iwtc objective tc intensity analysis viii · 120 130 140 6:00 6:00 8:00 12:00 18:00 5:00 4:00 18:00...

Derrick Herndon and Chris Velden

University of Wisconsin - Madison

Cooperative Institute for Meteorological Satellite Studies

8th International Workshop on Tropical Cyclones

December 3, 2014

Jeju, South Korea

Objective TC Intensity Analysis

Microwave Sounders AMSU, SSMIS & ATMS

ADT

ARCHER

Super Typhoon Jelewat 2012

DAV-T

JMA TRMM

IWTC

VIII

• > 85 % of the Tropical Cyclone intensity estimates are based

exclusively on satellite imagery

• TC Intensity Estimate Uncertainty = Forecast Uncertainty

• Dvorak method is good but can provide erroneous estimates

in some situations.

• Increasing the number of skillful TC intensity estimates

improves TC current intensity

Forecast process starts

with current intensity

and position

+ =

IWTC

VIII TC Intensity Analysis: Motivation

Intensity Uncertainty: IBTrACS

Figure 3 from Knaff et al 2010

IWTC


Recon vs Dvorak for 15W (MSW)

30

40

50

60

70

80

90

100

110

120

130

140

6:00 6:00 8:00 12:00 18:00 5:00 4:00 18:00 7:00

9-Sep 10-Sep 10-Sep 11-Sep 12-Sep 18-Sep 19-Sep 19-Sep 20-Sep

B1 B5 B3 B4 B2

Current Intensity Uncertainty: Dvorak

Double Blind Experiment Using 5 Dvorak Experts for Typhoon Sinlaku 2008

IWTC


Recon vs Dvorak for 15W (MSW)

30

40

50

60

70

80

90

100

110

120

130

140

6:00 6:00 8:00 12:00 18:00 5:00 4:00 18:00 7:00

9-Sep 10-Sep 10-Sep 11-Sep 12-Sep 18-Sep 19-Sep 19-Sep 20-Sep

Recon B1 B5 B3 B4 B2 Blind Mean

Current Intensity Uncertainty: Dvorak

Double Blind Experiment Using 5 Dvorak Experts for Typhoon Sinlaku 2008

IWTC


Current Intensity Uncertainty: Forecast Guidance

IWTC


IWTC

VIII

JMA TRMM

CIMSS ARCHER

Microwave Imagers Microwave Sounders

CIRA AMSU

CIMSS AMSU

JMA AMSU

CIMSS SSMIS

CIMSS ATMS

CIRA MTCSWA

SATCON

Ensemble Methods

CIMSS ADT

JMA CLOUD

Univ AZ DAV-T

Geostationary

Review of Current Methods

TC Intensity Analysis

= New Since IWTC-VII

Warmest eye pixel

Eyewall temperatures

Hurricane Dolly, 23 July 2008 1126 UTC

CIMSS Automated Rotational

Hurricane Eye Retrieval (ARCHER)

• Objective and automated passive

microwave intensity and position

estimation from 85-92 GHz imagery

• Intensity component evaluates TC

eyewall completeness and intensity.

• Eyewall completeness score and

eyewall intensity score are combined

for a final score that typically varies

from 0 to 100.

• Scores are roughly correlated with

intensity

- score > 25 represents Vmax > 65 kts

- score > 60 represents Vmax > 85 kts

ARCHER scores have been used by the

ADT since 2008 and the algorithm is now

an integral component of the ADT.

Additionally eye size is computed. Eye size

represents surface eye assuming 45°

slope.

Primary eye size source for AMSU, SSMIS,

ATMS and SATCON

IWTC

VIII TC Intensity Analysis: ARCHER

Microwave,

GEO (Visible, Near-IR, IR),

ASCAT

ARCHER multi-spectral TC position estimation

Objective near real-time position estimates could assist

with several algorithms (Sounders, DAV, CLOUD, etc)

IWTC

VIII TC Intensity Analysis: ARCHER

• Based on Dvorak EIR Technique

• Utilizes “Scene Type” logic tree

• Employs many of the rules and

intensity constraints

• Passive Microwave input since

2008

Spiral Centering

» First guess interpolated from official TC forecast

» Fits 5° log spiral to grid points within search radius around first guess position

» Calculates Tb gradients along spiral; determines position and rotation where minimum exists

Ring Fitting

» Spiral Centering position serves as first guess

» Fits series of rings with different radii at grid points within search region

» Searches for single ring that fits maximum Tb gradients

IWTC

VIII TC Intensity Analysis: CIMSS ADT

Utilization of Passive Microwave (PMW) Intensity Score

– “Organization/Eye Score” If ARCHER scores exceed empirically-

determined thresholds, ADT intensity estimates are adjusted.

– PMW code is now incorporated into latest version

ARCHER Score > 25

ADT T# raised to 4.3

Implementation of Updated TC Wind/Pressure Relationship The ADT estimates TC maximum sustained surface winds. To get the

accompanying minimum SLP, a wind>pressure relationship is used based

on recent research (Courtney et al. 2011).

IWTC

VIII TC Intensity Analysis: ADT

NORTH ATLANTIC – 2010 TC Season

– Independent comparisons between ADT and SAB intensity estimates

– ADT and SAB estimates w/in +/- 30 minutes

– Closest NHC Best Track intensity (co-located w/ aircraft

reconnaissance in situ measurement w/in 2 hours)

106 total matches (homogeneous)

bias aae stdv

SAB:CI# -0.22 0.48 0.57

SAB:Win -1.40 7.77 10.23

SAB:MSL 5.01 8.20 9.78

ADT:CI# -0.02 0.58 0.73

ADT:Win 2.59 8.22 10.47

ADT:MSL 2.22 8.94 11.35

Note: SAB analysts do have access to, or

awareness of, the recon reports. While this

influence is difficult to quantify, it offers a

stringent comparison test for the ADT.

