“Frankenstorm” is what the U.S. National Weather Service is calling the combination of Hurricane Sandy, an early winter storm heading east, and a blast of arctic air from the North. SAS headquarters is located in the middle of the U.S. east coast ... and we barely missed being the bulls-eye for this storm!
Frankenstorm is the largest hurricane in Atlantic history, with a maximum gale-force wind diameter of 930 miles (1500 km) as of 11:00 p.m. EDT on October 28. Do you think there will be much need for analytics after this storm makes landfall? ... is the most common mistake in SAS programming a missing semicolon? Duh!
And what better software to analyze & visualize storm data than SAS!
In this blog, I'd like to share a few SAS graphs that can be used to analyze hurricane data. Kind of showing the "Power of SAS" by showing the "Power of Hurricanes."
First, here's a map shaded by the number of previous hurricane strikes along the Florida coast, overlaid on a map showing streets & cities. Similarly, the map could be shaded by the $ amount of damage, etc:
Looking for a broader perspective? Here's a plot showing the worldwide "Accumulated Cyclone Energy" of the storms in the Northern and Southern hemispheres, plotted over time (this one looks a little better if you click on it, to view it in full resolution):
How about the amount of rainfall? Got that covered too! The size of the annotated blue dots represents the amount of rain at each monitoring station, and you can click on the dots to drill down and see the Google map:
And here are two interesting hurricane plots showing the storm surge & wind, right up until the time when the weather station stopped collection data (ie, up until the power went out, or the gauge broke):
And now a "quick quiz" ... name some items people might forget to put in their home emergency kit, in case the power goes out and/or their home is damaged? Let's assume they have the basics: food, water, flashlight, cash, medications, battery-powered radio, and a full tank of gasoline in the car.
What are those "extra items" you have found to be useful in the past, that others might not think of?
And to get more details about the samples above, and to download the SAS code that was used to create them, see the links below: