Severe Weather Probability (SWP) Product The  Severe  Weather  Probability  (SWP)  product provides an objective assessment of each storm’s potential to produce severe weather. Unfortunately, its sole input is VIL, and inaccuracies in VIL values will affect the SWP output. Like VIL, SWP is a volumetric product that uses vertically stacked grids to calculate severe potential. Why then would SWP be any better than VIL?   SWP grid boxes are much larger than VIL (24.2 x 24.2 nmi). Each SWP box contains 121 VIL grids. Since SWP analyses more area, it builds a larger, more reliable picture of each storm and is less likely to miss or underestimate them. SWP automatically extracts strong convective cells from current reflectivity patterns and estimates their probability to produce severe weather. Each convective  cell  is  assigned  a  number  that  represents  the probability that the cell will develop into a severe storm within  30  minutes.  By  assigning  percentage  values, SWP draws the user’s attention to these dangerous cells and  provides  an  objective  tool  for  evaluating  them. SWP can be displayed alone, but is best used as an overlay  on  other  products,  perhaps  VIL  or  Base Reflectivity (REF). Figure 2-41 is an example of the Severe  Weather  Probability  product. SWP data is calculated from VIL and ultimately base reflectivity. Therefore, SWPs are affected by all of the same factors that affect VIL and REF. Mesocyclone  (MESO)  Product Mesocyclones are areas of strong cyclonic rotation found in supercell thunderstorms. Such storms are normally  accompanied  by  severe  weather,  although not all mesocyclones produce tornadoes. The   WSR-88D   uses   extensive   computer processing of velocity data to build an extremely valuable  product  called  MESO  (mesocyclone).  The algorithm continuously searches for rotating wind fields produced by areas of strong shear. Shear is a speed and/or directional variation in the wind field with height. The algorithm is designed to identify three types of shear and categorize them accordingly; 2-D shear, 3-D shear, or mesocyclone. 2-D SHEAR.—This  is  an  area  of  horizontal rotation that meets the algorithm’s shear and symmetry tests. Symmetry determines the area’s balance and uniformity. 2-D shear lacks vertical consistency. It is only found at one elevation angle and cannot be linked at adjacent levels. For this reason, 2-D shear is said to be  "uncorrelated"  shear. 3-D SHEAR.—3-D shear has vertical consistency and can be linked to other elevations. However, 3-D shear   fails   the   symmetry   tests   required   for mesocyclone  classification.  The  shear  area  is  not balanced or uniform. 3-D shear is termed “correlated” shear because of its vertical link. MESOCYCLONE.— This   category   identifies shear regions that meet all algorithm requirements of size,  shape,  symmetry,  and  vertical  consistency associated with a mesocyclone. MESO, like any product, is just a tool. It should NEVER  be  used  as  a  stand-alone  source  of information,  and  its  findings  should  always  be confirmed with other products such as VEL. Although velocity data is processed up to 124 nmi from the RDA, the optimum effective range of this product is severely restricted  by  beam  broadening.  The  mesocyclone detection algorithm does not establish time continuity; this is left up to the operator. Figure 2-42 is an example of the MESO product. It  indicates  that  a  single mesocyclone (large circle) has been identified just northwest of the station. Tornadic Vortex Signature (TVS) Product Just as with the MESO product, the Tornadic Vortex Signature (TVS) algorithm performs extensive reanalysis of base velocity data to build each TVS product.  This  product  is  designed  to  search  out tornadic  signatures  within  mesocyclone  bearing storms. The TVS product is a small area of abnormally high shear  commonly  associated  with  tornadoes.  Like mesocyclones, TVSs are first detected at the storm’s mid-section and grow, both up and downward, with time. They reach cloud bases coincident with the appearance of a funnel cloud (as viewed from below). Studies suggest that TVSs are detectable 20 minutes prior to tornado touchdown (on average). Most TVSs detected   by   the   WSR-88D   are   associated   with tornadoes. However, not all tornadoes produce a TVS. Like the mesocyclone product, TVSs primary function is to alert users of high rotation and shear. An area with possible tornadic activity is indicated by an inverted 2-46