#Chicago Rain #####ChicagoRains is an open-source data science project exploring how rainfall affects our city, touching on topics including climate change, public transportation, and the dumping of sewage into Lake Michigan and the Chicago River. Our team is making this important data more accessible to the public, and engaging with citizen data scientists from across the community to analyze and understand it. Our aim is to create a localized, data-driven story to raise public awareness in order to facilitate change – whether in public policy, infrastructure investment, and/or individual habit.
###How Do I Get Involved?
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Follow our Slack Channel (Join our Slack channel)
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Check out our data on Google Drive
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Read the list of questions below. If you're interested in answering or working with others to do so
- Hack with us on Tuesday nights at the Merchandise Mart at ChiHackNight
- Announce it on the Slack Channel
- Reach out to @sbeslow or @pjsier
Feel free to add your own question to the list.
- Look through the directories in the repo, and check out the work that we're up to.
###Our List of Questions
It can be thunderstorming in one part of the city, and dry in another.
- Quantify and/or visualize how rainfall falls unevenly around the city -- by region? ward? zipcode? neighborhood?
- What kinds of things does this help us model?
- Given that we have this data, can we apply it to various other datasets including divvy, public transit, crime, 311 calls, ...
- How much rainfall does it take before a CSO happens?
- How often do we dump sewage in the lake, and how much rain does it take?
- Where do the most (and least) CSOs occur? Any ideas why?
- Create a predictive model of CSOs
- Create a time lapse of an event
- How often do 100-ysear events occur? 50-, 25-, 10-, 5-, 2-, 1-? What is an n-year storm
- Are we seeing an increase in heavier storms in Chicago over the last X years?
- Is it time for Northeast Illinois to update their benchmarks for n-year storms, so they do actually represent statistical recurrence?
- Is it time to rethink the concept of n-year storms?
- Map our FEMA and 311 data. What do you find? By ward? Zip? Neighborhood? region?
- How can we build a bigger, better database to get better information about how many households experience basement flooding?
- Is there a way to predict basement flooding?
- Can we use this data to help bike riders be more safe? Determine if a storm is too heavy to ride?
On this day, 6.86 inches of rain fell on Chicago -- the most ever in a single day, but most of it fell in a 3-hour span. What was the aftermath of that? How did the CSOs look? The bulk of it was overnight, so perhaps focus at next morning rush hour(?).
Heavy storms during rush hour are the worst. Dive into rainfall data specifically at those times.
The directories in this repo distinguish different storylines. Check them out and see if anything suits your fancy.