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Probabilistic Hurricane Storm Surge (P-Surge) PowerPoint Presentation
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Probabilistic Hurricane Storm Surge (P-Surge)

Probabilistic Hurricane Storm Surge (P-Surge)

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Probabilistic Hurricane Storm Surge (P-Surge)

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  1. Probabilistic Hurricane Storm Surge (P-Surge) Arthur Taylor MDL / OST December 4, 2006

  2. Introduction • NHC begins operational SLOSH runs 24 hours before landfall. • Provides a storm surge estimate for non-evacuation applications. • Problem: Surges are based on a single NHC forecast track and associated parameters. • When provided accurate input, SLOSH results are within 20% of high water marks. • Track and intensity prediction errors are the largest cause of errors in SLOSH surge forecasts and can overwhelm the SLOSH results.

  3. Probabilistic Storm Surge Methodology • Create an ensemble of SLOSH runs based on NHC’s official advisory and historic forecast errors. • Creates a probability of storm surge for this one forecast of this particular threatening hurricane. Not to be confused with FEMA’s 100-year surge levels. • Which hurricane forecast errors most impact storm surge? • Cross track error (impacts landfall location) • Along track error (impacts the timing of the storm) • Intensity errors • Structure of the storm errors

  4. SLOSH’s Input Track • Location • Can get from NHC’s advisory • Forward Speed • Can compute from NHC’s advisory • Radius of Maximum Winds (Rmax) • Not given in NHC’s advisory due to lack of skill in forecasting changes in Rmax • Pressure • Can only get the current value (no forecast values) from NHC’s advisory

  5. SLOSH’s Rmax and Pressure • Since NHC’s advisory does not provide Rmax, or forecast Pressure, we need to compute them. • The SLOSH parametric wind model relates Rmax, Pressure, and Maximum Wind Speed (Vmax). Given any two, the third can be computed. • Vmax is provided in NHC’s advisory. • Since the current Pressure is provided, one can estimate the current Rmax. • We assume that Rmax remains constant, then calculate the resulting Pressures.

  6. Example: Katrina Advisory 23

  7. Varying Katrina’s Tracks • The NHC’s cone of error is 50% of possible cross track error. • We include 90% of possible cross track error (roughly 3 times the size of the cone of error). • Spacing based on size of the storm

  8. Varying the Other Parameters: • Size: Small (30%), Medium (40%), Large (30%) • Forward Speed: Fast (30%), Medium (40%), Slow (30%) • Intensity: Strong (30%), Medium (40%), Weak (30%)

  9. Determine Which Basins to Run • We try all SLOSH input tracks in all operational basins: • For each basin, eliminate tracks which never forecast tropical storm force winds. • Remove basins where all the tracks were eliminated. • Treat eliminated tracks as if they generated no surge in a basin.

  10. Calculate probability of exceeding X feet • Look at each cell in each SLOSH run. • If the surge exceeds X, add the weight associated with that SLOSH run to the total. • The weight of a run is: cross track weight * along track weight * intensity weight * size weight • The total weight is the probability of exceeding X feet.

  11. Katrina Adv 23: Probability > 5 feet of storm surge

  12. Calculate height exceeded by X percent of ensemble storms. • Determine the exceedance surge height, for each cell, so that only X percent of the ensemble surges exceed it. • For each cell, sort the heights of each ensemble SLOSH run. • Starting from the tallest height, sum the weights until the sum is equal to the given percentage, X. • The height associated with the last weight added is the exceedance height for that cell.

  13. Katrina Adv 23: 10% of the ensemble storms exceed this height

  14. Where can you access our product?http://www.weather.gov/mdl/psurge • When is it available? • Beginning with the first NHC advisory forecasting landfall of a hurricane in 24 hours. • Available approx. 1-2 hours after the advisory release time.

  15. Customer Feedback From: 6-1-2006 To: 11-15-2006 Total Number of Responses: 126 What is your affiliation?

  16. Customer Feedback Scores What is the perceived technical quality of the storm surge graphics? How easy are the storm surge graphics to interpret and use?

  17. Customer Feedback Comments • “Excellent product should save lives.” • “Nice product. Easy to read.” • “Storm surge is the one area that local forecasters either rarely mention or speak in such generalities that the information is useless. This tool is greatly appreciated by those on us living in the coastal high hazard area.” • “I need to know what my risk of storm surge is where I live - this graphical representation brings an important level of visual realization to this dangerous situation.” • “Extend the product out to 48 hours prior to landfall instead of 24 hours.” • “You only give two ranges of storm surge…10% and > 5 feet. Add additional thresholds to the graphics.” • “Needs ability to zoom in closer to effected areas.” • “Hard to understand the 10 % exceedance graphic.”

  18. Is it statistically Reliable? • If we forecast 20% chance of exceeding 5 feet, does it actually exceed 5 feet 20% of the time? • Step 1: Create forecasts for various projections and thresholds for the following storms: Bonnie98, Bret99, Charley04, Claudette03, Dennis05, Earl98, Floyd99, Frances04, Georges98, Gaston04, Isabel03, Ivan04, Jeanne04, Katrina05, Lili02, Wilma05 • Step 2: Get a matching analysis of storm surge. • Step 3: In each grid cell when we forecast 15-25% probability of exceeding 5 feet, calculate the observed relative frequency. Repeat for other probability groups, threshold values, and forecast projections.

  19. >2 ft Forecasts 12hr 24hr 36hr 48hr

  20. >5 ft Forecasts 12hr 24hr 36hr 48hr

  21. >7 ft Forecasts 12hr 24hr 36hr 48hr

  22. Current Development • We were “experimental” in 2006, and plan on becoming “operational” in 2007. • We are investigating other methods of verifying the forecasts. • We are working on adding the data to the NDGD (National Digital Guidance Database). • We are working on delivering the data to AWIPS. • We are developing more training material. • Based on the feedback from 2006, we plan to add more “zoom” capability.

  23. Future Development • We would like to include probability over a time range, both incremental and cumulative. • We would like to allow interaction with the data in a manner similar to the SLOSH Display program. • We would like to investigate its applicability to Tropical storms.