Don Resio, Senior Scientist, US Army ERDC-CHL Data Needs for Coastal Storm Surge Estimation IbTrACS Meeting Honolulu, HI April 12, 2011

Outline of Talk Beyond “evacuation forecasting” and climate change Some existing needs Coastal Flood Protection & Risk Estimates (USACE) Flood Insurance Rates (FEMA) Licensing of sites for nuclear power plants (NRC) Sufficient information for surge risk estimation

Two Major Types of Data Needs Forecasts: Go/No-Go Evacuation Decision - long lead time (3-5 days) - must be conservative - uncertainty “factored in” Storm-Approach Operations - time-phased information - late evacuation routing - gate/spillway decisions - uncertainty quantified Post-Storm Operations - time-phased information - accurate damage assessment - accurate systems assessment - critical recovery decisions Planning/Risk Mitigation: Accurate Hazard Climatology - consistent data set - long period of record - uncertainty quantified - climatic variability Accurate Response Specification - human response - system response Quantified Risk/Alternatives - time-phased options **** - climatic variability - uncertainty quantified - Objective “cost” estimates Current forecast systems focus on this problem

Climate Variability Whereas tropical storm frequency alone may be key to understanding and quantifying some aspects of climate change, major impacts may relate more to and variations in storm surge potential

Tropical Storms and Hurricanes (23 = $334B K=$133B) Heat/Drought (15 = $130B) Interior Flooding (15 = $74B) Severe Weather (19 = $31B) Fires (10 = $19B ) Blizzard (2 = $12B) Ice (2 = $6B) Northeasters (1 for $2B) Gulf Oil Spill (2010)9/11 Trade Center $20 – $40B$20 - $30B Three Mile Island $1B EXTREMES ARE WHAT CREATES DISASTERS

Three steps in understanding/quantifying risk : 1.Hazard identification/quantification 2. Vulnerability Assessment 3. Risk Analysis Storm frequency is insufficient to quantify surge levels at a coast. For example: Storm size is critical to storm surges along a coast No “Cat 5” design for New Orleans!

For single storms we typically use HWIND-type of products to force models Reconstructed Winds, 1200 UTC 29 Aug 2005 HWINDS

But for Hazard/Risk Assessment, we need statistics of 6 basic parameters General form for surge response at location x and time t: Bottom line: There are 5 important storm parameters plus storm track and the changes in near-coast storms that have to be considered in JPM.

LAND WATER Based on data from Oceanweather, decay during approach to land is about the same as post-landfall decay. BUT: Variations near a coast must also be recognized/estimated. Relationship is specific to northern GOM

Similar results in the time domain have been found by NHC in its own studies.

In addition to the necessity of properly modeling physical phenomena for critical events – It is also necessary to understand and quantify their probabilities. To accomplish this, we must accurately specify all of the myriad forcing processes within a probabilistic framework.

Statistical Approach – Fitting the Modeling into Risk JPM with Optimal Sampling (JPM-OS) Joint probability matrix: All the surges are put into appropriate bins. Different storms can produce results in the same bin. Must include uncertainty!! Uncertainty is model/system specific Reduction in uncertainty reduces cost Adding uncertainty increases cost Uncertainty added in each mapping

In any dimension we have for the pdf the ability to map from an n-dimensional space into a 1-dimensional space via a Dirac delta-function δ And the CDF which uses the Heaviside Function (an integral of the delta function)

Since we remain imperfect, we need to consider an error term also!!!! This means that we can leave some degree of randomness in our solutions – as long as we can estimate the statistical characterization of this term – which also includes tides, wind field errors, errors in physics, other omissions, etc. The expected return period can be estimated from the CDF via the assumption that the storm occurrence is governed by a stationary Poisson process, with an average frequency of occurrence of λ. Unfortunately, nature often deviates from this simplistic assumptions – with years containing many storms not following the same distribution as years with few storms

Present Status Insufficient data exists in “public” data sources Data from Oceanweather and Applied Research Associates is used for driving surge models Updates/improvements of these data are difficult to accomplish An extension to IbTrACS would go a long way to help improve our ability to estimate hazards/risks worldwide

QUESTIONS??