IWTC

VIII TC Intensity Analysis: ADT

University of Arizona Deviation Angle Variance – Technique

Objective IR-based method that measures level of axisymmetry

- Imagery re-sampled to 10 km resolution

- Best Track used for position estimate (new innovation)

- DA calculated at each pixel at a radius from the TC center

- Distribution of DA values is related to intensity

Ideal Case

Real Case

IWTC

VIII TC Intensity Analysis: DAV-T

Fixed radius can present problems in basins

with greater variance in TC size.

Therefore use a 2D parametric surface

to account for this variability.

Method Performance

ATL: RMSE = 12.9 knots (2004-2010)

EPAC: RMSE = 13.4 knots (2005-2011)

WPAC: RMSE = 14.3 knots (2007-2011)

Tendency to be too strong for 25-45 knots

Tendency to be too weak for > 65 knots

*Note very limited ground truth in WPAC

Continued validation efforts, especially

outside the Atlantic

Need for objective TC size estimates

IWTC

VIII TC Intensity Analysis: DAV-T

DAV Estimates for Hurricane Celia 2010

JMA Cloud Grid Information Objective Dvorak Analysis (CLOUD)

Semi-objective IR-based method that provides a continuum of estimates

starting with Early Dvorak Analysis through the Dvorak Technique

Cloud patterns are picked by the analyst

- Early Stage, Curved Band, Eye, Embedded Center, Shear

Manual center location is then

performed

CLOUD then computes a CI#

Estimates are performed hourly and

then a 3 hour average is used for

the CI

JMA CLOUD results compared to aircraft

data during ITOP 2010 (Kishimoto 2014)

IWTC

VIII TC Intensity Analysis: CLOUD

Shanghai Institute TC Intensity Method used at CMA

Use MTSAT digital IR data to extract features within 135 km related to

TC intensity.

Features computed are:

- Number of convective cores

- Distance of these cores to TC center

- Core blackbody temperature

Currently being used to aid in

post-analysis

Performance compared to CMA BT

Vmax = 0.912V6h + 0.009Num + 0.037Lon –

0.035Lat + 0.41DISmin + 0.019TBBdiff + 5.467

IWTC

VIII TC Intensity Analysis: Shanghai

Institute TC Intensity Method

• Flown aboard NOAA 15-19, METOP A/B, Aqua,

FY Series

• 2 Instruments: AMSU-A (temperature)

AMSU-B/MHS (moisture)

• Primary channels of interest are AMSU-A

5-8 and channel 16 on AMSU-B

• Data must be limb-corrected

• 48 km at nadir increasing to > 80 km at limb

Special Sensor Microwave Imager/Sounder

• Flown aboard F16-19

• Primary channels of interest are channels 3-5

(sounder) and channel 17-18 (imager)

• 37.5 km resolution

AMSU/ATMS - CROSSTRACK

SSMIS - CONICAL

IWTC

VIII TC Intensity Analysis: Sounders

Temperature

Sounder

Resolution (km)

Moisture Sounder

/Imager Resolution

(km)

Swath Width

(km)

# of

Sats

Scan

Type

AMSU 48 (nadir) 79 x

149 (limb)

16 (nadir) 27 x 52

(limb) 2340 7

Cross-

track

SSMI

S 37.5 12 1700 4 Conical

ATMS 32 (nadir) 70 x

137 (limb)

16 (nadir) 30 x 68

(limb) 2500 1

Cross-

track

IWTC


Channel 8

Channel 7

Channel 6

Channel 9

CIMSS AMSU Vertical Cross Section of

Tb Anomaly for Typhoon Lekima

AMSU-A Weighting Functions

for channels 3-10

IWTC


Compute environmental temperature

Locate warmest pixel

Calculate Tb 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)

TC

Pre

sure

An

om

aly

(m

b)

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)

TC

Pre

ssu

re A

no

ma

ly (

mb

)


0

10

20

30

40

50

60

70

80

90

100

110

120

-1 0 1 2 3 4 5 6 7 8


TC

Pre

ssu

re A

no

ma

ly (

mb

)

Filter sample to remove all cases where TC eye

is smaller than instrument resolution.

Get relationship between Tb anomaly and

MSLP anomaly

CIMSS Microwave Sounder Intensity Estimation: MSLP

IWTC


Compute environmental temperature

Locate warmest pixel

Calculate Tb anomaly

CIMSS Microwave Sounder Intensity Estimation: MSLP

IWTC


Correct Tbs for Hydrometeor

scattering

- For AMSU use a channel

differencing approach using

channels 2 and 15

Match anomalies to aircraft-measured

MSLP anomaly

Remove all cases where TC is small compared

To AMSU FOV

Under-sampling of TC warm core

due to FOV location offset from true TC position

Near Limb Footprint

Under-sampling of TC warm core

due to small TC eye

Apply bias correction

accounting for eyewall slope

Microwave Sounder MSLP Bias Corrections

IWTC



-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)

TC

Pre

sure

An

om

aly

(m

b)

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


TC

Pre

ssu

re A

no

ma

ly (

mb

)


0

10

20

30

40

50

60

70

80

90

100

110

120

-1 0 1 2 3 4 5 6 7 8


TC

Pre

ssu

re A

no

ma

ly (

mb

)

Compare to Instrument

Footprint

Get TC Eye Size

Adjust MSLP

if needed

Primary source is microwave estimate of eye size

from ARCHER

If ARCHER is not available then use IR estimate of

eye size from ADT

If neither is available use ATCF/Warning agency

estimate

IWTC


CIMSS Microwave Sounder Intensity Estimation: Vmax

Primary term = Instrument-measured MSLP anomaly from MSLP algorithm

Secondary Term = Inner core Tb gradient

Same MSLP for these 2 warm

cores but different Vmax

Third term = Some measure of convective organization/magnitude.

- This relates to the efficiency of mixing

momentum to the surface.

- Derived from 89-91 GHz imagery

- For AMSU use AMSU-B. For

SSMIS/ATMS use ARCHER Again, same MSLP for these

2 storms but different Vmax

Finally: Correct Vmax for storm motion latitude & TC size

IWTC


CIRA AMSU

Statistical-based temperature retrieval at 23 vertical levels

Tbs are corrected to account for CLW and Ice Scattering Attenuation

6 Parameters Used in Multiple Regression to Estimate MSLP and Vmax

- Maximum Tb anomaly, scan resolution

- Derived pressure drop from 0-600 km

- Tangential wind at z= 5 km,

- RMW at z = 3 km

- CLW

Temperature anomly for Typhoon Usagi

September 20 , 2013 1300 UTC

IWTC


Estimates of R34, R50 and R64 are also produced

Estimates of MSLP, Vmax and structure parameters provided to NHC

and JTWC via ATCF

Performance

Algorithm performs best for storms

< 65 knots

Too weak bias when TC eye is small

Vmax MAE = 10.8 knots

Vmax RMSE = 14.0 knots

CIRA AMSU Estimates for Typhoon Usagi

September 20 , 2013 1300 UTC

CIRA AMSU

IWTC


JMA AMSU (2013)

Tb Anomalies derived from AMSU Channels 6-8

Anomalies matched to 22 TCs in 2008 and

tested against 57 TCs in 2009-2011

Algorithm uses maximum anomaly from

AMSU channels 6-8

Bias correction is applied to estimates to

Account for position offset of AMSU FOV

Relative to true TC position based on BT

Scattering of Ice Water (Grody 2001) is used

to correct Tb for attenuation due to

hydrometeors

Validation versus JMA Dvorak Yielded Bias of 0.3 hPa and MAE of 10.1 hPa

IWTC


JMA TRMM Cluster Analysis is performed for 19, 37 and 85 GHz Imagery

Clusters are located either within a radial distance from the TC

center or within quadrants aligned with the TC motion vector

Regression analysis of the Tb associated with these clusters is then

performed

Some subjective re-classifying of the clusters is still necessary

JMA introduced this method in

2014 and further refinements

of the method are expected.

IWTC

VIII TC Intensity Analysis: JMA TRMM

The CSU Fundamental Climate Data Record (FCDR) project provides inter-calibrated SSM/I & SSMIS sensors. (Sapiano et al. 2012; Berg et al. 2012). TMI-AMSR-E data sets provided by NASA. WindSat digital data provided by NRL-DC WindSat team

TMI

AMSR-E/2

WINDSAT

# of TC overpasses

3000

6400

7200

13000

9600

10300

6400

4300

2400

19600

8500

?

~100,000

IWTC

VIII TC Intensity Analysis: Imagers

GOES Visible SSM/I 85 GHz

Microwave imager data provides structural characteristics not always found in typical Vis/IR imagery.

Segmented 85 GHz

Image feature extraction

Machine Learning Application

Leave-One(TC)-Out Cross Validation

Training and Testing

Utilize new NRL TC microwave imager data set with

consistent 89 GHz, 37 GHz Tbs, remapping & recentering

Feature selection to reduce redundant and irrelevant features

IWTC


Extracting TC Features Polar Coordinates Azimuthal Averages

IWTC


TC Feature Extraction: Gradient Axisymmetric

The deviation angle of the gradient vector (calculated at every pixel in a 2 deg radius – left panel) from a radial extending from the center pixel is determined. The variance of the deviation angle of the gradient vector is calculated as the axisymmetric measure. (Courtesy of Liz Ritchie, U. of Arizona)

Stronger storms have more organized rainbands and eyewall features and produce lower deviation variance values (implying higher axisymmetry).

Weaker storms have disorganized rainbands and the variance values are higher (lower axisymmetry).

Best Track: 40 kts Low gradient axisymmetry

Best Track: 90 kts High gradient axisymmetry

Significant convection: Intensity estimate too high without axisymmetry measure.

Minimal convection: Intensity estimate too low without axisymmetry measure.

Θ

IWTC


The strengths and weaknesses of each 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 intensity estimate

ADT CIRA AMSU CIMSS AMSU CIMSS SSMIS

SATCON

IWTC

VIII TC Intensity Analysis: SATCON

Example: ADT Scene type vs. performance

Weights are based on situational analysis for each member

• Weights are RMSE for each member in given scenario

• Example criteria: scene type (ADT)

scan geometry/under-sampling bias (AMSU)

RMSE 14 knots RMSE 12 knots RMSE 18 knots

CDO EYE SHEAR

IWTC


CIRA RMSE 12 knots

CIMSS RMSE 10 knots

CIRA RMSE 15 knots

CIMSS RMSE 12 knots

CIRA RMSE 18 knots

CIMSS RMSE 15 knots

A B C

AMSU weights are dependent on:

• TC position relative to AMSU warm core position

• TC eye size (AMSU resolution is 50 km at nadir)

IWTC


SATCON weighting equation for three member estimate for

both MSLP and Vmax

Interpolate the member estimates then weight the interpolated values.

Result is increased number of members available to match to ADT

Decreases spurious temporal variability

Account for too strong bias at weak TC stage / too weak bias for strongest

storms

IWTC


Changes Made to SATCON Since IWTC-VII

Use SATCON weighted MSLP to get pressure-wind estimate

Make adjustments for TC size (ROCI), latitude and storm motion

Adjust MSW for TC eyes that are smaller/larger than climo

- only use eye size if ARCHER score > 25

Add 2 STD Deviation error bounds

Same MSLP for these 2 storms but different MSW

IWTC


SATCON P-W Pseudo Member

ERC

IWTC


CIMSS SATCON for Hurricane Earl 2010

ERC

IWTC


CIMSS SATCON for Super Typhoon Haiyan 2013

IWTC


CIMSS SATCON for Hurricane Arthur 2014

ATMS

MSW

(Kts)

CIMSS

AMSU

CIMSS

ADT

CIRA

AMSU

CIMSS

SSMIS

SATCO

N

Subj. Dvorak

(Operational)

BIAS -1.0 -0.6 -5.2 - 0.6 -0.7 0.2

AVG

ERROR 10.0 9.0 12.1 8.3 6.7 7.0

RMSE 12.4 11.6 16.0 10.5 8.3 9.2

2006-2012 Homogenous sample of N=275 matches (except CIRA AMSU=187) with NHC recon-aided Best Track

estimates. “Subj. Dvorak” is the average of subjective operational Dvorak estimates from TAFB and SAB.

MSW

(Kts)

CIMSS

AMSU

CIMSS

ADT

CIMSS

SSMIS SATCON

BIAS -1.0 0.2 -1.0 -0.9

AVG ERROR 9.8 9.3 8.2 6.9

RMSE 12.1 12.0 10.4 8.6

SATCON Performance compared to individual members 2006-2012. N= 1467 (interpolated values)

IWTC


N = 18 SATCON

Vmax

Dvorak

Vmax

BIAS - 1.5 - 4.9

AVG ERROR 8.4 10.8

RMSE 9.9 13.1 SUMMARY

A weighted consensus of up to four objective satellite-based methods to

estimate TC intensity (SATCON) shows skill compared to conventional

Dvorak-based methods

Skill verified in WPAC (TCS-08 and ITOP-2010) though small sample

Estimates are provided to NHC, JTWC, BOM , La Reunion and Fiji in real-

time

S-NPP ATMS and other possible members such as NRL PMW and DAV

method to could be added in future

IWTC


WPAC Performance

Aircraft verification

during TPARC-08 and ITOP-

2010

CIRA Multi-Platform Tropical Cyclone Surface Wind Analysis

Objectively combines surface wind vectors derived from AMSU,

scatterometers and geostationary feature track winds.

Each source is given a weight based on storm intensity and

proximity to the TC inner core.

25 KT 35 KT 65 KT

IWTC

VIII TC Intensity Analysis: MTCSWA

All wind vectors are adjusted to a 700 hPa level then reduced to sea level

using a factor of 0.9 within 100 km then linearly decreasing to a factor

of 0.75 out to 700 km

The 0.9 factor assumes that convection

is active in the TC inner core

Motion asymmetry is added

Work well for depicting the 2D wind

field and can be used for intensity

analysis for weaker TCs or storms

with a broad inner core

IWTC


Thanks to

Kim Wood, Joe Courtney, Jeff Hawkins, Tsukasa Fujita, Thierry DuPont,

Xiaoqin Lu and Hui Yu

Panel discussion on Evolving Methods to Estimate TC Intensity from Satellites

Today noon – 1:10

Objective TC Intensity Analysis IWTC

VIII

Adjust AMSU

pressure if

needed

ADT Estimate of Eye Size

Compare to AMSU-A

FOV resolution

Example: ADT provides

information to AMSU

In eye scenes, IR can be used

to estimate eye size

CIMSS AMSU uses eye size

information to correct

resolution under-sampling

CIRA estimates can also

be corrected

CIMSS SATCON Algorithm Cross-algorithm information sharing

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

CIMSS SATCON Algorithm

ADT determines scene

is a SHEAR scene

CIMSS AMSU indicates no

sub-sampling present

CIRA AMSU: little sub-

sampling due to position offset

from FOV center

SATCON Weighting:

ADT = 18 % CIMSS AMSU =41 % CIRA AMSU = 41 %

Center of TS Chris

CIMSS SATCON Algorithm

Analysis of Sat-Based TC Intensity

Estimation in the WPAC 2008 and 2010

N=14 Dvorak Consensus

Oper

Dvorak Consensus

(w/Koba)

ADT

w/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 Estimation

in the WNP During TCS-08

N=14 ‘Blind’

Dvorak Consensus

Oper

Dvorak Consensus

(w/Koba)

ADT

w/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= 4.7

Blind and Oper Dvorak conversion is Knaff/Zehr

Comparison of All Satellite-based Estimates – MSLP (mb)

1999-2010 SATCON Compared to a Simple

Straight Consensus

N = 289 SATCON

MSLP

SIMPLE

MSLP

SATCON

Vmax

SIMPLE

Vmax

BIAS 0.1 - 1.6 -0.5 - 3.0

AVG

ERROR 4.6 5.0 7.1 8.1

RMSE 6.5 7.5 8.9 10.5

Independent sample. Vmax validation in knots vs. BT. MSLP validation in hPa vs.

recon. Negative bias = method was too weak. SIMPLE is simple average of the 3 members

CIMSS AMSU Algorithm

Calculation of AMSU environmental Tb

8 FOV steps

~ 400 km nadir

~ 600 km limb

A = Old Method

B = New Method

C = Noisy channel

D = Topospheric anomaly

in domain

Microwave Sounders

AMSU-A Tb

anomaly > 1.4K ?

