Coastal Inundation Risk for SE Florida Incorporating Climate Change Impact on Hurricanes & Sea Level Rise

Transcription

1 Coastal Inundation Risk for SE Florida Incorporating Climate Change Impact on Hurricanes & Sea Level Rise Y. Peter Sheng and V.A. Paramygin Justin R. Davis, Andrew Condon, Andrew Lapetina, Tianyi Liu, & Ruizhi Zou University of Florida Coastal and Oceanographic Engineering, ESSIE, University of Florida

2 Overview Increased Risk of Storm Surge and Coastal Inundation due to Climate Change -> increased cyclone activity and SLR Fed and states set policies, but mitigation and adaptation activities are often carried out at local level Coastal Resilience requires the cooperation of federal & state agencies and local communities, as well as researchers Mitigation and adaptation starts from risk assessment Coastal inundation risk in SE Florida using 3 methods Adaptation and Mitigation of Coastal Inundation A 24/7 Forecasting system for Florida A Super Fast forecasting system during hurricanes Ensemble Forecasting (psurge, multiple models)

3 Increasing Coastal Inundation Risk due to Increased Storms and SLR Episodic Events + Slow Change

4 Options for Mitigation of Coastal Inundation

5 The Big Picture Tremendous interest in the role of coastal wetlands in reducing storm surge and inundation But, how well does coastal wetlands reduce storm surge?

6 Method 1 Factors affecting storm surge storm and local factors Storm intensity: higher wind speed and lower central pressure create higher surge Storm size: larger storms have larger wind fetch creating higher surge Angle of landfall: more head on landfall creates higher surge Storm forward speed: the faster moving storms lead to higher surge due to speed of forward motion contributing to higher wind speeds Offshore bottom slope: gentle sloping bottoms (Gulf coasts) produce higher surge, further inland inundation but lower waves

7 Optimal Storm Generation: JPM-OS (Condon and Sheng, Ocean Engineering, 2012; Natural Hazards, 2012) Method of choice (FEMA) for BFE generation is the Joint Probability Method (JPM) Probabilistic description of the storm rate and storm characteristics (ΔP, R max, V f, θ, X land ) used to define a synthetic storm set Results of numerical simulation of synthetic storm set Combination of probabilistic description and calculated inundation used to generate the annual probability of exceeding any desired level 2) Fit characteristics to pdf 3) Discretize pdf Ex) 4 Values Repeat for all other variables 1) Analyze climatology Run simulations covering entire parameter space (1000 s of simulations)

8 Optimal Storm Generation: JPM-OS Downside to JPM is requirement of thousands of simulations to cover the parameter space not computationally efficient / feasible with state of the art modeling systems JPM Storm Parameters ΔP (mb) (P mb) R max (n.mi.) V f (mph) θ X land 33 (980) 53 (960) 73 (940) 93 (920) 113 (900) Spaced every 5 n. mi. from +200 to -120 relative to CREF (65 locations) Traditional JPM set consists of: 5 x 6 x 4 x 6 x 65 = 46,800 storms JPM Optimal Sampling (JPM-OS) developed to avoid this issue in BFE generation (Resio 2007, Toro et al. 2010a,b) Methods require expert knowledge Not easily transported to different domains BFE specific, no MOM/ Forecast

9 Coastal Inundation Map for Future Climate 100 Year Storm Metrics Scenario Affected Population Just Value of Affected Property (2009 $) Total Flooded Area (km 2 ) Total Flooded Volume (km 3 ) Present Day 264,910 12,057,786,368 3, Best Case 190,899 10,494,974,976 3, Mid-Range 325,718 16,178,281,472 3, Worst Case 677,577 42,104,897,536 5,

10 Method 2 A Statistical Hurricane Model was run 100 times for the 19-yr period of Number Year 0 Number of hurricanes Number of storms SST anomalies

11 Method 3 Climate and Sea Level Change Global Predictions 21 st century climate change experiments: Early ( ) Late ( ) Positive AMO & Negative AMO phases SST from CanESM2 and CCSM4 Sea surface heights for historical and RCP4.5 scenarios, 8 CMIP5 models Use AVISO (satellite) 1/3 degree sea level dataset + tidal gauges with long term records

12 Downscaling Tropical Cyclones (NCSU) Scale Selective Data Assimilation (SSDA) approach 12km grid spacing for the Southeastern US Two representative phases negative and positive Tropical cyclones are extracted from the downscaled results Number of storms striking SE US CanESM-EN CanESM-EP

13 Method 4: 24/7 Forecasting System for Florida Coast SE Florida domain: - 180,000 grid cells - Min grid size: ~40m, avg. grid size ~300m - Four cycles per day: 24-hr nowcast + 72-hr forecast - Output: water level + velocity - 1-year goal: 3D baroclinic, 3D currents, salinity Real-time results on SECOORA portal

14 BFE Maps (SE Florida) from Method 1, 2, and 3

15 BFE Map Comparison Difference with a baseline (historical)

16 Scenario No SLR 30 cm 100 cm CanESM-EN + + Tracks CanESM-EP + + CanESM-LN + + CanESM-LP + + Climatology + Climatology CanESM-EN CanESM-EP CanESM-LN CanESM-LP

