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TC Intensity Estimation From Satellite TC Intensity Estimation From Satellite Microwave SoundersMicrowave Sounders
Derrick Herndon and Chris VeldenDerrick Herndon and Chris Velden
International Workshop on Satellite Analysis of Tropical CyclonesInternational Workshop on Satellite Analysis of Tropical CyclonesHonolulu, HI 13-16 April 2011Honolulu, HI 13-16 April 2011
University of Wisconsin - MadisonUniversity of Wisconsin - Madison
Cooperative Institute for Meteorological Cooperative Institute for Meteorological Satellite StudiesSatellite Studies
Jeff HawkinsJeff HawkinsNaval Research Laboratory Monterey, CANaval Research Laboratory Monterey, CA
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
• Flown aboard NOAA 15-19, METOP and Aqua• 2 Instruments: AMSU-A (temperature), AMSU-B (moisture)• Primary channels of interest are 5-8 on AMSU-A which measure upper-level warm core temperature anomalies that can be directly related to TC intensity
The Advanced Microwave Sounding Unit -- AMSU
Pre
ssu
re
Longitude
AMSU-A Atmos Contribution Functions
Result: AMSU-A Tb Anomaly Cross-Section
AMSU-A Tb
Ch 8
Ch 7
Ch 6
Ch 5
~150 hPa
~250 hPa
~400 hPa
~600 hPa
Relationship Between AMSU TRelationship Between AMSU Tbb Anomaly Anomaly and TC MSLPand TC MSLP
-1
0
1
2
3
4
5
6
7
90092094096098010001020
Channel 8 Tb anomalies (150-200mb) versus collocated and coincident recon MSLP measurements
Sources of Relationship Spread
• Hydrometeor scattering (cooling) near TC core• FoV resolution issues related to TC core size• Juxtaposition of TC core relative to nearest FoV positions
Pressure (mb)
Tb
Ano
mal
y (K
)
• Field of View (FoV) resolution varies across the scan swath due
to the instrument’s cross-track scanning strategy
• Best spatial resolution at nadir is ~50km
• Spatial resolution variability needs to be taken into account
relative to the TC core position in the swath. A TC core-sized
warm anomaly viewed at 50km will be better resolved then at
80km.
AMSU Sensor CharacteristicsAMSU Sensor Characteristics
FOV 1 FOV 30
50 km80km 80 km
NadirLimb Limb
AMSU Sensor CharacteristicsAMSU Sensor CharacteristicsPrecipitation EffectsPrecipitation Effects
Hydrometeor scattering Corrected
• Radiative scattering due to eyewall hydrometeors can act to cool the Tb signal and mask the true warm core signal, especially for channels 6 and 7. The result is an underestimate of intensity.
• This ‘contamination’ can be mitigated by comparing AMSU-A ch. 2 and 15 and then applying a statistical correction to ch. 4-8
TC core
Pressure Anomaly vs Ch6 Raw and Ch6 Corrected
-20
0
20
40
60
80
100
120
-6 -4 -2 0 2 4 6 8
Ch6 Tb Anomaly
Recon Measured Pressure Anomaly
TB6 Corrected Tb6 Raw Poly. (TB6 Corrected)
(K)
