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CSTAR HSLC Research Update Keith Sherburn

CSTAR HSLC Research Update Keith Sherburn. 7/26/2012. HSLC Radar Climatology Update. Jason Davis July 26, 2012. Outline. Decision Trees Composite Parameter. TREE 1: EVENTS VS. NULLS. SIGNIFICANT TORNADOES. SIGNIFICANT EVENTS. 2. HSLC CONVECTION. 1. SIGNIFICANT WINDS. NULLS. 1.

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CSTAR HSLC Research Update Keith Sherburn

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  1. CSTAR HSLC Research UpdateKeith Sherburn 7/26/2012

  2. HSLC Radar Climatology Update Jason Davis July 26, 2012

  3. Outline • Decision Trees • Composite Parameter

  4. TREE 1: EVENTS VS. NULLS SIGNIFICANT TORNADOES SIGNIFICANT EVENTS 2 HSLC CONVECTION 1 SIGNIFICANT WINDS NULLS

  5. 1 NULLS SIGNIFICANT EVENTS • Primary discriminating parameters: • Effective shear magnitude tends to be higher in significant events • Low- and mid-level lapse rates generally higher in significant events • Composite parameters (e.g., significant tornado parameter and vorticity generation • parameter) show reasonable skill • Other comments: • Some discriminating parameters not listed (e.g., higher sea-level pressure and 500 • mb height for nulls) may be a result of regional biases in the datasets; northern • CWAs have much lower percentage of nulls than events.

  6. 2 SIGNIFICANT WINDS SIGNIFICANT TORNADOES • Primary discriminating parameters: • Most unstable parcel’s CIN is generally lower in tornado cases, though the • optimal threshold (-10 J/kg) is so low, it may not be operationally viable • Lifted indices generally have a higher magnitude in tornado cases • V-components of deep-layer (0-6 km; 0-8 km) shear tend to be higher in wind • events; this is likely an indication of the importance of boundary-relative winds • Other comments: • As before, some parameters may be a result of regional influences, since northern • CWAs generally had many more significant wind events than significant tornadoes.

  7. TREE 2: CONVECTIVE MODES DISCRETE SUPERCELLS LINE SUPERCELLS SUPERCELLS 2 HSLC CONVECTION 1 CLUSTER/LINE SUPERCELLS 3 NON-SUPERCELLS CLUSTER SUPERCELLS

  8. 1 NON-SUPERCELLS SUPERCELLS • Primary discriminating parameters: • Many wind and shear components are statistically skillful, with V components • typically higher in non-supercells and U components higher in supercells • LFC heights tend to be lower in supercell cases • Low-level lapse rates and SB CAPE also are generally higher in supercell cases, • suggesting that low-level instability is a main discriminator • Other comments: • Though the wind components are skillful, preliminary analysis (not shown at this • time) shows that this does not seem to be correlated with the shear and wind • vector orientations relative to associated synoptic boundaries.

  9. 2 LINE AND CLUSTER SUPS DISCRETE SUPERCELLS • Primary discriminating parameters: • Again, shear and wind components, especially those in the deeper layers or • at higher levels, respectively, are skillful, with higher V components in line • and cluster supercell cases and higher U components in discrete cases • Mid-level lapse rates tend to be higher in discrete cases, suggesting a necessity • for deeper regions of instability in order for cells to become discrete

  10. 3 CLUSTER SUPERCELLS LINE SUPERCELLS • Primary discriminating parameters: • All CAPE parameters tend to be higher in the case of line supercells, indicating • that the main difference in these two environments is the amount of available • instability • LFC heights are generally higher for cluster supercells • V components of 0-8 km shear and upper-level winds are typically larger in line • supercell cases, indicating that not just the thermodynamic profile is relevant • in discriminating between line and cluster supercells • Other comments: • In fact, line and cluster supercells show the biggest differences in preliminary • investigations of shear and wind orientation relative to synoptic-scale boundaries

  11. Questions, comments… ? FEEDBACK ON DECISION TREES?

  12. Composite Parameter • Designed to discriminate SIGNIFICANT HSLC SEVERE REPORTS (EF2+ tornadoes, 65+ kt winds, 2”+ hail) from HSLC nulls • Recall our definition of a null: • Any tornado or severe thunderstorm warning issued on a convective day (1200 UTC – 1200 UTC) by a WFO when no severe reports were collected in that CWA during that convective day

  13. (Preliminary) Composite Parameter • Derived through the calculation of skill scores between significant events and nulls, • as the 1st decision tree was based off of • Terms are normalized by the optimal value of each parameter based on the skill • scores ^Name and formula subject (and likely) to change

  14. SIGNIFICANT EVENTS VS. NULLS* *i.e., a “false alarm” would be a null; non-significant events are not included

  15. SIGNIFICANT EVENTS VS. NULLS* *i.e., a “false alarm” would be a null

  16. SIGNIFICANT EVENTS VS. ALL OTHERS* *i.e., a “false alarm” would be a null or a non-significant severe event

  17. SIGNIFICANT EVENTS VS. ALL OTHERS* *i.e., a “false alarm” would be a null or a non-significant severe event

  18. Composite Parameter • How well does it perform with all significant tornadoes in our region? • Can test POD using SPC relational database of all tornadoes for our CWAs between 2006-2011

  19. Composite Parameter *Top set is ALL significant tornadoes from 2006-2011; bottom is HSLC significant tornadoes

  20. ANY QUESTIONS, COMMENTS, oR SUGGESTIONS?

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