Abstract:

The focus of this project is uncertainty quantification (UQ) of storm surge impacts due to uncertainty in wind predictions, focusing on hurricanes in the Gulf of Mexico, with a specific focus on the New Orleans region. The original input data, which is the best track of Hurricane Gustav, is obtained from NOAA. We use a perturbation technique to generate a series of ensembles as model inputs for our UQ analysis. Then a hydrological shallow water model ADCIRC has been used to obtain model outputs (i.e. water elevation time series on specified stations & maximum water surface elevation over time), corresponding to the ensemble inputs. The dataset has been organized in the following way: 2 scenarios represent different sources of uncertainty input. In the first scenario, the sources of uncertainty stem from the track (parametrized by 2 random variables) and the maximum wind speed (parametrized by 1 random variable) of the hurricane. In the second scenario, the sources of uncertainty come from the maximum wind speed (parametrized by 1 random variable) and the Manning’s n coefficient (parametrized by 2 random variables). For each scenario, we split the dataset (150 ensembles in total) into two parts: training (100 ensembles) and validating (50 ensembles). For both training and validating set, we provide inputs as well as model output data, respectively. The training set is used to build the (polynomial chaos) surrogate model of the maximum water surface elevation. The validation set, independent from the training set, allows us to validate the accuracy of the surrogate before conducting the statistical analysis.

Suggested Citation:

C. Chen, P. Sochala, M. Isakandarani, C. Dawson. 2019. Polynomial chaos analysis of hurricane wind parameters in the Gulf of Mexico from 2008-08-28 to 2008-08-31. Distributed by: GRIIDC, Harte Research Institute, Texas A&M University–Corpus Christi. doi:10.7266/N73777BS

Publications:

Sochala, P., Chen, C., Dawson, C., & Iskandarani, M. (2019). A polynomial chaos framework for probabilistic predictions of storm surge events. Computational Geosciences, 24(1), 109–128. doi:10.1007/s10596-019-09898-5

Purpose:

The data was generated as part of a research project to apply uncertainty quantification techniques to improve hurricane wind parameters using available data collected during a hurricane.

Data Parameters and Units:

Wind drag limit (unitless); maximum wind speed (m/s); longitude of the hurricane center (degrees); latitude of the hurricane center (degrees); water elevation time series in height above geiod (meters); maximum water surface elevation in height above geoid (meters); sea surface height above geoid (m); surface submergence state (unitless); surface canopy coefficient (unitless); surface directional effective roughness length (m); mannings n at sea floor (unitless); time since 08-28-2008 06:00:00 (seconds). Description of the file organization are as follows: 1. dataset_for_scenario_1/ A) dataset_for_scenario_1_training/ The training dataset is used for constructing the surrogate model, 100 ensembles in total. --dataset_for_input/variations_on_fort15_windDragLimit/ fort.15_XXX: ADCIRC model parameter input files. Each fort.15_XXX contains an ensemble of wind drag limit. --dataset_for_input/variations_on_fort22_MaxWindSpeed_Longitude_Latitude/ HTS_XXX.txt: ADCIRC wind input files. Each HTS_XXX.txt contains an ensemble of the wind paramters (maximum wind speed, longitude of the hurricane center, latitude of the hurricane center) -- dataset_for_output/QoI_fort61_stations_timeseries/ fort.61_XXX: ADCIRC water elevation time series output files. Each fort.61_XXX is produced by running ADCIRC with the corresponding fort.15_XXX and HTS_XXX.txt files. stdout_21.txt & stdout_51.txt: water elevation time series at location #21 and #51 (Intermediate post analysis files for visualization purposes, can be ignored). ==> Need change here. -- dataset_for_output/QoI_maxele_overtime/ maxele.63.nc_XXX: ADCIRC maximum water surface elevation output files. Each maxele.63.nc_XXX is produced by running ADCIRC with the corresponding fort.15_XXX and HTS_XXX.txt files. B) dataset_for_scenario_1_validate/ The validate dataset is used for validating the surrogate model, 50 ensembles in total. The underlying folder structure and description is very similar to training dataset. -- dataset_for_input/variations_on_fort15_windDragLimit/ fort.15_XXX: ADCIRC model parameter input files. Each fort.15_XXX contains an ensemble of wind drag limit. -- dataset_for_input/variations_on_fort22_MaxWindSpeed_Longitude_Latitude/ HTS_XXX.txt: ADCIRC wind input files. Each HTS_XXX.txt contains an ensemble of the wind parameters (maximum wind speed, longitude of the hurricane center, latitude of the hurricane center) -- dataset_for_output/QoI_fort61_stations_timeseries/ fort.61_XXX: ADCIRC water elevation time series output files. Each fort.61_XXX is produced by running ADCIRC with the corresponding fort.15_XXX and HTS_XXX.txt files. -- dataset_for_output/QoI_maxele_overtime/ maxele.63.nc_XXX: ADCIRC maximum water surface elevation output files. Each maxele.63.nc_XXX is produced by running ADCIRC with the corresponding fort.15_XXX and HTS_XXX.txt files. 2. dataset_for_scenario_2/ A) dataset_for_scenario_2_training/ The training dataset is used for constructing the surrogate model, 100 ensembles in total. -- dataset_for_input/variations_on_fort13_Marshland_Forest/ fort.13_XXX: ADCIRC manning's coefficient input files. Each fort.13_XXX contains an ensemble of manning's coefficient. -- dataset_for_input/variations_on_fort22_MaxWindSpeed/ HTS_XXX.txt: ADCIRC wind input files. Each HTS_XXX.txt contains an ensemble of the maximum wind speed. -- dataset_for_output/QoI_fort61_stations_timeseries/ fort.61_XXX: ADCIRC water elevation time series output files. Each fort.61_XXX is produced by running ADCIRC with the corresponding fort.15_XXX and HTS_XXX.txt files. -- dataset_for_output/QoI_maxele_overtime/ maxele.63.nc_XXX: ADCIRC maximum water surface elevation output files. Each maxele.63.nc_XXX is produced by running ADCIRC with the corresponding fort.15_XXX and HTS_XXX.txt files. B) dataset_for_scenario_2_validate/ The validate dataset is used for validating the surrogate model, 50 ensembles in total. The underlying folder structure and description is very similar to training dataset. -- dataset_for_input/variations_on_fort13_Marshland_Forest/ fort.13_XXX: ADCIRC manning's coefficient input files. Each fort.13_XXX contains an ensemble of manning's coefficient. -- dataset_for_input/variations_on_fort22_MaxWindSpeed/ HTS_XXX.txt: ADCIRC wind input files. Each HTS_XXX.txt contains an ensemble of the maximum wind speed. -- dataset_for_output/QoI_fort61_stations_timeseries/ fort.61_XXX: ADCIRC water elevation time series output files. Each fort.61_XXX is produced by running ADCIRC with the corresponding fort.15_XXX and HTS_XXX.txt files. -- dataset_for_output/QoI_maxele_overtime/ maxele.63.nc_XXX: ADCIRC maximum water surface elevation output files. Each maxele.63.nc_XXX is produced by running ADCIRC with the corresponding fort.15_XXX and HTS_XXX.txt files. 3. model_common_input_for_ADCIRC/ --fort.14: Mesh and bathymetry file of ADCIRC simulations.

Methods:

The uncertainty quantification method used is polynomial chaos.

Individual Files: