objective, satellite-based tropical cyclone center-fixing tony wimmers and chris velden university...

Objective, Satellite-Based Tropical Cyclone Center-Fixing

Tony Wimmers and Chris VeldenTony Wimmers and Chris Velden

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

Sponsored by the Oceanographer of the Navy through the PEO C4I PMW-120 program office and the Naval Research Laboratory

Principal GoalPrincipal Goal• Create an objective, Create an objective, automated algorithm to automated algorithm to locate the rotational locate the rotational centers of TCs evident in centers of TCs evident in microwave, IR, or visible microwave, IR, or visible imagesimages

• Should be resilient to Should be resilient to identifying identifying ““false eyesfalse eyes”” (moats) (moats) but robust enough to detect but robust enough to detect partial eyes and convergent partial eyes and convergent cloud spiral signaturescloud spiral signatures

• Should rely only loosely on a Should rely only loosely on a first-guess (forecast) position first-guess (forecast) position estimateestimate

• Should provide position Should provide position estimate uncertainty indicesestimate uncertainty indices

“First guess”

Center fix

ARCHER: Automated Rotational Center Hurricane Eye Retrieval

Wimmers, A. J., and C. S. Velden, 2010: Objectively determining the rotational center of tropical cyclones in passive microwave satellite imagery.

Journal of App. Meteor and Clim., e-View doi: 10.1175/2010JAMC2490.1

ARCHER research/development statusARCHER research/development status

• Returns a numerical score that relates to an estimated center position, a Returns a numerical score that relates to an estimated center position, a 2-D score field that corresponds to the likelihood of having found the correct 2-D score field that corresponds to the likelihood of having found the correct position, and eyewall diameter if an eyewall is identifiedposition, and eyewall diameter if an eyewall is identified

• Currently operates on the following:Currently operates on the following:

Basic ARCHER ApproachBasic ARCHER Approach

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””

Circulation is indicated by spirally-oriented bands caused by convergent flow and horizontal shearing

Spiral-fitting conceptSpiral-fitting concept

Algorithm: determine the alignment of the image gradients with a spiral vector field

Spiral-fitting conceptSpiral-fitting concept

““Spiral ScoreSpiral Score”” component component

• Calculated at every sample point (dot) on Calculated at every sample point (dot) on the TC image, then interpolated to the the TC image, then interpolated to the resolution of the image (contour plot)resolution of the image (contour plot)

• 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

(lon, lat)gradient of the log of the image

spiral unit vector field centered on (,)

““Ring scoreRing score”” component component

• The scores are proportional to the The scores are proportional to the average dot product of the image average dot product of the image gradient and a radial unit vector on a ringgradient and a radial unit vector on a ring

• Ring scores are assigned to the center Ring scores are assigned to the center of a ring of points inside an eyewallof a ring of points inside an eyewall

Combined (final) ARCHER scoreCombined (final) ARCHER score

• wwSSSS is the is the ““relative weightrelative weight”” (next slide) (next slide)

• Lat/Lon of max(CS) point is final Lat/Lon of max(CS) point is final ARCHER estimate of TC center fix ARCHER estimate of TC center fix

“First guess”

Center fix

Best track

Additional ProceduresAdditional Procedures

• Images are pre-processed to compensate for any parallax shift, and Images are pre-processed to compensate for any parallax shift, and then resampled to a 0.05then resampled to a 0.05 rectangular grid rectangular grid

• We introduce a small We introduce a small ““penaltypenalty”” for positions that stray far from the first for positions that stray far from the first guess, to help mitigate gross errorsguess, to help mitigate gross errors

• If the Combined Score does not exceed a fixed threshold value, then If the Combined Score does not exceed a fixed threshold value, then the algorithm can default back to the first guess (OFC forecast) positionthe algorithm can default back to the first guess (OFC forecast) position

• The relative weight and the combined score thresholds are dependent The relative weight and the combined score thresholds are dependent on sensor type, and for MW are calibrated for three modes that each on sensor type, and for MW are calibrated for three modes that each behave differently under the ARCHER scheme: Tropical Storm, Cat 1, behave differently under the ARCHER scheme: Tropical Storm, Cat 1, and Cat 2-5 strength TCsand Cat 2-5 strength TCs

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

1) Wider domain1) Wider domain


2) Zoomed view 2) Zoomed view


3) With best track position3) With best track position


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


5) Spiral score5) Spiral score


6) Ring score6) Ring score


7) Combined score7) Combined score


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

“First guess”

Center fix

Best track

Example: Evolving eyewall (Chaba 2010)Example: Evolving eyewall (Chaba 2010)

