Abstract
Abstract. This study presents and applies three separate processing methods to improve high-order moments estimated from 35 GHz (Ka band) vertically pointing radar Doppler velocity spectra. The first processing method removes Doppler-shifted ground clutter from spectra collected by a US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program Ka-band zenith pointing radar (KAZR) deployed at Oliktok Point (OLI), Alaska. Ground clutter resulted from multiple pathways through antenna side lobes and reflections off a rotating scanning radar antenna located 2 m away from KAZR, which caused Doppler shifts in ground clutter returns from stationary targets 2.5 km away. After removing clutter in the recorded velocity spectra, the second processing method identifies multiple separate and sub-peaks in the spectra and estimates high-order moments for each peak. Multiple peaks and high-order moments were estimated for both original 2 and 15 s averaged spectra. The third processing step improves the spectrum variance, skewness, and kurtosis estimates by removing velocity variability due to turbulent broadening during 15 s averaging intervals. Applying the multiple peak processing to Doppler velocity spectra during liquid-only clouds can identify cloud and drizzle particles and during mixed-phase clouds can identify liquid cloud and frozen hydrometeors. Consistent with previous studies, this work found that spectrum skewness assuming only a single spectral peak was a good indicator of two hydrometeor populations (for example, cloud and drizzle particles) being present in the radar pulse volume. Yet, after dividing the spectrum into multiple peaks, velocity spectrum skewness for individual peaks is near zero, indicating nearly symmetric peaks. This suggests that future studies should use velocity skewness of single-peak spectra as an indicator of possible multiple hydrometeor populations and then use multiple-peak moments for quantitative studies. Three future activities will continue this work. First, KAZR spectra from several ARM sites have been processed and are available in the ARM archive as a principal investigator (PI) product. ARM programmers are evaluating these processing methods as part of future multiple-peak products generated by ARM. Third, MATLAB code generating the Oliktok Point products has been uploaded as supplemental material for public dissemination.
Highlights
Pointing radars operating in the Ka band (35 GHz) are important remote sensing instruments providing quantitative and high-resolution observations for studying the vertical structure and dynamics of clouds and precipitation (Görsdorf et al, 2015)
Pointing radars increase their sensitivity by transmitting multiple pulses and produce Doppler velocity spectra for each range gate and dwell
This study presents three separate methods to improve high-order moments estimated from Doppler spectra
Summary
Pointing radars operating in the Ka band (35 GHz) are important remote sensing instruments providing quantitative and high-resolution observations for studying the vertical structure and dynamics of clouds and precipitation (Görsdorf et al, 2015). In contrast to wind profilers, Ka-band cloud radars have significantly higher frequencies and very narrow beam widths (on the order of 0.3◦) such that Doppler velocity spectrum broadening due to horizontal motion through the radar beam is negligible (Shupe et al, 2008; Kollias et al, 2007). These narrow beam widths result in very narrow clutter peaks in the Kaband cloud radar velocity spectra with insects appearing as very narrow spectral peaks (Luke et al, 2008). The MATLAB code used to perform the analysis is available as supplemental material
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