Clutter Mitigation, Multiple Peaks, and High-Order Spectral Moments in 35-GHz Vertically Pointing Radar Velocity Spectra

Williams, C. R.; Maahn, Maximilian; Hardin, Joseph; Boer, Gijs de

doi:10.5194/amt-2018-66

Cited by 2 publications

(2 citation statements)

References 27 publications

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“…Once the "clean" Doppler spectra are obtained, a Multipeaks Picking Procedure (MPP) is used (see e.g. [11,30,40]) to identify at most three peaks for each range gate as the averaged spectra may still contain some ground-clutter and flyers echoes in addition to the atmospheric signal. Selection of one single peak would therefore lead to wrong estimates as non-atmospheric echoes may remain after the SAM processing.…”

Section: Atmospheric Doppler Spectrummentioning

confidence: 99%

Rapid Scale Wind Profiling with Autoregressive Modeling and L-Band Doppler Radar

Domps¹,

Marmain²,

Guérin³

2021

Preprint

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Radar Wind Profilers (RWP) are well-established instruments for the probing of the atmospheric boundary layer, with the immense advantage of long-range and allweather operation capability. One of their main limitations, however, is a relatively long integration time compared to other instruments such as lidars. In the context of L-band RWP we show that the use of Autoregressive (AR) modeling for the antenna signals combined with the Maximum Entropy Method (MEM) allows for a correct estimation of radial wind velocity profiles even with very short time samples. A systematical analysis of performance is made with the help of synthetic data. These numerical results are further confirmed by an experimental dataset acquired near the landing runways of Paris Charles de Gaulle (CDG) Airport, France, and validated using a colocated optical lidar at the Aerological station of Payerne, Switzerland. It is found that the AR-MEM approach can successfully derive reliable wind estimates using integration times as short as 2.5 s where the classical spectral approach can barely provide any measurement. In addition, the technique helps mitigating the impact of uncooperative flyers in the processing of the atmospheric echo, leading to a more successful application of the wind estimation algorithm.

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Section: Atmospheric Doppler Spectrummentioning

confidence: 99%

Rapid Scale Wind Profiling with Autoregressive Modeling and L-Band Doppler Radar

Domps¹,

Marmain²,

Guérin³

2021

Preprint

View full text Add to dashboard Cite

show abstract

“…Increasingly sophisticated methods to identify and remove insect clutter have been developed (see e.g. Kalapureddy et al, 2018; Luke et al, 2008; Williams et al, 2018, 2021). Generally, these algorithms delineate range gates containing insects, clouds, an insect/cloud mix or precipitation.…”

Section: Introductionmentioning

confidence: 99%

Using cloud radar to investigate the effect of rainfall on migratory insect flight

et al. 2022

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1. The fate of migrating insects that encounter rainfall in flight is a critical consideration when modelling insect movement, but few field observations of this common phenomenon have ever been collected due to the logistical challenges of witnessing these encounters. Operational cloud radars have been deployed around the world by meteorological agencies to study precipitation physics, and as a byproduct, provide a rich database of insect observations that is freely available to researchers. Although considered unwanted 'clutter' by the meteorologists who collect the data, the analysis method presented here enables ecologists to delineate co-occurring signals from insects and raindrops.2. We present a method that uses image processing techniques on cloud radar velocity spectra to examine the fate of migrating insects when they encounter precipitation. By analysing velocity spectra, we can distinguish flying insects from falling rain and compare the relative density of insects in flight before, during and after the rainfall. We demonstrate the method on a case of insect migration in Oklahoma, USA.3. Using this method, we show the first reconstructed images of migrating insect layers in flight during rainfall. Our analysis shows that mild to moderate rainfall diminishes the number of insects aloft but does not cause full termination of migratory flight, as has previously been suggested.4. We hope this technique will spur further investigations of how changing weather conditions impact insect migration, and enable some of the first of such studies in regions of the world that are underrepresented in the literature.

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Clutter Mitigation, Multiple Peaks, and High-Order Spectral Moments in 35-GHz Vertically Pointing Radar Velocity Spectra

Cited by 2 publications

References 27 publications

Rapid Scale Wind Profiling with Autoregressive Modeling and L-Band Doppler Radar

Rapid Scale Wind Profiling with Autoregressive Modeling and L-Band Doppler Radar

Using cloud radar to investigate the effect of rainfall on migratory insect flight

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