Technical a Gaussian Mixture Model to Separate Birds and Insects in Single-Polarization Weather Radar Data

Recent and archived data from weather radar networks are extensively used for the quantification of continent-wide bird migration patterns. While the process of discriminating birds from weather signals is well established, insect contamination is still a problem. We present a simple method combining two Doppler radar products within a Gaussian mixture model to estimate the proportions of birds and insects within a single measurement volume, as well as the density and speed of birds and insects. This method can be applied to any existing archives of vertical bird profiles, such as the European Network for the Radar surveillance of Animal Movement repository, with no need to recalculate the huge amount of original polar volume data, which often are not available.

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A simple method to separate birds and insects in single-pol weather radar data

10.1101/2021.03.08.434434 ◽

2021 ◽

Cited By ~ 1

Author(s):

Raphaël Nussbaumer ◽

Baptiste Schmid ◽

Silke Bauer ◽

Felix Liechti

Keyword(s):

Bird Migration ◽

Doppler Radar ◽

Weather Radar ◽

Gaussian Mixture ◽

Radar Data ◽

Volume Data ◽

Huge Amount ◽

Single Measurement ◽

Simple Method ◽

Radar Networks

AbstractRecent and archived data from weather radar networks are extensively used for quantification of continent-wide bird migration pattern. While discriminating birds from weather signals is well established, insect contamination is still a problem. We present a simple method combining two doppler radar products within a single Gaussian-mixture model to estimate the proportions of birds and insects within a single measurement, as well as the density and speed of birds and insects. The method can be applied to any existing archives of vertical bird profiles, such as the ENRAM repository (enram.eu) with no need to recalculate the huge amount of original polar volume data, which often are not available.

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Real-Time Detection and Filtering of Chaff Clutter from Single-Polarization Doppler Radar Data

Journal of Atmospheric and Oceanic Technology ◽

10.1175/jtech-d-12-00158.1 ◽

2013 ◽

Vol 30 (5) ◽

pp. 873-895 ◽

Cited By ~ 19

Author(s):

Yong Hyun Kim ◽

Sungshin Kim ◽

Hye-Young Han ◽

Bok-Haeng Heo ◽

Cheol-Hwan You

Keyword(s):

Real Time ◽

Doppler Radar ◽

Meteorological Data ◽

Three Dimensional ◽

Weather Radar ◽

Cost Effective ◽

Radar Data ◽

Control Procedure ◽

South Korean ◽

Single Polarization

Abstract In countries with frequent aerial military exercises, chaff particles that are routinely spread by military aircraft represent significant noise sources for ground-based weather radar observation. In this study, a cost-effective procedure is proposed for identifying and removing chaff echoes from single-polarization Doppler radar readings in order to enhance the reliability of observed meteorological data. The proposed quality control procedure is based on three steps: 1) spatial and temporal clustering of decomposed radar image elements, 2) extraction of the clusters’ static and time-evolution characteristics, and 3) real-time identification and removal (or censoring) of target echoes from radar data. Simulation experiments based on this procedure were conducted on site-specific ground-echo-removed weather radar data provided by the Korea Meteorological Administration (KMA), from which three-dimensional (3D) reflectivity echoes covering hundreds of thousands of square kilometers of South Korean territory within an altitude range of 0.25–10 km were retrieved. The algorithm identified and removed chaff clutter from the South Korean data with a novel decision support system at an 81% accuracy level under typical cases in which chaff and weather clusters were isolated from one another with no overlapping areas.

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