FEATURES AND FIRST EXPERIENCE OF CALIBRATING W-BAND METEOROLOGICAL RADARS USING LASER DISDROMETER DATA
DOI:
https://doi.org/10.18372/2310-5461.68.20736Keywords:
radar system, meteorological radar, millimeter-wave radars, radar reflectivity, scattering, signal processing, calibration, resonant scatteringAbstract
Calibration of weather radars remains a significant challenge in radar meteorology when it comes to quantitative measurements. While traditional methods have proven themselves well for radars operating at centimeter wavelengths, the advent of millimeter-wave cloud radars, especially at W-band frequencies, poses unique calibration challenges. This is primarily due to the differences in the scattering of the sounding signal by hydrometeors, when the wavelength becomes of the same order as the diameters of the scatterers and instead of a simple Rayleigh model, it is necessary to switch to resonant scattering models. Another significant problem is the strong attenuation of millimeter waves in both precipitation and atmospheric gases. This work explores the numerous subtleties of W-band cloud radars and evaluates viable calibration strategies to ensure accurate measurements. The emphasis is on a calibration approach using disdrometer rain data, in particular the distribution of drops in both size and ground-level droplet velocity. Similar calibration approaches are expected for use in European W-band cloud radars that provide data to ACTRIS, a European research infrastructure dedicated to the observation of short-range atmospheric components such as aerosols, clouds and gases, and the study of their interactions. In this paper, synchronous data from a mobile weather station are used as additional information needed to implement algorithms for comparing and fusing radar and disdrometer data. Key aspects of the methodology are outlined, implemented in a research software tool, and demonstrated. This software tool has the potential to be extended to facilitate the comparison of additional Doppler moments and spectra using disdrometer and cloud radar inputs. Illustrative examples are provided demonstrating the capabilities of the software for comprehensive analysis of radar reflectivity, Doppler spectra, and other meteorological parameters, including their statistics, thereby improving the calibration process.
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