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Ocean University of China

Ocean University of China. Extreme value prediction of typhoon events- models and applications. Prof. Liu Defu. Disaster Prevention Research Institute. Ocean University of China. Historical review of the typhoon disaster.

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Ocean University of China

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  1. Ocean University of China Extreme value prediction of typhoon events- models and applications Prof. Liu Defu Disaster Prevention Research Institute

  2. Ocean University of China Historical review of the typhoon disaster Hurricane Katrina in 2005 induced the most catastrophic failure of an engineering system in the history of United States: approximately 2000 people died as a result of this disaster in New Orleans. Direct costs are estimated to approach 400 billions dollars. At the end of April, 1991, the tropical cyclone induced storm surges led to140 ,000 people deaths and economical damage was over three billion dollars in Bangladesh. In 2008, Cyclone Nargis made landfall with sustained winds of 130 mph in Burma and caused a huge tidal surge to sweep inland. The death toll from this storm reached more than ten thousands.

  3. Ocean University of China Tab. 2006 Typhoondisaster detail

  4. Ocean University of China The typhoon characteristics are usually described by using maximum central pressure difference (ΔP), radius of maximum wind speed (Rmax), moving speed of typhoon center (s), minimum distance between typhoon center and target site (δ ), and typhoon moving angle (θ ). But one of the chief advantages lies in taking the annual typhoon frequency (λ) into account as a discrete random variable in the new model derivation.

  5. Ocean University of China Different combinations of typhoon characteristics led to corresponding disasters In order to test the calculation errors of the model, typhoon 5612#, 7413#, and 9711# are taken as the samples. The detail of these typhoons is following: • In 1956, typhoon 12# made landfall with sustained winds of 130 mph and 923hPa atmospheric pressure. The storm surge caused by this super typhoon reached 4.2m. • Typhoon 7413# landed with 968hPa atmospheric pressure and the maximum wind power reached Force 12.The water level caused by typhoon 7413# exceeded history record. • Typhoon 9711# which landed on August 18 is the most influential typhoon in north and middle regions of Zhejiang Province in history. Tab. The joint probability of samples

  6. Ocean University of China In this model, the long term probability characteristics of typhoon factors such as the typhoon occurring frequency (λ), drop of central pressure (ΔP), radius of maximum wind speed(Rmax), typhoon moving speed (S), minimum distance between typhoon center and certain area (δ) are considered. Fig. The tracks of typhoon Tab.3 Comparison of storm surge at Zhapu station with return period* and joint return period**

  7. Ocean University of China Typhoon duration from landfall to dissipation (t) Historical reviews show that typhoon Nina in 1975 with duration 101 hours, induced Banqiao dam in the inland province Henan collapse and lead to 62 downstream dams collapse . typhoon Bilis in 2006 from landfall to dissipation persisted for 120 hours. So typhoon duration from landfall to dissipation (t) must be considered for extreme event prediction. Typhoon Nina The track of typhoon Nina

  8. Ocean University of China Double layer nested multi-objective probability model Double layer nested multi-objective probability model (DLNMOPM) is proposed, in which the joint probability prediction of different typhoon characteristics(such as the typhoon occurring frequency , drop of central pressure, radius of maximum wind speed, typhoon moving speed, minimum distance between typhoon center and certain area, typhoon moving angle and duration from typhoon land to dissipation)are taken as the first layer and typhoon induced disaster factors(such as strong wind, storm surge, huge wave, heavy rain, flood, and so on)are taken as the second layer. The new model will be used to establish typhoon disaster zoning and the prevention criteria system.

  9. Ocean University of China The double-layer nested multi-objectiveprobability model Select the target site Typhoon occurring frequency λ Joint probability analysis by using P-ISP Maximum central pressure difference (ΔP) Storm surge Heavy rain Flood Strong wind Huge wave Radius of maximum wind speed (Rmax) Moving speed of typhoon center (s) Minimum distance between Typhoon center and target site (δ) Joint probability analysis using MCEVD Typhoon moving angle (θ) Typhoon duration from landfall to dissipation (t) The first layer The second layer Typhoon disaster zoning and protection criterion

  10. Ocean University of China Theory of Multivariate Compound Extreme Value Distribution (MCEVD) Since 1972 Rita typhoon attacked on Dalian Port and induced severe catastrophe, we were studied on statistical prediction model of typhoon induced wave height and wind speed. The first publication in US (J. of Waterway Port Coastal & Ocean Eng. ASCE, 1980, ww4 ) proposed an new model “Compound Extreme Value Distribution” used for China sea, then the model was used in “Long term distribution of hurricane characteristics for Gulf of Mexico &Atlantic coasts, U.S.(OTC.1982). During the past few years, CEVD has been developed into Multivariate Compound Extreme Value Distribution (MCEVD) and applied to predict and prevent typhoon induced disasters for offshore and coastal areas.

  11. Ocean University of China The MCEVD is derived based on the theory measure and order statistics by compounding a discrete distribution with multivariate distribution as follows: (1) This can be proved as follows:

  12. Ocean University of China Therefore, Eq. (1) is proved. As mentioned above, the frequency of typhoon (hurricane, winter storm) occurrence can be fitted to Poisson distribution: In which, -- mean value of the annual typhoon frequency; -- joint probability domain; -- probability density function and cumulative function; -- stochastic variables such as ΔP, Rmax, s, δ, θ, t, and so on.

