Post on 15-Jan-2016
description
TC Intensity Estimation: SATellite TC Intensity Estimation: SATellite CONsensus (SATCON)CONsensus (SATCON)
Derrick Herndon, Chris Velden, Tony Wimmers, Tim Olander
International Workshop on Tropical Cyclone Analysis and IntensityInternational Workshop on Tropical Cyclone Analysis and IntensityHonolulu, HI 13-16 April 2011Honolulu, HI 13-16 April 2011
University of Wisconsin - Madison
Cooperative Institute for Meteorological Satellite Studies
Jeff HawkinsNaval Research Laboratory Monterey, CA
The support of the research sponsors, the Oceanographer of the Navy through the program office at the PEO C4I&Space/PMW-120, under program element PE-0603207N and the Office of Naval Research under program element PE-0602435N is gratefully acknowledged.
Motivation
• Contemporary methods to estimate TC intensity can vary by more than 40 knots
• Several objective TC intensity methods exist, but the goal of SATCON is to assess the current intensity by combining the confident aspects of the individual objective estimates into a single “best” estimate
TCS-08 result showing the spread of 5 expert Dvorak analysts for TY Sinlaku (15W) who were blind to recon obs
Recon vs Dvorak for 15W (MSW)
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B1 B5 B3 B4 B2
Even taking an average of five expert Dvorak intensity
estimates can lead to significant differences.Recon vs Dvorak for 15W (MSW)
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Recon B1 B5 B3 B4 B2 Blind Mean
SATCON MembersADT (Advanced Dvorak Technique)
Uses IR imagery to objectively assess storm cloud patterns and structure to infer intensity
Latest version uses information from MW to make adjustments
Clear Eye Pinhole Eye Large Eye
ShearCurved Band Uniform
SATCON Members: CIMSS AMSU
Channel 6
Channel 7
Channel 8
350 mb
250 mb
150 mb
AMSU Tb Anomaly vertical cross section for Katrina 2005
70 Knots
125 knots
55 Knots
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-1 0 1 2 3 4 5 6 7 8
AMSU Channel 8 Tb Anomaly MagnitudeTC
Pre
ssu
re A
nom
aly
Mag
nit
ud
e
SATCON Members: CIRA AMSU
IR image from NRL TC Page
Similar to CIMSS approach, however the AMSU-A Tb are used to retrieve a temperature profile at 23 pressure levels. Estimates of Vmax are then determined from the thermal warm core structure and non-linear balance equation.
SATCON Strategy
The strengths and weaknesses of each objective method are assessed based on
statistical analysis, and that knowledge is used to assign weights to each method in the
consensus algorithm based on situational performance to arrive at a single superior
intensity estimate
Another important component of SATCON is cross-method information sharing
• Utilize relationships that exist between the output parameters of the individual member algorithms
• Unique information from each of these parameters can be shared between the algorithms to improve the performance of the individual members
• Situational corrections can be made to each algorithm’s intensity output, then the member weights re-derived to produce an improved consensus estimate
Adjust AMSU pressure if
needed
SATCON cross-method information sharing
ADT Estimate of Eye Size
Compare to AMSU-A FOV resolution
In clear eye scenes, IR can be used to estimate eye size
CIMSS AMSU uses eye size information to correctresolution sub-sampling
Example: ADT to CIMSS AMSU
Example: Objective estimates of eye size from CIMSS ‘ARCHER’ method (using MW imagery)
Currently, CIMSS AMSU method uses IR-based eye size or values from op center if no eye in IR
MW imagery (MI) often depicts eyes when IR/ADT cannot
ARCHER method (Wimmers and Velden, 2010) uses objective analysis of MI and accounts for eyewall slope
SATCON cross-method information sharing
