Transcript TC Intensity Estimation: SATellite CONsensus (SATCON) Derrick Herndon, Chris Velden, Tony Wimmers, Tim Olander University of Wisconsin - Madison Cooperative Institute for Meteorological Satellite Studies Jeff Hawkins Naval.

TC Intensity Estimation: SATellite
CONsensus (SATCON)
Derrick Herndon, Chris Velden, Tony
Wimmers, Tim Olander
University of Wisconsin - Madison
Cooperative Institute for Meteorological
Satellite Studies
Jeff Hawkins
Naval Research Laboratory Monterey, CA
International Workshop on Tropical Cyclone Analysis and Intensity
Honolulu, HI
13-16 April 2011
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)
140
130
120
110
100
90
80
70
60
50
40
30
6 :0 0
6 :0 0
8 :0 0
1 2 :0 0
1 8 :0 0
5 :0 0
4 :0 0
1 8 :0 0
7 :0 0
9 -Sep
1 0 -Sep
1 0 -Sep
1 1 -Sep
1 2 -Sep
1 8 -Sep
1 9 -Sep
1 9 -Sep
2 0 -Sep
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)
140
130
120
110
100
90
80
70
60
50
40
30
6 :0 0
6 :0 0
8 :0 0
1 2 :0 0
1 8 :0 0
5 :0 0
4 :0 0
1 8 :0 0
7 :0 0
9 -Sep
1 0 -Sep
1 0 -Sep
1 1 -Sep
1 2 -Sep
1 8 -Sep
1 9 -Sep
1 9 -Sep
2 0 -Sep
B2
B lind M ean
Rec on
B1
B5
B3
B4
SATCON Members
ADT (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
Uniform
Curved Band
Shear
SATCON Members: CIMSS AMSU
Channel 8
150 mb
Channel 7
250 mb
Channel 6
350 mb
55 Knots
AMSU TbAMSU-A
Anomaly
cross
Chanel 8 Tb vertical
Anomaly vs Recon
Del-P section for Katrina 2005
TC Pressure Anomaly Magnitude
120
-1
100
70 Knots
80
60
40
20
0
0
1
2
3
4
5
6
7
AMSU Channel 8 Tb Anomaly Magnitude
8
125 knots
SATCON Members: CIRA AMSU
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.
IR image from NRL TC Page
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
SATCON cross-method information sharing
Example: ADT to CIMSS AMSU
ADT Estimate of Eye Size
In clear eye scenes, IR can
be used to estimate eye size
Compare to AMSU-A
FOV resolution
Adjust AMSU
pressure if
needed
CIMSS AMSU uses eye size
information to correct
resolution sub-sampling
SATCON cross-method information sharing
Example: Objective estimates of eye size from CIMSS
‘ARCHER’ method (using MW imagery)
Currently, CIMSS AMSU method uses IRbased 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
ARCHER eye = 33 km
Information can be input to CIMSS
AMSU method
SATCON cross-method information sharing
CIMSS AMSU position with bracketing correction can be
applied to correct CIRA AMSU estimate
CIRA MSW Error Compared to AMSU-B Tb Near TC Center
-70
R2 = 0 .1 7 9 1
-60
-50
-30
-20
-10
20
10
0
-10
-20
-30
-40
0
10
20
30
AMS U-B 89 Gh z Tb For FO V Use d for Estim ate
-50
-60
-70
MSW Error (knots)
-40
SATCON Weighting Scheme
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)
Example: ADT Scene type vs. performance
CDO
RMSE 14 knots
EYE
RMSE 12 knots
SHEAR
RMSE 18 knots
SATCON Weighting Scheme
Example: AMSU scan geometry vs. performance
A
CIRA RMSE 12 knots
CIMSS RMSE 10 knots
B
CIRA RMSE 15 knots
CIMSS RMSE 12 knots
C
CIRA RMSE 18 knots
CIMSS RMSE 15 knots
Additional SATCON Adjustments
• 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
SATCON Examples
ADT determines scene
is an EYE scene
B
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 %
SATCON Examples
Center of TS Chris
ADT determines situation
is a SHEAR scene
CIMSS AMSU indicates no
sub-sampling present
CIRA AMSU: little/no subsampling error due to position
offset from FOV center
SATCON Weighting:
ADT = 18 % CIMSS AMSU =41 % CIRA AMSU = 41 %
1999-2010 SATCON Performance (Vmax)
N = 289
CIMSS
AMSU
CIMSS
ADT
CIRA
AMSU
SATCON
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
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
1999-2010 SATCON Performance (Vmax) WPAC
N = 18
CIMSS
AMSU
CIMSS
ADT
CIRA
AMSU
SATCON
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
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
1999-2010 SATCON Performance (MSLP)
N = 289
CIMSS
AMSU
CIMSS
ADT
CIRA
AMSU
SATCON
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
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
1999-2010 SATCON Performance
Comparison to simple ave/consensus (un-weighted)
N = 289
SIMPLE
MSW
SATCON
MSW
SIMPLE
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
Independent sample. Validation is coincident with aircraft recon +/- 3 hours from
estimate time. Negative bias = method was too weak.
