Extreme weather continues to wreak havoc: Can we create a hyperlocal advanced warning?

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Extreme weather is by definition unpredictable, but by studying the historical trends in a given area, we can get a better idea of what to expect in a quantifiable manner.  Why is this important?  Because creating better preparation often takes money, and it’s important to know that this type of preparation can make a real difference.  It’s impossible to put a specific value on human life, but just looking at property damage you could take your local community, review the trends for extreme weather (quantity and type), review the damage from those prior events, and estimate what you should expect in the next 5-10 years as the number of events increases.  This can be a powerful tool in asking your community for support, especially if you can find reliable investments that can help to prevent property and community damage, or that can reduce the risk of human loss.

While calculating the past losses from extreme weather varies from community to community, being able to determine past extreme weather trends can be surprisingly simple.  With a little coding, we can even take in the data we have about quantifiable losses and merge it with historical data trends.

For this tutorial, we will take a realistic example of how you could examine a particular type of extreme weather event and match it with the negative effects it has on your community.  To keep it simple, we will use historical weather data via API.  We will cross-reference the number and trend of winter storms for a given location, then cross-reference it with the number of delivery delays for prescription medicines, indicating stress to the overall health and safety of the community.

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