| A large part of the research in the radar meteorology is devoted to the
evaluation of the radar data quality and to the radar data processing. Even
when, a set of absolute quality indexes can be produced (like as ground
clutter presence, beam blockage rate, distance from radar, etc.), the final
product quality has to be determined as a function of the task and of all
the processing steps.
In this paper the emphasis lies on the estimate of the rainfall at the
ground level taking extra care for the correction for ground clutter and
beam blockage, that are two main problems affecting radar reflectivity data
in complex orography. In this work a combined algorithm is presented that
avoids and/or corrects for these two effects. To achieve this existing
methods are modified and integrated with the analysis of radar signal
propagation in different atmospheric conditions. The atmospheric
refractivity profile is retrieved from the nearest in space and time
radiosounding. This measured profile is then used to define the `dynamic
map' used as a declutter base-field. Then beam blockage correction is
applied to the data at the scan elevations computed from this map.
Two case studies are used to illustrate the proposed algorithm.
One is a summer event with anomalous propagation conditions and the other one is a winter event.
The new algorithm is compared to a previous method of clutter
removal based only on static maps of clear air and vertical reflectivity
continuity test. The improvement in rain estimate is evaluated applying
statistical analysis and using rain gauges data. The better scores are
related mostly to the ``optimum" choice of the elevation maps, introduced by
the more accurate description of the signal propagation.
Finally, a data quality indicator is introduced as an output of this scheme.
This indicator has been obtained from the general scheme, which takes into
account all radar data processing steps. |