Articles | Volume 16, issue 9
https://doi.org/10.5194/amt-16-2381-2023
https://doi.org/10.5194/amt-16-2381-2023
Research article
 | 
09 May 2023
Research article |  | 09 May 2023

Calibrating radar wind profiler reflectivity factor using surface disdrometer observations

Christopher R. Williams, Joshua Barrio, Paul E. Johnston, Paytsar Muradyan, and Scott E. Giangrande

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Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2022-1405', Anonymous Referee #1, 12 Feb 2023
    • AC1: 'Reply on RC1', Christopher Williams, 21 Mar 2023
  • RC2: 'Comment on egusphere-2022-1405', Anonymous Referee #2, 27 Feb 2023
    • AC2: 'Reply on RC2', Christopher Williams, 21 Mar 2023
  • RC3: 'Comment on egusphere-2022-1405', Anonymous Referee #3, 06 Mar 2023
    • AC3: 'Reply on RC3', Christopher Williams, 21 Mar 2023

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Christopher Williams on behalf of the Authors (21 Mar 2023)  Author's response   Author's tracked changes   Manuscript 
ED: Publish as is (24 Mar 2023) by Stefan Kneifel
AR by Christopher Williams on behalf of the Authors (05 Apr 2023)  Manuscript 
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Short summary
This study uses surface disdrometer observations to calibrate 8 years of 915 MHz radar wind profiler deployed in the central United States in northern Oklahoma. This study had two key findings. First, the radar wind profiler sensitivity decreased approximately 3 to 4 dB/year as the hardware aged. Second, this drift was slow enough that calibration can be performed using 3-month intervals. Calibrated radar wind profiler observations and Python processing code are available on public repositories.