FEMA’s Coastal Flood Hazard 

Analyses in the Atlantic 

Ocean and Gulf of Mexico

Probabilistic Flood Hazard Assessment – Panel 7 

 

January 31, 2013 
2

Agenda

 Introduction to FEMA’s Mission & Coastal Flood Hazard Mapping 

 JPM-OS for Storm Surge Modeling in the Atlantic Ocean & Gulf of Mexico 

 Areas for Collaboration & Improvement 

 
3

FEMA & Flood Hazard Mapping

 
4

FEMA & Flood Hazard Mapping
5

Atlantic Ocean & Gulf of Mexico
6

Numerical Modeling Framework

STEP 1: 

Storm 

Characterization

STEP 2: Storm Surge 

Modeling STEP 3: Return Period 

Analysis 

OUTPUT:

1% Annual 

Chance Still 

Water Level

STEP 4: Overland 

Wave Analysis

OUTPUT: 

Flood 

Insurance 

Rate Map
7

Step 1: Storm Forcing

A. Storm Rate and Storm Characterization 

B. JPM-OS and Representative Synthetic Storms 

C. Validation of “OS” using SLOSH or a coarse ADCIRC mesh 
8

Step 1A: Storm Characterization

• storm occurrence rate λ

• pressure deficit ΔP 

• radius of the exponential pressure profile Rmax

• forward velocity Vf

• storm heading θ

• landfall location d
9

Step 1A: Establishing Storm Rate 

(storms/year/km)

= ∑

(all storms)

( ) 1

i

di k

T

λ































 = −

2

2

1

exp 2

1 ( )

d

i

d

i h

d

h

k d

π

hd ~ 200 km

Landfalling Hurricanes Bypassing Hurricanes

hθ ~ 30°
10

Step 1A: Establishing Storm 

Heading
11

Step 1A: Characterization of Storm 

Parameters

0 0 P[ P x] exp[ (x / u) ( P / u) ] x P k k ∆ > = − + ∆ > ∆
12

Step 1A: Characterization of Storm 

Parameters
13

1. The geometry of the tracks is defined based on: 

a) Similar work performed by USACE for probabilistic storm surge studies for 

MS & LA

b) Historical tracks for the regions (as performed in NC, SC)

 

2. Storm parameters, Rp, ΔP, and B are specified for each point along the 

track, based on the specified conditions at landfall from the 

probabilistic analysis. 

Step 1B: Storm Tracks
14

Step 1B: JPM Development

[ ] ... ( ) [ ( ) ] [ ( ) ]

1

max(1 ) ∫ ∫ ∑=

> = + > ≈ + >

n

i

i m i

x yr X m P η η λ f x P η x ε η d x λ P η x ε η

Annual rate 

(storms/km/yr)

Joint Probability 

Distribution of Storm 

Characteristics

Storm generated 

surge

( , , landfall location , ) i Pi Rpi Vf ,i, i i x = ∆ θ

Annual rate 

for synthetic 

storm i

Numerical model 

estimate of storm 

surge elevation

1. Discretize ΔP into multiple broad slices 

2. Within each slice, discretize the joint probability distribution of ΔP , Rp, 

Vf and θ using Bayesian Quadrature. 

3. Discretize landfall location by offsetting each synthetic storm by Rp, as 

measured perpendicular to the track. 

4. Compute the probability, pi, assigned to each synthetic storm as the 

product of the probabilities from the first 3 steps. 

 
15

Step 1B: Reference Synthetic Storms
16

Step 1B: JPM-OS Development

Probability ∆P 

(mb) Rp

(nmi)

Vf

(m/s)

Theta

(deg)

0.248 26.0 36.6 6.8 23.0

0.209 35.3 16.3 6.8 23.0

0.139 42.0 33.2 6.8 23.0

0.094 46.8 14.9 6.8 23.0

0.049 48.9 10.3 5.9 26.6

0.033 56.5 36.4 4.2 61.1

0.057 57.8 19.2 3.9 -12.7

0.046 58.8 17.5 7.1 86.8

0.035 61.7 14.4 11.3 -8.0

0.030 63.4 34.0 9.5 -10.9

0.026 80.4 9.5 5.5 23.7

0.034 87.0 20.2 6.8 28.3

Example: JPM-OS representation of joint probability distribution 

of storm characteristics for landfalling hurricanes
17

Step 1B: JPM-OS Synthetic Storms

Hurricanes 

– Landfalling and Bypassing

Tropical Storms 

– Landfalling and Bypassing
18

Step 1C: Comparing Reference and 

JPM-OS Synthetic Storm Suites
19

Step 1C: Comparing JPM and 

JPM-OS
20

Step 2: Hydrodynamic & Wave 

Modeling

 
21

Step 2: Single Storm SWL Result
22

Step 3: JPM-OS SWL Results
23

Step 3: Accounting for Uncertainty
24

Step 3: Accounting for Uncertainty

 ε1 This is the contribution from the astronomical tide. A storm can make 

landfall at any phase of the tide. This epsilon term is used to represent the effect 

of random phasing of the maximum storm surge and the astronomical tide. 

 ε2 This epsilon term represents the changes in surge heights due to 

unaccounted variability in the value of Holland B. This parameter is used in the 

PBL numerical model of hurricane winds and pressures to account for the radial 

gradients. 

 ε3 This epsilon term represents the departures between modeled and 

measured surge levels and is used to express variations in the surge heights due 

to lack of accuracy in the modeling results. 

 ε4 This epsilon term represents the uncertainty associated with using 

idealized wind fields for the surge simulations, instead of the “best” or measured 

wind fields. 
25

Step 3: Accounting for Uncertainty

 The effect of the inclusion of the uncertainty term is shown by the blue 

line in the figure below 

 
26

Step 3: Final SWL Results

 
27

 

Step 3: Final SWL Results
28

What can we share with Partners?

 2D storm surge modeling 

• Seamless Digital Elevation Model

• Model mesh

• Model choice

• Overland wave modeling

 Storm characterization & tropical system behavior 

• Progress in understanding

• Knowledge transfer needed

• Area for plentiful future research

 Treatment of Uncertainty 
29

Questions?

Thank you to Chris Reed (URS), Alan Niedoroda (URS), Chris Jones, Mark 

Osler (Baker), Darryl Hatheway (AECOM) & Cheryl Johnson (Accenture) for 

their shared expertise in this presentation. 

 

Thank you to all FEMA mapping partners, who are the reason this 

substantial program has been so successful. 

 

 

Contact information: 

Tucker Mahoney 

tucker.mahoney@fema.dhs.gov 

770-220-5626