Detecting the melting layer with a micro rain radar using a neural network approach

Abstract

A new method to determine the melting layer height using a micro rain radar (MRR) is presented. The MRR is a small vertically pointing frequency-modulated continuous-wave radar that 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 due to 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. To train the neural network, the melting layer height is determined manually. The neural network is trained and tested using data from two sites that cover all seasons. For most cases, the neural network is able to detect the correct melting layer height well. Sensitivity studies show that the neural network is able to handle different MRR settings. Comparisons to radiosonde data and cloud radar data show a good agreement with respect to the melting layer heights.