Pothole Season: Counting Freeze–Thaw Days
Ten years of real Detroit daily temperatures, one definition, and a question about trends.
Name:
Class period:
Date:
Standards
HS-ESS3-5 — Analyze geoscience data and the results from global climate models to make an evidence-based forecast of the current rate of climate change and its regional impacts.
SEP 4 — Analyzing and interpreting data. Middle school: use the monthly summary and bar graph steps only.
Why Does This Matter?
Every late winter Detroit crews rush to patch potholes. Water seeps into cracks in the pavement, freezes and expands by about 9%, then thaws and leaves a gap; traffic breaks the weakened pavement. The key weather ingredient is air temperature crossing 0°C again and again. Weather data lets you count that.
Objective
Count freeze–thaw days in each of nine Detroit winters, graph the results, and judge whether the data show a trend.
Materials
- Dataset: detroit_daily_weather_2015_2024.csv (real daily high, low, and mean temperature, precipitation, and snowfall for Detroit, from the Open-Meteo historical weather archive)
- Spreadsheet software with IF, COUNTIF, and chart tools
- A calculator
Note: This is a computer-based data lab — no physical safety hazards.
Procedure
- Define a freeze–thaw day as a day when the minimum temperature is below 0°C and the maximum temperature is above 0°C.
- Add a column that equals 1 for a freeze–thaw day and 0 otherwise (for example =IF(AND(C2<0,B2>0),1,0)).
- Define each winter as November 1 through March 31, labeled by its ending year (November 2015–March 2016 is winter 2016). Count the freeze–thaw days in each of the nine complete winters, 2016 through 2024.
- Make a bar or line graph of freeze–thaw days by winter. Calculate the mean and the range.
- Count the freeze–thaw days in each month (November through March) across all nine winters to find which month has the most.
- Add a linear trendline to your winter graph and record its slope.
Data Table
| Winter (ending year) | Freeze–thaw days | Total snowfall (cm, optional) |
|---|---|---|
| 2016 | ||
| 2017 | ||
| 2018 | ||
| 2019 | ||
| 2020 | ||
| 2021 | ||
| 2022 | ||
| 2023 | ||
| 2024 |
Analysis Questions
- Describe the pattern in freeze–thaw days across the nine winters. What are the mean and the range?
- Does your trendline slope up or down? Can nine winters support a claim about a long-term trend? Explain how weather differs from climate.
- Which month had the most freeze–thaw days? Why might that month be hard on pavement?
- How could a city public-works department use this kind of analysis to schedule pothole crews or budget for repairs?
- List two limitations of this analysis (for example, the data come from a weather model, and air temperature is not pavement temperature).