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along range time as there are samples. That is, sample spacing is typically equal to pulse
duration and therefore consecutive samples are almost independent. Closer sampling (i.e.,
oversampling) has some advantages (Section 4.2).
Radials of spectral moments are transmitted to the RPG (a radial of velocities is in the top right
part of Fig. 2). Spectral moments are displayed at Weather Forecast Offices, are recorded, and
are also processed by algorithms to automatically identify hazardous weather features,
estimate amounts of precipitation, and to be used in numerical models among other
applications. Example displayed in Fig. 2 (right bottom) is the field of Doppler velocities
obtained by the WSR-88D in Dove, North Carolina during the Hurricane Irene on Aug 28 th ,
2011 at 2:29 UTC. The end range on the display is 230 km which is also the range up to which
quantitative measurements are currently being made. Extension to 300 km is planned.
Fig. 2. Information path from time series to output of algorithms.
The radar is sufficiently sensitive to detect precipitation at much larger ranges where the
beamwidth and observations high above ground mar quantitative interpretation of
impending weather on the ground. At the elevation of 0.5 o , the radar makes two scans:
one with the longest PRT (3.1 ms) for estimating reflectivities unambiguously up to 465
km in range, the other with one of the short PRTs to estimate unambiguously velocity
over a sufficiently large span. The ambiguities in range and velocity are inherent to
pulsed Doppler radars. Reflections from scatterers spaced by the unambiguous range ( r a
= cT s /2 where T s is pulse repetition time) appear at the same delay with respect to the
reference time (determined by the last of two transmitted pulse). Obvious increase in
range can be made by increasing T s . And this is fine for measurements of reflectivity but
would harm measurements of velocity. At the 10 cm wavelength Doppler velocities are
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