Vaisala RVP900, User Manual, Page: 200 / 484

Implementation Example
GMAP has been extensively evaluated for use in the US WSR88D ORDA network up-grade
(Ice et al, 2004). They conclude that GMAP meets the ORDA requirements. Their study was
based on a built-in simulator that is provided as part of the RVP900 and the
Ascope utility.
The simulator allows users to construct Doppler spectra, process them and evaluate the
results (Sirmans and Bumgarner, 1975). This is an essential tool for evaluating the system
performance.
The following figure shows an example of the simulations for the very difficult case when the
weather has zero velocity, that is, it is perfectly overlapped with clutter. The upper left graph
shows the weather signal with -40 dB power without any clutter or GMAP filtering. The
graph on the upper right shows the same spectrum with 0 dB of clutter power added for a
clutter width of 0.012 (0.3 m/s at S band, 1000 Hz PRF). This is a CSR of 40 dB. The panel at
the lower left shows the weather signal after GMAP filtering.
In each of the moment plots, there are several values that are displayed. The left-most num-
ber shows the value at the range cursor which is positioned as indicated by the vertical line.
To the right, the
m
value is the mean and the
s
value the standard deviation as averaged over
all range bins (1000 in this example). For velocity these are in normalized units expressed as
a fraction of the Nyquist interval. For reflectivity the values are in dB.
Some key points are:
• The mean velocity is correctly recovered as expected (the m value in the plot), but the
standard deviation is higher (0.06 vs 0.04 in normalized units).
• The Cor dBZ shows 40.2 dB of C.Rej . This is the difference between the Tot dBZ
and the Cor dBZ values. The expected value is 40 dB in this case. This indicates that
GMAP has recovered the weather signal in spite of the aggressive clutter filtering that is
required.
• The standard deviation of the Tot dBZ is greater in the weather plus clutter (4.35
normalized units) as compared to the weather-only case. This is caused by the
fluctuations in the clutter power in the Gaussian clutter model.
• The standard deviation of the Cor dBZ after GMAP filtering, while not as low as for the
weather-only case are lower than the weather plus clutter case. In other words, the
GMAP processing removes some of the high variance in the dBZ estimates that is
caused by clutter, but is not quite as good as doing nothing
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