Daniel Brown, Rick Knabb, Mike Brennan & Mark DeMaria

Daniel Brown, Rick Knabb, Mike Brennan & Mark DeMaria

Tropical Cyclone Wind SpeedProbabilities: Recent Developments and

Future Plans

Tropical Cyclone Wind SpeedProbabilities: Recent Developments and

Future Plans

1000 Track Realizations

MC Probability ExampleHurricane Ike – 7 Sept 2008 12 UTC

64 kt 0-120 h Cumulative Probabilities

JHT Project Tasks(from DeMaria and Kidder)

Improved Monte Carlo wind probabilities using situationally-dependent track error distributions (2007-2009)

-Track error depends on Goerss Predicted Consensus Error (GPCE)

Decrease time step to one hour (2009-11)-Reduces noise for fast moving storms, also needed for landfall applications

Landfall timing and intensity distributions (2009-11)

-Intensity probability table began using Monte Carlo technique in 2008-Accounts for land but does not provide assessment of landfall intensity probabilities as probabilities are valid only at a point in time-Develop tools to convey wind timing uncertainty

-inclusion in HURREVAC?

Line integral probabilities (2009-11)-Could be used to estimate the probability that any portion of the warning area would receive hurricane force winds

Hurricane Watch/Warning Guidance (2009-11)

Goerss Predicted Consensus Error (GPCE)

Predicts error of TVCN track forecast• Consensus of GFS, UKMET, NOGAPS, GFDL, HWRF, GFDN, ECMWF

GPCE Input• Spread of TVCN member track forecasts• Initial latitude• Initial and forecasted intensity

Explains 15-50% of TCVN track error variance

GPCE estimates radius that contains ~70% of TCVN verifying positions at each forecast time

Task 1: Forecast Dependent Track Errors

Use GPCE input as a measure of track uncertainty

Divide NHC track errors into three bins based on GPCE values• Low, Medium and High

For real time runs, use probability distribution for the appropriate real time GPCE value tercile

• Different forecast times can use different distributions

Relies on relationship between NHC track errors and GPCE value

Probabilities tighten (spread) when GPCE values are small (large)

72 hr Atlantic NHC Along Track Error Distributions Stratified by GPCE

0

5

10

15

20

25

30

35

40

-600 -400 -200 0 200 400 600 800

Along Track Error (nmi)

Fre

qu

en

cy

(%

)

Lower GPCE Tercile

Upper GPCE Tercile

DeMaria et al. 2009 (accepted to Wea. Forecasting)

Evaluation Procedure

Near real time parallel runs began during second half of 2008 hurricane season and continued through 2009

Qualitative Evaluation: 34, 50, and 64 kt probabilities posted to web page for evaluation

-Operational, GPCE, and difference plots

Quantitative Evaluation: Calculate probabilistic forecast metrics from output on NHC breakpoints

-Performed by DeMaria et al. for 2008 cases.

-2009 verification for Atlantic and east, central, west Pac will be included in final report 12/4/09

Current Operational VersionCurrent Operational Version

Experimental VersionExperimental Version

34 kt 0-120 h cumulative probability difference field (GPCE-Operational)

GPCE values in “low” tercile through 72 h “medium” tercile at 96 h

Qualitative Evaluation Tropical-Storm-Force Wind Probabilities

Ida- Advisory #14

Current Operational VersionCurrent Operational Version

Experimental VersionExperimental Version

34 kt 0-120 h cumulative probability difference field (GPCE-Operational)

All GPCE values in “low” tercile

Qualitative Evaluation Tropical-Storm-Force Wind Probabilities

Bill- Advisory #18

64 kt 0-120 h cumulative probability difference field (GPCE-Operational)

All GPCE values in “low” tercileExperimental VersionExperimental Version

Current Operational VersionCurrent Operational Version

Experimental VersionExperimental Version

Qualitative Evaluation Hurricane-Force Wind Probabilities

Bill- Advisory #18

2008 Quantitative EvaluationCalculate probabilities at NHC breakpoints

-Operational and GPCE versions -34, 50, and 64 kt -12-hr cumulative and incremental to 120 h

-169 forecasts X 257 breakpoints = 43,433 data points at each forecast time

Two evaluation metrics -Brier Score -Optimal Threat Score

Brier Score Improvements2008 GPCE MC Model Test

0

1

2

3

4

5

6

7

8

9

10

12 24 36 48 60 72 84 96 108 120

Forecast Period

Bri

er S

core

Imp

rove

men

t (%

)

64 kt Cumulative

50 kt Cumulative

34 kt Cumulative

0

1

2

3

4

5

6

7

8

9

10

12 24 36 48 60 72 84 96 108 120

Forecast PeriodB

rier

Sco

re Im

pro

vem

ent

(%)

