1. Probabilistic Guidance for Hurricane Storm Surge (P-surge) Arthur Taylor and Bob Glahn Meteorological Development Laboratory, National Weather Service January 22, 2008

2. Probabilistic Storm Surge 2008 Hurricane Storm Surge Damage Galveston 1900 – 6,000 to 12,000 deathsGalveston 1900 – 6,000 to 12,000 deaths Okeechobee 1928 – more than 2,500 deathsOkeechobee 1928 – more than 2,500 deaths Florida Keys, Labor Day 1935 – 408 deathsFlorida Keys, Labor Day 1935 – 408 deaths New England 1938 – 600 deathsNew England 1938 – 600 deaths Audrey 1957 – 390 deathsAudrey 1957 – 390 deaths Camille 1969 – 256 deathsCamille 1969 – 256 deaths Hugo 1989 – 50 deathsHugo 1989 – 50 deaths Opal 1995 – 9 deathsOpal 1995 – 9 deaths Katrina 2005 – more than 1,800 deathsKatrina 2005 – more than 1,800 deaths Aerial Photo overlay of Katrina 2005 storm surge over Hancock County, Mississippi The greatest potential for loss of life related to a hurricane is from the storm surge.

3. Richelieu Apartments - Before Camille 1969

4. Richelieu Apartments - After Camille 1969

5. Probabilistic Storm Surge 2008 Storm Surge Forecasting The Sea, Lake, and Overland Surges from Hurricanes (SLOSH) model is the National Weather Services (NWS) operational hurricane storm surge model. The NWS uses composites of its results to predict potential storm surge flooding for evacuation planningThe NWS uses composites of its results to predict potential storm surge flooding for evacuation planning The National Hurricane Center (NHC) begins operational SLOSH runs 24 hours before forecast hurricane landfallThe National Hurricane Center (NHC) begins operational SLOSH runs 24 hours before forecast hurricane landfall The operational runs are based on a single NHC forecast track and its associated parameters. When provided accurate input, SLOSH results are within 20% of high water marks.When provided accurate input, SLOSH results are within 20% of high water marks. Track and intensity prediction errors cause large errors in SLOSH forecasts and can overwhelm the SLOSH results.Track and intensity prediction errors cause large errors in SLOSH forecasts and can overwhelm the SLOSH results.

6. Probabilistic Storm Surge 2008 Hurricane Ivan: A Case Study

7. Probabilistic Storm Surge 2008 Probabilistic Storm Surge Methodology Use an ensemble of SLOSH runs to create probabilistic storm surge (P-surge) Intended to be used operationally so it is based on NHCs official advisory.Intended to be used operationally so it is based on NHCs official advisory. P-surges ensemble perturbations are determined by statistics of past performance of the advisoriesP-surges ensemble perturbations are determined by statistics of past performance of the advisories Hurricane forecast errors which impact storm surge: Cross track errors (impacts Location)Cross track errors (impacts Location) Along track errors (impacts Forward Speed)Along track errors (impacts Forward Speed) Intensity errors (impacts Pressure)Intensity errors (impacts Pressure) Size of the storm errors.Size of the storm errors.

8. Probabilistic Storm Surge 2008 Katrina Advisory 23

9. Probabilistic Storm Surge 2008 Varying Katrinas Tracks Include 90% of possible cross track error (roughly 3 times the size of the cone of error). Include 90% of possible cross track error (roughly 3 times the size of the cone of error). Spacing based on size of the storm Spacing based on size of the storm

10. Probabilistic Storm Surge 2008 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%) The weight of a run is: cross track weight * along track weight * intensity weight * size weight

11. Probabilistic Storm Surge 2008 Is P-surge Statistically Reliable? If we forecast a 20% chance of storm surge exceeding 5 feet numerous times, then on 20% of those times storm surge should exceed 5 feet. Create a reliability diagram comparing the ratio of occurrence with forecast probability.Create a reliability diagram comparing the ratio of occurrence with forecast probability. Problem: Insufficient observations Number of hurricanes making landfall is relatively small.Number of hurricanes making landfall is relatively small. Observations are made where there has been surge.Observations are made where there has been surge. 340 observations for storms between 1998-2005

12. Probabilistic Storm Surge 2008 SLOSH Hindcast Used SLOSH hindcast runs for observations. NHC used best historical information for inputNHC used best historical information for input Given accurate input, model results are within 20% of high water marks.Given accurate input, model results are within 20% of high water marks.Advantage: Uniform observations everywhere, even where there is little or no surge.Uniform observations everywhere, even where there is little or no surge.Disadvantage: Same surge model used in analysis as in P-surge.Same surge model used in analysis as in P-surge.