Precip Correction – Example: Channel 6
AMSU MSLP Estimate Error vs Eye Size
R2 =
-40.0
-20.0
0.0
20.0
40.0
60.0
80.0
-60.00-50.00-40.00-30.00-20.00-10.000.0010.00
Difference Between Eye Size and FOV Resolution (km)
MSLP Error (mb)
AMSU Sensor Characteristics: AMSU Sensor Characteristics: Sub-Sampling IssuesSub-Sampling Issues
Near Limb Footprint
Nadir Footprint
Compare to AMSU Footprint
Eye Size (~2 x RMW)
Adjust AMSU estimated pressure,
if neededEye size is used as aproxy for warm core size
AMSU FOV
AMSU: Sub-Sampling IssuesAMSU: Sub-Sampling Issues
ADT (IR)
AMSU FOV
ARCHER (MW)
Primary source of eye size: microwave estimate from ARCHER, if available
If ARCHER not available then use IR estimate from ADT
If neither is available use latest OFC estimate (ATCF)
Developing the Relationship Between Developing the Relationship Between AMSU TAMSU Tbb and MSLP and MSLP
-1
0
1
2
3
4
5
6
7
8
90092094096098010001020
For channels 6/7/8, separate well-resolved cases out from the sub-sampled cases to develop the final regression relationships
Pressure (mb)
Tb
Ano
mal
y (K
)
Well-resolved cases
Sub-sampled cases
Developing the Relationship Between Developing the Relationship Between AMSU Tb and MSLPAMSU Tb and MSLP
Summary
• Apply scattering correction to Tb’s
• Remove sub-sampled cases
• Regress Tb to MSLP anomaly for each channel and use relationships for initial estimates of MSLP anomaly
AMSU Channel 6 vs Delta_P
-20
-10
0
10
20
30
40
50
60
70
80
90
100
110
-2 -1 0 1 2 3 4 5 6 7
Chaneel 6 Tb Anomaly (K)
AMSU Channel 7 Tb vs Delta_P
-10
0
10
20
30
40
50
60
70
80
90
100
110
-1 0 1 2 3 4 5 6 7 8
Channel 7 Tb Anomaly (K)
AMSU Channel 8 vs Delta_P
0
10
20
30
40
50
60
70
80
90
100
110
120
-1 0 1 2 3 4 5 6 7 8
Channel 8 Tb Anomaly (K)
TC Pressure Anomaly (mb)
CH 6 CH 7
CH 8
• Storm center may fall between nearest AMSU FOV centers (“Bracketing Effect”)• Results in sub-sampling of the warm core• Use convolved AMSU-B moisture channels to assess• Adjust MSLP (only applied if initial MSLP est < 995 mb)
• TC center between nearest FOVs• AMSU-B 89 Ghz Tb shows adjustment to AMSU TC estimate is necessary
• TC center is well-centered on FOV• AMSU-B 89 Ghz indicates no adjustment needed
AMSU: Another Sub-Sampling IssueAMSU: Another Sub-Sampling Issue
Ch 16 – 89Ghz Ch 16 – 89Ghz
AMSU-B 89 Ghz (convolved) Average Tb VS MSLP Error
-20.0
-10.0
0.0
10.0
20.0
30.0
40.0
50.0
60.0
-60 -50 -40 -30 -20 -10 0 10 20
AMSU-B 89 Gz Tb
MSLP Error (mb)
Relationship used to Adjust MSLP Estimate if “Bracketing Effect” Noted
AMSU-A in center - no correctionAMSU-A partially in eyewall - apply correction
Eye smaller than AMSU-A FOV, - apply correction
Iris 2001: Core is very small and nearest AMSU-A FOV is in moat. Signal suggests (incorrectly) that no correction is required.
