1. Application of the Computer Vision Hough Transform for Automated Tropical Cyclone Center-Fixing from Satellite Data Mark DeMaria, NOAA/NCEP/NHC Robert DeMaria, CIRA/CSU NCAR-CSU Tropical Cyclone Workshop January 8, 2014 Boulder, CO

2. Outline Tropical cyclone center fixing from satellites The circular Hough transform Application to tropical cyclones Preliminary results Improvement through multi-spectral analysis

3. Only west Atlantic and around Hawaii have routine aircraft center fixes Satellite data used subjectively to find centers across the globe Improvements to accuracy in real-time highly desirable Aircraft Data Availability

4. Center location (fixing) Center Location = surface center –Center of circulation –Usually close to the lowest sea-level pressure Visible and IR methods – Dvorak –Eye –Distinct and inferred center with shear pattern and low-level clouds –Spiral bands and curved cloud lines –Wedge method Using animation –Low-level cloud motions –Deep layer cloud motions –Ignore cirrus layer cloud motions –Mid-level centers tilted from surface center Using microwave images –Thick cirrus clouds in visible and IR images obscure features below, used for center location –Thick cirrus clouds in microwave images are more transparent, and the microwave images may often provide better views of features, for improved center locations Using 3.9-micrometer images at night New Day-Night band from VIIRS

5. Center Location Nearly all methods subjective –Exception is CIMSS ARCHER method that fits spiral patterns to microwave imagery from LEO satellites Many more geostationary images than center fixes –Automated methods would allow use of high temporal resolution of IR and visible data 5

6. Circular Hough Transform Hough transform developed for computer vision applications to detect features Originally developed for lines and edges Later generalized to shapes Circular Hough transform applied to accurately detecting centers of breeder reactors Application to finding tropical cyclone centers 6

7. Circular Hough Transform for case with known radius

8. Generalization for Unknown Radius Estimate range of possible radii Perform CHT for range of test radii Calculate 2-D accumulation matrix for each test radius Scale accumulation matrices by radius Average scaled matrices Center is point with the most votes or some weighted average around the maximum Can be generalized to multiple circles –Automated coin identification 8

9. Application to TC Center Fixing from IR Data Apply cold threshold to IR image to isolate cold clouds Apply edge detection method –Take Laplacian of IR brightness temperature –Apply threshold to |Laplacian| Perform CHT for a range of radii 10 to 300 km in 1 km intervals Use combined accumulation matrix to find the center 9

10. Hurricane Katrina Example

11. Accumulation Matrix for Radii from 45 to 112 Pixels

12. Charley 2004 – Very small but intense hurricane Katrina 2005 – Classic large, intense hurricane Ericka 2009 – Very disorganized weak tropical cyclone, did not make it to hurricane strength Earl 2010 – Strong hurricane in higher latitudes Sandy 2012 – Unusually large but only moderate strength, non-classical hurricane structure IR images every 6 hr for lifecycle of each storm –135 images Tropical Cyclone Cases

13. Eye Detection Examples Katrina 08/29/00 2005 Earl 09/02/06 2010 Charley 08/13/18 2004 Katrina 08/25/18 2005 Ericka 09/02/18 2009 Sandy 10/19/18 2012 No Eye Cases Eye Cases

14. Mean CHT error: 91 km Storms with eyes: 54 km Bias X: 6 km Bias Y: 8.5 km Bias Explained by Parallax Results

15. Results by Storm:

16. Primary Error Sources Sheared storms –Circulation center displaced from cold cloud shield Storms with eyes –Radii on scale of outer cloud shield gets more “votes” than radii on the eye scale 16

17. Tropical Storm Erika 17 X

18. Eye Center Out-Voted

19. Next Steps Accumulation matrices may be useful for eye detection –Multiple solutions for centers Use CHT from IR data as first guess to visible algorithm Combine with other information –Shear vector –Microwave imagery, day-night band –Time continuity of displacement 19