Why rapid computation?

Research Lead The University of North Carolina at Chapel Hill CHC-R 5th Annual Meeting January 31-February 1, 2013

AdcircLite-NC: Rapid evaluation of storm surge and wave forecasts using

the Notre Dame Surrogate Forecast Generator (AdcircLite for North Carolina)

Brian BlantonRenaissance Computing Institute

University of North Carolina at Chapel Hill

Jesse Bikman, MS CandidateDepartment of Marine Sciences

University of North Carolina at Chapel Hill

Alexander TaflanidisAndrew Kennedy

Department of Civil & Environmental Engineering and Earth SciencesUniversity of Notre Dame


Why rapid computation?

• Urgent forecasting needed before disaster strikes• Forecast simulations are resource intensive, requiring 2.5 - 3

hours computation time on 192 processor systems– Direct simulation of multiple high-resolution ensemble members

practically impossible.

• Need to Accelerate forecast data throughput– Much more computer hardware (not likely)– Use rapid statistical methods instead


Our ApproachImplement a response surface method (RSM) that rapidly predicts a response influenced by

several variables

• Method developed by collaborators at UND• Use pre-existing large data set of storm surge simulations

from FEMA coastal Flood Insurance Study for NC• Make available rapid predictions to existing publication

mechanisms


Leveraging of other Activities• Previous FEMA coastal flood hazard analysis• U Notre Dame’s expertise in optimization

methods, and experiences in Hawaii waves• RENCI’s Cyber Infrastructure


Why use a Response Surface Method?

• Long history in engineering, chemistry…

• … more recently in hazards (Resio , Irish, et al.)

• “Easy” to use higher-order interpolation

• High accuracy compared to zeroth-order methods


Why use a Response Surface Method?Direct Simulation

Surrogate Model

Hawaii Wave Prediction Example

Surge Estimation


Project Goal and Expected Architecture

Components in orange already exist. Components in box on the right are already a part of the North Carolina Forecast System.

Components in blue will be established by this project.

AdcircLite-NC


What does AdcircLite-NC do?Uses 648 simulation dataset:• Water level, wave heights• Hurricane parameters (radius to max winds, forward speed, etc…)

648 surge/wave simulations from FEMA FIS Surge response for one hurricane track


What does the RSM look like?

= quadratic basis functions

Central pressure deficit (Cp)Radius to maximum winds (Rm)Holland B shape parameter (B)Storm forward speed (Vf)Storm heading (θ)Along-coast distance (X0)

X = [Cp, Rm, B, Vf, θ, X0];

= estimated response at x

= coefficients

NB = number of basis functions


Progress to date:Project started 1 Jan 2013, Year 5.5

Task 1. Preliminary datasets and testing of the UNDInterpolator

– Focused on getting mechanics and code developed

– Established code in MATLAB to interact with database– Implemented initial version of UNDInterpolator in MATLAB– Experimenting with interpolator parameters


Example:• Select 100 points along NC coast

• Use all of dataset to build a storm surge surrogate model

• Use Hurricanes Fran (1996) and Isabel (2003) landfall parameters and surrogate model to “predict” historical response

IsabelFran

Very Preliminary Results


Next steps, near-term• Establish better control and validation sets• Formal optimization of parameters in the

UNDInterpolator• Evaluation of different validation criteria• Interpolators for significant wave height

estimation.


Next steps, long-termIncorporation of AdcircLite-NC predictions into NC-CERA

• AdcircLite-NC will produce standard ADCIRC output

• Publish output files to existing data server

• Same alert mechanism used by NCFS

• Spatial grid defined in netCDF output files

Why rapid computation?

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