Eye Size < AMSU-A

FOV resolution ?

Get TC position and ancillary

data from ATCF

• previous (or forecast) 6-hour

position is used to estimate

storm motion and location

• Eye Size

• Environmental pressure (P_env)

Apply Limb Correction

to AMSU A/B data

Apply hydrometeor scattering

correction to AMSU-A channels 4-8

Locate warmest AMSU-A pixel (Tb_warmest)

within 2 FOV of TC center. Calculate the

environmental temperature (Tb_env) at a

distance of 8 FOV from TC center for

channels 6-8 then estimate Tb anomaly for

each channel (Tb_warmest - Tb_env)

Use each Tb anomaly value to get pressure

anomaly (del_P) contribution for that channel

Get weighted average of each channel-based

del-P to find initial TC del_P

Find average AMSU-B 89 Ghz Tb within

AMSU-A FOV using center-weighted averaging

(convolution of AMSU-B to AMSU-A)

Apply AMSU-B bias

correction to del_P

Apply resolution

bias correction

to del_P

Find AMSU-A Tb inner core gradient at

1 FOV and 2 FOV distant from center

for channel 7

Find largest AMSU-B 89 Ghz

gradient within 150 km of center

Estimate MSW using final del-P, latitude,

AMSU-A inner core gradient and AMSU-B

89Ghz gradient. Add 50% of storm motion

to MSW

Yes

CIMSS AMSU TC

Intensity Algorithm

MSLP = P_env - del_P

Yes

No

No

AMSU-A scan FOV is located entirely

in the large TC eye. AMSU FOV is near

nadir. Scattering minimal to none.

AMSU-A scan FOV contains TC eyewall.

Eye is small. AMSU-A FOV near scan edge.

Significant scattering within the FOV

CIMSS Sounder Algorithms

AMSU-B 89 GHz image with AMSU-A

FOV closest to TC center

AMSU-B 89 GHz image with AMSU-A

FOV closest to TC center

Two scattering scenarios with different AMSU/TC geometry

AMSU Channel 8 Tb Versus Recon MSLP

-1

0

1

2

3

4

5

6

7

90092094096098010001020

Channel 8 Tb anomalies versus aircraft-measured MSLP

Sources of Error

• Hydrometeor scattering near core

• Resolution issues related to core size

• Position of storm relative to scan position

Pressure (mb)

Tb A

nom

aly

(K

)


-1

0

1

2

3

4

5

6

7

8

90092094096098010001020

Separate well-resolved cases from the sample

for each channel of interest

Pressure (mb)

Tb A

nom

aly

(K

)

Well-resolved cases

TC eye Size > FOV


All Cases

CIMSS Sounder Algorithms

• Resolution of the instrument varies across the scan

swath due to the cross-track scanning strategy

• ATOVS AAPP Pre-Processor.

• Limb correct data (Goldberg et al 2001)

• Presence of hydrometeors can scatter/depress Tb’s

- Need to correct for attenuation effects

Microwave Sounders

FOV 1 FOV 30

50 km 80km 80 km

AMSU-A Scan Swath

CIMMS AMSU

• Inner core gradient contribution to MSW estimate

• Two different inner core Tb gradients for these storms.

• Related to Holland B parameter (Holland 1980)

Small compact warm core Warm core expanding

AMSU Ch7 for Hurricane Isabel 2003


• Storm center may fall between AMSU Footprints (FOV)

• Results in under-sampling of the warm core

• Use convolved AMSU-B moisture channel to adjust MSLP

• Only applied if initial MSLP estimate < 995 mb

• Proxy for TC position offset (bracketing factor)

• TC Center between FOV

• Cold AMSU-B 89 Ghz Tb used

to adjust AMSU TC estimate

• TC Center is centered on FOV

• Warm AMSU-B 89 Ghz

indicates no adjustment needed


AMSU-A in center no correction AMSU-A partially in eyewall,

apply correction

Eye smaller than AMSU-A FOV,

apply correction

Iris 2001. Core is very small and

AMSU-A FOV is in moat.

Signal suggests (incorrectly) that

no correction is required.

Midget TC

• Atmospheric sounding channels are similar to AMSU.

• Slight differences in the height the channels represent

• 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

determination of TC structure information (eye size, RMW) at the

time of the sounder TC intensity estimate.

• Flown aboard F16-19

CIMSS SSMIS Algorithm

N = 876 AMSU

MSLP

Dvorak

MSLP

AMSU

MSW

Dvorak

MSW

BIAS - 0.4 - 2.2 - 0.3 - 2.6

AVG

ERROR 5.5 8.8 8.3 7.7

RMSE 7.6 11.7 10.8 10.0

1999-2012. Both dependent and independent data to maximize

sample size. Validation is recon pressure within 3 hours of AMSU

pass for pressure and Best Track coincident with recon for MSW.

Sample includes Atlantic, East Pacific and West Pacific (N=21).


MSW = Maximum Sustained Winds

SDR data provided by FNMOC

Training data from 2006-2012 (ATL/EPAC/WPAC) N=369

- This period characterized by decreased storm activity and weaker storms

Algorithm logic similar to AMSU

Derive Tb anomalies for channels 3-5 and match to aircraft

measured pressure anomaly (P_env – MSLP)

CIMSS SSMIS Algorithm

CH 3 CH 4 CH 5

CIMSS ATMS Algorithm

AMSU SSMIS ATMS

MW Sounder

Inter-comparison.

