Detecting the Melting Layer with a Micro Rain Radar Using a Neural Network Approach

Abstract

A new method using the Micro Rain Radar (MRR) to determine the melting layer height is presented. The MRR is a small vertically pointing frequency modulated continuous wave radar which measures Doppler spectra of precipitation. From these Doppler spectra, various variables such as Doppler velocity or spectral width can be derived. The melting layer is visible through a higher reflectivity and an acceleration of the falling particles, among others. These characteristics are fed to a neural network to determine the melting layer height. For the training of the neural network, the melting layer height is determined 5 manually. The neural network is trained and tested using data from two sites covering all seasons. For most cases, it is well able to detect the correct melting layer height. Sensitivity studies show that the neural network is able to handle different settings of the MRR. Comparisons to radiosonde data and cloud radar data show a good agreement in melting layer heights.