Tropical Cyclone Intensity Estimation Using Advanced Microwave Sounding Unit (AMSU)

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Tropical Cyclone Intensity Estimation Using Advanced Microwave Sounding Unit (AMSU) Derrick Herndon UW-Madison CIMSS Mark DeMaria NOAA/NESDIS/CIRA Kurt F. Brueske, Major, USAF United States Air Force Academy Department of Physics Chris Velden UW-Madison CIMSS John Knaff Colorado Institute for Research in the Atmosphere (CIRA)

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Tropical Cyclone Intensity Estimation Using Advanced Microwave Sounding Unit (AMSU). Derrick Herndon UW-Madison CIMSS. Chris Velden UW-Madison CIMSS. John Knaff Colorado Institute for Research in the Atmosphere (CIRA). Kurt F. Brueske, Major, USAF - PowerPoint PPT Presentation

Transcript of Tropical Cyclone Intensity Estimation Using Advanced Microwave Sounding Unit (AMSU)

Page 1: Tropical Cyclone Intensity Estimation Using Advanced Microwave Sounding Unit (AMSU)

Tropical Cyclone Intensity Estimation UsingAdvanced Microwave Sounding Unit (AMSU)

Derrick HerndonUW-Madison CIMSS

Mark DeMariaNOAA/NESDIS/CIRA

Kurt F. Brueske, Major, USAFUnited States Air Force Academy Department of Physics

Chris VeldenUW-Madison CIMSS

John KnaffColorado Institute for Research in the Atmosphere (CIRA)

Page 2: Tropical Cyclone Intensity Estimation Using Advanced Microwave Sounding Unit (AMSU)

Tropical Cyclone Intensity Estimation Using NOAA-KLM SeriesAdvanced Microwave Sounding Unit (AMSU)

Warm Core Observations

• MSLP estimates derived from AMSU-A radiances - Provides measure of upper level warm anomaly magnitude - Channels 7 and 8 located at average ht of anomaly (150-250mb) - Anomaly strength directly related to intensity

929hPaHurricane Inez 1966 Hurricane Floyd 1999

• AMSU flown aboard NOAA 15, 16 and 17 as well as Aqua - 6 estimates per day (2 more with Aqua)

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CIRA AMSU Tropical Cyclone Algorithm

V(r,Sample r/z tangential windcross-section from AMSUretrieval (steps 1-4)

1. Retrieve T(x,y,z) from all AMSU-A channels2. Correct T for rain and ice effects3. Hydrostatic integration for P(x,y,z) 4. Gradient wind for V(r,z)5. Statistical Prediction Independent Variables: Parameters from retrieved T, P, V Dependent Variables: Max Wind (Vmax) Min Sea-Level Pressure (MSLP) Azimuthally averaged radii of 34, 50, 64 kt winds (r34, r50, r64)6. Fit parametric wind model to r34, r50, r64 and storm speed to get asymmetric radii

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2002 Real-Time Test • Algorithm developed from 1999-2001 Sample • 2002 Real-Time Runs

– Initiated at 00, 06, 12, 18 UTC– Storm positions from ATCF– Analysis restricted to storms within 700 km of AMSU data swath– Results sent to TPC via ftp

• Evaluation Samples– 1999-2001 Developmental cases (N=473)– 2002 All Atlantic/East Pacific cases (N=288)– 2002 Atlantic/East Pacific cases with recon (N=64)

• Ground “Truth” for Evaluation– NHC Best Track Vmax and MSLP– NHC Forecast/Advisory for wind radii

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AMSU Estimate Vmax (kt)

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AMSU Estimate MSLP (hPa)

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Predicted R64 (nmi)O

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Predicted R34 (nmi)

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Predicted vs. “Observed” Scatter Plots for 2002 Real-Time Runs(Total and Recon-Only Samples)

Vmax MSLP

R34 R50 R64

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Error Summary for CIRA Algorithm:Developmental, 2002 All and 2002 Recon

Samples

Wind Radii Mean Absolute Error (nmi)

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CIMSS AMSU Tropical Cyclone Algorithm

• Statistical Method Based on 1999-2001 regression against recon obs - Linear fit (R2 = 0.82)

• Independent estimates in 2002 comparable to Dvorak technique

• ATCF message provides RMW (Used as a proxy for anomaly size)

• Improved logic accounts for anomaly height, sub-sampling

• Channel 7 retrieval used to account for storms near limb

FOV 1 FOV 30

Resolution ~ 50km

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2002 Results for Atlantic Basin

Compared to Dvorak (N= 60) in hPa

CIMSS DvorakMean Error 3.24 4.52Std Dev 2.29 3.40Bias -0.28 -0.90RMSE 3.95 5.62

Avg MSLP of sample 1002.4

Atlantic statistics for AMSU versus Recon (+/- 3 hrs) in hPa (N=63)

Mean Error 3.24 Std Dev 2.29 Bias -0.42 RMSE 3.96

Avg MSLP of sample 1002.6

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2002 Atlantic Basin Results

AMSU81% within +/- 0.5T

NOAA/NESDIS Satellite Analysis Branch (SAB) vs.

AMSU (N=34, +/- 2hrs of aircraft reconnaissance)

SAB 78% within +/- 0.5T

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AMSU vs. Recon for Hurricane Isadore

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20 Mile Eye Storm on edge of satellite Swath

(FOV 3)

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Future WorkImprove Technique

• Bias correction when storm is near satellite limb

• Separate treatment of pinhole eye storms using new coefficients

• Time averaging / smoothing

• Add channel 8 retrieval

• Integrate algorithm into NHC/TPC operations

• Addition of AMSU on Aqua (2 more passes per day)

• Basin specific coefficients (need sufficient “observations”)

Confidence Indicator

• Measure Based on FOV, eye size (RMW), anomaly height

Page 12: Tropical Cyclone Intensity Estimation Using Advanced Microwave Sounding Unit (AMSU)

Summary

• Penetrates cloud cover

• 55 Ghz region radiances can quantify inner core thermal structure / changes.

• Temperature anomaly strength directly associated with tropical cyclone intensity

• Skill comparable to, and in some cases better than, the Dvorak estimates

• An important new addition to the forecaster “tool kit”

AMSU provides unique tropical cyclone perspective

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Conclusions from 2002 Evaluation• Vmax, MSLP (CIRA):

– 2002 (independent) performance very similar to (slightly improved) over dependent sample

– Intensity underestimated for small-cored systems• Wind Radii (CIRA Method):

– 2002 recon-only errors generally similar to dependent sample– Tendency for high bias for R50 and R64– Observed R50 and R64 more asymmetric than predicted

• Addition of second AMSU channel (CIMSS): – Accounts for variability in TC temperature anomaly height

• Improvements resulting from advanced algorithm logic (CIMSS): – Based on evaluation of 3 years of estimates, continues to evolve

• Additional improvements foreseen in 2003:– Characterization and new regressions for small-cored storms

• JHT pathway in 2003:– Continue evaluation of 2002 performance– Implement algorithm upgrades and re-evaluate after 2003 season– If successful and approved, activate improved algorithms at TPC