1. Complete eyewall1. Complete eyewall

Center-fix

Example: Evolving eyewall Example: Evolving eyewall

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

Center-fix

Example: Evolving eyewallExample: Evolving eyewall

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

Center-fix


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

Center-fix


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

Center-fix


6. Completed eyewall replacement cycle6. Completed eyewall replacement cycle

Center-fix

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

• Independent from calibration sample, Independent from calibration sample, 85GHz only85GHz only

• 40% tropical storm, 20% Cat 1, 40% Cat 2-540% tropical storm, 20% Cat 1, 40% Cat 2-5

• Simulated forecast position errors of 0.1Simulated forecast position errors of 0.1, 0.4, 0.4 and 0.7 and 0.7 for each image, weighted for each image, weighted to match the distribution of typical forecast fix errors in the NATLto match the distribution of typical forecast fix errors in the NATL

• Validation uses cases that are < 3 hours from an aircraft position fix. NHC Best Validation uses cases that are < 3 hours from an aircraft position fix. NHC Best Track is used as “truth.”Track is used as “truth.”

Validation Results, 85-92 GHzValidation Results, 85-92 GHz

• The RMS errors have been adjusted to account for the displacement The RMS errors have been adjusted to account for the displacement between the rotational center at the surface and at the image levelbetween the rotational center at the surface and at the image level

• Errors are ~5% larger in other basins due to greater OFC forecast Errors are ~5% larger in other basins due to greater OFC forecast position errorposition error

• Errors improve with increasing Vmax (organization/structure)Errors improve with increasing Vmax (organization/structure)

Trop. Storm Cat 1 Cat 2-5 All

Default rate 83% 15% 0.01% 37%

% worsened 0.8% 0.1% 0.0% 0.4%

RMSE (w/o defaults)

0.17 0.060 0.070 0.064

RMSE (all) 0.22 0.10 0.070 0.15

Defaults are defined as those cases where ARCHER did notexceed thresholds and the first guess forecast position is retained

ARCHER: Adapting to IR imageryARCHER: Adapting to IR imagery

• The ADT (next presentation by Olander) employs a forerunner version of ARCHER that operates The ADT (next presentation by Olander) employs a forerunner version of ARCHER that operates on IR data.on IR data. It It uses an ad hoc rules-based approach and is very resilient to big false-positives.

• We are developing a more effective ARCHER-IR method with better cal/val, good theoretical connections to ARCHER-MW, and including uncertainty information.

• Latest scheme still under developmentLatest scheme still under development

(Low organization)

Organization score = 0.91

(Medium organization)


(High organization)


ARCHER-IR: Example output ARCHER-IR: Example output

• 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

Cal/Val results, All IR imageryCal/Val results, All IR imagery

• The independent validation showed probabilities greater than or equal The independent validation showed probabilities greater than or equal to these benchmark certainty valuesto these benchmark certainty values• It is not necessary to vary any ARCHER parameters with TC intensity. It is not necessary to vary any ARCHER parameters with TC intensity. (Not so with MW.)(Not so with MW.)

% of sample Prob. error < 0.2° Prob. error < 0.4° Prob. error < 1.0°

No center-fix 26% -- -- --

Lowest bin of Organization Score

4% 8% 23% 66%

Second bin 23% 16% 41% 87%

Third bin 27% 41% 77% 99%

Highest bin 19% 67% 95% 100%

• ARCHER MW intensity estimates are now integrated into the Advanced Dvorak ARCHER MW intensity estimates are now integrated into the Advanced Dvorak Technique algorithm (further details in next presentation on the ADT)Technique algorithm (further details in next presentation on the ADT)

Method:Method: Score is based on the robustness of the eyewall structure as depicted in 85GHz Score is based on the robustness of the eyewall structure as depicted in 85GHz

brightness temperatures, and is objectively determined from two parameters:brightness temperatures, and is objectively determined from two parameters:1)1) ““Difference componentDifference component””: Measure the difference between the warmest pixel in the : Measure the difference between the warmest pixel in the

eye and the warmest pixel on the eyewall ring (similar to the Dvorak Technique)eye and the warmest pixel on the eyewall ring (similar to the Dvorak Technique)

2)2) ““Completeness componentCompleteness component””: Add 15 points to the score if …: Add 15 points to the score if …o >85% of the points on the eyewall are <232K (>85% of the points on the eyewall are <232K (““the absolute measurethe absolute measure””) OR) ORo >85% of the points on the eyewall are >20K colder than the warmest pixel in the eye >85% of the points on the eyewall are >20K colder than the warmest pixel in the eye

((““the relative measure)the relative measure)