Also use HAMSR

data from HS3 field

campaign.

AMSU resolution is ~ 50 km at nadir

Sub-sampling corrections required when eye

is small compared to footprint

Weaker system, AMSU FOV

near center Strong system, AMSU FOV

near center

Strong system, AMSU FOV

offset from center

AMSU

Advanced Dvorak Technique

• Statistics show that the more estimates that are available the more accurate

the resulting current intensity estimate

• DT has known biases and limitations

- Takes several years to master the technique

- Can be time intensive at times

- Requires sufficient staff and training

- Is inherently subjective

• Need exists for objective methods that provide additional skillful estimates

• Availability of real-time global digital satellite data allows for automated algorithms

that can compliment the DT

• Reduce subjectivity in TC intensity estimates

– Analyst subjectivity can be introduced in assessing scene

type, applying certain DvT parameters and rules, and

determining TC storm center locations

• Promote uniformity -- Given the above, significant variation in DvT estimates

can sometimes exist between Operational Forecast

Centers (OFCs), as documented by IBTrACS

-- Provide objectively-based estimates as a guidance tool

• Original Goal

– Obtain an accuracy at least on par with the DvT

Why develop an objective Dvorak Technique (DvT)?

Advanced Dvorak Technique Motivation

Advanced Dvorak Technique Description Summary

• Features of the ADT

– Utilizes Longwave IR imagery; enhanced with microwave data

– Based on original manual Dvorak Technique (DvT), but

expands upon the analysis principles

– Completely automated and objective

– Can provide rapid-refresh (5-min)

real-time estimates (DvT is only 6-hourly)

****************************************************

UW - CIMSS

ADVANCED DVORAK TECHNIQUE

ADT-Version 8.1.3

Tropical Cyclone Intensity Algorithm

----- Current Analysis -----

Date : 28 AUG 2005 Time : 154500 UTC

Lat : 26:14:25 N Lon : 88:20:05 W

CI# /Pressure/ Vmax

6.8 / 926.0mb/134.8kt

Final T# Adj T# Raw T#

6.7 6.7 6.7

Latitude bias adjustment to MSLP : -0.6mb

Estimated radius of max. wind based on IR : 33 km

Center Temp : +20.2C Cloud Region Temp : -69.9C

Scene Type : EYE

Positioning Method : RING/SPIRAL COMBINATION

Ocean Basin : ATLANTIC

Dvorak CI > MSLP Conversion Used : ATLANTIC

Tno/CI Rules : Constraint Limits : NO LIMIT

Weakening Flag : ON

Rapid Dissipation Flag : OFF

****************************************************

landfall

Examples of wide TC intensity

estimate discrepancies between

Operational TC Forecast Centers

20-30 hPa differences

Advanced Dvorak Technique Motivation

Advanced Dvorak Technique ADT Development Timeline

• The development timeline of the ADT

1980s

Dvorak objective EIR

technique outlined

(Dvorak, 1984)

Late 1980s – 1990’s

DD - Digital Dvorak

technique (Zehr, 1989)

1995 - 2001

ODT - Objective Dvorak

Technique

(Velden et al., 1998)

2001 – 2004

AODT - Advanced

Objective Dvorak

Technique

(Olander et al., 2002)

2004 - present

ADT - Advanced

Dvorak Technique

(Olander and

Velden, 2007)

1990 1985 1995 2000 2005

Advanced Dvorak Technique ADT Development History

• ODT – Objective Dvorak Technique

– First attempt to automate EIR Dvorak Technique

methodology

– Analysis limited to strong tropical storm and greater

intensities

– Implemented “history file” storing previous analyses

– Manual storm center selection only

• AODT – Advanced Objective Dvorak Technique

– Expanded to allow analysis over entire storm lifecycle

– Initial automated storm centering methodology implemented

• ADT – Advanced Dvorak Technique (Current Version)

– New image objective analysis approaches have been

implemented

– Include input from passive microwave imagers (85-92 GHz)

– Added advanced automated storm centering routine

(ARCHER)

Clear Eye

Large Eye

Pinhole Eye

>=38km Radius

Examples of ADT Eye Region Scene Types

Advanced Dvorak Technique Eye Scene Type Examples

Get User Inputs

Read TOPO File

Output ADT

Analysis Write History File

Intensity Analysis?

Yes

No

Center Positioning?

Automated

Manual

Read Cursor

Location

List/Graph

History File

Read Forecast

SC/RF Analysis

Select Center Fix

Perform Scene Analysis

Calculate Intensity

Estimates

TC Over Land? Yes

No

Manual Scene

Override?

Advanced Dvorak Technique ADT Overview Flowchart

Determine Eye and Cloud

Region Temperatures

Perform Scene Analysis

Perform FFT Analysis on

Eye and Cloud Regions

Calculate Convective Symmetry and

Eye Region Std Deviation Values

Derive Eye and Cloud Region “Scene Scores”

(based on various environmental analysis parameters)

Determine Scene Type

From Scene Scores

CDO Curved Band Shear Eye

Cloud Scenes Eye Scenes

Perform 10° Log

Spiral Analysis

Calculate Distance

to Convection

- Measure CDO Size

- Embedded Center Check

- Pinhole Eye Check

Determine Eye Size

Advanced Dvorak Technique Scene Type Determination Flowchart

Calculate Intensity Estimates

Derive Raw T# Value

(based on analysis of current image)

- Regression Analysis for CDO/Eye Scenes

- Convective Curvature for Curved Band

- Distance to Convection for Shear

History File Utilized?

