The NCAR airborne 94-GHz cloud radar: calibration and data processing

Abstract

The 94-GHz airborne HIAPER Cloud Radar (HCR) has now been deployed in three major field campaigns. NCAR has developed an extensive set of quality assurance and quality control procedures which are applied to all collected data.Engineering measurements performed both in the laboratory and in an antenna measurement chamber yielded calibration characteristics for the antenna, reflector, and radome. These calibration results are applied during flight, to produce the radar moments available in real-time. However, temperature changes in the instrument during flight affect the receiver gains, leading to some bias in the calibration values applied in real time. Post project, we estimate the temperature -induced gain errors and apply gain corrections to improve the quality of the final data set. In addition, the reflectivity calibration is monitored by comparing sea surface cross section measurements against theoretically -calculated model values. These comparisons confirm that HCR is calibrated to within 1 dB of the theory. A radar echo classification algorithm was developed to identify "cloud echo" and distinguish it from artifacts such as the echo from the surface, transmitter leakage , and a number of other categories.Model reanalysis data and digital terrain eleva tion data were interpolated to the radar time-range grid of the radar data, to provide an environmental reference. These fields were used for the sea surface calibration and also are made available as an aid for scientific research.

Melting Layer Detection and Observation with the NCAR Airborne W-Band Radar

“…In addition to the Doppler radar fields, such as DBZ, VEL, and LDR, reanalysis data from the ERA5 model, which have been interpolated to the HCR time-range grid via linear interpolation in four dimensions (three space and the time dimension), are also provided. For a detailed description of HCR data, data processing, and quality control, see [2]. The variables used in the melting layer detection algorithm are DBZ, LDR, VEL, spectrum width (WIDTH), and the FLAG field, which discriminates between cloud echo and other echo types [2].…”

“…For a detailed description of HCR data, data processing, and quality control, see [2]. The variables used in the melting layer detection algorithm are DBZ, LDR, VEL, spectrum width (WIDTH), and the FLAG field, which discriminates between cloud echo and other echo types [2]. The 0 • C isotherm of the interpolated ERA5 temperature field (TEMP) is used as a first estimate of the melting layer altitude and for comparison with the resulting melting layer product.…”

“…It appears at a radar range equal to twice the height of the aircraft above the surface, and it recedes and approaches in range as the aircraft ascends or descends. A mechanism to detect the back-lobe echo was developed by [2], but because the LDR of the back-lobe echo strongly resembles the characteristics of the melting layer, the thresholds used by [2] were tightened to remove the echo more aggressively. We reject data where DBZ is less than −18 dBZ (as opposed to −20 dBZ in [2]) and WIDTH is greater than 1 m s −1 (1.4 m s −1 ).…”

“…A mechanism to detect the back-lobe echo was developed by [2], but because the LDR of the back-lobe echo strongly resembles the characteristics of the melting layer, the thresholds used by [2] were tightened to remove the echo more aggressively. We reject data where DBZ is less than −18 dBZ (as opposed to −20 dBZ in [2]) and WIDTH is greater than 1 m s −1 (1.4 m s −1 ). These new thresholds successfully identified the majority of the back-lobe echo, except for a few cases which will be discussed in Section 3.5.…”

“…One of the instruments deployed by EOL on the NSF/NCAR High-performance Instrumented Airborne Platform for Environmental Research (HIAPER) Gulfstream V aircraft is the HIAPER Cloud Radar (HCR, [1]), a 94 GHz W-band radar. Since 2015, HCR standard radar data products from three major field campaigns have been released to the scientific community [2]. The HCR team is committed to developing new data products to assist scientists in accomplishing their research goals and to increase the benefit of HCR data to the scientific community.…”