly applied cloud retrievals combine radar and MWR to derive LWC profiles (Zhao et al, 2012): The LWP from a MWR constrains the retrieval, while the radar reflectivity (Z e ) determines the shape of the LWC profile (Frisch et al, 1995). As a few drizzle drops can dominate Z e while negligibly contributing to LWC (Fox & Illingworth, 1997), the accuracy of those retrievals deteriorates once drizzle is present in the cloud (Khain et al, 2008;Pujol et al, 2007). This is particularly unfortunate as drizzle is often found in marine stratocumulus clouds (Stevens et al, 2003).…”

Simulations of X band thunderstorm airborne radar observations

“…It has to be noted that cloud droplets have been added to precipitation by using temperature through a relation we have developped from microwave radiometric profiler observations (to be published), log(LWC/1.68) = 0.027 T − 0.88, where LWC is liquid water content (in g m − 3 ), log denotes decimal logarithm and the factor 1.68 takes into account the fact that LWC field is more extended than precipitation field. One can use as well the relation of Pujol et al (2007b) which relies cloud droplet reflectivity factor to LWC at S band, Z e,S = 0.026 LWC 1.61 . The step 3 consists in converting, for each identified hydrometeor, Z e,S to physical parameters as precipitation rate R or water content, through the various relations explicited in the fourth column of the Table 3.…”

“…The literature is rich of examples of radar simulators (Vivekanandan et al, 1993;Giuli et al, 1994;Anagnostou and Krajewski, 1997;Capsoni et al, 2001;Haase and Crewell, 2000;Féral et al, 2003a,b;Pujol et al, 2007a,b). The meteorological target can be built by means of hydrometeor size distributions, for example to study cloud droplet attenuation at different wavelengths (Pujol et al, 2007a) and the influence of drizzle on liquid water content retrievals for warm clouds at S band (Pujol et al, 2007b). Observed data can also be considered as input data of the radar simulator.…”

A new analysis of fine aerosol capture by raindrops at terminal velocities

“…In below-cloud scavenging by rain, the diameter of raindrops generally ranges from 50 to 500 μm (Michaelides, 2008;Pujol, Georgis, & Sauvageot, 2007), and raindrops of higher than 6 mm diameter are unstable and break into smaller drops (Pruppacher & Klett, 1997). The terminal velocities of raindrops with different diameters in this range and the corresponding Reynolds numbers are calculated by the two correlations and the results are summarized in Table 1, where Re¼d c u 0 /ν, and ν is the kinematic viscosity of air.…”