Coastal Emergency Risks Assessment (CERA)
cera.coastalrisk.live
This repository is maintained by the LSU CERA-Group, a team of scientists, researchers, and developers dedicated to studying the potential impacts of storm surge and inland flooding caused by landfalling tropical cyclones. We focus on providing accurate and timely information to decision-makers and first responders to support their preparedness efforts and ultimately save lives and properties.
Our objective is to simulate and visualize storm surge using advanced computer models like ADCIRC and the cutting-edge CERA visualization technology. By this tutorial series we are trying to open our knowledge to the research community for the post-proscesing and visualization of storm surge data.
The tutorials use Python, Jupyter, NumPy, pandas, Matplotlib, netCDF4, Cartopy, Pillow, and ipywidgets.
The recommended setup uses Conda/Mamba with packages from conda-forge:
conda env create -f environment.yml
conda activate cera-tutorials
python -m ipykernel install --user --name cera-tutorials --display-name "Python (cera-tutorials)"Alternatively, with pip:
python3 -m venv .venv
source .venv/bin/activate
python3 -m pip install -r requirements.txtCartopy and netCDF4 depend on compiled libraries, so Conda/Mamba is recommended if pip installation fails.
| Tutorial | Directory |
|---|---|
| A Beginner's Guide to Analyzing ADCIRC NetCDF Data with Python | Analyzing NetCDF Files/ |
| Matplotlib Contouring for ADCIRC NetCDF Data | Creating Map Contours with Matplotlib/ |
| Geospatial Data Visualization: Introduction to Cartopy | Adding Map Features with Cartopy/ |
| Visualizing a Single NHC Track with Matplotlib | Visualizing a Single NHC Track with Matplotlib/ |
| Visualizing Multiple NHC Tracks with Matplotlib | Visualizing Multiple NHC Tracks with Matplotlib/ |
| Stage-Discharge Curve Fitting for River Flow | Calculating River Flow/ |
Explains the structure of an ADCIRC NetCDF file using the Python library NetCDF4, and how its well-organized layout enables analysis of large geospatial datasets.
Uses Matplotlib to turn ADCIRC NetCDF data into contoured storm surge maps for the Northern Gulf and the Atlantic Coast, with attention to clean geometries for GIS workflows.
Introduces the Cartopy library for geospatial visualization: maps with varying projections, overlaying coordinate points, and customizing map appearance.
Renders one ATCF best-track file into a publication-style map, optionally with validation stations overlaid.
Plots a catalog of Atlantic best-track files as regional overview maps, colored by wind speed.
Fits a stage-discharge curve for a tidal river station.
If you have any questions, suggestions, or would like to get in touch with our team, please feel free to reach out to us. Together, we can make a significant impact in enhancing our preparedness and resilience to storm-related challenges.
CENTER FOR COMPUTATION AND TECHNOLOGY, LOUISIANA STATE UNIVERSITY