Yes

No

Apply Dvorak Technique “Rule 8” Constraints

(to limit growth/decay of Raw T# over time)

Adj Raw T#

Calculate Time Averaged Final T# Values

3-hr Unweigthed Average

Determine Current Intensity CI# Value

- Apply Dvorak Technique “Rule 9” Weakening Rule

- Implement East Pacific Rapid Dissipation Rule

Compute MSLP Latitude Bias Adjustment Output Intensity

Estimate Values

Advanced Dvorak Technique Intensity Derivation Flowchart

Spiral Centering • Fits 5° log spiral vector

field to the IR image

• Calculates a grid of

scores that indicates the

alignment between the

spiral field and the IR Tb

gradients (maximum at

the spiral center

Ring Fitting • Calculates a grid of

scores that indicates

the best fit to a range

of possible ring

positions and

diameters (maximum

at the eye center)

Advanced Dvorak Technique Automated Storm Centering

Advanced Dvorak Technique Automated Storm Centering

• Uses the 85GHz brightness

temperature signal to deduce the

vigor and organization of the

developing eyewall/eye, and

calculate an intensity score

• Successful in loosely

differentiating between storms

• Greater than ~72 knots

• Greater than ~90 knots

• If thresholds are exceeded, PMW

scores are converted to either T# of

4.3 or 5.0 in the ADT

• The scheme has been operating in

the ADT since 2008

Warmest eye pixel

Eyewall temperatures

Hurricane Dolly, 23 July 2008 1126 UTC

DMSP SSM/I 85GHz (H) brightness temperature

Advanced Dvorak Technique PMW Intensity Estimate Score

More intense;

Closer to Best Track

More accurate during

rapid intensification


Eliminated false intensity

“plateau”; Closer to Best Track

More closely follows rapid

intensification; More

accurate maximum intensity

resulted


EAST/CENTRAL PACIFIC – 2010 TC Season – Independent comparisons between ADT and SAB intensity estimates

– ADT and SAB estimates w/in +/- 30 minutes

– Closest NHC Best Track intensity

Advanced Dvorak Technique ADT Validation: Comparisons with SAB DvT

126 total matches (homogeneous)

bias aae stdv

SAB:CI# -0.05 0.33 0.43

SAB:Win 0.48 5.91 8.54

SAB:MSL 0.08 4.59 6.73

ADT:CI# -0.07 0.28 0.36

ADT:Win -0.38 5.94 7.73

ADT:MSL 0.88 3.81 5.36

Note: NHC is using the ADT increasingly,

especially in the EPAC. While difficult to

quantify, their BT may reflect ADT influences.

Intensity range affected most by

PMW “eye score” addition

Advanced Dvorak Technique ADT Validation (Vmax, vs. Recon)

• Comparison of latest ADT version with PMW and previous version w/o PMW

Mean Error

Bias

Mean Error

Bias

Advanced Dvorak Technique Current Status and Availability

ADT real-time homepage : http://tropic.ssec.wisc.edu/real-time/adt


****************************************************

UW - CIMSS

ADVANCED DVORAK TECHNIQUE

ADT-Version 8.1.3

Tropical Cyclone Intensity Algorithm

----- Current Analysis -----

Date : 28 AUG 2005 Time : 154500 UTC

Lat : 26:14:25 N Lon : 88:20:05 W

CI# /Pressure/ Vmax

6.8 / 926.0mb/134.8kt

Final T# Adj T# Raw T#

6.7 6.7 6.7

Latitude bias adjustment to MSLP : -0.6mb

Estimated radius of max. wind based on IR : 33 km

Center Temp : +20.2C Cloud Region Temp : -69.9C

Scene Type : EYE

Positioning Method : RING/SPIRAL COMBINATION

Ocean Basin : ATLANTIC

Dvorak CI > MSLP Conversion Used : ATLANTIC

Tno/CI Rules : Constraint Limits : NO LIMIT

Weakening Flag : ON

Rapid Dissipation Flag : OFF

****************************************************

ADT

Current Intensity

“Bulletin”


===== ADT-Version 8.1.3 =====

--------Intensity------- -Tno Values-- ---Tno/CI Rules--- -Temperature-

Time Final/MSLPLat/Vmax Fnl Adj Ini Cnstrnt Wkng Rpd Cntr Mean Scene EstRMW MW Storm Location Fix

Date (UTC) CI MSLP /BiasAdj/(kts) Tno Raw Raw Limit Flag Wkng Region Cloud Type (km) Score Lat Lon Mthd Comments

