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Track Weather
Changes

Learn to collect and analyze data showing how weather conditions change over time, using tools, tables, and graphs to spot patterns.

Earth & Space Science

What Is Weather?

Weather describes the state of the atmosphere at a specific place and time. It includes conditions you can measure: temperature, precipitation, humidity, wind speed, air pressure, and cloud cover.

Temperature
How hot or cold the air is, measured in \( ^\circ\text{F} \) or \( ^\circ\text{C} \)
Precipitation
Water falling from the sky: rain, snow, sleet, or hail
Humidity
The amount of water vapor in the air, expressed as a percentage

Key Weather Variables

Wind Speed
How fast air moves, measured in mph or km/h with an anemometer
Air Pressure
The force exerted by the atmosphere, measured in millibars (mb) with a barometer
Cloud Cover
Fraction of sky covered by clouds, described as clear, partly cloudy, or overcast

Why Track Weather Over Time?

A single weather reading is just a snapshot. To understand patterns and trends, scientists collect data at regular intervals: hourly, daily, or weekly. Tracking over time lets us:

1
Identify patterns: recognize seasonal cycles and recurring weather events
2
Make forecasts: predict upcoming weather based on observed trends
3
Compare locations: see how weather differs between regions or altitudes
4
Study climate change: detect long-term shifts by analyzing decades of data

Weather Instruments

Thermometer Temperature Barometer Air Pressure Rain Gauge Precipitation Anemometer Wind Speed % Hygrometer Humidity

The Data Collection Rule

For weather data to be useful and comparable, you must follow a consistent protocol. This means collecting data at the same time, in the same place, using the same instruments, at regular intervals.

1
Same time daily: record at the same hour (e.g., 8:00 AM each morning)
2
Same location: keep instruments in the same spot away from buildings and pavement
3
Same units: always use \( ^\circ\text{C} \) or \( ^\circ\text{F} \), never mix them

Weather vs. Climate

Weather Climate
Definition Atmospheric conditions right now Average conditions over 30+ years
Time Scale Hours to days Decades to centuries
Changes Rapidly, even minute to minute Very slowly over long periods
Example "It's \(32^\circ\text{F}\) and snowing today" "Winters here average \(28^\circ\text{F}\)"
Data Needed Single observation Thousands of observations

How to Analyze Weather Data

1
Organize: put data into a table with columns for date, time, and each variable
2
Calculate averages: find the mean for each variable over your time period, e.g., \(\bar{T} = \frac{\sum T_i}{n}\)
3
Find the range: subtract the lowest from the highest value: \(\text{Range} = T_{\max} - T_{\min}\)
4
Graph it: plot a line graph with time on the x-axis and the variable on the y-axis
5
Identify trends: look for upward/downward patterns, spikes, or cycles

Example 1: Reading a Data Table

A student records the high temperature each day for one week:

Day Mon Tue Wed Thu Fri Sat Sun
High (\( ^\circ\text{F} \)) 72 75 78 74 68 65 70

Example 2: Graphing Temperature

60 65 70 75 80
Temp (\(^{\circ}\text{F}\))
 Mon Tue Wed Thu Fri Sat Sun
Peak: \(78^\circ\text{F}\)
Low: \(65^\circ\text{F}\)
 Daily High Temperature (1 Week)

Example 3: Multi-Variable Analysis

60 65 70 75 80 85
Temp (\(^{\circ}\text{F}\))
 Mon Tue Wed Thu Fri Sat Sun Temperature Precipitation

Fronts and Air Pressure

Cold Air Mass High Pressure Dense, dry air H Warm Air Mass Low Pressure Light, moist air L Cold Front Cold air pushes under warm air

Identifying Weather Patterns

Once you graph weather data, look for these common patterns:

Diurnal Cycle
Temperature rises during the day and falls at night: a daily repeating pattern
Seasonal Trends
Temperatures are higher in summer and lower in winter, following a yearly curve
Frontal Events
Sudden drops in temperature and pressure signal a cold front passing through
Correlation
Two variables moving together (e.g., humidity rises as precipitation increases)

Seasonal Temperature Curve

30 40 50 60 70 80
Avg Temp (\(^{\circ}\text{F}\))
 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Winter Spring Summer Fall

Common Mistakes in Weather Tracking

✕ Inconsistent Timing
Recording at 7 AM one day and 2 PM the next: temperature naturally varies by time of day, so comparisons are meaningless.
✕ Moving the Station
Relocating instruments mid-study: different spots have different microclimates (shade, pavement, elevation).
✕ Ignoring Units
Mixing \( ^\circ\text{F} \) and \( ^\circ\text{C} \) in the same data set, or forgetting to label axes on graphs.

Weather Variables Summary

Variable Instrument Unit What It Tells You
Temperature Thermometer \( ^\circ\text{F} \) or \( ^\circ\text{C} \) How hot or cold
Precipitation Rain gauge inches or cm How much water fell
Humidity Hygrometer % Moisture in the air
Wind Speed Anemometer mph or km/h How fast air moves
Air Pressure Barometer mb or inHg Incoming weather changes
Cloud Cover Observation Oktas or description Sky conditions

Question 1 of 5

A student records the outside temperature every day at 8:00 AM for two weeks. On Day 6, she sleeps in and records it at 1:00 PM instead. How does this affect her data?

Question 2 of 5

Which instrument would you use to determine whether a low-pressure system is approaching your area?

Question 3 of 5

A city's average July temperature over 30 years is \(85^\circ\text{F}\). This year, the July average was \(78^\circ\text{F}\). Which statement is most accurate?

Question 4 of 5

A student collects high temperatures for 5 days: 60, 62, 58, 64, 61 (all in \( ^\circ\text{F} \)). What is the range of this data set?

Question 5 of 5

On a graph, temperature is dropping sharply, air pressure is falling, and precipitation is increasing. What is the most likely explanation?