Workshop on

Probabilistic Flood Hazard Assessment

(PFHA)

PROGRAM

January 29 - 31, 2013, 8:30 a.m.–6:30 p.m. (EST)

U.S. NRC Headquarters Auditorium

11555 Rockville Pike, Rockville, MD 20852

Recent Work and Future Directions in Coastal 

Surge Modeling and Sea Level Extremes 

within NOAA

Stephen Gill and Jesse Feyen

NOAA National Ocean Service

Panel 7: Extreme Storm Surge for Coastal Areas
Storm Surge Modeling at NOAA

• NOAA uses surge models to predict storms, assess 

risks, and understand historical events

• Forecast guidance operational requirements are 

strict

– Timeliness and robustness are key; leads to bias for 

efficiency over accuracy

– Cost-effectiveness also needed for ensemble and 

probabilistic predictions

– NOAA predicts storms via efficient SLOSH and ADCIRC 

implementations

• Highly accurate hindcasts require increased 

resolution and more complex parameterizations
Sea, Lake, and Overland Surges from Hurricanes 

(SLOSH): NWS’ Operational Surge Model

• The basis for tropical cyclone products

• Uses numerous coastal domains (basins) 

– Structured grids of limited extent and resolution

– From tens of meters to a few kilometers offshore

– Sub-grid cell features to model barriers (such as 

levees or roadways) and waterways

• Simple hurricane model driven by storm track, 

radius of maximum winds, and central pressure

Further info: http://slosh.nws.noaa.gov/sloshPub
SLOSH’s Basins

Basins are efficiently sized but 

can have difficulty capturing larger 

storms and are limited by size and 

orientation of structured grid cells
Contrasting Structured and Unstructured Grids – SLOSH and the 

ADVANCED CIRCULATION MODEL FOR OCEANIC,COASTAL AND 

ESTUARINE WATERS (ADCIRC) ( examples for New Orleans, Pensacola)
Computing Surge Hazard Analyses

• SLOSH’s primary function is to compute surge 

hazard analysis for hurricane evacuation studies

– NHC runs around 15,000 hypothetical storms in each 

basin to create composites of potential surge

– Results define surge hazard for evacuation zones

– More info from the National Hurricane Program: 

http://www.iwr.usace.army.mil/nhp/

MEOW = Maximum Envelopes of Water

Worst case snapshot for a particular storm category, forward 

speed, trajectory, and initial tide level, incorporating uncertainty 

in landfall location 

MOM = Maximum of Maximums

Combines all MEOWs for a particular storm category
Generating a MEOW Composite of Maximum 

Envelopes of Water in the 

New Orleans basin for all 

Cat 3 hurricanes moving north 

at 25 mph during high tide
Rmax=25 mi

(forecast)

Hurricane Ivan (2004) Surge Based on NHC 12 hr. Advisory

Forecast uncertainties mean models 

need to be able to run multiple 

scenarios quickly rather than 

accurately compute a single result – 

potential conditions can change 

significantly up to landfall
Rmax=40 mi

Hurricane Ivan (2004) Surge Based on NHC Storm Best Track 

Forecast uncertainties mean models 

need to be able to run multiple 

scenarios quickly rather than 

accurately compute a single result – 

potential conditions can change 

significantly up to landfall
Computing Storm Surge Probabilities

• P-Surge: storm surge ensemble based on NHC forecast 

advisory

– Perturbation of cross-track error, along-track error, 

intensity error, and size error

• Used to calculate probabilities and exceedances

– “Probability of water exceeding X feet”; available on 

NHC’s website: http://www.nhc.noaa.gov/index.shtml

– “Height exceeded by X%” of ensemble members; 

available at MDL: http://www.weather.gov/mdl/psurge/

• Operational time constraint of getting an answer out within 

30-minutes of Advisory release time
Perturbing the Hurricane Forecast

• Perturb across 90% of 

possible track error 

(roughly 3 times the size 

of the cone of error)

• Error distributions for 

cross track, along track 

and intensity:

– Assume a normal 

distribution

– Use a 5-year “mean 

absolute error”

• Results in hundreds of 

storms run through a 

dozen basins resulting in 

thousands of simulations
Katrina Advisory 23 - Probability of > 5 

feet of Storm Surge
Extra-Tropical Storm Surge

• Extra-Tropical Storm Surge (ETSS)

– Finite differencing model developed by the 

Meteorological Development Laboratory

– Modified SLOSH to predict storm surge heights from 

extra-tropical storms

– Global Forecast System for wind forcing

– Structured grid with finer resolution overland, and 

coarser offshore

• Does not include

– Tides, waves, river flow

– Overland storm surge
Extratropical Storm Surge Website

Combine the ETSS output with:

• Observations from NOS / CO-OPs

• Tides computed from 

constituents provided by 

NOS/CO-OPS

• Uses a 5 day running average 

error to improve total water level 

forecast

• Provides guidance on flooding 

(when total water level exceeds 

the HAT)

NOS/OPC also has ETSS model 

output

• http://www.opc.ncep.noaa.gov/e

t_surge/et_surge_info.shtml

• Animations of maps of ETSS 

output with GFS pressure fields

http://www.weather.gov/mdl/etsurge
ADCIRC-based Operational Surge 

Predictions

– Extratropical Surge and Tide Operational 

Forecast System (ESTOFS)

– Operational forecast guidance for extratropical 

storms in Western North Atlantic basin

– Computes surge with tides (4X per day)

