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Figure 2-36.(A) Vertical wind profile,
Figure 2-37.Composite Reflectivity (CR) product.

Aerographers Mate, Module 03-Environmental Satellites and Weather Radar
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blowing from west to east at the height of the display. At point 2, the zero line is oriented east to west. In this instance, inbound velocities are to the south so the wind direction must be 180° near the surface. Figure (D) is an example of the WSR-88D velocity display. As you can see, areas of red and orange indicate flow away from the radar, while areas of green and blue indicate flow toward the radar. The colors can then be compared to the color scale above to determine wind speed. Again,  successful  coverage  from  this  product depends on the size and amount of scatterers available. When  ground  clutter  or  anomalous  propagation contaminate the radar beam, all velocities will be biased toward zero. When range folding occurs, purple shading might obscure valuable data, causing you to miss  significant  features.  Keep  in  mind  that  all velocities are relative to the RDA, not the PUP. DERIVED  PRODUCTS Derived products are enhanced renditions of base products that provide observers and forecasters with a unique  perspective  of  radar  information.  In  the following text, we will discuss some of the more commonly  used  derived  products. Composite Reflectivity (CR) Product Recall that base reflectivity provides a “birds eye” view of the radar coverage area. While this is very useful, base products provide data from only a single elevation  angle.  Thus,  only  a  slice  of  the  overall atmosphere is presented, and valuable information above or below the radar beam may be overlooked. To sample the entire volume scan, radar operators must view each slice individually. This time-consuming process is impractical for the operational user. The WSR-88D offers Composite Reflectivity (CR) as a partial  solution. The CR product contains information found in base   reflectivity.   However,   one   very   important difference  exists: composite  reflectivity  operates  on  a  summation principle. That is, the algorithm first compiles data from all elevations (volumetric), and then produces a product which displays only the strongest  returns for all regions of the radar coverage area. In building the CR product, the algorithm considers only intensity as its criteria. Size, shape, characteristic, and altitude are not  factored. The CR offers a    “sneak-peek”  advantage  over base reflectivity, but should never replace the use of other reflectivity products. When using CR, operators are less likely to miss significant targets since only reflectivity   maximas   are   displayed.   The   major downside of this product is its loss of target heights. This limitation poses serious problems since echo heights relate closely to storm development. Without height data, targets become deceiving. This product is normally accompanied by an attribute table that ranks storms according to severity and includes forecast movement and the likelihood of each storm to produce a variety of conditions (hail, mesocyclones, tornadoes, etc.). Keep in mind that values displayed for a given location  could  have  come  from  any  altitude  or elevation angle. In fact, extensive ground clutter may severely contaminate this product, creating the illusion of   intense   storms   where   nothing   exists.   This occurrence  is  common  when  superrefractive conditions are present. Figure 2-37 is an example of the Composite  Reflectivity  product. Vertically Integrated Liquid (VIL) Product Most WSR-88D products emphasize a target’s horizontal  details.  The  Vertically  Integrated  Liquid (VIL) product provides an estimate of atmospheric liquid-water  content  in  the  vertical.  It  serves  a multitude of purposes, but is primarily designed to evaluate storm severity. The  VIL  product  is  compiled  from  extensive reanalysis of base reflectivity data. It totals reflectivity within a given column of the atmosphere and then displays a product of tallied values. The function of the VIL algorithm is to estimate the amount of liquid water contained in a storm, and then display that value (kilograms/meter squared) in a graphical form. In its initial   stages,   the   VIL   algorithm   holds   many similarities  to  composite  reflectivity.  It  builds  a volumetric product by compiling reflectivity data from all  elevation  angles.  The  difference  is  that  VIL displays tallied values for the entire column (fig. 2-38). CR displays only the reflectivity maxima regardless of altitude.   Users   can   quickly   evaluate   storms   by comparing VIL columns. VIL is useful when monitoring general echo pat- terns  for  signs  of  development.  In  convective  situa- tions, VIL is directly related to updraft strength, which translates into storm severity. The VIL, product was designed to distinguish severe from nonsevere storms, but it is also used as a hail indicator (very high dBZs). 2-40







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