Reply on RC3

Abstract

<strong class="journal-contentHeaderColor">Abstract.</strong> Radar Doppler spectra observations provide a wealth of information about cloud and precipitation microphysics and dynamics. The interpretation of these measurements depends on our ability to simulate these observations accurately forward. The effect of small-scale turbulence on the radar Doppler spectra shape has been traditionally treated by implementing the convolution process on the hydrometer reflectivity spectrum and environment turbulence. This approach assumes that all the particles in the radar sampling volume respond the same to turbulent scale velocity fluctuations and neglects the particle inertial effect. Here, we investigate the impact of particle inertia on the forward modelled radar Doppler spectra. A physics-based simulation is developed to demonstrate that big droplets, with large inertia, are unable to follow the rapid change of velocity field in a turbulent environment. These findings are incorporated to a new radar Doppler spectra simulator. Comparison between the traditional and the newly formulated radar Doppler spectra simulators indicates that the conventional simulator leads to an unrealistic broadening of the spectrum, especially in strong turbulence environment. Doppler spectra observed from the W-band Cloud Radar at South Great Plain (SGP) observatory are used to validate the fidelity of the two Doppler spectrum simulation methods. The result indicates that the Doppler spectrum generated from the proposed approach is more consistent to the observed Doppler spectrum while the conventional simulator misrepresents the Doppler spectrum morphology. This study provides clear evidence to illustrate the droplets inertial effect on radar Doppler spectrum and develops a physics-based simulator framework to accurately emulate the Doppler spectrum for a given Droplet Size Distribution in turbulence field. The proposed simulator has various potential applications to the cloud/precipitation studies and provides a valuable tool to decode the cloud microphysics and dynamics properties from Doppler radar observation.