Hurricane center-fixing with the Automated Rotational Center Hurricane Eye Retrieval (ARCHER) method

Tony Wimmers, Chris VeldenTony Wimmers, Chris Velden

University of Wisconsin - Cooperative Institute for Meteorological Satellite Studies (CIMSS)

Sponsored by The Oceanography of the Navy through the PEO C4I PMW-150 program office and the Naval Research Laboratory

MotivationMotivation

• Forecasting (track)Forecasting (track)

• Input into automated retrievals (intensity, Input into automated retrievals (intensity, eye diameter, ERC…)eye diameter, ERC…)

Real time and reanalysisReal time and reanalysis

ObjectiveObjective

• Automated, robust location of Automated, robust location of TC rotational centers in individual TC rotational centers in individual microwave or IR imagesmicrowave or IR images

• Must be resilient to false eyes Must be resilient to false eyes (moats), obstructions in the eye, (moats), obstructions in the eye, partial eyes, partial scan coveragepartial eyes, partial scan coverage

• Must rely only loosely on a first-Must rely only loosely on a first-guess (forecast) position estimateguess (forecast) position estimate

• Must apply to microwave and IR Must apply to microwave and IR imageryimagery

“First guess”

Center fix

85 GHz (H) TMI retrieval

Additional information can be found in Additional information can be found in Wimmers, A. and C. Velden, 2010: Wimmers, A. and C. Velden, 2010: Objectively Determining the Rotational Center of Tropical Cyclones in Passive Microwave Satellite Imagery, J. Appl. Meteor., 49, 2013–2034, 2010.

ARCHER overviewARCHER overview

1) Produce a 1) Produce a 2D field 2D field (contoured) (contoured) that expresses that expresses how well a how well a location location registers as the registers as the center of the center of the large-scale large-scale spiralspiral pattern pattern

““Spiral ScoreSpiral Score””

2) Produce a 2) Produce a separate 2D separate 2D field that rates field that rates how well a how well a location is location is centered inside centered inside a a circular ring circular ring of convectionof convection ““Ring ScoreRing Score””

3) Combine the two 2D 3) Combine the two 2D fields as a weighted sum fields as a weighted sum into a single score fieldinto a single score field

““Combined ScoreCombined Score””

ARCHER: Additional proceduresARCHER: Additional procedures

• Images are pre-processed to compensate for a ~12 km parallax shiftImages are pre-processed to compensate for a ~12 km parallax shift

• If the Combined Score at the center fix does not exceed a certain If the Combined Score at the center fix does not exceed a certain threshold value, then the algorithm defaults back to the first guess threshold value, then the algorithm defaults back to the first guess positionposition

Example: Unresolved eye (Dennis 2005)Example: Unresolved eye (Dennis 2005)

1) Wider domain1) Wider domain

Example: Unresolved eye (Dennis 2005)Example: Unresolved eye (Dennis 2005)

2) Zoomed view 2) Zoomed view

Example: Unresolved eye (Dennis 2005)Example: Unresolved eye (Dennis 2005)

3) With best track position3) With best track position

Example: Unresolved eye (Dennis 2005)Example: Unresolved eye (Dennis 2005)

4) With simulated forecast position (first guess)4) With simulated forecast position (first guess)

Example: Unresolved eye (Dennis 2005)Example: Unresolved eye (Dennis 2005)

5) Spiral score5) Spiral score

Example: Unresolved eye (Dennis 2005)Example: Unresolved eye (Dennis 2005)

6) Ring score6) Ring score

Example: Unresolved eye (Dennis 2005)Example: Unresolved eye (Dennis 2005)

7) Combined score7) Combined score

Example: Unresolved eye (Dennis 2005)Example: Unresolved eye (Dennis 2005)

8) Compare to best track position8) Compare to best track position

“First guess”

Center fix

Best track

Example: Asymmetric eye (Chaba 2010)Example: Asymmetric eye (Chaba 2010)

1. Strong, complete eyewall1. Strong, complete eyewall

Center-fix

Example: Asymmetric eye (Chaba 2010)Example: Asymmetric eye (Chaba 2010)

2. Shearing leads to asymmetric eyewall pattern2. Shearing leads to asymmetric eyewall pattern

Center-fix

Example: Asymmetric eye (Chaba 2010)Example: Asymmetric eye (Chaba 2010)

3. Eyewall only evident on the western side3. Eyewall only evident on the western side

Center-fix

Example: Asymmetric eye (Chaba 2010)Example: Asymmetric eye (Chaba 2010)