13. Reliability Diagrams for Forecasts > 5 feet 48hr 21589 12hr 21085 17877 26042 25268 28810 43648 59354 90598 176494 286559 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0102030405060708090100 Probability forecast (%) > 5 feet Ratio of Occurrence 5010 100 24hr 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 15064 14340 39439 42265 64931 57568 71179 125725 246406 380314 0 1 0102030405060708090 Probability forecast (%) > 5 feet Ratio of Occurrence 1205 9107 7488 20908 32818 75688 111020 212597 448559 545396 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0102030405060708090100 Probability forecast (%) > 5 feet Ratio of Occurrence 1997 36hr 229 4195 11217 27574 45712 69783 90632 182758 311550 476672 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0102030405060708090100 Probability forecast (%) > 5 feet Ratio of Occurrence

14. Probabilistic Storm Surge 2008 Probability of > X feet of Storm Surge To calculate the probability of exceeding X feet: For each cell, add the associated weights of the hypothetical storms whose maximum surge values are greater than X feet.For each cell, add the associated weights of the hypothetical storms whose maximum surge values are greater than X feet.Example: Five hypothetical storms have weights of 0.1, 0.2, 0.4, 0.2, and 0.1Five hypothetical storms have weights of 0.1, 0.2, 0.4, 0.2, and 0.1 The first two exceeded X feet in a given cell.The first two exceeded X feet in a given cell. The probability of exceeding X feet in that cell is: 30% (0.1 + 0.2 = 30%)The probability of exceeding X feet in that cell is: 30% (0.1 + 0.2 = 30%)

15. Probabilistic Storm Surge 2008 Probability of > 5 feet of Storm Surge for Katrina Adv 23

16. Probabilistic Storm Surge 2008 Height Exceeded by X percent of the Ensemble of Storms To calculate the height exceeded by X percent of the ensemble runs: For each cell, find the surge value where the weights of the surge values which are higher add up to a value < X.For each cell, find the surge value where the weights of the surge values which are higher add up to a value < X.Example: Five hypothetical storms have maximum surge values of 6, 5, 4, 3, 2 feet and respective weights of 0.2, 0.4, 0.1, 0.1, 0.2.Five hypothetical storms have maximum surge values of 6, 5, 4, 3, 2 feet and respective weights of 0.2, 0.4, 0.1, 0.1, 0.2. The height exceeded by 60% of the ensemble is 4 feet, since the 6 foot value represents the top 20% of the storms, and the 5 foot value represents the next 40%.The height exceeded by 60% of the ensemble is 4 feet, since the 6 foot value represents the top 20% of the storms, and the 5 foot value represents the next 40%.

17. Probabilistic Storm Surge 2008 Height Exceeded by 10% of the Ensemble for Katrina Adv 23

18. Probabilistic Storm Surge 2008 http://www.weather.gov/mdl/psurge When is it available? Beginning when the NHC issues a hurricane watch or warning for the continental USBeginning when the NHC issues a hurricane watch or warning for the continental US As close to the advisory release time as possibleAs close to the advisory release time as possible

19. Probabilistic Storm Surge 2008 Current Development We were experimental in 2007We were experimental in 2007 The model is running in NCEPs job stream.The model is running in NCEPs job stream. The data are flowing to the National Digital Guidance Database (NDGD)The data are flowing to the National Digital Guidance Database (NDGD) The data will soon be available to NWS forecast offices.The data will soon be available to NWS forecast offices. A decision will be made soon on becoming operational in 2008.A decision will be made soon on becoming operational in 2008. We continue to develop training material.We continue to develop training material. We continue to update the error statistics.We continue to update the error statistics.