MW scores are generally between 0 (no structure, weak TC) and 100 (powerful TC)MW scores are generally between 0 (no structure, weak TC) and 100 (powerful TC) Conversion to ADT VmaxConversion to ADT Vmax: : Scores >20 Scores >20 Vmax ≥ 72 kts, Scores >60 Vmax ≥ 72 kts, Scores >60 Vmax ≥ 90 kts Vmax ≥ 90 kts

Example: Image for Example: Image for TC 26W (2009)TC 26W (2009) [24 Nov 1052 [24 Nov 1052

UTC]UTC]

Difference component: 268K (eye pixel) - 251K (warmest Difference component: 268K (eye pixel) - 251K (warmest eyewall pixel) = 17 pointseyewall pixel) = 17 points

Completeness component: 93% of eyewall pixels >20K Completeness component: 93% of eyewall pixels >20K colder than warmest pixel in eye colder than warmest pixel in eye +15 points +15 points

Result: Score: 17+15 = 32 Result: Score: 17+15 = 32 ADT Vmax = 72 kts (JTWC ADT Vmax = 72 kts (JTWC estimate was 65 kts at this time)estimate was 65 kts at this time)

ARCHER Microwave Intensity ApplicationARCHER Microwave Intensity Application

Application of the MW intensity scores to the ADTApplication of the MW intensity scores to the ADT

1. If the MW score exceeds 20, the ADT current intensity value is reset to 72kts IF the ADT has not yet identified an EYE scene type.

2. If the MW score exceeds 60, the ADT current intensity value is reset to 90kts IF the ADT has not yet identified an EYE scene type.

3. If the ADT analyzes an EYE scene before the MW scores exceed the 20 threshold, then the MW is not used.

4. Currently, the MW scores are only employed in the ADT for TC formative stages. The ARCHER method’s estimates are not robust enough in other TC stages, as indicated by validation studies. An approach being developed at NRL may be promising (later presentation by Hawkins).

ARCHER-ADT Methodology SummaryARCHER-ADT Methodology Summary

SummarySummary• A fully automated and objective TC center finding routine based solely on A fully automated and objective TC center finding routine based solely on satellite imagery has been developed, called ARCHER. satellite imagery has been developed, called ARCHER.

• The primary version that operates on 85GHz passive microwave imagery The primary version that operates on 85GHz passive microwave imagery has been fully tested and validated, with an overall RMS center-fix position has been fully tested and validated, with an overall RMS center-fix position error of 0.15error of 0.15. In general, accuracy increases with TC intensity.. In general, accuracy increases with TC intensity.

• A new version still under development for geostationary IR imagery yields a A new version still under development for geostationary IR imagery yields a center fix along with a certainty estimate, allowing more options for the end-center fix along with a certainty estimate, allowing more options for the end-user.user.

• ARCHER can also diagnose intensity estimates from 85GHz imagery in ARCHER can also diagnose intensity estimates from 85GHz imagery in developing TC cases. These estimates are now passed to the ADT.developing TC cases. These estimates are now passed to the ADT.

• Other ARCHER applications not discussed here include TC visualization, Other ARCHER applications not discussed here include TC visualization, eyewall diameter retrieval, rapid intensification, 37GHz and Vis apps.eyewall diameter retrieval, rapid intensification, 37GHz and Vis apps.

Final Remarks Final Remarks

DistributionDistribution

• A free, licensed version of ARCHER is available for distribution (Matlab code). The A free, licensed version of ARCHER is available for distribution (Matlab code). The user must have a source for the input satellite data and OFC track forecasts.user must have a source for the input satellite data and OFC track forecasts.

HURSATHURSAT

• ARCHER has been tested by NCDC on the IBTrACS HURSAT dataset (Knapp) and ARCHER has been tested by NCDC on the IBTrACS HURSAT dataset (Knapp) and yields good results, and will be further employed in the IBTrACS project.yields good results, and will be further employed in the IBTrACS project.

Ongoing workOngoing work

• Current research involves a cross-comparison of ARCHER accuracy from microwave, Current research involves a cross-comparison of ARCHER accuracy from microwave, IR and Visible imagery, and deriving an optimal approach to combine coincident IR and Visible imagery, and deriving an optimal approach to combine coincident multispectral results into a single multispectral results into a single ““bestbest”” estimate. estimate.

• Looking into the possibility of extending ARCHER to operate on 37GHz imagery.Looking into the possibility of extending ARCHER to operate on 37GHz imagery.

AcknowledgmentsAcknowledgments

• Special thanks to Jeff Hawkins of the Naval Research Laboratory, and the Office of Naval Research for the support towards the development and continued advancement of the ARCHER!

objective, satellite-based tropical cyclone center-fixing tony wimmers and chris velden university...

Documents

d score field

eyewall slide

numerical score

guess center fix slide

combined score thresholds

estimated center position

image spiral unit vector

ring ring scores