SATCON and Dvorak MSW Stats for 1999-2010 Independent SATCON Sample
Binned by Category
12
10
8
Knots
6
4
2
N =6 7
N =1 3 9
N =8 3
0
-2
-4
-6
T D-T S
C A T 1-2
C A T 3-5
SA T C O N BI A S
D V K BI A S
SA T C O N A BS E RR
D V K A BS E RR
SA T C O N RM SE
D V K RM SE
HURRICANE PALOMA 2008
130
120
110
100
MSW (knots)
90
80
70
60
50
40
30
110607
110618
110622
110707
110710
110718
110721
110807
110810
110818
Date (MMDDHH)
s atc on new
rec on
dvk
s atc on_old
C I M SS A M SU
A DT
C I R A A M SU
HURRICANE KATRINA 2005
170
160
150
140
130
MSW (knots)
120
110
100
90
80
70
60
50
40
30
082408
082419
082511
082611
082720
082808
082812
082820
082908
082912
Date (MMDDHH)
s atc on new
rec on
dvk
s atc on_old
C I M SS A M SU
A DT
C I R A A M SU
HURRICANE RITA 2005
160
150
140
130
120
MSW (knots)
110
100
90
80
70
60
50
40
30
20
092320
092312
092220
092209
092120
092011
091908
091819
091810
091808
Date (MMDDHH)
s atc on new
rec on
dvk
s atc on_old
C I M SS A M SU
A DT
C I R A A M SU
HURRICANE BILL 2009
140
130
120
110
MSW (knots)
100
90
80
70
60
50
40
30
082310
082306
082207
082120
082109
082021
081917
081908
081820
081817
Date (MMDDHH)
s atc on new
rec on
dvk
s atc on_old
C I M SS A M SU
A DT
C I R A A M SU
HURRICANE RITA 2005
160
150
140
130
120
MSW (knots)
110
100
90
80
70
60
50
40
30
20
092320
092312
092220
092209
092120
092011
091908
091819
091810
091808
Date (MMDDHH)
s atc on new
rec on
dvk
s atc on_old
C I M SS A M SU
A DT
C I R A A M SU
SATCON Web Site
http://cimss.ssec.wisc.edu/tropic2/real-time/satcon
References
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 TropicalCyclone 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 SatelliteBased 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.
Analysis of Sat-Based TC Intensity
Estimation in the WNP During TCS-08
Comparison of All Satellite-based Estimates – Vmax (Kts)
N=14
‘Blind’
Dvorak
Consensus
Oper
Dvorak
Consensus
ADT
CIMSS
SATCON
AMSU
w/MW
(w/Koba)
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
Analysis of Sat-Based TC Intensity
Estimation in the WNP During TCS-08
Comparison of All Satellite-based Estimates – MSLP (mb)
N=14
‘Blind’
Dvorak
Consensus
Oper
Dvorak
Consensus
ADT
CIMSS
SATCON
AMSU
w/MW
(w/Koba)
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= 4.7
Blind and Oper Dvorak conversion is Knaff/Zehr