  13. Ocean University of China In the formula CEVD instead of ,the following formulas can be used for PNLTCED: However, it also can be solved by P-ISP.

  14. Ocean University of China Engineering applications1. Prediction of the disaster in New Orleans induced by hurricane Katrina • Study showed that the 50 yrs and 1000yrs hurricane central pressure P0 predicted by CEVD were close to the Standard Project Hurricane (SPH) and Probable Maximum Hurricane (PMH) proposed by NOAA respectively in most of the coastal areas, • except Zone 1 of Florida coasts and Zone A of Gulf coasts where more severe and reasonable results were obtained using CEVD

  15. Ocean University of China Comparison between NOAA and CEVD SPH and PMH are only close to CEVD 30~40yr and 120yr return values, respectively. In 2005, hurricane Katrina and Rita attacked coastal area of the USA, which caused deaths of about 2000 people and economical loss of $400 billion in the city of New Orleans and destroyed more than 110 platforms in the Gulf of Mexico. The disaster certified that using SPH as flood-protective standard was a main reason of the catastrophic results. Comparison among MCEVD and other methods

  16. Ocean University of China • After Hurricane Katrina2005, we reanalyzed hurricane disaster along American coasts. Study shows, in Region 2,4,7,11, the predicted hurricane strength using our model are close to those of other researchers, but in Region1,3,6,8,10 our results are more greater, especially significant in New Orleans area and Florida. The destroy of New Orleans approved our theory is reasonable.

  17. Ocean University of China 2 Design water level for disaster prevention in Shanghai Shanghai is located in the estuarine area of the Yangtze River in China. Historical observation data shows that typhoon induced surges, flood peak run-off from the Yangtze River and astronomical spring tides have caused significant losses of lives and properties to Shanghai City. The combined effects of storm surge, upper river flooding and spring tides on the coastal structures is the prime factor for disaster prevention

  18. Ocean University of China Fig . Diagnostic check of spring tide. Fig. Diagnostic check of flood. Tab. Typhoon frequency in Shanghai (1962-1987)

  19. Ocean University of China Fig. Diagnostic check of storm surge. Tab. shows that the design water level for a 100-yr joint return period event predicted by PNLTCEVD is close to the 1000-yr water level predicted by the traditional univariate extrapolation method for Shanghai.

  20. Ocean University of China 3. Discussion on Coastal Nuclear Power Plant Safety Regulations of China Furthermore, more than 37 nuclear power plants along coast of South-east China Sea are constructing or in planning and designing state. Adequate estimations of extreme high-water levels are very important for coastal hazard mitigation because the coastal areas of the world are becoming increasingly populated.

  21. Ocean University of China Design Basic Flood (DBF), Probable Maximum Typhoon (PMT), Standard Project Typhoon (SPT) and Probable Maximum Storm Surge (PMSS) will be discussed. According to “HAD101/11”, PMSS should be obtained based on PMT. So aiming at PMT with different combinations of typhoon characteristics, some sensitive factors should be selected as control factors and substituted into procedure of GUA and GSA. The PMSS corresponding to PMT of different sea areas can be derived by repeated calculations.

  22. Ocean University of China Typhoon characteristics (λ、 ΔP、 Rmax、 s 、δ、 θ、 t) Layer 1 Joint probability analysis GUA& GSA Storm surge (SS) model Max. SS? No Layer 2 Yes Spring tide Wave height PMSS Joint probability analysis Design criteria for nuclear engineering Float chart of of DLNMPM

  23. Ocean University of China According to the GSA results of existing data, annual typhoon frequency (λ), maximum central pressure difference (ΔP), radius of maximum wind speed (Rmax), moving speed of typhoon center (s) and typhoon duration (t) are selected as control factors for PMSS analysis. For joint probability analysis, the marginal distribution parameters of λ,ΔP, Rmax, s, t should be confirmed. Results show thatλfits to Poisson distribution, while ΔP, Rmax, s and t can be described by Generalized Extreme Value Distribution (GEVD). (See Table 4 and Fig 2)

  24. Ocean University of China For joint probability analysis, the marginal distribution parameters of λ,ΔP, Rmax, s, t should be confirmed, results show thatλfits to Poisson distribution.

  25. Ocean University of China Distribution diagnostic testing of ΔP Distribution diagnostic testing of Rmax Distribution diagnostic testing of s Distribution diagnostic testing of t

  26. Ocean University of China Using DLNMPM, some combinations of typhoon characteristic factors with different joint return period can be gotten Tab Extreme water level with different combination

  27. Ocean University of China Tab. The comparison between CEVD and traditional DBF It can be seen that 1000 years return values of storm surge, spring tide (3.85+2.75=6.6m) and wave height (7.9m) should be more severe than HAF0111 proposed DBI (6.35m) with 100 years return period wave height (6.6m).

  28. Ocean University of China Conclusions The theory of MCEVD and DLNMOPM model is based on the combinations of typhoon process maximum data sampling and joint probability analysis of typhoon characteristics and their corresponding extreme sea environments. It can be widely used not only in climatologic disaster prediction, but also for engineering project risk assessment. The 1975 typhoon Nina and 2005 hurricane Katrina give the most important lesson: they are only natural hazards, but when natural hazards combined with human hubris, the natural hazards should be become disaster, catastrophe sooner or latter. We hope: human hubris always out of decision making.

  29. Ocean University of China Thank you for your attention!

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