Geoscience Reference
In-Depth Information
12
Quality Control Algorithms
Applied on Weather Radar Reflectivity Data
Jan Szturc, Katarzyna Ośródka and Anna Jurczyk
Institute of Meteorology and Water Management - National Research Institute
Poland
1. Introduction
Quality related issues are becoming more and more often one of the main research fields
nowadays. This trend affects weather radar data as well. Radar-derived precipitation data
are burdened with a number of errors from different sources (meteorological and technical).
Due to the complexity of radar measurement and processing it is practically impossible to
eliminate these errors completely or at least to evaluate each error separately (Villarini &
Krajewski, 2010). On the other hand, precise information about the data reliability is
important for the end user.
The estimation of radar data quality even as global quantity for single radar provides very
useful and important information (e.g. Peura et al., 2006). However for some applications,
such as flash flood prediction, more detailed quality information is expected by hydrologists
(Sharif et al., 2004; Vivoni et al., 2007, Collier, 2009). A quality index approach for each radar
pixel seems to be an appropriate way of quality characterization (Michelson et al., 2005;
Friedrich et al., 2006; Szturc et al., 2006, 2008a, 2011). As a consequence a map of the quality
index can be attached to the radar-based product.
2. Sources of radar data uncertainty
There are numerous sources of errors that affect radar measurements of reflectivity volumes
or surface precipitation, which have been comprehensively discussed by many authors (e.g.
Collier, 1996; Meischner 2004; Šálek et al., 2004; Michelson et al., 2005).
Hardware sources of errors are related to electronics stability, antenna accuracy, and signal
processing accuracy (Gekat et al., 2004). Other non-meteorological errors are results of
electromagnetic interference with the sun and other microwave emitters, attenuation due to a
wet or snow (ice) covered radome, ground clutter (Germann & Joss, 2004), anomalous
propagation of radar beam due to specific atmosphere temperature or moisture gradient
(Bebbington et al., 2007), and biological echoes from birds, insects, etc. Next group of errors is
associated with scan strategy, radar beam geometry and interpolation between sampling points,
as well as the broadening of the beam width with increasing distance from the radar site.
Moreover the beam may be blocked due to topography (Bech et al., 2007) and by nearby objects
like trees and buildings, or not fully filled when the size of precipitation echo is relatively small or
the precipitation is at low altitude in relation to the antenna elevation (so called overshooting).
