| Popis: |
Accurate estimation of the Freezing Level (FL) is essential in radar rainfall estimation to mitigate the bright band enhancement, to classify hydrometeors, to correct for rain-attenuation and to calibrate radar measurements. Here we present a novel and robust FL estimation algorithm that can be applied to either Vertical Profiles (VPs) or Quasi-Vertical Profiles (QVPs) built from operational polarimetric weather radar scans. The algorithm depends only on data collected by the radar itself, and it is based on the detection of strong gradients within the profiles and relies on the combination of several polarimetric variables. The VPs and QVPs of ZH showed a good similarity in the profiles (r ≈ 0.7) even though the QVPs are built from low-elevation angles. The algorithm is applied to one year of rainfall events and validated using measured FLs from radiosonde data. The results demonstrated that combining the profiles of ZH, ΡHV and the gradient of the velocity V showed the best FL estimation performance when using VPs, whereas combining the profiles of ZH, ΡHV and ZDR showed the best FL estimation performance when using QVPs. The VP computed from the gradient of the velocity showed to be extremely valuable in the FL estimation when using VPs. The errors in the FL estimation using either VPs or QVPs are within 250 m. |