ARCHER eye = 33 km Information can be input to CIMSS AMSU method
SATCON cross-method information sharing
CIRA MSW Error Compared to AMSU-B Tb Near TC Center
R2 = 0.1791
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AMSU-B 89 Ghz Tb For FOV Used for Estimate
MS
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rror
(k
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CIMSS AMSU position with bracketing correction can be applied to correct CIRA AMSU estimate
SATCON Weighting Scheme
Example: ADT Scene type vs. performance
Weights are based on situational analysis for each member• Separate weights for MSW and MSLP estimates• Example criteria: scene type (ADT) scan geometry/sub-sampling (AMSU)
RMSE 14 knots RMSE 12 knots RMSE 18 knots
CDO EYE SHEAR
CIRA RMSE 12 knotsCIMSS RMSE 10 knots
CIRA RMSE 15 knotsCIMSS RMSE 12 knots
CIRA RMSE 18 knotsCIMSS RMSE 15 knots
A B C
Example: AMSU scan geometry vs. performance
SATCON Weighting Scheme
• Use ARCHER scores to determine how much motion component to add. A greater component is added to storms with strong well developed eyewalls, and less component for storms with poor inner core structure
• Use the statistically superior SATCON MSLP estimate to estimate MSW using TC structure information. Take an average of this P-W derived MSW estimate and the SATCON MSW weighted estimate to get final MSW
• ARCHER TC eye size is used to adjust MSW upward for for small eyes and downward for large eyes
Additional SATCON Adjustments
SATCON Examples
ADT determines scene is an EYE scene
CIMSS AMSU: Good near nadir pass. Eye is well-resolved by AMSU resolution
CIRA is sub-sampled by FOV offset with TC center
SATCON Weighting:ADT = 28 % CIMSS AMSU =47 % CIRA AMSU = 25 %
B
SATCON Examples
ADT determines situation is a SHEAR scene
CIMSS AMSU indicates no sub-sampling present
CIRA AMSU: little/no sub-sampling error due to position offset from FOV center
SATCON Weighting:ADT = 18 % CIMSS AMSU =41 % CIRA AMSU = 41 %
Center of TS Chris
1999-2010 SATCON Performance (Vmax)
Independent sample. Values in knots. Validation is Best Track Vmax coincident with aircraft recon +/- 3 hours from estimate time. Negative bias = method was too weak.
Important Note: “Dvorak” performance values are derived from a consensus of available estimates (the consensus is usually superior to individual OFC estimates
N = 289CIMSS
AMSU
CIMSS
ADT
CIRA
AMSUSATCON Dvorak
BIAS 0.6 - 2.0 -7.1 - 0.5 - 1.9
AVG ERROR
8.7 10.5 11.7 7.1 7.7
RMSE 11.1 14.3 15.6 8.9 9.9
Cases: ATL = 263 EPAC = 8 WPAC = 18
1999-2010 SATCON Performance (Vmax) WPAC
Independent sample. Values in knots. Validation is Best Track Vmax coincident with aircraft recon +/- 3 hours from estimate time. Negative bias = method was too weak.
Important Note: “Dvorak” performance values are derived from a consensus of available estimates (the consensus is usually superior to individual OFC estimates
N = 18CIMSS
AMSU
CIMSS
ADT
CIRA
AMSUSATCON Dvorak
BIAS - 3.7 - 2.0 -7.2 - 1.5 - 4.9
AVG ERROR
7.37 10.5 14.0 8.4 10.8
RMSE 9.0 14.3 17.0 9.9 12.5
1999-2010 SATCON Performance (MSLP)
Independent sample. Values in millibars. Validation is coincident with aircraft recon +/- 3 hours from estimate time. Negative bias = method was too weak.
Important Note: “Dvorak” performance values are derived from a consensus of available estimates (the consensus is usually superior to individual OFC estimates
N = 289CIMSS
AMSU
CIMSS
ADT
CIRA
AMSUSATCON Dvorak
BIAS 0.3 - 2.5 -2.6 0.1 -2.0
AVG ERROR
5.4 8.9 6.8 4.6 6.8
RMSE 7.3 12.5 10.4 6.5 9.3
Cases: ALT = 263 EPAC = 8 WPAC = 18
1999-2010 SATCON PerformanceComparison to simple ave/consensus (un-weighted)
Independent sample. Validation is coincident with aircraft recon +/- 3 hours from estimate time. Negative bias = method was too weak.
