Application of Dual-Polarization Radar Melting-Layer Detection Algorithm

Abstract

A polarimetric melting-layer detection algorithm developed for an S-band radar has been modified for use by the King City C-band radar in southern Ontario, Canada. The technique ingests radar scan volume data to determine the melting-layer top and bottom and to diagnose temporal and spatial variations of the meltinglayer heights. The thickness of the melting layer is also derived from the algorithm. Detailed case studies of two frontal systems over this region are described, comparing the radar-derived melting-layer height with aircraft measurement of the height of the 08C isotherm. The analysis demonstrated the ability to detect rapidly changing melting-layer heights during frontal passages in the region. A range of melting-layer heights for a 3-yr period was investigated and produced detections from close to the ground up to about 5.0 km. Comparison of algorithm results to output from a numerical weather prediction model over the 3-yr period showed good agreement. The correlation coefficient of the heights of the 08C wet-bulb temperature with the radar-derived melting-layer tops was 0.96. The time series of the algorithm output was used to detect frontal passages and showed that the algorithm should be useful for approximately 19 frontal passages per year in this region.

Rain or snow: hydrologic processes, observations, prediction, and research needs

“…Mixed-phase events, however, are difficult to quantify using coupled depth-and photographic-based techniques (Floyd and Weiler, 2008). Acoustic distance sensors, which are now commonly used to monitor the accumulation of snow (e.g., Boe, 2013), have similar drawbacks in mixed-phase events, but have been effectively applied to discriminate between snow and rain (Rajagopal and Harpold, 2016). Meteorological information such as temperature and relative humidity can be used to compute the phase of precipitation measured by bucket-type gauges.…”

“…Unlike warm-season convective precipitation, the freezing level during a cold-season precipitation event can vary spatially. This phenomenon has prompted the use of polarimetric variables to first detect the melting layer, and then classify hydrometeors (Boodoo et al, 2010;Thompson et al, 2014). Although there has been some success in developing two-stage cold-season hydrometeor classification algorithms, there is little in the published literature that explores the potential contributions of these algorithms for partitioning snow and rain for hydrological modeling.…”

A Dual-Polarization Radar Hydrometeor Classification Algorithm for Winter Precipitation

“…Melting-layer classification on these wet snow pixels with relatively high SNR (.10 dB) is handled with the same general methodology presented by Giangrande et al (2008) to account for variable meltinglayer heights in each 108 azimuthal sector of a PPI or for a single RHI. Following the methodology of Giangrande et al (2008) and Boodoo et al (2010), the melting-layer top, median, and base are defined by the heights (AGL) below which 80%, 50%, and 20%, respectively, of all wet snow gates reside in each sector. Only wet snow pixels between the 5-35-km range are used to determine these melting-layer (ML) height statistics to avoid nonuniform beam filling (Ryzhkov 2007), other sampling errors that degrade the quality of polarimetric variables at extremely close and far ranges, and any substantial beam ascent with range.…”

“…This is not the case for winter precipitation though, which motivates use of a polarimetric radar-based melting-layer detection algorithm to identify wet or melting snow and then inform additional classification steps below and above this radar brightband layer (Giangrande et al 2008;Boodoo et al 2010).…”

Measuring Snow with Weather Radar

“…In a modern weather radar service, the overestimation is corrected using knowledge of the vertical profile of reflectivity (Koistinen et al, 2003). Recently, Giangrande et al (2005) and Boodoo et al (2010) have shown, that the parameters of dual-polarization radars can be used effectively to follow the temporal and spatial variation of the melting layer height and thickness. This is especially important in cold and temperate climates, where much of precipitation is associated with fronts, because in frontal situations the temperature gradients are sharp.…”