17 CanESM-EP ( ) + 30cm SLR Modeled Max Surge+SLR bathtub

18 CanESM-LP ( ) + 100cm SLR Modeled Max Surge+SLR bathtub

19 BFE with Land Use Features

20 Wetlands of Miami-Dade County, Florida

21 Vegetation Resolving Surge & Inundation Modeling Improve modeling of the influence of vegetation on storm surge by including the skin friction drag and profile drag, which are proportional to the wetted area and frontal area, respectively, throughout the water column, i.e., in 3D Includes the dissipation of turbulent stresses by skin friction and the generation of turbulent kinetic energy due to wakes Quantify the influence of vegetation on storm surge Investigate the model s performance for a real storm Use the verified model for mitigation and adaptation planning Sheng, Y.P., A. Lapetina, and G. Ma (2012). The reduction of storm surge by vegetation canopies: Threedimensional simulations, Geophysical Research Letters, Lapetina, A. and Y.P. Sheng (2013). Three-Dimensional Modeling of Storm Surge and Inundation including the Effects of Coastal Vegetation, Estuaries and Coasts, Lapetina, A. and Y.P. Sheng. Advances in Storm Surge and Coastal Inundation Modeling: Vegetation, Velocity Structure, and Sediment Transport, in preparation.

22

23 Q: How well do coastal vegetation reduce storm surge? A: Likely varies because of -Canopy height (cm) -Canopy width (km) -Canopy density (stems/m 2 ) Vegetation Dissipation Potential

24 Q: Do storm characteristics affect dissipation rates? A: Likely depends upon -Storm forward speed -Storm intensity Vegetation Dissipation Potential

25

26 An Integrated, Quasi-Operational 24/7 A Nowcasting/Forecasting CH3D System for Nearshore Wind, Wave, 3D Baroclinic Circulation, Storm Surge and Inundation This CH3D-SWAN system is fast. ½-1 hour per forecast cycle vs. a few minutes for SLOSH.

27 Hurricane Andrew. Model Grid and Storm Track

28 Southeast Florida Coast Water Surface Elevation (cm, NAVD88) 150 Observed Data Haulover Pier, Florida Simulated (with waves) Simulated (without waves) /23/ /24/ /25/1992 Julian Day

29 Hurricane Andrew (1992)

30 Hurricane Andrew (1992)

31 Storm Surge Atlas Map

32 SLOSH MOMs We are working with NHC to compare MOMs produced using

33 East Florida Coast

34 East Florida Coast Heavy Rainfall lowered the salinity at Pine Island from 30 to 5 psu. 3D Baroclinic model is needed! Loss of shellfish TS Fay (2008)

35 NW Florida Northern Gulf of Mexico Low River Flow High Salinity Loss of Oyster

36 Water Quality Inundation is not the only problem/. Water Quality is a major concern for Florida Brown tide is hammering IRL

37 State of the Art of Storm Surge & Inundation Modeling State of the art coupled hydrodynamic and wave models can predict the inundation threat from an approaching hurricane with high resolution and accuracy. (ADCIRC, CH3D, CMEPS, FVCOM, SELFE). These models are not highly efficient and often cannot be run sufficiently fast to provide results two hours prior to advisory issuance within a six hour forecast cycle. See results of The SECOORA Testbed: CH3D, CMEPS, SLOSH, ADCIRC, FVCOM The IOOS Testbed: ADCIRC, FVCOM, SELFE, SLOSH Coastal Hazards Summit 2013 To produce timely inundation forecast, coarser grid models without wave setup contributions, are typically used which sacrifices resolution and physics. The SLOSH model of the NHC runs much faster than the other models. Typically the NHC has one hour at most from the time the most recent track intensity information is received to complete storm surge forecasts for the next h for inclusion in the latest advisory. SLOSH is used in the generation of forecasts and probabilistic products (P-Surge; Glahn et al. 2009; Taylor and Glahn 2008). Now P-Surge 2 is coming!

38 Condon, Sheng, and Paramygin (2012) MWR Volume 141, pp Presents an efficient forecast method by applying a multidimensional interpolation technique to a predefined optimal storm database to generate the surge response for any storm based on its landfall characteristics. This technique, which provides a digital lookup table to predict the inundation throughout the region, is applied to the southwest Florida coast for Hurricanes Charley (2004) and Wilma (2005). Because of the quick generation of the inundation response for a single storm, the response of thousands of possible storm parameter combinations can be determined within a forecast cycle. Takes 5 minutes for one forecast cycle, vs. hours for CH3D-SSMS. The thousands of parameter combinations are assigned a probability based on historic forecast errors to give a probabilistic estimate of the inundation forecast, which compare well with observations.

39 Toward High-Resolution, Rapid, Probabilistic Forecasting of the Inundation Threat from Landfalling Hurricanes Monthly Weather Review, Volume 141, pp

40 Charley (2004) and Wilma (2005)

41 Wilma (2005) Inundation Map CH3D Results Adaptive Interpolation

42 Survey A:Will the following action enhance coastal resilience in SE Florida? B:What is the priority for the following action? lowest //////////////highest A B Quantify coastal inundation risk for current & future climates with probabilistic inundation maps 5 5 Maintain 24/7 forecasting system 5 4 Compare products with federal products 4 4 Develop a Super Fast Coastal Surge/Inundation Forecasting System 5 5 Assess the role of wetland on dissipating inundation in SE FL 5 4 What is the best way for us to share our results with you? How will you use our results? (e.g., emergency planning, resource planning, infrastructure planning, etc//...)