System and Method for Predicting Tornado Activity

• US 20090182507A1
• Filed: 01/10/2008
• Published: 07/16/2009
• Est. Priority Date: 01/10/2008
• Status: Active Grant

• Current Assignee: Baron Services Incorporated
• Original Assignee: Baron Services Incorporated
• Inventors: Havin, Matthew Alan, Baron, Robert O. SR., Dreisewerd, Robert J. JR.
• Granted Patent: US 7,917,291 B2
• Time in Patent Office: Days
• US Class Current: 702/3
• CPC Class Codes: G01W 1/10 Devices for predicting weather conditions computers per se G06; display devices G09

Abstract

The present system and method detects and predicts potential tornadic activity. In one aspect, the invention predicts potential tornadic activity based on radar data. In another aspect, the invention predicts potential tornadic activity based on an integrated and composite

Claims

1. A method of predicting current tornado activity comprising

(a) receiving model data for a first time period and a second time period indicative of tornadic activity, wherein said first time period is prior to the current time and said second time period is subsequent to the current time;

(b) generating a first time period model data tornado potential index and a second time period model data tornado potential index using said model data;

(c) generating a current time model data tornado potential index from said first time period model data tornado potential index and said second time period model data tornado potential index;

(d) receiving radar data indicative of tornadic activity;

(e) generating a radar data tornado potential index using said radar data;

(f) generating a composite tornado potential index using said current time model data tornado potential index and radar data tornado potential index.

2. The method of claim 1 wherein the received model data comprises CAPE, CIN, and helicity.

3. The method of claim 1 wherein the received radar data comprises TVS data, MESO data, VIL data, dBz data, and hail data.

4. The method of claim 1 wherein the step of generating a first time period model data tornado potential index and second time period model data tornado potential index uses CAPE data, CIN data, helicity data, wind difference data, and LCL data.

5. The method claim 1 wherein the step of generating a radar data tornado potential index uses TVS data, MESO data, dBz data, VIL data, and hail data.

6. The method of claim 1 further comprising displaying the composite tornado potential index on a map.

7. The method of claim 6 wherein said displaying step comprises using different colors to depict different values of the composite tornado potential index.

8. A system for predicting tornadic activity comprising a processor communicating with a model data source to receive model data and a radar data source to receive radar data, said processor configured to process a subset of said model data to create a model data potential tornado index and a subset of said radar data to create a radar data potential tornado index, and further configured to process said model data potential tornado index and said radar data potential tornado potential index to create a model data/radar data composite index.

9. The system of claim 8 wherein the subset model data comprises CAPE data, CIN data, helicity data, wind difference data, and LCL data.

10. The system of claim 8 wherein the subset of radar data comprises TVS data, MESO data, VIL data, dBz data, and hail data.

11. The system of claim 10 wherein the subset of radar data are assigned weighted values to create potential tornado index.

12. The system of claim 8 wherein said model data potential tornado index and radar data tornado potential index are assigned weighted values.

13. A method of predicting tornado activity based on radar data comprising

(a) receiving radar data comprising tornado indicator data;

(b) assigning weighted values to said tornado indicator data;

(c) generating a radar data potential tornado index using said weighted tornado indicator data.

14. The method of claim 13 wherein tornado indicator data comprises TVS data, MESO data, VIL data, dBz data, and hail data.

15. The method of claim 13 wherein tornado indicator data comprises TVS data and MESO data, and TVS data is given a higher weight than MESO data.

16. The method of claim 13 further comprising the steps of creating a model data potential tornado index from model data indicative of tornadic activity and creating a composite radar data/model data potential tornado index from said radar data potential tornado index and said model data potential tornado index.

17. The method of claim 16 wherein the step of creating a model data potential tornado index uses CAPE data, CIN data, helicity data, wind difference data, and LCL data.

18. The method of claim 16 wherein the step of creating a model data tornado index uses a time weighted average derived from a model data tornado index for a prior time period and a model data tornado index for a future time period.

19. The method of claim 13 further comprising displaying the radar data potential tornado index on a map.

20. The method of claim 16 further comprising displaying the composite radar data/model data potential index on a map.

21. The method of claim 20 wherein an icon is displayed for locations in which the composite radar data/model data potential index values exceed a certain threshold.

22. The method of claim 16 further comprising displaying a ring where the radar data indicates a potential tornado and wherein the inside color of the ring corresponds to the composite radar data/model data potential tornado index.