1. HAZUS and Hurricane Ivan Model predictions and measured wind speeds Greg Gaston Ph.D. gggaston@una.edu Associate Professor Geography Department University of North Alabama Training and Travel supported by a Research Grant from the UNA College of Science

3. Ivan: “Alabama’s Hurricane” of 2004

4. September 2004

12. May 2005...

13. July 2005...

14. 2005 July

16. 100,000 years of simulated storms...extrapolated from historic storm tracks

17. http://www.aoml.noaa.gov/hrd/tcfaq/mh05.jpg

18. Hurricanes in the Atlantic Basin: 1851-2004 http://www.aoml.noaa.gov/hrd/tcfaq/E11.html

19. What is HAZUS? GIS-based software tools (ArcGIS) GIS-based software tools (ArcGIS) Loss estimation software that estimates physical damage from earthquakes, hurricanes, and floods Loss estimation software that estimates physical damage from earthquakes, hurricanes, and floods Available from FEMA free of charge (www.fema.gov/hazus) Available from FEMA free of charge (www.fema.gov/hazus)

20. Why HAZUS? Earthquakes, floods, and hurricanes generate billions of dollars in losses Earthquakes, floods, and hurricanes generate billions of dollars in losses Knowing potential losses: Knowing potential losses: Enables better planningEnables better planning Allows for improved infrastructure to protect people and reduce economic lossesAllows for improved infrastructure to protect people and reduce economic losses HAZUS can estimate potential future losses HAZUS can estimate potential future losses

21. Damage estimation/response and planning The Federal Emergency Management Agency (FEMA) has spent over $40 million developing and improving a model for damage prediction in the built environment The Federal Emergency Management Agency (FEMA) has spent over $40 million developing and improving a model for damage prediction in the built environment Originally, only used for earthquake damage, the HAZUS MH has been expanded to include multiple hazards (hurricane winds and flooding) Originally, only used for earthquake damage, the HAZUS MH has been expanded to include multiple hazards (hurricane winds and flooding)

22. HAZUS-MH Loss Estimation Methodology EarthquakeFlood Hurricane

23. Hurricane Model - Hazard 90 - 100 100 - 110 110 - 120 120 - 130 130 - 140 140 - 150 150 - 1 6 0 Design Peak Gust Hurricane Wind Speeds (mph) In Open Terrain Track model for storms affecting the Gulf and Atlantic coasts, and Hawaii Track model for storms affecting the Gulf and Atlantic coasts, and Hawaii Hurricane wind field model developed with NSF funding Hurricane wind field model developed with NSF funding Regional mappings of land-use to surface roughness Regional mappings of land-use to surface roughness

24. Hurricane Hazard Model Storms initiated in: Storms initiated in: AtlanticAtlantic CaribbeanCaribbean Gulf of MexicoGulf of Mexico Eastern PacificEastern Pacific Central PacificCentral Pacific Storm curvature Storm curvature Multiple land falls Multiple land falls Changes in intensity Changes in intensity design wind speeds in ASCE-7-98 design wind speeds in ASCE-7-98

25. Wind Field Model Solves full non-linear equations of motion for translating hurricane; then establishes parameters for fast running simulation Solves full non-linear equations of motion for translating hurricane; then establishes parameters for fast running simulation Storm asymmetriesStorm asymmetries Changing sea-surface roughnessChanging sea-surface roughness Air-sea temperature differenceAir-sea temperature difference Translation speedsTranslation speeds

26. Hurricane Model – Building Classification Building components determine degree of damage Building components determine degree of damage 1,884 building classes 1,884 building classes Building TypeBuilding Type Number of storiesNumber of stories Roof StrapsRoof Straps Wall ConstructionWall Construction Roof CoveringRoof Covering Etc.Etc.

27. Example: Sensitivity to Wind Speed ±10% ±70%

28. User Defined (Single Storm) Scenario Type 3 options: 3 options: Define manuallyDefine manually Import from exported file (other HAZUS users)Import from exported file (other HAZUS users) Import storm advisory from the Hurrevac FTP siteImport storm advisory from the Hurrevac FTP site

29. Questions and Assumptions How well does HAZUS predict peak wind gusts from a hurricane as it tracks inland? How well does HAZUS predict peak wind gusts from a hurricane as it tracks inland? Working Assumption: As the HAZUS model integrates accepted NOAA hurricane models (Hurwind, Hursim). The accuracy of the wind predictions will be highest very near landfall. Accuracy will degrade as the storm tracks inland. Working Assumption: As the HAZUS model integrates accepted NOAA hurricane models (Hurwind, Hursim). The accuracy of the wind predictions will be highest very near landfall. Accuracy will degrade as the storm tracks inland.

30. Limitations and Caveats Ivan (2004) is the only hurricane examined (for this presentation) Ivan (2004) is the only hurricane examined (for this presentation) Peak Wind gust data from Alabama stations Peak Wind gust data from Alabama stations Data were taken from NOAA’s National Hurricane Center http://www.nhc.noaa.gov/2004ivan.shtml Data were taken from NOAA’s National Hurricane Center http://www.nhc.noaa.gov/2004ivan.shtml http://www.nhc.noaa.gov/2004ivan.shtml

31. Mesonet Data StationsRegional Airport Weather Stations (ASOS)

32. Spatial locations... Spatial location data for each reporting station was collected either from Auburn University (Mesonet stations) or from the AirNav website for ASOS sites. Spatial location data for each reporting station was collected either from Auburn University (Mesonet stations) or from the AirNav website for ASOS sites.

