Utilizing Code for Dynamic Data Visualization of National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS) Data during Hurricane Ian

Data visualization is important in the research and understanding of the impacts of extreme events. The Category 4 tropical cyclone Hurricane Ian in September 2022 had devastating impacts on the communities in and around Fort Myers, Florida with a record storm surge of 7.26 feet and winds exceeding 150 mph. This project aims to present users with a concise and accessible strategy to retrieve and display data from NOAA’s National Ocean Service. In this process, we retrieved tide gauge data from CO-OPS API (application programming interface) URL Builder observed as Hurricane Ian moved through the region. Data retrieved included water level above mean higher high water, atmospheric pressure, wind speed, and wind direction. Using Jupyter Notebooks with Python, we were able to display oceanographic and atmospheric data associated with this natural disaster. Additionally, this code was translated to R language to benefit a broader range of users. This process, as outlined in Jupyter Notebooks, successfully demonstrates CO-OPS API data retrieval and visualization. With these example notebooks, users can manipulate parameters to aid in the research and understanding of Hurricane Ian and other natural disasters.