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.
To Devolve or Not To Devolve? Welfare Reform in the States
This article analyzes variation in the degree to which states have responded to the devolution of welfare at the federal level by devolving authority over welfare policy to local government. I find that to the extent that states have devolved authority to lower levels of government, they tend to be states that already had a high degree of involvement of local government in welfare provision. In states without this record of local government involvement, the devolution that has occurred has not generated greater involvement of local government, but rather responsibility has been devolved to regional entities with ties to workforce development and with a substantial degree of business involvement. As states gain increasing authority over a redistributive policy, they may begin to treat it as a subset of a larger developmental policy—workforce development.