Quality index scheme for quantitative uncertainty characterization of radar‐based precipitation

Abstract

A quality index scheme is proposed which is designed to evaluate the quality of different radar-derived rainfall products including processed radar data and precipitation accumulations. The idea of the quality index scheme is based on selection of quality factors, determination of their quality indices and computation of one final quality index. The factors were selected depending on the particular kind of precipitation field. In the proposed scheme the quality index for each quality factor is determined using regression relationships between quality factors and data errors calculated from rain gauge -radar observation differences. Finally, all the individual quality indices are summarized to a final quality index applying appropriate weights. The quality index is computed for each pixel of radar-derived precipitation field independently. The quality information field obtained in this way is attached to the radar-based precipitation product and can be used to generate the precipitation field as percentiles of probability density functions.

Definition and impact of a quality index for radar-based reference measurements in the H-SAF precipitation product validation

“…Friedrich et al, 2006;Szturc et al, 2011). The algorithm here presented is based mainly on already assessed techniques, but introduces also some new approaches.…”

Precipitation accumulation analysis – assimilation of radar-gauge measurements and validation of different methods

“…In order to investigate the error dependencies between radar and gauges, we use an indicator that describes the hy- drological aspects of the errors (Szturc et al, 2011), namely, the absolute difference between observed and analyzed precipitation accumulation as a function of the magnitude of the observed value (i.e. gauge data).…”

Quality Control Algorithms Applied on Weather Radar Reflectivity Data

“…Moreover non-precipitation echoes, such as ground clutter, are often characterized by high variability that differs from that for stratiform precipitation echoes. Spatial variability can be quantified as 3-D reflectivity gradient or standard deviation in a certain spatial grid (Szturc et al, 2011) and should be taken into account in quality index determination.…”

“…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, 2006Szturc et al, , 2008aSzturc et al, , 2011. As a consequence a map of the quality index can be attached to the radar-based product.…”