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Applications of QC and Merged Doppler Spectral Density Data from Ka-Band Cloud Radar to Microphysics Retrieval and Comparison with Airplane in Situ Observation

1
State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100086, China
2
Hebei Weather Modification Center, Shijiazhuang 610225, China
3
Anhui Sun-Create Electronics Ltd. Co., Hefei 230088, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(13), 1595; https://doi.org/10.3390/rs11131595
Received: 15 May 2019 / Revised: 27 June 2019 / Accepted: 28 June 2019 / Published: 4 July 2019
(This article belongs to the Special Issue Remote Sensing of Clouds)
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Abstract

The new Chinese Ka-band solid-state transmitter cloud radar (CR) uses four operational modes with different pulse widths and coherent integration and non-coherent integration numbers to meet long-term cloud measurement requirements. The CR and an instrument-equipped aircraft were used to observe clouds and precipitation on the east side of Taihang Mountain in Hebei Province in 2018. To resolve the data quality problems caused by attenuation in the precipitation area; we focused on developing an algorithm for attenuation correction based on rain drop size distribution (DSD) retrieved from the merged Doppler spectral density data of the four operational modes following data quality control (QC). After dealiasing Doppler velocity and removal of range sidelobe artifacts; we merged the four types of Doppler spectral density data. Vertical air speed and DSD are retrieved from the merged Doppler spectral density data. Finally, we conducted attenuation correction of Doppler spectral density data and recalculated Doppler moments such as reflectivity; radial velocity; and spectral width. We evaluated the consistencies of reflectivity spectra from the four operational modes and DSD retrieval performance using airborne in situ observation. We drew three conclusions: First, the four operational modes observed similar reflectivity and velocity for clouds and low-velocity solid hydrometeors; however; three times of coherent integration underestimated Doppler reflectivity spectra for velocities greater than 2 m s−1. Reflectivity spectra were also underestimated for low signal-to-noise ratios in the low-sensitivity operational mode. Second, QC successfully dealiased Doppler velocity and removed range sidelobe artifacts; and merging of the reflectivity spectra mitigated the effects of coherent integration and pulse compression on radar data. Lastly, the CR observed similar DSD and liquid water content vertical profiles to airborne in situ observations. Comparing CR and aircraft data yielded uncertainty due to differences in observation space and temporal and spatial resolutions of the data. View Full-Text
Keywords: Doppler spectral density; attenuation correction; DSD and air vertical speed retrieval Doppler spectral density; attenuation correction; DSD and air vertical speed retrieval
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Liu, L.; Ding, H.; Dong, X.; Cao, J.; Su, T. Applications of QC and Merged Doppler Spectral Density Data from Ka-Band Cloud Radar to Microphysics Retrieval and Comparison with Airplane in Situ Observation. Remote Sens. 2019, 11, 1595.

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