Calibrating radar wind profiler reflectivity factor using surface disdrometer observations

Author:

Williams Christopher R.ORCID,Barrio Joshua,Johnston Paul E.,Muradyan PaytsarORCID,Giangrande Scott E.ORCID

Abstract

Abstract. This study uses surface disdrometer reflectivity factor estimates to calibrate the vertical and off-vertical pointing radar beams produced by an ultra high frequency (UHF) band radar wind profiler (RWP) deployed at the US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program Southern Great Plains (SGP) Central Facility in northern Oklahoma from April 2011 through July 2019. The methodology consists of five steps. First, the recorded Doppler velocity power spectra are adjusted to account for Nyquist velocity aliasing and coherent integration filtering effects. Second, the spectrum moments are calculated. The third step increases the signal-to-noise ratio (SNR) due to inflated noise power estimates during convective rain events that cause SNR to be biased low. The fourth step determines the RWP calibration constant for one radar beam (called the “reference” beam) by comparing uncalibrated RWP reflectivity factors at 500 m above the ground to 1 min resolution surface disdrometer reflectivity factors. The last step uses the calibrated reference beam reflectivity factor to calibrate the other radar beams during precipitation. There are two key findings. The RWP sensitivity decreased by approximately 3 to 4 dB yr−1 as the hardware aged. This drift was slow enough that the reference calibration constant can be estimated over 3-month intervals using episodic rain events. The calibrated moments are available on the DOE ARM data archive, and the Python processing code is available on public repositories.

Funder

Biological and Environmental Research

National Oceanic and Atmospheric Administration

Publisher

Copernicus GmbH

Subject

Atmospheric Science

Reference49 articles.

1. Angevine, W. M., Buhr, M. P., Holloway, J. S., Trainer, M., Parrish, D. D., MacPherson, J. I., Kok, G. L., Schillawski, R. D., and Bowlby, D. H.: Local meteorological features affecting chemical measurements at a North Atlantic coastal site, J. Geophys. Res., 101, 28935–28945, 1996.

2. Angevine, W. M., Grimsdell, A. W., McKeen, S. A., and Warnock, J. M.: Entrainment results from the Flatland boundary layer experiments, J. Geophys. Res., 103, 13689–13701, 1998.

3. ARM: Radar Wind Profiler (915RWPPRECIPMOM), 2011-03-22 to 2019-08-18, Southern Great Plains (SGP) Central Facility, Lamont, OK (C1), Compiled by Muradyan, P., Atmospheric Radiation Measurement user facility, ARM Data Center [data set], https://doi.org/10.5439/1025128, 1998a.

4. ARM: Radar Wind Profiler (915RWPPRECIPSPEC), 2011-03-22 to 2019-08-18, Southern Great Plains (SGP) Central Facility, Lamont, OK (C1), Compiled by Muradyan, P., Atmospheric Radiation Measurement user facility, ARM Data Center [data set], https://doi.org/10.5439/1025129, 1998b.

5. ARM: Radar Wind Profiler (915RWPWINDMOM), 2014-03-06 to 2019-03-10, Southern Great Plains (SGP) Central Facility, Lamont, OK (C1), Compiled by Muradyan, P., Atmospheric Radiation Measurement user facility, ARM Data Center [data set], https://doi.org/10.5439/1025136, 1998c.

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