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AdcircLite-NC Rapid computation of storm surge and waves for NC coastal waters Brian Blanton Renaissance Computing Institute/UNC Chapel Hill Jesse Bikman,

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Presentation on theme: "AdcircLite-NC Rapid computation of storm surge and waves for NC coastal waters Brian Blanton Renaissance Computing Institute/UNC Chapel Hill Jesse Bikman,"— Presentation transcript:

1 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 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 Eye of storm locationProbability 72 hours out10% 48 hours out12 – 18% 36 hours out20 – 25% 24 hours out35 – 45% 12 hours out60 – 70%

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 Fran and 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 Ẑ i (x) = response at x b(x) = basis functions a i (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 Fran and 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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