Abstract

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.

Highlights

  • The bright band in radar meteorology shows the location of the layer where solid precipitation melts into rain via a complex process

  • The thickness of the melting layer (ML) is influenced by the precipitation intensity in the training data, and the ML thickness detected by the neural network (NN) in the test data is influenced by the precipitation intensity

  • We have developed an NN to detect the ML from micro rain radar (MRR) data operationally

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Summary

Introduction

The bright band in radar meteorology shows the location of the layer where solid precipitation melts into rain via a complex process. The bright band has been detected since the beginning of radar meteorology in the 1940s (e.g., Byers and Coons, 1947), it is not yet fully understood. The detection of this layer is important for various applications, including the correction of precipitation estimation or the prediction of the kind of precipitation at the surface. The detection of the ML at airports can help assess the real-time and nearfuture risk of icing by providing information on where melting is currently taking place and where it has taken place in the near past, which can complement other measurements such as ground temperature

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