1. Create 3D CAPPI products of radial velocity for the 2 radars in the common projection
at the grid height spacing.
The horizontal resolution of the CAPPI products is subject to the following constraints:
• The resolution of the CAPPI pixels is set to be twice the spacing of the input radial
velocity data. For example, for 125-m (410 ft i in) input bins, the CAPPI resolution is
set to 250 m (820 ft 3 in).
• The number of CAPPI pixels for each output resolution grid element should be at
least 9 (3 × 3).
If this is not the case, then the resolution of the CAPPI is increased.
In the same example, if the output resolution were 2 km (1.2 mi) then per the 250-m
(820 ft 3 in) pixel spacing in (1) there would be 8 × 8 = 32 pixels for each output grid
point.
• The maximum number of pixels in the CAPPI is 1100 × 1100. The CAPPI is clipped at
this value.
For a 40 km (24.9 mi) range span (80 km (49.7 mi) total across the output array),
there would be (4 pixels/km)*80 (km) = 320 pixels in the CAPPI (320 × 320 for a
square projection).
2. The data from the radial velocity CAPPI products are processed with the multiple
Doppler algorithms to obtain a grid of (x,y) wind vectors at the original CAPPI
resolution (for example, 320 × 320).
3. The high-density wind vectors are averaged to reduce the data to the final output grid.
Continuing the example, with 4 pixels per km in the CAPPI and a an output resolution
of 2 km (1.2 mi), we would average 8 × 8 = 32 wind vectors for each output grid point.
4. To eliminate noise and speckle eects, a grid point is thresholded if there are fewer
than 3 values to average or less than 25 % coverage.
In the example, the 25 % would correspond to 8 wind estimates.
When the vector averages are computed, a Wind Quality Index (WQI) is also calculated and
stored with the data. This is used for thresholding when the product is displayed.
The WQI is computed from the variances #sigma#
2
x
and¨#sigma#
2
y
of the individual
components of each (x,y) wind vector that is computed from the CAPPI data. For every
CAPPI velocity pair that contributes to the final X and Y wind, the 2 variance terms are also
computed so that WQI can be derived as:
WQI = 1.0 −
σ
x
2
+ σ
y
2
2
/V
norm
where
V
norm
V
norm
is a normalization term, and is the standard deviation that would result if
uniformly distributed random vectors at half the Nyquist velocity were input to the
algorithm, that is, that case would produce a WQI of 0.
V
norm
=
V1
u
+ V2
u
2
/2 2
where
V1
u
and
V2
u
are the Nyquist velocities for the two CAPPI input products.
WQI is set to 0 if the above calculation yields a negative number. Zero corresponds to a
terrible fit among the dual Doppler winds that are averaged into each output grid; and 1.0
corresponds to perfect agreement of all the data.
Chapter 5 – Configuring and Scheduling Optional IRIS Products
RESTRICTED 175
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