4. Sub-pixel eye and banding only on the west4. Sub-pixel eye and banding only on the west

Center-fix

Example: Asymmetric eye (Chaba 2010)Example: Asymmetric eye (Chaba 2010)

5. Sub-pixel eye and a developing secondary eyewall5. Sub-pixel eye and a developing secondary eyewall

Center-fix

Example: Asymmetric eye (Chaba 2010)Example: Asymmetric eye (Chaba 2010)

6. Completed eyewall replacement cycle6. Completed eyewall replacement cycle

Center-fix

Validation: 2005 season, North AtlanticValidation: 2005 season, North Atlantic

• Independent from calibration sampleIndependent from calibration sample• Uses the NHC best track as Uses the NHC best track as ““truthtruth””• Only uses cases that are < 3 hours from an aircraft position fixOnly uses cases that are < 3 hours from an aircraft position fix

Effect of vertical wind shearEffect of vertical wind shear

• The algorithm performance will degrade in cases The algorithm performance will degrade in cases of high vertical shear, because of displacement of high vertical shear, because of displacement between the centers of rotation at the surface and between the centers of rotation at the surface and the image height, and also loss of symmetrythe image height, and also loss of symmetry

• Because of this we separate the test sample into Because of this we separate the test sample into Group A (low/moderate shear) and Group B (high Group A (low/moderate shear) and Group B (high shear)shear)

• Group B is <10% of the sampleGroup B is <10% of the sample

• The ARCHER error for Group B averaged to be The ARCHER error for Group B averaged to be about double that of Group Aabout double that of Group A

Results: 85-92 GHz (H)Results: 85-92 GHz (H)

Group A

RMS (w/o defaults) 0.06

RMS (all) 0.15

0.060.15

Results: 85-92 GHz (H)Results: 85-92 GHz (H)

Group A

RMS (w/o defaults) 0.06

RMS (all) 0.15

Results: 85-92 GHz (H)Results: 85-92 GHz (H)

Group A

RMS (w/o defaults) 0.06

RMS (all) 0.15

Default rate 37%

Results: 85-92 GHz (H)Results: 85-92 GHz (H)

Default rate

Trop. storm 83% (*)

Category 1 15%

Category 2-5 0.01%

Group A

RMS (w/o defaults) 0.06

RMS (all) 0.15

Default rate 37%

Tropical Storm exampleTropical Storm example

Center fix

Best track (.25 away)

ARCHER: Adapting to IR imageryARCHER: Adapting to IR imagery

• Calibrated and validated to a probability density function (PDF)Calibrated and validated to a probability density function (PDF)

Error, degreesError, degrees Error, degrees

(Low organization)

Organization score = 0.91

(Medium organization)

Organization score = 1.55

(High organization)

Organization score = 2.60

ARCHER: Output for IR imageryARCHER: Output for IR imagery

• Numerical output:Numerical output:Forecast position (lon, lat): -61.10, 36.70Forecast position (lon, lat): -61.10, 36.70Center-fix position (lon, lat): -60.81, 36.47Center-fix position (lon, lat): -60.81, 36.47Eye confidence (%) = 31Eye confidence (%) = 31Error distribution parameter (alpha) = 6.39Error distribution parameter (alpha) = 6.39Probability of error < 0.2° (%) = 36.5 Probability of error < 0.2° (%) = 36.5 Probability of error < 0.4° (%) = 72.4 Probability of error < 0.4° (%) = 72.4 Probability of error < 0.6° (%) = 90.0 Probability of error < 0.6° (%) = 90.0 Probability of error < 1.0° (%) = 98.8 Probability of error < 1.0° (%) = 98.8

• Graphical output:Graphical output:

Center-fix

Spiral grid Combined grid

Often ~95% for more organized TCs Often ~95% for more organized TCs

Final remarksFinal remarks

DistributionDistribution

• A free, licensed version of ARCHER is available for distribution (Matlab code).A free, licensed version of ARCHER is available for distribution (Matlab code).

HURSATHURSAT

• ARCHER does work with HURSAT and yields good results, although the imagery ARCHER does work with HURSAT and yields good results, although the imagery becomes twice-interpolated (once from HURSAT and then again by ARCHER), becomes twice-interpolated (once from HURSAT and then again by ARCHER), which means the result can often be improved by using original data.which means the result can often be improved by using original data.

