Snowpack Trends at Ski Resorts

ISEF Category: Earth and Environmental Sciences

Subcategory: Climate Science  ·  Difficulty: Intermediate  ·  Setup: Home Setup  ·  Time: 1 to 2 Months

The Hook

A ski resort can look open from the parking lot and still be one warm week away from closing. That kind of timing matters for jobs, tourism, and water planning. You can test whether low-elevation resorts are losing their spring and fall snow safety net. Satellite data gives you the wide view, and survival analysis turns that view into a real model.

What Is It?

This project looks at how long snow lasts at low-elevation ski resorts during the edges of the season, when conditions are most fragile. "Shoulder season" means the weeks near opening and closing, when a resort depends on just enough snow to stay open. If that snow disappears earlier in spring or arrives later in fall, the resort becomes less reliable.

MODIS is a NASA satellite system that measures snow cover across large areas. You can treat it like a weather camera that checks whether a location is snow-covered on each day. Survival analysis is a statistics method often used to study time until an event happens. Here, the event could be the first snow-free period long enough to end operations, or the failure to keep enough snow cover for skiing.

Your goal is to connect satellite snow-cover patterns to operational viability. In plain terms, you are asking, "How long can a resort stay open, and how has that changed over time?"

Why This Is a Good Topic

This is a strong science fair topic because the data are public, the question is testable, and the analysis has a clear real-world use. You can compare resorts, seasons, elevation bands, or regions without needing a lab. You also get to learn satellite data handling, time-series thinking, and survival analysis, which are useful skills in climate science.

Research Questions

• How does shoulder-season snow-cover duration change at low-elevation ski resorts over time?
• What is the effect of elevation on the length of snow-covered shoulder seasons?
• Does the timing of first seasonal snow loss predict resort closing dates?
• To what extent do nearby resorts show similar snow-cover survival patterns?
• Which climate variables, such as temperature or precipitation, best explain changes in operational viability?
• How does the year-to-year variability in MODIS snow cover compare between low- and high-elevation resorts?
• What is the effect of region on the probability that a resort stays viable into spring?

Basic Materials

• Laptop or desktop computer with internet access.
• Spreadsheet software, such as Google Sheets or Excel.
• USGS or NASA snow-cover data from MODIS or a similar public archive.
• List of ski resort locations and elevations from public websites.
• NOAA climate data for temperature and snowfall comparisons.
• Map tool or GIS viewer, such as Google Earth or QGIS.
• Notebook for tracking site selection, dates, and assumptions.

Advanced Materials

• Laptop or desktop computer with internet access.
• R or Python for statistical analysis.
• QGIS for mapping resort locations and snow-cover layers.
• MODIS snow-cover products from NASA or NOAA archives.
• Resort operation history from public reports or archived resort websites.
• Elevation and terrain data from USGS or a similar public source.
• NOAA gridded climate data for trend comparisons.
• Statistical package for survival analysis, such as R survival or lifelines in Python.

Software & Tools

• QGIS: Maps resort locations, elevation, and snow-cover patterns over time.
• Google Earth: Helps you check site locations and compare terrain at each resort.
• R: Runs survival analysis, trend tests, and data visualizations.
• Python: Cleans data, matches satellite records to resort sites, and models trends.
• ImageJ: Measures snow-cover area from screenshots or exported map images if you need a manual backup method.

Experiment Steps

1. Define your outcome, such as the last date a resort maintains usable snow cover in spring or the first date it loses reliable snow cover in fall.
2. Choose a small set of low-elevation resorts and a comparison group so your sample has a clear contrast.
3. Build a data table that matches each resort to yearly MODIS snow-cover records and basic climate variables.
4. Decide how you will turn satellite snow cover into one operational metric, such as season length, persistence, or failure time.
5. Select a survival-analysis approach that fits your data structure and plan the control variables you need.
6. Test whether elevation, region, or climate trends explain changes in viability, then check that your result holds under a different definition of snow failure.

Common Pitfalls

• Using resort names without matching exact coordinates, which can link your data to the wrong pixel or nearby slope.
• Treating a single snow-free day as a season ending, which can exaggerate volatility in satellite records.
• Mixing high-elevation and low-elevation resorts without separating them, which can hide the shoulder-season trend.
• Ignoring cloud contamination or missing MODIS observations, which can make snow persistence look better or worse than it is.
• Choosing a survival endpoint that does not match resort operations, which weakens the link between snow cover and viability.

What Makes This Competitive

A stronger project goes beyond a simple trend line. You can compare more than one survival definition, test whether elevation interacts with region, and check whether your result stays the same under different snow-cover thresholds. You can also add a meaningful validation step, such as comparing satellite snow cover with resort opening and closing histories. That kind of careful analysis makes the project feel like real climate research.

Project Variations

• Compare shoulder-season snow viability for resorts in one mountain range versus another.
• Swap MODIS for another public snow dataset and test whether the trend still appears.
• Model opening-date and closing-date survival separately to see whether spring or fall is changing faster.

Learn More

• NASA Earthdata: Search for MODIS snow-cover products and data guides in the NASA Earthdata portal.
• USGS Earth Explorer: Find satellite and elevation data for mapping ski resort locations and terrain.
• NOAA National Centers for Environmental Information: Get climate records for temperature, snowfall, and long-term trends.
• R Survival Manual: Look for this free online manual to learn survival analysis in R.
• PubMed: Search review articles on snow cover, mountain climate change, and remote sensing methods.