33. Stations used to evaluate Ivan’s Wind Gusts

35. Ivan’s Actual Track... Re-formed and back into Texas

36. CITY DESIG NATOR DATE/TIM E_ peak gusts MPH modeled values model - actual percent_differe nce Alexander CitKALX16/15004182410.50 BirminghamKBHM17/00534882340.41 CovingtonOPNA116/102267119520.44 CullmanK3A116/17404559140.24 DothanKDHN16/19005466120.18 FairhopeGCSA116/041872146740.50 Florence *C016817/00504340-3-0.06 Ft.Payne *K4A916/19205240-12-0.29 Ft. RuckerKOZR16/09554475310.42 GadsdenKGAD16/17354362190.31 Grand BayGBYA116/051771130590.45 HuntsvilleKHSV16/2153465150.10 Huntsville *KMDQ16/224240 0-0.01 LauderdaleRLDM616/11135483290.35 Maxwell AFBKMXF16/17556690240.27 MobileKMOB16/064475137620.45 MontgomeryKMGM16/13535890330.36 Muscle Shoals *KMSL16/21104640-6-0.15 SemmesSEMA116/050059137780.57 TroyKTOI16/11284381380.47 TuscaloosaKTCL16/14534979300.37

37. Size of the circle at each station indicates the magnitude of the difference between the model prediction and the observed wind speeds

38. Magnitude of difference between model prediction and station records and distance from the coast.

39. % Difference between model predictions and observed peak gusts. Color bands indicate 50 mile increments from the coast.

40. CITY DESIGNA TORmodel - actualpercent_differencedist to coast Miles Alexander CitKALX410.50180 BirminghamKBHM340.41219 CovingtonOPNA1520.4444 CullmanK3A1140.24268 DothanKDHN120.1876 FairhopeGCSA1740.502 Florence *C0168-3-0.06305 Ft.Payne *K4A9-12-0.29296 Ft. RuckerKOZR310.4267 GadsdenKGAD190.31255 Grand BayGBYA1590.459 HuntsvilleKHSV50.10296 Huntsville *KMDQ0-0.01315 LauderdaleRLDM6290.35122 Maxwell AFBKMXF240.27138 MobileKMOB620.4513 MontgomeryKMGM330.36132 Muscle Shoals *KMSL-6-0.15294 SemmesSEMA1780.5713 TroyKTOI380.47102 TuscaloosaKTCL300.37183

41. % Difference and Distance from Coast

42. DistanceNumber of stationsAverage Error

43. Analysis and General Observations: From these data HAZUS model over- estimates wind speed. From these data HAZUS model over- estimates wind speed. Stations closer to the coast have a greater over-estimation. Stations closer to the coast have a greater over-estimation. At distances 200-300 miles inland, the agreement between the model and actual values is very high. At distances 200-300 miles inland, the agreement between the model and actual values is very high. In the case of Ivan, the model results are in many cases twice as high as the actual winds measured. In the case of Ivan, the model results are in many cases twice as high as the actual winds measured.

44. Is Ivan a special case? Does the HAZUS model accurately predict damage/loss in spite of over estimating wind velocity?

45. Peak Wind Gusts Final Hurrevac track (red line) Black line... Final corrected track

46. “... Final Corrected Track...” By using the parameters contained in the NWS forecast advisory with no modification, HAZUS overestimates wind velocity. By using the parameters contained in the NWS forecast advisory with no modification, HAZUS overestimates wind velocity. An experimental NWS model H*wind provides a better solution An experimental NWS model H*wind provides a better solution

47. Final Corrected track uses H*WIND landfall parameters and NHC track coupled with surface wind speed and pressure measurements from C-MAN stations, Buoys, ASOS and FCMP tower data

48. Comparison of NHC and H*WIND Wind Speeds – Hurricane Ivan

49. Hurricane Ivan Wind Field Validation Example

50. Model results from the “Final Corrected Track” released just after landfall... Much higher accuracy

53. Conclusions... The model results for Ivan using the hurrevac track/storm parameter data over estimate the winds by as much as 57% The model results for Ivan using the hurrevac track/storm parameter data over estimate the winds by as much as 57% The patterns of over estimation as related to the coast are virtually unchanged...model predictions are generally significantly over-estimated near the coast. The patterns of over estimation as related to the coast are virtually unchanged...model predictions are generally significantly over-estimated near the coast. The methodology for creating a final track needs to be fully documented!! The methodology for creating a final track needs to be fully documented!!

54. Modified Conclusions Using the same methodology with Charley, Francis, and Jeanne from 2004 on the NWS track/storm parameters (not the adjusted final track) Using the same methodology with Charley, Francis, and Jeanne from 2004 on the NWS track/storm parameters (not the adjusted final track) The results are consistent in that the tendency to overestimate wind field can be clearly seen in the results The results are consistent in that the tendency to overestimate wind field can be clearly seen in the results However, the increase in accuracy as a function of distance from the coast is no longer apparent. However, the increase in accuracy as a function of distance from the coast is no longer apparent.

57. Finally HAZUS MH appears to do an acceptable job of modeling wind speeds and thus can create accurate estimations of damage and loss from hurricane winds HAZUS MH appears to do an acceptable job of modeling wind speeds and thus can create accurate estimations of damage and loss from hurricane winds The best data for estimation comes from the “final corrected track” (which is now strongly recommended by FEMA) The best data for estimation comes from the “final corrected track” (which is now strongly recommended by FEMA)