The NCAR Airborne 94-GHz Cloud Radar: Calibration and Data Processing

Ulrike Romatschke, Michael Dixon, Peisang Tsai, Eric Loew, Jothiram Vivekanandan, Jonathan Emmett and Robert Rilling
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Ulrike Romatschke: Earth Observing Laboratory, National Center for Atmospheric Research (NCAR), Boulder, CO 80301, USA
Michael Dixon: Earth Observing Laboratory, National Center for Atmospheric Research (NCAR), Boulder, CO 80301, USA
Peisang Tsai: Earth Observing Laboratory, National Center for Atmospheric Research (NCAR), Boulder, CO 80301, USA
Eric Loew: Earth Observing Laboratory, National Center for Atmospheric Research (NCAR), Boulder, CO 80301, USA
Jothiram Vivekanandan: Earth Observing Laboratory, National Center for Atmospheric Research (NCAR), Boulder, CO 80301, USA
Jonathan Emmett: Earth Observing Laboratory, National Center for Atmospheric Research (NCAR), Boulder, CO 80301, USA
Robert Rilling: Earth Observing Laboratory, National Center for Atmospheric Research (NCAR), Boulder, CO 80301, USA

Data, 2021, vol. 6, issue 6, 1-25

Abstract: The 94-GHz airborne HIAPER Cloud Radar (HCR) has been deployed in three major field campaigns, sampling clouds over the Pacific between California and Hawaii (2015), over the cold waters of the Southern Ocean (2018), and characterizing tropical convection in the Western Caribbean and Pacific waters off Panama and Costa Rica (2019). An extensive set of quality assurance and quality control procedures were developed and applied to all collected data. Engineering measurements yielded calibration characteristics for the antenna, reflector, and radome, which were applied during flight, to produce the radar moments in real-time. Temperature changes in the instrument during flight affect the receiver gains, leading to some bias. Post project, we estimate the temperature-induced gain errors and apply gain corrections to improve the quality of the data. The reflectivity calibration is monitored by comparing sea surface cross-section measurements against theoretically calculated model values. These comparisons indicate that the HCR is calibrated to within 1–2 dB of the theory. A radar echo classification algorithm was developed to identify “cloud echo” and distinguish it from artifacts. Model reanalysis data and digital terrain elevation data were interpolated to the time-range grid of the radar data, to provide an environmental reference.

Keywords: radar; cloud physics; reflectivity; radial velocity (search for similar items in EconPapers)
JEL-codes: C8 C80 C81 C82 C83 (search for similar items in EconPapers)
Date: 2021
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