64 kt Incremental

50 kt Incremental

34 kt Incremental

Cumulative Incremental

Threat Score Improvements2008 GPCE MC Model Test

-6

-4

-2

0

2

4

6

8

10

12

12 24 36 48 60 72 84 96 108 120

Forecast Period (hr)

TS

Ove

rlap

Are

a In

crea

se (

%)

64 kt Incremental

50 kt Incremental

34 kt Incremental

-6

-4

-2

0

2

4

6

8

10

12

12 24 36 48 60 72 84 96 108 120

Forecast Period (hr)

TS O

verl

ap A

rea

Incr

ease

(%

)

64 kt Cumulative

50 kt Cumulative

34 kt Cumulative

Cumulative Incremental

Intensity Probability Table• Provides chances that the

intensity will fall within certain categories

• Land effects included in calculation

• For storms near land the probabilities tend to be more evenly spread among the various categories

• Provides intensity probabilities for a specific time, not location Cannot be used for to determine landfall intensity

• Decision makers are looking for landfall intensity probabilities -What is the chance the storm will be category 3 at landfall?

Dean 2007 Isabel 2003

<1% <1% <1% <1% 1% 3% 17%

<1% <1% <1% <1% 1% 3% 14%

<1% <1% 1% 1% 4% 22% 21%

99% 99% 99% 99% 95% 72% 47%

<1% 2% 5% 5% 8% 29% 17%

3% 7% 9% 10% 14% 22% 13%

58% 43% 33% 36% 28% 16% 11%

38% 44% 44% 40% 33% 5% 5%

1% 4% 8% 10% 12% 1% 1%

Maximum Wind Speed (Intensity) Probability TableFrom NHC Advisory 185 PM EDT Aug 17, 2007

<1% <1% <1% <1% <1% <1% 1%

<1% <1% <1% <1% <1% 1% 1%

<1% <1% <1% 2% 3% 7% 10%

100% 100% 100% 98% 97% 92% 89%

<1% 1% 3% 9% 13% 18% 22%

1% 3% 10% 17% 19% 21% 20%

29% 25% 40% 40% 34% 31% 26%

67% 63% 41% 27% 24% 19% 17%

3% 9% 6% 5% 6% 4% 3%

Maximum Wind Speed (Intensity) Probability TableFrom NHC Advisory 155 PM EDT Sep 9, 2003

NHC Forecast 140 145 140 135 135 125 125NHC Forecast 130 140 145 150 150 115 120

More interaction with landMore tracks remaining

over waterless probability of hurricane higher probability

of hurricane

Verifying IntensityVerifying Intensity

KatrinaAdvisory #14

<1% <1% <1% <1% 8% 46% 58%

<1% <1% <1% <1% 13% 26% 20%

1% 3% 4% 5% 20% 13% 6%

99% 97% 96% 94% 58% 15% 17%

26% 21% 19% 18% 14% 3% 2%

60% 47% 34% 26% 12% 2% 4%

13% 25% 34% 34% 19% 5% 5%

1% 3% 7% 14% 12% 4% 4%

<1% <1% 1% 2% 3% 1% 1%

Maximum Wind Speed (Intensity) Probability TableFrom NHC Advisory 145 PM EDT Aug 26, 2005

Official NHC Intensity Forecast72 hour forecast- 135 mph (cat. 4)

NHC Forecast 105 110 115 120 135 40 30

Katrina Landfall Intensity 130 mph (cat. 3)

18

t=72 h Many tracks already

inland at 72 h

VerifyingIntensitycat. 1

Landfall Intensity Probability Example

• Prototype GUI allows user to select breakpoints for landfall probability applications-Includes landfall timing, intensity distributions, line integral probs, watch/warning guidance

• Could be transitioned to ATCF

Line Integral Probabilities

Hurricane Ike 12 Sept 2008 00 UTC

Maximum 0-120 hr cumulative 64 kt wind prob = 53%

98.3% of realizations cross the coast between Port Aransas and Morgan City

Line integral probability of 64 kt winds anywhere between Port Aransas and Morgan City = 75%

o Port Aransas

o Morgan City

NHC Hurricane Warnings Objective Scheme Hurr Warnings

Future: Watch/Warning Guidancefrom Shumacher et al.

First Guess (Prelim w/ Ivan) : pup = 10.0%, pdown = 2.0%

Best fit: pup = 8.0%, pdown = 0.0%

Summary• Continue evaluation of GPCE version of wind probabilities

-Decision on implementation (2007-09 JHT project) by spring 2010

• Landfall intensity probabilities -Specialists expected to have the capability to examine landfall

intensity probabilities during 2010 season -Possible inclusion of landfall probabilities in tropical cyclone

discussion

• Line integral probabilities -May have the capability to examine these in 2010

• Hurricane watch/warning guidance-Still a couple of years away

-Changes to watch/warning lead times could impact development -Hoped that objective watch/warning guidance could be used for

collaborative TC watch/warning approach