Preprints
https://doi.org/10.5194/egusphere-2026-3304
https://doi.org/10.5194/egusphere-2026-3304
12 Jun 2026
 | 12 Jun 2026
Status: this preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).

Estimating Beam Pointing of Vertically Pointing Cloud Radars Using Radiosonde Measurements

Min Deng, Scott Giangrande, Adam K. Theisen, Karen Johnson, Iosif A. Lindenmaier, Timothy G. Wendler, Jennifer Comstock, Marquette Rocque, Zeen Zhu, and Alyssa Matthews

Abstract. Accurate beam pointing is essential for vertically pointing cloud radars, as even small tilting off zenith introduces projections of horizontal wind into Doppler velocity measurements. These effects can bias the interpretation of vertical air motion and hydrometeor fall speeds, leading to systematic errors in cloud and precipitation retrievals.

We present a method to estimate and validate radar beam pointing angle using collocated radiosonde observations. When the radar beam is tilted, the observed Doppler velocity exhibits a cosine dependence on wind direction due to projection of horizontal wind onto the beam, with an amplitude proportional to wind speed. By normalizing Doppler velocity with horizontal wind speed, this geometric dependence can be isolated, enabling quantitative retrieval of off-zenith beam pointing estimation.

The method is applied to the Ka-band ARM Zenith Radar (KAZR) and the Marine W-band ARM Cloud Radar (MWACR) during the Cloud and Precipitation Experiment at kennaook (CAPE-k). Results show a clear wind-direction dependence consistent with small but measurable beam pointing offsets. Differences in Doppler velocity between KAZR and MWACR further reduce the influence of hydrometeor fall velocity and vertical air motion, providing an independent constraint on relative pointing errors. Application to KAZR observations at ARM fixed sites and recent field campaigns further demonstrates that the method is robust across a range of atmospheric conditions. This approach provides a practical and scalable tool for evaluating radar beam pointing using routinely available radiosonde data, with direct implications for improving the accuracy of ARM cloud and precipitation products.

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Min Deng, Scott Giangrande, Adam K. Theisen, Karen Johnson, Iosif A. Lindenmaier, Timothy G. Wendler, Jennifer Comstock, Marquette Rocque, Zeen Zhu, and Alyssa Matthews

Status: open (until 18 Jul 2026)

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Min Deng, Scott Giangrande, Adam K. Theisen, Karen Johnson, Iosif A. Lindenmaier, Timothy G. Wendler, Jennifer Comstock, Marquette Rocque, Zeen Zhu, and Alyssa Matthews
Min Deng, Scott Giangrande, Adam K. Theisen, Karen Johnson, Iosif A. Lindenmaier, Timothy G. Wendler, Jennifer Comstock, Marquette Rocque, Zeen Zhu, and Alyssa Matthews
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Latest update: 12 Jun 2026
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Short summary
Cloud radars are used to measure air motion, clouds, and precipitation, but small pointing errors can reduce their accuracy. We developed a method to detect these errors using routine weather balloon observations. Tests with several radar systems in different environments showed that the method can identify small but important pointing biases, helping improve the accuracy and long-term consistency of weather and climate observations.
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