Kindergarten Earth & Space Science — Unit 1: Weather & Seasons
📚 Grade: Kindergarten🧭 Unit: K-ESS2 Unit 1 — Weather & Seasons🔢 Lesson: 6 of 6 — Final Lesson!⏱️ Duration: 30–45 minutes
📊 🌤️ 🔭 🌍
Real scientists look at patterns to predict what comes next!
📋 NGSS Standard: K-ESS2-1 — Use and share observations of local weather conditions to describe patterns over time.
🎯 Learning Objective
Students will analyze a week of weather data to identify patterns and predict tomorrow's weather.
🔬 The Big Idea
Scientists don't just observe — they look for patterns. When you collect weather data over days, weeks, and months, you start to see patterns: sunny days often come after rainy days, certain months are always colder, storms follow certain types of clouds. These patterns are how meteorologists (weather scientists) predict future weather!
💡 Key vocabulary: pattern, data, observation, prediction, meteorologist, bar graph
📦 Materials
🏠 What You Need
⭐ Weather Watcher Journal from Lesson 1 (you need this!)
Crayons
Ruler (optional, for neat graph lines)
Weather Patterns worksheet (next page)
🔬 Let's Get Started
Step 1 — Look Back at Your Journal (5 min)
Get out the Weather Watcher Journal from Lesson 1. Look through all 5 days together. Ask:
"What type of weather showed up most often?"
"Did any days seem connected? (Like: cloudy day was followed by rain?)"
"Was there any weather that surprised you?"
Step 2 — Count and Tally (5 min)
Count how many days each weather type appeared in your journal:
☀️ Sunny days: ___
⛅ Cloudy days: ___
🌧️ Rainy days: ___
🌬️ Windy days: ___
❄️ Snowy days: ___
Step 3 — Make a Bar Graph (10 min)
Use the bar graph on the worksheet. For each weather type, color in one box per day. For example, if you had 3 sunny days, color 3 boxes in the sunny row. Use different colors for each weather type!
Step 4 — Find the Pattern (5 min)
Look at your completed graph. Ask:
"Which bar is the longest? That was the most common weather."
"Which bar is the shortest? That was the rarest weather."
"Based on the pattern, what kind of weather do you predict for TOMORROW?"
Step 5 — How Meteorologists Work (5 min)
Explain: "Real weather scientists collect much more data — years and years of observations from thousands of locations all over the world. They use powerful computers to find patterns in all that data. That's how they predict weather 10 days ahead!"
💡 Fun fact: The old saying "Red sky at night, shepherd's delight — red sky in the morning, shepherd's warning" is actually based on real weather patterns! A red sunset often means dry air is moving in from the west (good weather coming). A red sunrise means moisture is approaching from the east (bad weather coming).
💬 Discussion Questions
🗣️ Talk about these together:
What was the most common type of weather this week? Does that seem normal for this time of year?
Did you see any patterns between days? (Like: was it always windier before it rained?)
How accurate do you think your prediction for tomorrow is? How could you test it?
Big Question (Unit Wrap-Up): Meteorologists study weather for their whole careers. What tools do you think they use?
💡 Suggested answer: Thermometers (temperature), barometers (air pressure — changes before storms!), anemometers (wind speed), rain gauges (how much rain fell), weather satellites from space that take pictures of clouds, and powerful computers that analyze millions of data points from around the world. Weather forecasting has improved dramatically — we can now predict weather 10 days out with reasonable accuracy. Before modern tools, farmers relied on signs in nature: red sky at night = good weather coming; unusual animal behavior before storms.
🚀 Extensions
📺 Watch a Forecast: Find a 10-day weather forecast online. Check back each day to see how accurate it was. Does accuracy decrease for days farther in the future?
📅 Month-Long Data: Keep going with the weather journal for a whole month! Look for monthly patterns.
🌍 Compare Cities: Look up the week's weather for another city. How does it compare to yours? Why might they be different?
📚 Read Aloud:National Geographic Readers: Weather by Kristin Baird Rattini
🎓 Unit Wrap-Up — Weather & Seasons Complete!
You've explored all 6 lessons in the K-ESS2 Weather & Seasons unit. Here's what you've learned:
🌤️
Lesson 1: What Is Weather?
Identified 4+ weather types & kept a Weather Watcher Journal
🌬️
Lesson 2: Wind
Built a pinwheel & measured wind using a 0–3 strength scale
💧
Lesson 3: Water Cycle
Observed evaporation & condensation; traced the water cycle
🍂
Lesson 4: Four Seasons
Sequenced & described all 4 seasons; learned about Earth's tilt
🐻
Lesson 5: Animals & Weather
Described migration, hibernation, food storage, & camouflage
📊
Lesson 6: Weather Patterns
Analyzed data, built a bar graph, & made a weather prediction
🌍 The Big Picture
Weather is the atmosphere doing its thing right now — powered by the sun. Wind moves heat around. Water cycles endlessly through evaporation and rain. Seasons shift as Earth tilts. And living things — from squirrels to bears to YOU — have all found clever ways to thrive through every kind of weather. That's what science is all about: understanding patterns in the world around us!
Retrieving Lesson 1 Journal: If the journal was completed each day, this lesson is more meaningful. Even 3 of 5 days is sufficient to find patterns.
Bar graph tips: For kindergartners, the graph on the worksheet uses box-coloring rather than actual measured bars — this is developmentally appropriate. If the child is ready, you can draw actual bars using a ruler.
Weather prediction accuracy: If their prediction for tomorrow was wrong — that's a great learning moment! "Scientists are wrong sometimes too. That's why they keep collecting data and refining their models."
Connecting to NGSS: K-ESS2-1 asks students to use observations to describe patterns over time. This lesson directly hits that standard — comparing daily data and identifying which type occurred most often IS pattern analysis at the K level.
Assessment: Can the child identify the most common weather from their journal data? Can they complete a bar graph? Can they make a prediction and explain why?
🔑 PARENT ANSWER KEY — Detach before giving worksheet to students
Note on Answers
Because this lesson uses the child's real weather journal data, there are no fixed "correct" answers for the tallies and graph. What matters is the process:
Did the child accurately transfer the data from their journal to the tally table?
Does their bar graph match their tally counts?
Is their prediction reasonable given the pattern they observed? (e.g., if it was mostly sunny, predicting sunny tomorrow is a reasonable, data-driven prediction)
Key Science Concepts
Data collection over time reveals patterns — this is the foundation of science
Predictions based on patterns are not guesses — they are educated inferences from evidence
Bar graphs are a visual way to compare quantities — longer bar = more days of that weather type
Meteorologists use the same logic, just with vastly more data points and computers
Meteorologist Tools (for Discussion)
🌡️ Thermometer — measures temperature (in °F or °C)
🌬️ Anemometer — measures wind speed (connected back to Lesson 2!)
☔ Rain gauge — collects and measures precipitation
🔵 Barometer — measures air pressure; falling pressure often means a storm is coming
🛰️ Weather satellites — cameras in space that track cloud cover and storm systems
💻 Computers — run complex models analyzing millions of data points to forecast weather
✅ What Success Looks Like
Child accurately counted and tallied weather from their journal
Bar graph matches the tally counts
Child can identify the most common weather type from the graph
Child made a prediction AND gave a reason based on the pattern (not just a guess)
Child can name at least 2 tools meteorologists use
