The documentation of this repo is currently in a shambles but some effort will be made soon to make things more clearly explained in terms of what script generates what kind of video. -brian
Inspired by: /r/dataisbeautiful and /u/Tjukanov
I tried to implement some of the enhancements that users requested in the reddit posting.
That ended up being this kind of thought process:
- Ignored all storm basins except the North American Atlantic Basin as that's where most of the (Western) damage is concentrated. (However Asian typhoons have been measured to be quite a bit stronger.)
- I took each track and figured out the category of the hurricane at any given time.
- At each time interval apply some 'damage' to the lat/long that the storm is currently located at.
- The damage formula was: (storm category + 2)^2 This accounted for tropical storms and tropical depressions. The square is because the Saffir-Simpson Hurricane Categories are a roughly logarithmic scale. Also, according to the Saffir-Simpson scale, wind is the primary source of damage from hurricanes and air pressure increases as the square of velocity.
Gifs of all mentioned videos here
That lead to this gif: 100 Years of Hurricane Intensities
One can see some interesting trends, like hurricanes rapidly losing strength once they go onshore. But many improvements were possible.
- To make it less busy I binned the intensities into 0.2* x 0.2* (lat/long) squares.
- I used a 25 year average, ending on the last year of the interval
- I normalized all of the years heatmaps (gamma) using the values from the highest intensity interval. This helps to see the relative activity by interval.
That resulted in: Hurricane 25 Year Moving Average 'Damage' Heat Map
This seemed more useful but storm intensity and detail was lost. Some of the feedback on the original post requested color by strength and category.
- I took each track and determined the 'instantaneous' category using the Wind Speed feature of the data.
- I then used the category data to determine color as well as the size of a scatter plot dot.
- To make the animations smoother I interpolated between time intervals using a cubic algorithm. This lead to smoother color and size graduations.
- I also applied cubic interpolation to the latitude and longitude data so that the tracks were solid rather than dots.
- Because storms have widely varying durations I normalized the durations of all of the storms in one year to the duration of the longest storm. Then I used interpolation to get the correct number of frames for each year. (For making the video)
- Finally I ran the process in succession, saving previous years as white intensity transparent pngs. These were used to show the tracks of the previous 5 years of storms.
This all resulted in: Atlantic Hurricane Tracks Animated by Year (fast speed) See video link for slower speeds that are more comprehensible.
The 5 years of historical tracks makes things a bit too busy but this particular video takes a long time to render a new one until a later date. The combining color of the tracks was to indicate areas being hit more than once but I think in the future I will simply keep the most 'powerful' color.
Finally just to see what it would look like I made a sort of cinemagraph of 100 years of the Atlantic Hurricane Data. That was a good programming challenge but didn't turn out as well as I would have liked. Over the course of a minute all ~1500 storms are activated and put through their tracks in turn.
That looked like the following: 100 Years of Hurricanes Cinemagraph