Development and validation of a supervised machine learning radar Doppler spectra peak-finding algorithm
<p>In many types of clouds, multiple hydrometeor populations can be present at the same time and height. Studying the evolution of these different hydrometeors in a time–height perspective can give valuable information on cloud particle composition and microphysical growth processes. However,...
Main Authors: | H. Kalesse, T. Vogl, C. Paduraru, E. Luke |
---|---|
Format: | Article |
Language: | English |
Published: |
Copernicus Publications
2019-08-01
|
Series: | Atmospheric Measurement Techniques |
Online Access: | https://www.atmos-meas-tech.net/12/4591/2019/amt-12-4591-2019.pdf |
Similar Items
-
Fingerprints of a riming event on cloud radar Doppler spectra: observations and modeling
by: H. Kalesse, et al.
Published: (2016-03-01) -
Evaluating cloud liquid detection against Cloudnet using cloud radar Doppler spectra in a pre-trained artificial neural network
by: H. Kalesse-Los, et al.
Published: (2022-01-01) -
Identifying cloud droplets beyond lidar attenuation from vertically pointing cloud radar observations using artificial neural networks
by: W. Schimmel, et al.
Published: (2022-09-01) -
peakTree: a framework for structure-preserving radar Doppler spectra analysis
by: M. Radenz, et al.
Published: (2019-09-01) -
Multiple peak processing algorithm for identification of atmospheric signals in Doppler radar wind profiler spectra
by: Thomas Griesser, et al.
Published: (1998-12-01)