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

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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

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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

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• 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

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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 =

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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

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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

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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

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Chaneel 6 Tb Anomaly (K)

AMSU Channel 7 Tb vs Delta_P

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Channel 7 Tb Anomaly (K)

AMSU Channel 8 vs Delta_P

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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

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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