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Culture, Climate Science & Education
Lab One
Get Climate Data for Your Area and
Make Temp and Precip Charts
In this lab you will: (1) order climate data for your area, (2) download the data, (3) learn the difference between absolute and anomaly temperature charts, and (4) build both types of charts with the data. Watch video tutorials below for each of these steps, then make temp & precip charts for your home town.
It's one thing to read about climate change and how temperatures and precipitation patterns are changing across the globe and across continents. It's something altogether different to look at a specific area, where you live for example, examine the data, and determine what's been happening over the last 20 years, 50 years, or 100 years. That's what you'll do in this lab. From the long-term trends you see, you can begin to make predictions about the future. In this lab you will: (1) order the data, (2) download the data, (3) learn the difference between absolute and anomaly temperature charts, and (4) build each type of chart with the data. Click on the buttons below to watch video tutorials for each of these steps, then do each step yourself to view and chart data for your home town. Start by building temperature charts, then build precipitation charts. Finally, examine your charts and summarize the trends you see.
Note: You will need Adobe Flash Player for this lab. To download it, click the button at the bottom of this page.
You need to have downloaded climate data from NOAA to do this step of the Lab.
- Right click on the download link and select “Save to Downloads”.
- You should now have the “cvs” file in your downloads folder.
- Open Excel or another spreadsheet program and go to File>Import.
- Select the type of file. It is a “csv” file.
- Browse to your Download folder and select the file of csv climate data file that you downloaded.
- Step through the import wizard. The choices you will need to make include:
- File Type: Delimited
- Delimiters: Commas
- Select the proper format for each column. For date, check date and choose the proper format (YMD)
- Choose where you want to put the data. Choose “Existing Sheet”
- Change heading titles of your data table. You can get the column heading titles by going to this page: http://www1.ncdc.noaa.gov/pub/data/cdo/documentation/GHCNDMS_documentation.pdf
- Search the Excel table and replace the -9999 placeholders with hyphens (-).
Temperature anomalies are more important than absolute temperature.
A temperature anomaly is the difference from an average, or baseline, temperature. The baseline temperature is typically computed by averaging 30 or more years of temperature data.
A positive anomaly indicates the observed temperature was warmer than the baseline, while a negative anomaly indicates the observed temperature was cooler than the baseline.
When calculating an average of absolute temperatures, things like station location or elevation will have an effect on the data (ex. higher elevations tend to be cooler than lower elevations and urban areas tend to be warmer than rural areas). However, when looking at anomalies, those factors are less critical. For example, a summer month over an area may be cooler than average, both at a mountain top and in a nearby valley, but the absolute temperatures will be quite different at the two locations.
Using anomalies also helps minimize problems when stations are added, removed, or missing from the monitoring network. The above diagram shows absolute temperatures (lines) for five neighboring stations, with the 2008 anomalies as symbols. Notice how all of the anomalies fit into a tiny range when compared to the absolute temperatures. Even if one station were removed from the record, the average anomaly would not change significantly, but the overall average temperature could change significantly depending on which station dropped out of the record. For example, if the coolest station (Mt. Mitchell) were removed from the record, the average absolute temperature would become significantly warmer. However, because its anomaly is similar to the neighboring stations, the average anomaly would change much less.
You need to have ordered and downloaded climate data from NOAA to do this step of the Lab.
- Open a Google Sheet
- Go to: File>Import…
- In the window that opens, select “Upload”
- Drag your downloaded data file into the upload window
- Under “Import Action” select “Replace Existing Spreadsheet”
- Under “Separator Character” select “Comma”
- Click Import
- Change the dates to the proper format
- Select column A and go to: Insert>Column Right
- Select Cell B5 (this should be the first “value” cell in your new column and insert the following formula “=Left(A5,4)”
- Pull little blue box in the lower right-hand corner of the cell down to the bottom of the column. Now you should see years in each cell of the column.
- Title the column “Year” and center the values in the column
- Convert it from a formula to an absolute value.
- Select all the values in the column and copy them
- Go to Edit>Paste Special and select “Paste Values Only”
- With all the values selected select Format>Number>0
- Select the Year and Temperature columns and click the Insert Chart button.
- Choose a line chart and format the chart the way you want by clicking on the “Customize” tab. Be sure to include a trend line.
- Make a Temperature Anomaly Chart
- Return to the spreadsheet and swap places of the Temperature and Anomaly columns by selecting the Temperature column and dragging it to the other side of the Anomaly column. Then drag both columns over so they are next to the year column.
- Select the Year and Anomaly columns and click the Insert Chart button
- Choose a column chart and format the chart the way you want by clicking on the “Customize” tab. Be sure to include a trend line.
- Examine your charts and summarize the trend in temperature that has occurred since 1895. Now do the same for precipitation (if you didn't order precip data, go back to step one and order it, then make your charts.
You need to have downloaded climate data from NOAA to do this step of the Lab.
- Right click on the download link and select “Save to Downloads”.
- You should now have the “cvs” file in your downloads folder.
- Open Excel or another spreadsheet program and go to File>Import.
- Select the type of file. It is a “csv” file.
- Browse to your Download folder and select the file of csv climate data file that you downloaded.
- Step through the import wizard. The choices you will need to make include:
- File Type: Delimited
- Delimiters: Commas
- Select the proper format for each column. For date, check date and choose the proper format (YMD)
- Choose where you want to put the data. Choose “Existing Sheet”
- Change heading titles of your data table. You can get the column heading titles by going to this page: http://www1.ncdc.noaa.gov/pub/data/cdo/documentation/GHCNDMS_documentation.pdf
- Search the Excel table and replace the -9999 placeholders with hyphens (-).
Temperature anomalies are more important than absolute temperature.
A temperature anomaly is the difference from an average, or baseline, temperature. The baseline temperature is typically computed by averaging 30 or more years of temperature data.
A positive anomaly indicates the observed temperature was warmer than the baseline, while a negative anomaly indicates the observed temperature was cooler than the baseline.
When calculating an average of absolute temperatures, things like station location or elevation will have an effect on the data (ex. higher elevations tend to be cooler than lower elevations and urban areas tend to be warmer than rural areas). However, when looking at anomalies, those factors are less critical. For example, a summer month over an area may be cooler than average, both at a mountain top and in a nearby valley, but the absolute temperatures will be quite different at the two locations.
Using anomalies also helps minimize problems when stations are added, removed, or missing from the monitoring network. The above diagram shows absolute temperatures (lines) for five neighboring stations, with the 2008 anomalies as symbols. Notice how all of the anomalies fit into a tiny range when compared to the absolute temperatures. Even if one station were removed from the record, the average anomaly would not change significantly, but the overall average temperature could change significantly depending on which station dropped out of the record. For example, if the coolest station (Mt. Mitchell) were removed from the record, the average absolute temperature would become significantly warmer. However, because its anomaly is similar to the neighboring stations, the average anomaly would change much less.
You need the latest version of the free Adobe Flash Player for this lab.
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