The goal of this activity is to estimate the number of days of freezing weather (< 32 °F) that has been lost due to climate change. This activity is simultaneously environmental science, math, and "data analytics".
Some references refer to this as an increase in "the length of the freeze-free season (growing season)". For warmer locations (like southern California, or Florida, etc.) you may want to tell the students to modify the code so that it counts the days that are below 50 °F instead of 32 °F to estimate the impact of climate change.
The activity does not actually explain why the average temperature is increasing, but you can feel free to talk about the Greenhouse Effect (Advice: call it the "locked car in a sunny parking lot" effect).
The activity does not assume a particular model for how quickly the average temperature increases over time, or by a certain year.
If your city is not included on the website studying the impact of climate change on the Great Lakes, then you may need to test your code on a city that is listed there to see if you can come up with approximately the right number of freezing weather days that have been lost to climate change. If you can reproduce that number, then you can have some confidence that your estimate of the number of freezing weather days that has been lost is correct. In scientific coding, sometimes this is the best you can do: check that you get the right answer for a situation where you know what the right answer is, and then apply your code for a situation where you don't know the right answer.
We are still working to identify which "common core" math standards this activity may align with. If you have advice on this we would be grateful if you could send us an e-mail with that advice to orban@physics.osu.edu
This activity aligns well in a general sense with the Next Generation Science Standards statements on "computational thinking" for the High school level. Here is a quote from the relevant section:
"Mathematical and computational thinking in 9–12 builds on K–8 experiences and progresses to using algebraic thinking and analysis, a range of linear and nonlinear functions including trigonometric functions, exponentials and logarithms, and computational tools for statistical analysis to analyze, represent, and model data. Simple computational simulations are created and used based on mathematical models of basic assumptions."
Another general statement in this section is "Create and/or revise a computational model or simulation of a phenomenon, designed device, process, or system" and "Use simple limit cases to test mathematical expressions, computer programs, algorithms, or simulations of a process or system to see if a model “makes sense” by comparing the outcomes with what is known about the real world."
There are also a number of discipline-specific standards from the Next Generation Science Standards that this activity aligns with:
HS-ETS1-4. Use a computer simulation to model the impact of proposed solutions to a complex real-world problem with numerous criteria and constraints on interactions within and between systems relevant to the problem.
HS-ESS3-3. Create a computational simulation to illustrate the relationships among the management of natural resources, the sustainability of human populations, and biodiversity.
HS-ESS3-5. Analyze geoscience data and the results from global climate models to make an evidence-based forecast of the current rate of global or regional climate change and associated future impacts to Earth's systems.
HS-ESS3-6. Use a computational representation to illustrate the relationships among Earth systems and how those relationships are being modified due to human activity