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Data
Limitations
Return
to start of Tornado Warning Guideline
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These Guidelines are based on the work of
the National Severe Storms Laboratory and the WSR-88D Operational
Support Facility titled Tornado Warning Guidance (2nd Edition, Spring
1999) (can be found at http://www.osf.noaa.gov/otb/PAPERS/twg99/
) and the research conducted in this COMET Cooperative Project.
In order to maximize the accuracy of
our tornado warnings you should:
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Know your environment - check soundings and
modify them for ongoing atmospheric evolution.
Watch VWP for areas enhanced low altitude helicity. Perform frequent
mesoanalysis (NSSL/OSF).
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Many
storms types produce tornadoes.
In this
study, only one half of the tornadoes were produced by
supercells
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Watch for Bow
Echoes with very strong
wind velocities, high shear and notches near the apex of
the bow.
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Use Vr
and Vr shear functions as described
in this training module. They show good skill at identifying
tornadoes, but remember, they may not provide significant lead time.
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Tornado development can occur very quickly, often within 1 or 2
volume scans.
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Watch for boundary
interaction.
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Storm motion and tornado motion (direction and speed) may be
significantly different (documented in VORTEX). Be careful when
issuing tornado warnings for locations based on the storm cell centroid
motions; use the motion of the radar vortex signature, if it's
available available (NSSL/OSF).
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Know the limits of the
radar.
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Radar-observed vortex signature can, depending on range, appear to
dissipate prior to the dissipation of the
tornado, as the shrunken tornado vortex becomes
increasingly difficult to observe given WSR-88D sampling limitations.
This period without a radar-observable vortex signature may
include the most intense and damaging phase of the tornado. Continue
tornado warnings for a few volume scans following the dissipation of
the radar-observed vortex signature (NSSL/OSF)
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Study your forecast area for local terrain effects
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The WSR-88D TVS Algorithm needs work. While the old Algorithm rarely provided
indication of a tornado, the new algorithm has a very high false
alarm ratio. Adjustment of adaptable parameters may improve its
skill.
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Use spotter reports, storm history and any
available remotely sensed data
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