[32] - Hurricane Projection Assessment

Inspiration

Hurricanes are large, disruptive, and damaging weather events, and are becoming more frequent in recent times. When ill-prepared, they can cause massive property damage, disrupt modern society, and result in loss of life. Accurate forecasting is the most valuable tool we have to prevent the worst that hurricanes can cause. We wanted to create a program to assist in assessing the efficacy of hurricane forecasting and projections, with the hope that we will improve future models.

What it does

This program takes in data collected from recent hurricane weather advisories and displays how accurate the projections were using visualizations in Google Earth via kml files.

How we built it

Through the use of object oriented programming in Python, we performed data parsing and analysis of NOAA hurricane path projections. We utilized a class "Hurricane" to extract and parse data, and create Hurricane objects to store member variables for further manipulation. Then, that data was converted into Keyhole Markup Language (KML) to create visualizations in Google Earth.

Challenges we ran into and what we learned

Since our group had more object oriented programming experience in Java and C++, there was a learning curve moving over to Python. In particular, the way object were instantiated proved to be different enough that it required some research to fully understand. However, we did overcome that learning curve, and developed new Python programming skills as a result.

Built With

• github
• google-earth
• kml
• python