2005AUG23 211500 2.0 1009.0/ +0.0 / 30.0 2.0 2.0 2.0 NO LIMIT OFF OFF -4.76 -35.41 CRVBND N/A N/A 23.25 75.44 FCST

2005AUG23 214500 2.1 1008.2/ +0.0 / 31.0 2.1 2.2 2.6 0.2T/hour OFF OFF 5.84 -34.85 CRVBND N/A N/A 23.28 75.49 FCST


2005AUG23 224500 2.1 1008.2/ +0.0 / 31.0 2.1 2.3 2.3 NO LIMIT OFF OFF 3.84 -34.04 CRVBND N/A N/A 23.33 75.58 FCST





<records deleted>

2005AUG27 154500 4.8 973.5/ -0.1 / 84.8 4.6 4.9 4.9 NO LIMIT ON OFF -53.56 -68.93 EMBC N/A N/A 24.49 85.25 SPRL

2005AUG27 161500 4.8 973.5/ -0.1 / 84.8 4.7 5.0 5.0 NO LIMIT ON OFF -53.86 -68.15 EMBC N/A N/A 24.50 85.31 SPRL

2005AUG27 164500 4.8 973.5/ -0.1 / 84.8 4.8 5.1 5.1 NO LIMIT OFF OFF -60.06 -69.29 EMBC N/A N/A 24.51 85.49 SPRL


2005AUG27 174500 4.8 973.5/ -0.1 / 84.8 4.8 4.6 4.6 NO LIMIT OFF OFF -68.36 -70.79 UNIFRM N/A N/A 24.64 85.75 SPRL





<records deleted>

2005AUG28 104500 6.7 929.0/ -0.4 /132.2 6.7 6.8 6.8 NO LIMIT OFF OFF 19.64 -70.90 EYE 30 IR N/A 25.74 87.56 COMBO



2005AUG28 121500 6.8 926.1/ -0.4 /134.8 6.7 6.7 6.7 NO LIMIT ON OFF 18.54 -71.46 EYE 31 IR N/A 25.76 87.78 COMBO







<records deleted)






2005AUG29 111500 0.0 0.0/ +0.0 / 0.0 0.0 0.0 0.0 N/A N/A 99.50 99.50 LAND N/A N/A 29.37 89.54 COMBO






2005AUG29 141500 6.3 938.5/ -1.7 /122.2 5.5 5.7 5.7 NO LIMIT ON FLG -1.56 -61.88 EYE 27 IR N/A 30.00 89.45 COMBO


Utilizing history file /home/tlo/odt/ADTV8.1.3WV/history/2005KATRINA.ODT

Successfully completed listing

ADT

History

File

Listing

--------Intensity------- -Tno Values-- ---Tno/CI Rules--- -Temperature-

Time Final/MSLPLat/Vmax Fnl Adj Ini Cnstrnt Wkng Rpd Cntr Mean Scene EstRMW MW Storm Location Fix

Date (UTC) CI MSLP /BiasAdj/(kts) Tno Raw Raw Limit Flag Wkng Region Cloud Type (km) Score Lat Lon Mthd



ADT Time Series Intensity Plot

Advanced Dvorak Technique PMW Analysis : Textual/Graphical Products

• Graphics allow for visual analysis of eye

score evaluation process.

ADT PMW Analysis

Unique regressions for Western Pacific (also used in SHEM) to

account for colder

tropopause temperatures.

- regressions are based on WPAC Best Track data


Modifications for Western Pacific

Super Typhoon Haiyan Hurricane Katrina CAT 5

Comparison of Typhoon Haiyan to Hurricane Katrina to show differences

in IR temperatures at similar TC intensity

Courtney-Knaff-Zehr wind -> pressure relationship used to adjust

Vmax

to MSLP in order to account for TC size, motion, P_env and

latitude

- R34 is used as a proxy for tangential wind at 500 km

- ROCI may be a better size parameter


Modifications for Western Pacific

Monsoon Depression TC Genesis

ADT old MSLP = 1000 hPa

New Using CKZ = 988 hPa

Nearby observations support MSLP < 990 hPa

TC structure information is critical for several applications

including:

- Storm surge forecasts

- 2D wind fields

- Model initialization

- Input to microwave intensity

algorithms


Eye Size and RMW Estimation

TC eye size and Radius of Maximum

Winds (RMW) can be estimated from IR

imagery.

Estimates are most accurate when IR

eye is well-defined

ADT includes IR eye size in history file

Find distance from center to -45 C in

four directions and get average. This is

IR eye radius R_eye

RMW = 2.8068 + (0.8361*R_eye)

Average radius of -45 C

temperature

• Expand ADT to operate during/after Extratropical Transition

– Study with Manion and Evans (UW-Milwaukee) underway

• Improve Curved Band and Shear scene intensity estimates

– Main area(s) still needing improved analysis capabilities (especially during

tropical cyclone formation stage).

– Employ a regression-based methodology (as with Eye and CDO scene types);

Initial results show improvement over current “Dvorak-based” methods

• Employ latest ARCHER routine

– Update currently used auto-centering routines with latest routine

• Implement ADT into McIDAS-V

– Currently rewriting base ADT code from C to JAVA and implementing GUI

• Continue IR/WV differencing study (Olander and Velden, W&F, 2009)

– Initial algorithm developed but follow-up analysis not yet completed

– Shows some predictive elements with rapid deepening cases

– Could be used to improve ADT regression-based current intensity estimate

correlations for pre-Eye scene types (CDO and Embedded Center)

Advanced Dvorak Technique Planned ADT Additions

• ADT intensity estimates are routinely accessed and utilized in real-time

by several OFCs from the CIMSS web site:

http://tropic.ssec.wisc.edu/real-time/adt/adt.html

• Version 8.2.1 planned release in late Spring 2014

– Includes PMW image ingest and Eye Score determination algorithms

– Able to ingest/utilize HURSAT data

– McIDAS-V version of ADT-V8.2.1 will be available Spring/Summer 2014

• Efforts underway at NESDIS/SAB to integrate latest version into

operations, and to provide real-time estimates via ATCF

– Integrating Version 8.2.1 in very near future

• Official Hurricane Intensity Estimation algorithm for GOES-R program

– HIE/ADT also being tested/utilized in GOES-R Proving Ground since 2012

Advanced Dvorak Technique ADT Status and Availability

Example: Objective estimates of eye size from CIMSS ‘ARCHER’ method (using

MW imagery)

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 AMSU

method

CIMSS SATCON Algorithm Cross-algorithm information sharing

iwtc objective tc intensity analysis viii · 120 130 140 6:00 6:00 8:00 12:00 18:00 5:00 4:00 18:00...

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