Examples
• Start with regressions based on well-resolved cases and estimate pressure anomaly for each channel
• Use a weighted average of each channels pressure anomaly contribution to get the final pressure anomaly
• Make corrections for position within the scan swath (distance from nadir)
• Apply AMSU-B 98 Ghz Tb correction to account for bracketing
• Use estimated eye size to correct for sub-sampling due to resolution
Developing the Relationship Between AMSU Developing the Relationship Between AMSU Tb and MSLPTb and MSLP
• Start by removing storm motion component from the dependent sample validation (Best Track) MSW sample (1-min sust. wind)
• Regress storm-relative MSW against AMSU-measured MSLP anomaly
• Make situational corrections for Tb gradient of inner core, latitude, momentum transfer
• Once all corrections are applied, add storm motion (from BT or ATCF in real time) to AMSU MSW estimate
• AMSU MSW represents a 1-min sust. max sfc wind
AMSU: Max Sfc Winds (MSW) EstimationAMSU: Max Sfc Winds (MSW) Estimation
Inner core gradient contribution to MSW estimate
Tight warm core Warm core expanding
AMSU Ch7 for Hurricane Isabel 2003
AMSU: MSW EstimationAMSU: MSW Estimation
• Account for momentum transfer• Locate strongest 89 Ghz gradient within 150 km of center
AMSU 89Ghz for Hurricane Wilma 2005
Decreased MSW from convective component
AMSU: MSW EstimationAMSU: MSW Estimation
AMSU: PerformanceAMSU: Performance
N = 727N = 727 AMSU AMSU MSLPMSLP
Dvorak Dvorak MSLPMSLP
AMSU AMSU MSWMSW
Dvorak Dvorak MSWMSW
BIASBIAS - 0.1- 0.1 - 2.2- 2.2 - 0.1- 0.1 - 2.1- 2.1
AVG AVG ERRORERROR 5.35.3 6.56.5 7.87.8 7.97.9
RMSERMSE 7.37.3 9.19.1 9.99.9 9.59.5
Dependent Sample 1999-2006
MSLP in hPa, MSW in Kts
Validation is recon-measured central pressure within 3 hours of AMSU pass for MSLP and recon-aided Best Track for MSW
AMSU: PerformanceAMSU: Performance
N = 426N = 426 AMSU AMSU MSLPMSLP
Dvorak Dvorak MSLPMSLP
AMSU AMSU MSWMSW
Dvorak Dvorak MSWMSW
BIASBIAS -0.3-0.3 -2.7-2.7 0.30.3 - 2.6- 2.6
AVG AVG ERRORERROR 5.65.6 6.76.7 8.38.3 7.17.1
RMSERMSE 8.18.1 9.39.3 10.710.7 9.29.2
Independent Sample
MSLP in hPa, MSW in Kts
Validation is recon-measured central pressure within 3 hours of AMSU pass for MSLP and recon-aided Best Track for MSW
AMSU: PerformanceAMSU: Performance
N = 116N = 116 AMSU AMSU MSLPMSLP
Dvorak Dvorak MSLPMSLP
AMSU AMSU MSWMSW
Dvorak Dvorak MSWMSW
BIASBIAS - 0.1- 0.1 - 0.3- 0.3 4.94.9 - 1.2- 1.2
AVG AVG ERRORERROR 3.03.0 3.13.1 7.27.2 3.13.1
RMSERMSE 4.04.0 4.14.1 9.49.4 4.14.1
Independent Sample 2007-2010 Cases < 45 knots
MSLP in hPa, MSW in Kts
Validation is recon-measured central pressure within 3 hours of AMSU pass for MSLP and recon-aided Best Track for MSW
Ongoing/Future WorkOngoing/Future Work• Re-examine MSW estimates using improved motion component
• Address strong bias for weak storms caused by over-correcting Tb’s in the presence of center convection and associated hydrometeor scattering
• Add more Depression-stage cases to the sample
• Use improved fix accuracy from ARCHER position estimates to better correct errors from FOV “bracketing effect”
• Explore SSMIS Sounder as a viable complement to AMSU for TC intensity estimates
SSMISSSMIS
• Flown aboard active DMSP F16-18 satellites
• Atmospheric sounding channels are similar to AMSU
• Slightly different atmos contribution functions and peaks
• Much improved resolution at 37 km which is consistent across the
the scan swath due to the conical scanning strategy
• Improved resolution of co-located imager channels allows for
superior determination of TC structure info (eye size, RMW) at the
time of the sounder TC intensity estimate
SSMISSSMIS
SSMIS F17 compared to AMSU NOAA-15 for Choi-Wan 2009 (15W)
SDR Lower Air Sounder Tb’s adjusted to match AMSU Tb scale. Large eye allows both sensors to resolve warm core
SSMIS 91 Ghz AMSU 89 Ghz
SSMISSSMIS
SSMIS CH4 54.4 Ghz (~300mb) AMSU CH6 54.46 Ghz (~400mb)
SSMISSSMIS
SSMIS CH5 55.5 Ghz (~150mb) AMSU CH8 55.5 Ghz (~180mb)
SSMISSSMIS