Multi-beam raindrop size distribution retrievals on the Doppler spectra
Acquiring the raindrop size distribution from radar data is still a challenge. Generally this distribution is retrieved using the reflectivity, Z, and the differential reflectivity, Zdr, at S-band. The specific differential phase, Kdp, provides a third radar observable in the case of heavy precipitation to strengthen the retrieval technique. For S-band profiling radars, Kdp cannot be used, mainly because of the limited number of range bins containing rain. The Zdr measurement cannot be employed when the elevation is near the vertical, or in the case of drizzle and light rain. Therefore retrievals have to be performed on the measured Doppler spectra. For this purpose, the Doppler spectra of rain are modeled using Rayleigh scattering, the gamma distribution for the raindrop size, a size-shape relationship and a Gaussian kernel for the turbulence. Comparing the measured Doppler spectrum with the modeled one, a non-linear least-square fit technique is employed to obtain the parameters of the raindrop size distribution (D0, ?) and the turbulence broadening factor of the raindrop size spectrum (?0). The intercept parameter (Nw) and the radial wind component (v0) are estimated by scaling the broadened drop size distribution (DSD) along the spectral reflectivity axis and the Doppler velocity axis respectively. This approach has been proposed in (Moisseev et al, 2006). So far, this technique has not been further developed, exploited and validated. It is our intention to investigate this methodology using the Doppler-polarimetric TARA radar to retrieve raindrop size distribution from drizzle to heavy precipitation with high spatial and time resolution. Since TARA can profile in three directions, three raindrop size distribution profiles are estimated, which can give insight in the microphysical homogeneity of the precipitation
Multi-beam raindrop size distributions retrievals on the Doppler spectra: Influence of averaging and mean horizontal wind correction
Acquiring the raindrop size distribution (DSD) from radar data is still a challenge. For profiling radar, this distribution can be estimated from the Doppler spectra. However the Doppler spectrum is not a direct measure of the DSD. The radial component of the wind shifts the Doppler spectrum related to the raindrop size distribution along the Doppler velocity interval. Furthermore, the Doppler spectrum may be broadened by turbulence effect. The Doppler spectra of rain are modelled using Rayleigh scattering, the gamma distribution for the raindrop size, a size-shape relationship and a Gaussian kernel for the turbulence. Comparing the measured Doppler spectrum with the modelled one, a non-linear least-square fit technique is employed to obtain the parameters of the raindrop size distribution (D0, ?) and the turbulence broadening factor of the raindrop size spectrum (?0). The intercept parameter (Nw) and the radial wind component (v0) are estimated by scaling the broadened DSD along the spectral reflectivity axis and the Doppler velocity axis respectively. This approach has been proposed in [1]. So far, this technique has not been further developed, exploited and validated. It is our intention to investigate this methodology using the S-band Doppler-polarimetric TARA radar to retrieve raindrop size distribution from drizzle to heavy precipitation with high spatial and time resolution. Since TARA can profile in three directions, three raindrop size distribution profiles are estimated, which can give insight in the microphysical homogeneity of the precipitation. Because TARA can be used as wind profiler, the mean horizontal wind is estimated and a correction to remove the effect of the radial mean horizontal wind is implemented in the retrieval procedure. Comparison with and without correction is done. Another issue is averaging. Should the Doppler spectra be averaged before the non-linear least-square fit? How should they be averaged and how many averages should be carried out? These questions are discussed. High resolution multi-beams raindrop size distribution retrievals are illustrated and discussed.
Natural oscillations of small raindrops
REMOTE sensing of the rate of rainfall and the characteristics of hydrometeors with polarimetric radars is based on the assumption that the eccentricity of raindrops increases predictably with drop size1–3. Field observations, however, have shown that a particular raindrop size can have a wide range of shapes4,5 because of oscillations thought to be caused by drop collisions. Here we report observations of the shapes of small raindrops in circumstances where oscillations might occur sympathetically with eddy shedding in the drop's wake. The analysis of oscillations was aided by measurements of oscillation frequency, based on variations in rainbow angle and comparisons of mode energies. Our observations agree with quiescent shapes only for drops <1 mm in diameter. For 1–1.5 mm we discovered significant shape variability of distinct types corresponding to drop oscillations in axisymmetric and transverse modes. Our finding of reduced average distortion explains the mysterious shift away from quiescent distortion for small raindrops, postulated from radar observations6, and indicates the existence of an important class of raindrop oscillations—promoted not by collisions but by intrinsic aerodynamic forces.