Improved Radar Composites and Enhanced Value of Meteorological Radar Data Using Different Quality Indices

Abstract

Radar measurements are inherently affected by various meteorological and non-meteorological factors that may lead to a degradation of their quality, and the unwanted effects are also transferred into composites, i.e., overlapping images from different radars. The paper was aimed at answering the research question whether we could create ‘cleaner’ radar composites without disturbing features, and if yes, how the operational practice could take advantage of the improved results. To achieve these goals, the qRad and qPrec software packages, based on the concept of quality indices, were used. The qRad package estimates the true quality of the C-band radar volume data using various quality indices and attempts to correct some of the adverse effects on the measurements. The qPrec package uses a probabilistic approach to estimate precipitation intensity, based on heterogeneous input data and quality-based outputs of the qRad software. The advantages of the qRad software are improved radar composites, which offer benefits, among others, for aviation meteorology. At the same time, the advantages of the qPrec software are manifested through improved quantitative precipitation estimation, which can be translated into hydrological modeling or climatological precipitation mapping. Beyond this, the developed software indirectly contributes to sustainability and environmental protection—for instance, by enabling fuel savings due to the more effective planning of flight routes or avoiding runway excursions due to information on the increased risk of aquaplaning.

Accuracy of radar-estimated precipitation in a mountain catchment in Slovakia

“…The radar-based precipitation product used in our study was derived from the network of four C-band, dual-polarized Selex-Gematronik Meteor 735 CDP10 weather radars of the Slovak Hydrometeorological Institute and computed by the qRad and qPrec software packages developed at the Slovak Hydrometeorological Institute (Méri et al, 2021). The qRad software estimates the actual quality of the radar volume data by various quality indices and corrects some undesirable effects on the measurement (e.g., beam-blockage, ground-clutter, nonmeteorological echoes).…”

“…This can lead to over -or under estimation in some sub-areas of the domain. The calibrated input data fields are combined according to their precision and actual quality (Méri et al, 2021). The main limiting factors of radar measurements in mountainous areas are the beam-blockage and ground clutter with its possible removal from the reflectivity values by the radar software.…”

Improvement in algorithms for quality control of weather radar data (RADVOL-QC system)

“…The quantity called quality index (QI) plays an increasingly important role in quality control of weather radar data (e.g. Einfalt et al, 2010;Michelson et al, 2021) as it provides quantitative information on the quality of data but can also be used to generate more reliable individual products (Ośródka and Szturc, 2015) to produce composite maps (Fornasiero et al, 2006;Sandford and Gaussiat, 2012;Jurczyk et al, 2020a) or QPE based on multi-source information (Jatho et al, 2010;Jurczyk et al, 2020b;Méri et al, 2021).…”

“…Huge effort to resolve quality-related issues in radar observations has been made by various international research programmes, such as COST-717 (Michelson et al, 2005) and COST-731 (Rossa et al, 2010), EUMETNET OPERA (Huuskonen et al, 2014;Saltikoff et al, 2019), the BALTRAD project (Michelson et al, 2018), and others.…”

“…Different QC systems are designed to suit specific local conditions and are implemented in individual national meteorological services, e.g. ROPO in Finland (Peura, 2002); NMQ in NOAA, USA (Zhang et al, 2012); RADVOL-QC in Poland (Ośródka et al, 2014); qRad in Slovakia (Méri et al, 2021).…”