文件列表:

LICENSE (35149, 2023-07-07)
OLD (0, 2023-07-07)
OLD\Calc_WIS_Storms.py (8069, 2023-07-07)
OLD\Ian_VCR_StormList.npy (559344, 2023-07-07)
OLD\Scatter-Cvine_2mBerm_V1_NoBMI.fig (8923759, 2023-07-07)
OLD\Scatter-Tstudent_2mBerm_V1_NoBMI.fig (4621081, 2023-07-07)
OLD\Tide-8631044-Raw.mat (2170624, 2023-07-07)
OLD\Usim_mssmVCR-Cvine.mat (320184, 2023-07-07)
OLD\run_mssm.py (611, 2023-07-07)
example_input (0, 2023-07-07)
example_input\ST63183_v03.onlns (79771900, 2023-07-07)
example_input\Tide-8631044-Combined.csv (10322143, 2023-07-07)
example_input\Tide-8631044-Combined.txt (10322140, 2023-07-07)
example_output (0, 2023-07-07)
example_output\Inputs_mssm.txt (6, 2023-07-07)
example_output\StormList_10k_VCR_Berm1pt9m_Slope0pt04.csv (525629, 2023-07-07)
example_output\StormList_20k_VCR_Berm1pt9m_Slope0pt04.csv (1047837, 2023-07-07)
example_output\U_mssm.txt (16856, 2023-07-07)
example_output\Usim_mssm-Cvine.mat (640184, 2023-07-07)
example_output\Usim_mssm-Dvine.mat (640184, 2023-07-07)
mssmVines.R (2045, 2023-07-07)
multivariateSeaStorm.m (33290, 2023-07-07)
requirements (0, 2023-07-07)
requirements\CDVine_1.4.tar.gz (101130, 2023-07-07)
requirements\allfitdist.m (14103, 2023-07-07)
requirements\license_allfitdist.txt (1313, 2023-07-07)
requirements\t_tide_v1 (0, 2023-07-07)
requirements\t_tide_v1\g.mat (130261, 2023-07-07)
requirements\t_tide_v1\t_18constituents.mat (14568, 2023-07-07)
requirements\t_tide_v1\t_astron.m (4285, 2023-07-07)
requirements\t_tide_v1\t_constituents.mat (29224, 2023-07-07)
requirements\t_tide_v1\t_demo.m (4487, 2023-07-07)
requirements\t_tide_v1\t_equilib.dat (1176, 2023-07-07)
requirements\t_tide_v1\t_equilib.m (2316, 2023-07-07)
requirements\t_tide_v1\t_errors.m (7263, 2023-07-07)
requirements\t_tide_v1\t_example.mat (25600, 2023-07-07)
requirements\t_tide_v1\t_getconsts.m (5512, 2023-07-07)
requirements\t_tide_v1\t_predic.m (5265, 2023-07-07)
... ...

# A Multivariate Sea Storm Model Following the methods of Wahl et al. (2016), we develop a copula-based multivariate sea-storm model (MSSM) with functionality for gaussian, t-student, and vine copulas. The notebook provided at https://github.com/UNC-CECL/Barrier3D describes the MSSM components and an example application of the MSSM for use with Barrier3D - an exploratory barrier island evolution model. We provide a sample call below and describe the model inputs herein. `[stStorms, stSimStorms] = multivariateSeaStorm(sCopula, sWIS_filename, sWaterLevel_filename, fBeta, fBermEl, nSimStorm, bPlot, sOutput_filename)` The MSSM model `multivariateSeaStorm.m` is written in Matlab in order to utilize the t-tide package, which allows for robust fitting of tidal constituents to water level time series, but also calls the program `mssmVines.R` to use vine copulas from the `CDVine` package in `R`. There is one hardcoded directory in `mssmVines.R` that will need to be changed by the user based on the location of `Rscript`: ```#! /Library/Frameworks/R.framework/Resources/bin/Rscript```). Note that we followed the model of the MultiHazard toolbox https://github.com/rjaneUCF/MultiHazard for fitting and simulating from vine copulas, and thank them for an awesome toolbox. The MSSM model requires the following inputs: ``` Inputs: sCopula - copula to be fitted to storm variables; options are "c-vine", "d-vine", "gaussian", or "t-student" sWIS_filename - .onlns file downloaded from a USACE Wave Information Studies (WIS) bouy; must contain hourly records of wave height (m) sWaterLevel_filename - .txt file that contains hourly records of total water level in m NAVD88 as second column, first column is datetime; downloaded for each year from NOAA; must be either the same length or longer than WIS time record fBeta - beach slope nSimStorm - number of simulated storms to create fBermEl - erosion threshold; Wahl used 5% of dune toe heights; we use the average berm elevation (m NAVD88) bPlot - boolean for plotting sOutputFilename - string of prefix for csv output filename ``` In the example provided in the notebook at https://github.com/UNC-CECL/Barrier3D, we utilize a 35 year record of hourly wave hindcast data – including wave height (Hs) and wave period (Tp) – from the USACE’s Wave Information Studies buoy offshore Hog Island in the Virginia Coast Reserve (Station 63183, 22 m water depth) and hourly records of water level from the nearest NOAA tide gauge (Station 8631044, Wachapreague, VA) to create a list of 20,000 synthetic storms. We specify a berm elevation of 1.9 m (the average along Hog Island) and beach slope of 0.04. The c-vine produced the highest tau values (Kendall's Corelation Coefficient) over the elliptical Gaussian and T-student copulas, as well as the d-vine copula. `[stStorms, stSimStorms] = multivariateSeaStorm("c-vine", "ST63183_v03.onlns", "Tide-8631044-Combined.txt", 0.04, 1.9, 20000, true, "StormList_20k_VCR_Berm1pt9m_Slope0pt04.csv")`

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