How to Make a Climograph on Google Sheets

Creating a climograph - a chart that powerfully displays a location's average temperature and precipitation in a single view - is a classic task in geography, environmental science, and data visualization. While it might sound complex, Google Sheets has all the tools you need to build one from scratch. This guide will walk you through transforming raw climate data into a professional and insightful climograph, step-by-step.

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First Things First: Gather and Structure Your Climate Data

Before you can build the chart, you need accurate data formatted in a way that Google Sheets can understand. A climograph requires two key pieces of information for a specific location, averaged out for each month of the year:

• Average Monthly Precipitation: Usually measured in inches (in) or millimeters (mm). This will be represented by bars on your chart.
• Average Monthly Temperature: Usually measured in Fahrenheit (°F) or Celsius (°C). This will be represented by a line on your chart.

Where can you find this data? Official meteorological sources are best. Government agencies like the U.S. National Oceanic and Atmospheric Administration (NOAA) or organizations like the WorldClim project provide reliable historical climate data for locations all over the world.

How to Set Up Your Data in Google Sheets

The structure of your data is the most important step for success. If you get this wrong, Google Sheets will get confused and produce a messy, unreadable chart. You need a simple three-column layout:

1. Column A: Month
2. Column B: Average Precipitation
3. Column C: Average Temperature

Start with "Month" as your header in A1, and list the months from January to December below it. Place your precipitation and temperature headers in B1 and C1, respectively. Then, fill in the corresponding data for each month. Make sure the headers clearly state the units (e.g., "Precipitation (in)" or "Temperature (°F)").

Here’s an example using hypothetical data for Portland, Oregon:

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Creating the Basic Climograph: A Step-by-Step Guide

Once your data is neatly organized, it’s time to generate the chart. We'll start by creating the basic structure and then refine it into a polished climograph.

Step 1: Select Your Data

Click and drag your cursor to highlight all the data you just entered, from cell A1 down to the last data point in column C (in our Portland example, that’s cell C13). It's important to include the headers in your selection, as Google Sheets will use them to automatically label your chart series.

Step 2: Insert the Chart

With your data selected, navigate to the main menu and click Insert > Chart. Google Sheets will automatically analyze your data and suggest a chart type. Most of the time, its first guess won’t be a climograph, and that’s perfectly fine. A popup displaying the Chart editor and a default chart will appear.

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Step 3: Choose the "Combo Chart" Type

In the Chart editor panel on the right, under the "Setup" tab, find the "Chart type" dropdown menu. This is where you tell Google Sheets what you want to build.

Scroll down through the options until you find the "Combo chart." This is the ideal choice because it's specifically designed to handle two different chart types (like bars and a line) in one visualization.

After selecting it, you'll see your chart update. It’s starting to look more like a climograph, but the axes are still incorrect. Both the precipitation bars and the temperature line are being measured against the same vertical axis, which squishes one of them and makes the chart hard to read. We'll fix that next.

From Basic Chart to Polished Climograph: Customizing Your Visualization

This is where we fine-tune the chart’s appearance and functionality to make it clear, accurate, and professional. All of these options are found in the Chart editor panel under the Customize tab.

1. Set Up the Dual Y-Axes

This is the most critical step in making a true climograph. We need to assign the temperature data to its own, separate vertical axis on the right side of the chart.

• In the Chart editor, click the Series dropdown menu.
• You'll see options for both of your data series ("Avg. Precipitation" and "Avg. Temperature"). First, ensure the precipitation series is formatted as "Columns."
• Next, change the dropdown from your precipitation series to your temperature series (e.g., "Avg. Temperature (°F)").
• Look for the Axis dropdown below. It's likely set to Left axis. Click on it and change it to Right axis.
• While you're here, double-check that this series' type is set to Line.

As soon as you select Right axis, you'll see a major change. The temperature line will automatically rescale to its new axis on the right side of the chart, appearing much more clearly. You now have a functioning dual-axis climograph!

2. Add and Refine Titles and Labels

A chart without labels is just a picture. We need to tell the viewer exactly what they’re looking at.

• Click on the Chart & axis titles section in the Customize tab.
• Chart title: Give your graph a descriptive title. Something like "Climograph: Portland, Oregon" is perfect.
• Vertical axis title: This refers to the main (left) axis. Label it clearly with the units, such as "Average Precipitation (in)."
• Right vertical axis title: Add this title next. Label it "Average Temperature (°F)."
• Horizontal axis title: While somewhat obvious, it's good practice to add a title here. "Month" is sufficient.

3. Adjust Colors and Aesthetics

Clear, intuitive colors make your climograph easier to interpret at a glance. The convention is to use a shade of blue for precipitation (water) and a shade of red or orange for temperature (heat).

• Go back to the Series dropdown in the Customize tab.
• Select your precipitation series. Use the Color picker to choose a shade of blue for the bars.
• Switch to your temperature series. Choose a reddish or orange color for the line. You can also adjust the Line thickness to make it stand out more, perhaps to 2px or 4px.

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4. Tweak the Gridlines and Legend

• Legend: Under the Legend section, you can change its position. Placing it at the "Top" or "Bottom" can often give your chart a cleaner, wider look than having it on the side.
• Gridlines and Ticks: Under the Gridlines and Ticks section, you can specify how many major gridlines you want, which can help reduce visual clutter. You can also adjust gridlines for each axis independently, you might want fewer lines for temperature than for precipitation, for example.

How to Read and Interpret Your Climograph

With your final chart complete, you can now easily see the story of Portland's climate throughout the year.

• Follow the Bars (Precipitation): You can instantly see that precipitation is highest in the late fall and winter months (November, December, January) and lowest during the middle of summer (July).
• Trace the Line (Temperature): The temperature line shows a clear curve, peaking in July and August for the warmest months and dipping down in December and January for the coldest.
• Connect the Two: By looking at both together, you see the classic Pacific Northwest pattern: cold, wet winters and warm, dry summers.

This instant visual narrative is precisely why climographs are so effective. They condense a full table of data into a quick, intuitive pattern.

Final Thoughts

Learning to build visualizations like a climograph in Google Sheets gives you a powerful way to tell stories with data. By structuring your information properly, using the combo chart feature, and carefully customizing the dual axes, you can turn a simple spreadsheet into a professional-grade analytical tool.

This process of connecting data sources and manually building reports is a fantastic skill, but it’s often just the first step. When you're dealing with multiple data sources from marketing or sales tools, this manual work can consume hours every week. At Graphed, we created a way to skip the manual drudgery. You can connect your platforms like Google Analytics, Shopify, or Salesforce in a few clicks, then simply ask for the dashboard you need in plain English - like "create a dashboard comparing ad spend to revenue by campaign." We automate the entire process, giving you back time to focus on acting on your insights, not just building them.