Climate model-based probabilistic wind risk assessment under future climate

Transcription

1 Climate model-based probabilistic wind risk assessment under future climate Kazuyoshi Nishijima Associate Professor of Engineering Decision Analysis CERDA

2 CERDA Areas and current focuses Structural reliability theory Bayesian networks Scaled probability integral Natural hazard risks Wind hazard Wind vulnerability Flood vulnerability Decision analysis Real-time decision optimization Reliability in economics Life safety Climate change Assessment Adaptation 3 DTU Civil Engineering, Technical University of Denmark

3 Question to answer Typhoon Frequency vs. Intensity Wind-induced residential building risk increases? 13 DTU Civil Engineering, Technical University of Denmark

4 Inputs Hazard modeling AGCM simulation results within the KAKUSHIN program Probabilistic modeling methodology for typhoon events Fragility modeling Damage report for the typhoon Songda in 2004 Wind field simulated with JMA-NHM and JMA-RANAL/JMA-RSM 14 DTU Civil Engineering, Technical University of Denmark

5 Hazard modeling 15 DTU Civil Engineering, Technical University of Denmark

6 Extracted typhoons Current climate: Projected future climate: DTU Civil Engineering, Technical University of Denmark

7 Not enough typhoons for risk assessment Monte Carlo simulation with probabilistic typhoon model! 17 DTU Civil Engineering, Technical University of Denmark

8 AGCM simulation results Probabilistic modeling of typhoon events 18 DTU Civil Engineering, Technical University of Denmark

9 Occurrence model Re-sampling 19 DTU Civil Engineering, Technical University of Denmark

10 Transition model Temporary spatially inhomogeneous Markov model Translation speed Translation angle Central pressure Radius of maximum wind speed Model for each 5 x 5 grid and month. 20 DTU Civil Engineering, Technical University of Denmark

11 Wind field model Wind field at gradient height Wind speed [m/s] Given - Central pressure - Translation speed/angle - Radius of maximum wind speed 21 DTU Civil Engineering, Technical University of Denmark

12 Surface friction model Empirical relation u r, Considering Topography Land use Surface wind speed 22 DTU Civil Engineering, Technical University of Denmark

13 Simulated surface wind speed Maximum wind speeds during a typhoon event 23 DTU Civil Engineering, Technical University of Denmark

14 Monte Carlo simulation AGCM simulation 25 years x1000!! Monte Carlo simulation times of 1-year 24 DTU Civil Engineering, Technical University of Denmark

15 Fragility modeling 25 DTU Civil Engineering, Technical University of Denmark

16 Reported damage ratio of residential buildings (# of damaged buildings) (# of total buildings) Damage ratio km Kyushu island in Japan (Degree of damage is not differentiated.) Tomokiyo et al. (2009) 26 DTU Civil Engineering, Technical University of Denmark

17 Computation of wind field by Songda Japanese 25-year Reanalysis (JRA-25) JMA Non Hydrostatic Mesoscale Model (JMA-NHM) Large scale 5km mesh Small scale 1km mesh 27 DTU Civil Engineering, Technical University of Denmark

18 Computed wind field and pressure fields [m/s] [hpa] Wind speed/direction Sea level pressure 28 DTU Civil Engineering, Technical University of Denmark

19 Combining these 29 DTU Civil Engineering, Technical University of Denmark

20 Fragility model 30 DTU Civil Engineering, Technical University of Denmark

21 Hazard assessment Change of annual maximum wind speed statistics 0.86 Decrease 0.95 Decrease Increase 1.13 Increase Mean value 98-quantile (50-year wind) 31 DTU Civil Engineering, Technical University of Denmark

22 The answer (Projected future climate) (Current climate) = 0.87* * Simple average over 2249 locations in Japan 32 DTU Civil Engineering, Technical University of Denmark

23 Are you happy? 33 DTU Civil Engineering, Technical University of Denmark

24 Research agenda (1) Improved fragility/vulnerability model Design wind speed: around 30-35m/s in main Japanese islands 34 DTU Civil Engineering, Technical University of Denmark

25 Research agenda A failure mode Roofing Debris 35 DTU Civil Engineering, Technical University of Denmark

26 Research agenda Hybrid (statistical + engineering) approach 36 DTU Civil Engineering, Technical University of Denmark

27 Research agenda (1) Improved fragility/vulnerability model (2) Improved wind field model 37 DTU Civil Engineering, Technical University of Denmark

28 Thank you for your attention! 39 DTU Civil Engineering, Technical University of Denmark