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
Statistical Quality of Spectral Polarimetric Variables for Weather Radar
AbstractSpectral polarimetry for weather radar capitalizes on both Doppler and polarimetric measurements to reveal polarimetric variables as a function of radial velocity through spectral analysis. For example, spectral differential reflectivity at a velocity represents the differential reflectivity from all the scatterers that have the same radial velocity of interest within the radar resolution volume. Spectral polarimetry has been applied to suppress both ground and biological clutter, retrieve individual drop size distributions from a mixture of different types of hydrometeors, and estimate turbulence intensity, for example. Although spectral polarimetry has gained increasing attention, statistical quality of the estimation of spectral polarimetric variables has not been investigated. In this work, the bias and standard deviation (SD) of spectral differential reflectivity and spectral copolar correlation coefficient estimated from averaged spectra were derived using perturbation method. The results sh...
Atmospheric drag effects on the KOMPSAT-1 satellite during geomagnetic superstorms
We examine the atmospheric drag on the low earth-orbiting satellite, KOMPSAT-1 in a sun-synchronous orbit at ~685-km altitude starting in 1999, during a 3-month (October-December) period in 2003. This 3-month interval includes the October 29-30 and November 20 magnetic superstorms and weak to moderate storms. We observed that the daily KOMPSAT-1 drag acceleration transiently responses to transient storm-time disturbances. That is, there is an one-to-one correspondence between the KOMPSAT-1 drag accelerations and the storm events. We find that the drag acceleration correlates strongly with the level of geomagnetic disturbance. This indicates that the trajectory of KOMPSAT-1 is significantly perturbed during extremely disturbed intervals because of atmospheric density increase. The main contributor to the density increase is Joule heating associated with the geomagnetic activity rather than the solar EUV radiation, as reported by previous studies. We suggest that understanding how the upper atmosphere responses to the geomagnetic-associated heating is important to predict space weather impacts on low earth-orbiting satellites.