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Tropical Cyclone Wind Speed Probabilities: Recent Developments and Future Plans

Daniel Brown, Rick Knabb, Mike Brennan & Mark DeMaria. Tropical Cyclone Wind Speed Probabilities: Recent Developments and Future Plans. MC Probability Example Hurricane Ike – 7 Sept 2008 12 UTC. 1000 Track Realizations. 64 kt 0-120 h Cumulative Probabilities.

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Tropical Cyclone Wind Speed Probabilities: Recent Developments and Future Plans

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  1. Daniel Brown, Rick Knabb, Mike Brennan & Mark DeMaria Tropical Cyclone Wind SpeedProbabilities: Recent Developments and Future Plans

  2. MC Probability Example Hurricane Ike – 7 Sept 2008 12 UTC 1000 Track Realizations 64 kt 0-120 h Cumulative Probabilities

  3. 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)

  4. 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

  5. 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)

  6. 72 hr Atlantic NHC Along Track Error Distributions Stratified by GPCE DeMaria et al. 2009 (accepted to Wea. Forecasting)

  7. 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

  8. Qualitative Evaluation Tropical-Storm-Force Wind ProbabilitiesIda- Advisory #14 Current Operational Version Experimental 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

  9. Qualitative Evaluation Tropical-Storm-Force Wind ProbabilitiesBill- Advisory #18 Current Operational Version Experimental Version 34 kt 0-120 h cumulative probability difference field (GPCE-Operational) All GPCE values in “low” tercile

  10. Qualitative Evaluation Hurricane-Force Wind ProbabilitiesBill- Advisory #18 Current Operational Version Experimental Version 64 kt 0-120 h cumulative probability difference field (GPCE-Operational) All GPCE values in “low” tercile Experimental Version

  11. 2008 Quantitative Evaluation • Calculate 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

  12. Brier Score Improvements2008 GPCE MC Model Test Cumulative Incremental

  13. Threat Score Improvements2008 GPCE MC Model Test Cumulative Incremental

  14. 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 locationCannot 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?

  15. Maximum Wind Speed (Intensity) Probability Table From NHC Advisory 15 5 PM EDT Sep 9, 2003 Maximum Wind Speed (Intensity) Probability Table From NHC Advisory 18 5 PM EDT Aug 17, 2007 <1% <1% <1% <1% 1% 3% 17% <1% <1% <1% <1% <1% <1% 1% <1% <1% <1% <1% 1% 3% 14% <1% <1% <1% <1% <1% 1% 1% <1% <1% <1% 2% 3% 7% 10% <1% <1% 1% 1% 4% 22% 21% 99% 99% 99% 99% 95% 72% 47% 100% 100% 100% 98% 97% 92% 89% <1% 2% 5% 5% 8% 29% 17% <1% 1% 3% 9% 13% 18% 22% 3% 7% 9% 10% 14% 22% 13% 1% 3% 10% 17% 19% 21% 20% 29% 25% 40% 40% 34% 31% 26% 58% 43% 33% 36% 28% 16% 11% 38% 44% 44% 40% 33% 5% 5% 67% 63% 41% 27% 24% 19% 17% 3% 9% 6% 5% 6% 4% 3% 1% 4% 8% 10% 12% 1% 1% Dean 2007 Isabel 2003 More tracks remaining over water More interaction with land less probability of hurricane higher probability of hurricane Verifying Intensity Verifying Intensity NHC Forecast 130 140 145 150 150 115 120 NHC Forecast 140 145 140 135 135 125 125

  16. KatrinaAdvisory #14 Maximum Wind Speed (Intensity) Probability Table From NHC Advisory 14 5 PM EDT Aug 26, 2005 <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% Verifying Intensity Official NHC Intensity Forecast 72 hour forecast- 135 mph (cat. 4) cat. 1 Katrina Landfall Intensity 130 mph (cat. 3) t=72 h Many tracks already inland at 72 h 18 NHC Forecast 105 110 115 120 135 40 30

  17. 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

  18. 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% oMorgan City oPort Aransas

  19. 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% NHC Hurricane Warnings Objective Scheme Hurr Warnings

  20. 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

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