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AdcircLite -NC Rapid computation of storm surge and waves for NC coastal waters

AdcircLite -NC Rapid computation of storm surge and waves for NC coastal waters. Brian Blanton Renaissance Computing Institute/UNC Chapel Hill Jesse Bikman , MS Candidate Department of Marine Sciences, UNC Chapel Hill Alexander Taflanidis , Andrew Kennedy University of Notre Dame

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AdcircLite -NC Rapid computation of storm surge and waves for NC coastal waters

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  1. AdcircLite-NCRapid computation of storm surge and waves for NC coastal waters Brian Blanton Renaissance Computing Institute/UNC Chapel Hill Jesse Bikman, MS Candidate Department of Marine Sciences, UNC Chapel Hill Alexander Taflanidis, Andrew Kennedy University of Notre Dame Department of Civil & Environmental Engineering and Earth Sciences

  2. 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 • Planners/emergency managers need forecast information as quickly as possible • AdcircLite-NC provides storm surge and wave forecasts at response nodes by implementing UND surface response method [Show map with response nodes + screenshot of NC-CERA]

  3. Phased Evacuation Timeline for Chatham (GA) Emergency Management Agency

  4. Theoretical probabilities for a direct hit at a given location over time

  5. Project goals and expected results Task 1. Preliminary data and testing/calibration of UNDInterpolator • Establish response node evaluation dataset • [Assemble historical record of high water marks from tide gauge records?] • Hindcast hurricanes such as Franand Isabel Task 2. Expand to include wave characteristics • Expand UNDInterpolator to include significant wave height, period, direction Task 3. Integrate into North Carolina Forecast System • Post-process UNDInterpolator output into NC-CERA/OPeNDAP formats Task 4. Calibration and Skill Assessment • Cross validate to improve accuracy • Optimize for storm surge and wave heights

  6. Project goals and expected results [Should the previous slide instead just cover the milestones? Previous slide is very text heavy. Unsure if that is a problem.]

  7. What does AdcircLite-NC do? • Response Surface Method(RSM) — Given an set of input parameters, predict a response influenced by several variables • Input parameters for AdcircLite-NC: hurricane parameters • RSM for AdcircLite-NC: UNDInterpolator Could also mention that [RSM originally developed in 1950s to determine optimal operating conditions in chemical engineering applications(Myers et al., 1989)] [In coastal realm, RSM previously used for modeling wave crest elevation from wave spectra(Tromans et al., 2004, Gibson et al., 2007), and larval development from temperature/salinity(Lough et al., 1973)]

  8. What does ADCIRC-Lite do? AdcircLite-NC uses NHC best track and pre-computed dataset as inputs [Show map with hurricane track]

  9. What does AdcircLite-NC do? UNDInterpolator evaluates track response using pre-computed dataset [Show plot of LF tracks and plot of BP tracks]

  10. What does AdcircLite-NC’s RSM look like? Where x = vector containing hurricane track parameters Ẑi(x) = response at x b(x) = basis functions ai(x) = basis coefficients NB = number of basis functions

  11. What parameters are used? [Description of parameters, showing most of them via map.] [Introduce Holland B with r/RMW vs V_G/P(r) plots] [Holland B is not a parameter in the proposal’s RSM formulae, does that matter?]

  12. Progress to date: Task 1. Preliminary datasets and testing of the UNDInterpolator • Established testbed of response nodes • Compared UNDInterpolator output from response nodes to validated ADCIRC runs for hurricanes Franand Isabel

  13. Progress to date: [Generate results at 100 response points and compare to validated ADCIRC runs]

  14. Next steps, near-term [Hindcasting, optimizing weights for parameters in basis coefficients]

  15. Next steps, long-term [incorporation into NC-CERA]

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