N = 289SIMPLE
MSWSATCON
MSWSIMPLE MSLP
SATCON MSLP
BIAS - 3.0 - 0.3 -1.6 0.1
AVG ERROR
8.1 7.6 5.0 4.6
RMSE 10.5 9.6 7.5 6.5
Cases: ALT = 263 EPAC = 8 WPAC = 18
SATCON and Dvorak MSW Stats for 1999-2010 Independent SATCON SampleBinned by Category
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TD-TS CAT 1-2 CAT 3-5
Kn
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SATCON BIAS DVK BIAS SATCON ABS ERR
DVK ABS ERR SATCON RMSE DVK RMSE
N=139N=67
N=83
HURRICANE PALOMA 2008
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satcon new recon dvk satcon_old CIMSS AMSU ADT CIRA AMSU
HURRICANE KATRINA 2005
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satcon new recon dvk satcon_old CIMSS AMSU ADT CIRA AMSU
HURRICANE RITA 2005
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satcon new recon dvk satcon_old CIMSS AMSU ADT CIRA AMSU
HURRICANE BILL 2009
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satcon new recon dvk satcon_old CIMSS AMSU ADT CIRA AMSU
HURRICANE RITA 2005
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satcon new recon dvk satcon_old CIMSS AMSU ADT CIRA AMSU
SATCON Web Site
http://cimss.ssec.wisc.edu/tropic2/real-time/satcon
Brueske K. and C. Velden 2003: Satellite-Based Tropical Cyclone Intensity Estimation Using the NOAA-KLM Series Advanced Microwave Sounding Unit (AMSU). Monthly Weather Review Volume 131, Issue 4 (April 2003) pp. 687–697
Demuth J. and M. DeMaria, 2004: Evaluation of Advanced Microwave Sounding Unit Tropical-Cyclone Intensity and Size Estimation Algorithms. Journal of Applied Meteorology Volume 43, Issue 2 (February 2004) pp. 282–296
Herndon D. and C. Velden, 2004: Upgrades to the UW-CIMSS AMSU-based TC intensity algorithm.Preprints, 26th Conference on Hurricanes and Tropical Meteorology, Miami, FL, Amer. Meteor. Soc., 118-119
Olander T. and C. Velden 2007: The Advanced Dvorak Technique: Continued Development of an Objective Scheme to Estimate Tropical Cyclone Intensity Using Geostationary Infrared Satellite Imagery. Wea. and Forecasting Volume 22, Issue 2 (April 2007) pp. 287–298
Velden C. et al., 2006: The Dvorak Tropical Cyclone Intensity Estimation Technique: A Satellite-Based Method that Has Endured for over 30 Years. Bulletin of the American Meteorological Society Volume 87, Issue 9 (September 2006) pp. 1195–1210
Wimmers, A., and C. Velden, 2010: Objectively Determining the Rotational Center of Tropical Cyclones in Passive Microwave Satellite Imagery. Submitted to JAMC.
References
Analysis of Sat-Based TC Intensity Analysis of Sat-Based TC Intensity Estimation in the WNP During TCS-08Estimation in the WNP During TCS-08
N=14‘Blind’
DvorakConsensus
OperDvorakConsensus
(w/Koba)
ADTw/MW
CIMSSAMSU
SATCON
Bias 3.6 2.0 -3.6 2.9 -0.1
Abs Error
9.3 12.0 13.6 8.6 9.0
RMSE 11.9 14.9 17.4 10.1 10.6
Positive Bias indicates method estimates are too strong
Comparison of All Satellite-based Estimates – Vmax (Kts)
Analysis of Sat-Based TC Intensity Analysis of Sat-Based TC Intensity Estimation in the WNP During TCS-08Estimation in the WNP During TCS-08
N=14‘Blind’
DvorakConsensus
OperDvorakConsensus
(w/Koba)
ADTw/MW
CIMSSAMSU
SATCON
Bias 0.7 0.1 -1.0 -1.9 -1.3
Abs Error
5.2 7.5 10.7 4.9 6.0
RMSE 6.6 8.9 12.8 6.3 7.2
Positive Bias indicates method estimates are too strong. 2mem SATCON RMSE= 4.7Blind and Oper Dvorak conversion is Knaff/Zehr
Comparison of All Satellite-based Estimates – MSLP (mb)