Ongoing workOngoing work

• Current work involves a cross-comparison of ARCHER accuracy for microwave Current work involves a cross-comparison of ARCHER accuracy for microwave and IR imagery, and also finding the best way of combining microwave/IR results and IR imagery, and also finding the best way of combining microwave/IR results into a single storm track.into a single storm track.

ARCHER: Adapting to IR imageryARCHER: Adapting to IR imagery

• Calibrated and validated to a probability density function (PDF)Calibrated and validated to a probability density function (PDF)

(Low organization) (High organization)(Medium organization)

Error, degrees Error, degrees Error, degrees

Organization score = 0.91 Organization score = 1.55 Organization score = 2.60

ExtrasExtras

Forecast position errorForecast position error

North Atlantic

West Pacific

ARCHER: ARCHER: ““Spiral ScoreSpiral Score”” component component

• High values occur where the vector field High values occur where the vector field lines up with the image gradientslines up with the image gradients

ARCHER: ARCHER: ““Spiral ScoreSpiral Score”” component component

• High values occur where the vector field High values occur where the vector field lines up with the image gradientslines up with the image gradients

SummarySummary

• ARCHER has several unique innovations:ARCHER has several unique innovations:

– Balances the evidence from large-scale spiral edges with small-scale eyewall Balances the evidence from large-scale spiral edges with small-scale eyewall patternspatterns

– Has an optimized default to the first guess as a backup optionHas an optimized default to the first guess as a backup option

– Validated with a large, independent sample of imagesValidated with a large, independent sample of images

• The center-fix accuracy is ~16 km in all cases with low-to-moderate shear and ~6 The center-fix accuracy is ~16 km in all cases with low-to-moderate shear and ~6 km for non-default cases only.km for non-default cases only.

• Current applications include TC visualization, TC diameter size retrieval, intensity Current applications include TC visualization, TC diameter size retrieval, intensity estimation and prediction of rapid intensification.estimation and prediction of rapid intensification.

Applications (1 of 4): MIMICApplications (1 of 4): MIMIC

• (MIMIC: Morphed Integrated Microwave Imagery at CIMSS) using multi-satellite 85-92 (MIMIC: Morphed Integrated Microwave Imagery at CIMSS) using multi-satellite 85-92 GHz retrievals. Finding the center of rotation of each image is critical to blending them GHz retrievals. Finding the center of rotation of each image is critical to blending them together properly.together properly.

Applications (2 of 4): Microwave-based Intensity est.Applications (2 of 4): Microwave-based Intensity est.

• Eye and eyewall statistics in 85 GHz images add important TC intensity information to Eye and eyewall statistics in 85 GHz images add important TC intensity information to the MW-ADT at CIMSS in the 65-90 kt range, when eyes are often obscured by central the MW-ADT at CIMSS in the 65-90 kt range, when eyes are often obscured by central dense overcastdense overcast

Diagnostic image for TC 26W (2009), leading to a MW-ADT estimate of Diagnostic image for TC 26W (2009), leading to a MW-ADT estimate of Vmax = 73 kts. JTWC estimate was at 65 kts. [24 Nov 1052 UTC]Vmax = 73 kts. JTWC estimate was at 65 kts. [24 Nov 1052 UTC]

Applications (3 of 4): TC diameter informationApplications (3 of 4): TC diameter information

• ARCHER RMW is significantly lower than the value produced by JT. A lower RMW ARCHER RMW is significantly lower than the value produced by JT. A lower RMW would contribute to a better SATCON (Satellite Consensus) estimate for this TC, would contribute to a better SATCON (Satellite Consensus) estimate for this TC, indicating that it is probably more accurate (see indicating that it is probably more accurate (see Herndon and Velden: Herndon and Velden: SATCON SATCON Evaluation and Recent changesEvaluation and Recent changes, Poster 33)., Poster 33).

Applications (4 of 4): Rapid intensificationApplications (4 of 4): Rapid intensification

• Certain characteristics of the Certain characteristics of the eyewall in 37 GHz imagery can eyewall in 37 GHz imagery can indicate rapid intensification, but indicate rapid intensification, but previously this has only been previously this has only been shown manually*.shown manually*.

• The ARCHER algorithm can The ARCHER algorithm can automate this method by automate this method by identifying the eye and eyewallidentifying the eye and eyewall

• This is described in the talk, This is described in the talk, Improvements in the Statistical Improvements in the Statistical Prediction of TC Rapid Prediction of TC Rapid Intensification Intensification [Rozoff et al. [Rozoff et al. Thursday am session]Thursday am session]

* Kieper (2008; 28th AMS Conf. on Hurr. and Trop. Meteor.)