• Differs from higher resolution hindcast models

– Insufficient grid resolution at rivers, inlets, and barrier 

islands

– No overland grid coverage, waves, or river inflows
ESTOFS-Atlantic 

• East Coast 2001 tidal 

database grid (EC2001)

– 254,565 nodes

• Coastal resolution of 

approximately 3 km is 

not highly precise but 

efficient for operational 

forecasting
17

ESTOFS Graphic for February 1, 2013
Recent Work in Sea Level and Extreme 

Water Levels in NOAA
Relative Sea Level Trends at US Tide Stations

http://tidesandcurrents.noaa.gov/sltrends/index.shtml
Relative Sea Level Trends and Vertical Land Motion at Tide stations

Regions of significant vertical land subsidence

Tide Station Location Relative Sea Level Trend Estimated Vertical land Motion

Colonial Beach, VA 4.8 mm/yr (1.2 mm/yr) -3.1 mm/yr (0.3 mm/yr)

Lewisetta, VA 5.0 mm/yr (1.0 mm/yr) -2.4 mm/yr (0.4 mm/yr)

Gloucester Pont, VA 3.8 mm/yr (0.5 mm/yr) -2.4 mm/yr (0.1 mm/yr)

Sewells Point, VA 4.4 mm/yr (0.3 mm/yr) -2.6 mm/yr (0.11 mm/yr)

CBBT, VA 6.1 mm/yr (1.1 mm/yr) -3.3 mm/yr (0.4 mm/yr)

Grand Isle, LA 9.2 mm/yr (0.6 mm/yr) -7.6 mm/yr (0.2 mm/yr)

Sabine Pass. TX 5.7 mm/yr (1.1 mm/yr) -3.8 mm/yr (0.5 mm/yr)

Galveston Pier 21, TX 6.4 mm/yr (0.3 mm/yr) -4.7 mm/yr (0.2 mm/yr)

Galveston PP, TX 6.8 mm/yr (0.8 mm/yr) -4.9 mm/yr (0.4 mm/yr)

Freeport, TX 4.4 mm/yr (1.1 mm/yr) -3.6 mm/yr (0.4 mm/yr)

Rockport. TX 5.2 mm/yr (0.7 mm/yr) -3.6 mm/yr (0.4 mm/yr)

North Spit, Humboilt Bay, 

CA 4.7 mm/yr (1.6 mm/yr) -3.4 mm/yr (0.5 mm/yr)

Cordova, AK 5.7 mm/yr (0.9 mm/yr) -3.4 mm/yr (0.4 mm/yr)

Estimated standard errors of trends given in parentheses


Extreme Water Levels
Extreme Water Levels at US Tide Stations

http://tidesandcurrents.noaa.gov/est/



Preliminary Return Periods for Hurricane/Storm 

Sandy

Bridgeport, CT 120 years (25 - 2100 years)

The Battery, NY 1600 years (230 - 35,000 years)

Sandy Hook NJ 290 years (65 - 4000 years)

Atlantic City, NJ 25 years (12 - 60 years)

Kings Point, NY 23 years (11 - 66 years)

Using NOAA Exceedance Probability Analysis Methodology

http://tidesandcurrents.noaa.gov/est/
Projected Sea level Rise Scenarios up to 2100 in 

Response to Climate Change

Taken from: Global Sea Level Rise Scenarios for the United States National

Climate Assessment, December 6, 2012, NOAA Technical Report OAR CPO-1
Global Sea Level Rise Scenarios for the United States 

National Climate Assessment, December 6, 2012

• Global Mean Sea Level Rise Scenarios: Very high confidence (>9 in 10 

chance) that global mean sea level will rise at least 0.2 meters (8 

inches) and no more than 2.0 meters (6.6 feet) by 2100.

– Highest Scenario of global SLR by 2100 is derived from a combination of estimated 

ocean warming from the IPCC AR4 global SLR projections and a calculation of the 

maximum possible glacier and ice sheet loss by the end of the century.

– Intermediate-High Scenario is based on an average of the high end of semi-empirical, 

global SLR projections. Semi-empirical projections utilize statistical relationships 

between observed global sea level change, including recent ice sheet loss, and air 

temperature.

– Intermediate-Low Scenario is based on the upper end of IPCC Fourth Assessment 

Report (AR4) global SLR projections resulting from climate models using the B1 

emissions scenarios.

– The Lowest Scenario is based on a linear extrapolation of the historical SLR rate 

derived from tide gauge records beginning in 1900 (1.7 mm/yr).
Potential Impacts of Sea-Level Rise on Extreme 

Water Level Return Frequencies

• Subject of active scientific research 

– Use long-term tide gauge observations (>40 years)

– Perform extreme value analyses (two methods being 

investigated current exceedance probabilities

• Annual Maxima Method (AMM) with Generalized Extreme 

Value (GEV)

• Peak Over Threshold (POT) with Generalized Pareto 

Distribution (GPD)

– Estimate future extreme exceedance probabilities by using 

NCA SLR scenarios, vertical land motion estimates
Figure 3. Hourly observations at Honolulu before detrending (A) and GPD-derived 

plots (B-D) with application of NCA SLR Intermediate High (H) and Low (L) 

scenarios. (example from Marra and Sweet, NOAA, 2012)

Example Preliminary Analysis - Draft
ns

Questions?

Stephen Gill, NOAA/NOS Center for Operational Oceanographic 

Products and Services, Silver Spring, MD stephen.gill@noaa.gov

Jesse Feyen, NOAA/NOS Coast Survey Development Laboratory,

Silver Spring, MD jesse.feyen@noaa.gov