Winds from an optical flow technique using GOES-16/18 1-minute imagery


Robert Rabin(1,2)

Chris Velden, Dave Stettner, Steve Wanzong(2)

NOAA/NSSL(1) and UW-Madison/CIMSS(2)



BACKGROUND

    Wind vectors are estimated using a "Classical Variational Optical Flow algorithm" obtained courtesy of the Computer Vision Group, Feiburg, Germany. The algorithm is derived from High accuracy optical flow estimation based on a theory for warping by T. Brox, A. Bruhn, N. Papenberg, J. Weickert. T. Pajdla and J. Matas (Eds.), European Conference on Computer Vision (ECCV) Prague, Czech Republic, Springer, LNCS, Vol. 3024,  25-36, May 2004.

    Visible and IR image pairs from the GOES-16 Advanced Baseline Imager (ABI) mesosector bands 2 and 13. The IR images used are band 13 from GOES-16 and GOES-18.  The time interval of the images used is 1-minute. The horizontal resolution of the imagery at nadar is 0.5 km ans 2.0 km for visible and IR, respectively.  The images have been remapped to an equal latitude/longitude grid (visible: .005 deg, approximately 0.5 km spacing; IR: .02 deg, approximately 2 km grid spacing) before applying the algorithm. A parallax correction has not been applied. Wind vectors are computed at each grid point from the computed displacement along the eastward and southward directions during 1-minute time intervals.  Pressure level (height) assignments of wind vectors are based on Cloud Top Pressure estimates from the CLAVR-X products produced at CIMSS.  
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Real time GOES-16/18 wind products

The wind analyses use IR (band 13) imagery after a "super enhancement" has been applied. This enhancement is designed to dynamically show the coldest pixels with a temperature resolution of approximately 0.1 deg K with a dynamic range of 75 degrees from coldest to warmest pixels. This temperature range includes both the brightness temperatures of cloud tops and the earth's surface in clear sky regions.

GOES-16
 
Mesosector 1 GOES-16
Mesosector 2 GOES-16                                                 


GOES-18

Mesosector 1 GOES-18
Mesosector 2 GOES-18
                                  

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Archived Cases

13 April 2019 (Caddo Mounds, TX tornado)

IR: 16 UTC

IR: 17 UTC

IR: 18 UTC

Vis: 16 UTC

Vis: 17 UTC

Vis: 18 UTC

KPOE radar ref: 16 UTC

KPOE radar ref: 17 UTC

KPOE radar ref: 18 UTC

Comparison with observed radial velocity


28 May 2019 (Lawrence, Winwood, KS tornado)

IR: 23 UTC

VIS: 23 UTC

KTOP radar ref: 19 UTC

KTOP radar ref: 20 UTC

KTOP radar ref: 23 UTC

KTOP radar ref: 23 UTC constrained with observed Doppler radial velocites

Comparison with observed radial velocity

03 March 2019 (Alabama tornado)

Vis: 1951-2040 UTC 

Vis: 1931-2040 UTC

IR: 1951-1959 UTC

IR: 1931-2040 UTC

06 September 2017 (Irma)

IR: 1601-1605

VIS: 1601-1610

Vis (all layers animated gif) 1501-1559

VIS: 1501-1559

IR: 1501-1559

IR (without enhancement) 1759-1802

21 September 2019 (Ottawa Valley, Ontario tornado)

VIS: 2001-2059

VIS: 2101-2130

IR: 2001-2130

03 March 2020 (Middle Tennessee tornado outbreak)

IR: 03 March 20, 06:01-06:59 UTC

IR: 03 March 20, 07:01-07:59 UTC
 
25 March 2021 (Alabama tornado outbreak)

IR: 25 March 21, 19:00-19:59 UTC

IR: 25 March 21, 21:00-21:59 UTC

IR: 25 March 21, 22:00-2259 UTC

 

29 April 2021 (Hail Storms, OK and TX)

IR: 29 April 21, 01:00-01:59 UTC


21 June 2021 (Chicago southwest suburbs tornado)

IR: 21 June 21, 03:30-04:30 UTC


21 June 2021 (Mascouche, Quebec tornadic storm and high wind event in the Northeast US

Visible (band2) image at 1947 UTC: Approximate time of EF2 tornado. Parallax adjusted location of Mascouche relative to clouds at 10km height is indicated by the "X".

Visible: 21 June 2021, 19:00-19:59 UTC

IR: 21 June 2021, 19:00-19:59 UTC
 

WV (midlevel 6.9 micron): 21 June 2021, 19:01-19:59 UTC


11 December 2021 (Kentucky tornadoes. F4 tornado hit Mayfield around 03:30 UTC)

IR: 11 December 2021, 0300-0400 UTC


04 May 2022 (Earlsboro Seminole Oklahoma, F2; Lockett, TX, F3 tornadoes)

IR: 04 May 2022, 2300-2359 UTC

IR: 05 May 2022, 0000-0059 UTC

IR: 05 May 2022, 0100-0159 UTC

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HTML5 based applications used for interactive animations were developed by Tom Whittaker of the Space Science and Engineering Center  SSEC, University of Wisconsin-Madison.  The animations can take a while to load, depending on network speed, computer systems, etc.



Additional References:

Rabin, R. M., S. F. Corfidi, J. C. Brunner, C. E Hane, 2004: Detecting winds aloft from water vapor satellite imagery in the vicinity of storms. Weather, 59, 251-257. Click here

Rabin, R.M., J. Brunner, C. Hane, J. Haynes: Water vapor winds in vicinity of convection and winter storms. P3.4. 11th Conference on Satellite Meteorology and Oceanography, 15-18 October 2001, Madison, WI.  To view the extended abstract (as a pdf file) Click here.

        A more complete manuscript including an analysis of several convective cases is available by clicking here .
 

Links:

    Global winds: For real-time and archived data and more information on the satellite winds program at CIMSS see the "Tropical Cyclones Homepage":  Click here


Disclaimer. The products from GOES or other satellites shown here are experimental. These have been generated within a research environment and are not intended to be considered operational. Timeliness, availability, and accuracy are sought but not guaranteed.

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