Qualifier Adjustment
PMI
To optimize the PMI level, consider data acquired in the mode of (H+V) in PPP processing.
Having first optimized the previous four Doppler qualifiers, inspect echo classification data of
DB_HCLASS and seek for gates declared as “NoMet”, which are unlikely of meteorological
origin. These bins may appear as “NoMet” data in your display, or DB_HCLASS data might be
readily thresholded, depending on your color scales and the HydroClass configuration. In
order to get the other data types thresholded in the same fashion, activate PMI as a
thresholding mechanism in task configuration. The PMI threshold value to 0.45 implies the
same strength of suppression to other selected data types as seen in DB_HCLASS. It is
possible to recover more precipitation data, typically at edges of precipitation and the most
far echoes (virga) by reducing the PMI threshold, as appropriate. In these customizations, the
behavior of DB_HCLASS remains unchanged.
Secondary SQI Threshold
When thresholding dual pol, dBZ, and dBT reflectivity data with SQI , the comparison value
for accepting those data is the secondary SQI threshold that is defined in a slope and
oset from the primary user value. See 5.2.3 Mf — Clutter Filters (page 104).
The secondary threshold is more permissive (lower valued), and is traditionally used to
qualify LOG data only in the Random Phase processing mode.
The secondary SQI threshold is applied uniformly in all processing modes when dual pol or
reflectivity data are specified as being thresholded by SQI.
This gives you more freedom in applying an SQI threshold to your LOG data, because the
cuto value for dual pol and reflectivity can be chosen independently from the cuto value
for the other Doppler parameters. The full SQI test would not normally be applied to LOG
data, because of the so-called "black hole" problem, which is the loss of LOG data within
regions of high shear, even though, for instance, the
reflectivity itself was strong. You can
experiment with applying a secondary SQI threshold to help clean up the LOG data,
without introducing any
significant black holes.
7.5.3
Speckle Filter Processing
A speckle filter is a final pass over each output ray, in which isolated, single bins of velocity,
width, or intensity are removed.
There are two speckle removers in RVP900:
• 1D single-ray speckle filter (default)—This is used for any output parameter.
• 2D 3x3 speckle filter—If enabled, this is used for any output parameter.
This eliminates single pixel speckles, which allows the thresholds to be reduced for greater
sensitivity with fewer false alarms (speckles).
Both speckle filters remove isolated data points that are likely to be noise, interference,
aircraft, birds, or other point targets. Meteorological targets typically occupy multiple range
bins, so they are not
aected by the speckle filters. The benefits of using a speckle filter are:
• Displays look "cleaner" to observers
• Thresholds can be set slightly more sensitive without increasing the number of noise
pixels
RVP900 User Guide M211322EN-J
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