- Big Picture thesis: Due to its enormous size, the United States has always been a victim of a variety of natural disasters. In 2020 alone, there were 22 natural disasters that costed a combined total of 95 billion dollars in damage, 13 of which were severe storms. Among the natural disasters, the most prominent ones have been hurricanes, tornadoes, blizzards, floods, etc. Severe storms have an average cost of 2.3 billion dollars and unfortunately it also happens to be the most prominent out of all natural disasters in the US.
Natural disasters are not preventable even with extensive data. However, we can work to infer the patterns to minimize the lives lost and financial loss using the data. Wealth gap is a global issue and this holds true for the United States. This is why our analysis on socio-economic status and racial breakdown in each state is important. If lower-middle and lower class people are heavily populated in areas where severe storms are almost annual, the wealth gap would continue to increase and the cycle of being stuck in financial hardships would be inescapable for those people.
The following maps show the damage amount and the number of severe storms in each state. We can see that southern states and the midwest area are greatly affected financially by severe storms from figure 1. The midwestern states often get storms due to the clash of warm and humid air from the gulf of mexico and cold and dry air from Canada.
Our group plans on analyzing the factors influenced by these storm events within the U.S. Factors including the frequency of the storm events, average magnitude, GDP by state, infrastructure expenditure due to climate change by state. We will also be determining the socio-economic status and racial breakdown in each state in regards to the regions most effected by these storms.
- Interactive Page: In regards to our interactive page, our Big Data page will include a link to an interactive dashboard created either using Shiny or FlexDashboard, (we are still deciding which method is the best approach). We might create an interactive with our map diagrams that allow for users to navigate our data easily. For example, we could potentially create a map (color coded depended on the severity of the storms) and users can press on a specific location that will take them to another interactive plot with information on various factors that influence damage property by storm events. This is our initial thoughts, we will have to determine if this approach will work with our data.