Lab 05: Local Climate Data Analysis

Terence Day

Your friend is getting married, congratulations to them! And because they know you’ve become an expert on physical geography, they’d like you to help them choose between two possible places for the wedding. It is currently planned for June 21. The two places under consideration in BC are the lovely Stanley Park near Vancouver Harbour, and a delightful winery near Okanagan Centre. The ceremony will be held outdoors early- to mid-afternoon (the hottest time of day). Based on the climate, where would you advise your friend to get married?

In this lab you will use a variety of statistical analyses to answer questions on the best, most dependable climate to hold a wedding. The techniques are all used by physical geographers in a range of different applications, not just in the planning of weddings.

Learning Objectives

After completion of this lab, you will be able to

  • Obtain historical Canadian climate data using the Environment and Climate Change Canada website.
  • Calculate and interpret a mean (average).
  • Calculate the probability of extreme events occurring.
  • Construct and interpret graphs showing local climate trends.



Climatology is the study of climate through long-term weather patterns. When examined over time and space, areas with similar weather statistics can be identified, and are called climate regions. A Climate Normal is a 30-year (for example, 1981-2010, 1991-2020) average of climate conditions at a particular location. Climate Normals are used to for planning purposes and to determine official governmental policies at a larger scale.

Summary Statistics and Probability

Understanding of the following terms/concepts is required in order to complete this lab:

  • Mean or average.
  • Probability.
  • Data trends.

Types of Graphs and How to Create Them

Line graphs are generally used to show continuous data, or something that is a property, e.g., temperature changes over time. Graphs have a horizontal axis (x-axis) and a vertical axis (y-axis). An easy way to remember this is y to the sky. Generally, the convention is that the x-axis is the independent variable and the y-axis is the dependent variable. In the case of temperature graphs, the temperature (the dependent variable) depends on the month (the independent variable). The month doesn’t depend on the temperature.

Bar graphs present data as vertical or horizontal bars that are proportional in length to the value of something. They are used to show discrete or discontinuous data. For example, a bar graph is a good way to show the amount of precipitation that occurred over specific units of time. For example, when plotting Climate Normal precipitation, there will be one bar for each year, and the length of each of the 30 bars is proportional to the amount of precipitation that falls each year.

Drawing graphs is fairly easy by hand, but more professional-looking graphs can easily be constructed using your laptop or other device. We will practicing creating charts in Google Sheets, here, or you can use Microsoft Excel or other spreadsheet program.

In order to be sure that the data you are presenting makes sense to other people (or yourself later on) and is useful for your analyses, it is important to include some extra information, in addition to the data itself. Here is the checklist for graphs:

  • Is the x-axis the independent variable?
  • Are both axes labelled and do they include appropriate units (e.g., °C for temperature, mm for precipitation)?
  • Does the graph have a descriptive title or figure caption?
  • Do the size and scale of both axes on the chart make sense – not cramped up, nor too much white space? Can you view the data clearly?

Lab Exercises

In this lab you will collect historical climate data from the Environment and Climate Change Canada website, and analyse the data using statistical techniques in order to determine the probability of certain weather conditions (precipitation, extreme heat) occurring at the time of your friend’s wedding. You will also use statistical methods to assess whether or not precipitation and temperature have changed over the past 30 years, and reflect on how this may affect the recommendation you are making to your friend.

A Worksheet is provided for you to complete as you work through the lab exercises. Your instructor will provide you with instructions on how to submit it once complete.

EX1: Identifying Mean (Average) Conditions

First, you need to collect some data to help with your recommendations. Specifically, you need data for 30 years to obtain a Climate Normal (e.g., 1991 – 2020) for June 21. In this exercise you will collect Maximum Temperature (°C) and Total Precipitation (mm).

You will have to get the record for each year individually.

Step 1: Open the Environment and Climate Change Canada website.

Step 2: Once you are on the website, search for your site by typing the name in the Name box.

Step 3: Select daily as the Data Interval. Change the year to 2020 and select June for the month. The days will become greyed out – you will be given the entire month. Click Go.

Step 4: On the data page, scroll down to June 21 to see the data you need. If you have a smaller screen but would like to see the column headings with the data, you can reduce the size of the font by clicking <Ctrl><-> on your keyboard. Once you have recorded the information you need, change the year using the drop-down menu at the bottom of the page. Continue this process until you have all your data.

  1. Collect the data and add it to Table 5.1. The data for Vancouver Harbour are provided, as is the data for Okanagan Centre for 2020 (but check to make sure that it is correct). Bear in mind that there may be some missing data; if it’s missing then insert a dash (-). If precipitation is marked T then that means that there was just a trace. Enter the T on the table, but count is as zero in the calculation of the mean. Note that there is no data available at Okanagan Centre for 2019, but there is for all other years.
Table 5.1. Vancouver Harbour and Okanagan Centre Maximum Temperatures and Total Precipitation for June 21, 1991 – 2020
Vancouver Harbour Vancouver Harbour Okanagan Centre Okanagan Centre
Year Maximum Temperature (°C) Total Precipitation (mm) Maximum Temperature (°C) Total Precipitation (mm)
2020 20.7 0.0 27.0 0.0
2019 22.5 0.0
2018 22.0 0.0
2017 19.6 0.0
2016 18.5 15.6
2015 24.8 0.0
2014 19.7
2013 18.1 1
2012 21.0 0.0
2010 16.3
2009 18.3 0.2
2008 20.7 0.0
2007 22.1 0.2
2006 20.4
2005 23.4 6.0
2004 27.8 0.0
2003 17.7
2002 25.9 0.0
2001 24.9 0.0
2000 21.5 0.0
1999 17.9 2.8
1998 23.5 0.2
1997 16.6 21.8
1996 22.8 0.0
1995 20.1 0.0
1994 23.7 0.0
1993 16.3 3.2
1992 28.4 0.0
1991 16.1 0.2
  1. Calculate the mean value for each variable at both locations, and fill in the bottom row of Table 5.1. The mean can be calculated in Excel or Google Sheets using the expression =average(data), or you can calculate it by hand.
  2. What are these numbers telling you about whether or not it is a good idea to hold the wedding at Vancouver Harbour vs. Okanagan Centre? (1 – 2 sentences)

EX2: Examining the Probability of Rain or Extreme Temperatures

With your friend’s comfort in mind, you will want to make sure that the probability for rain and ridiculously hot or cold temperatures is low. Based on the 30-year record you have created, it is possible to calculate these probabilities.

If we take the number of days that it rained over the 30-year normal period, and then calculate the percentage of times that it rained, then we know the probability of it raining on June 21. To do the calculations you will need to know how many years it rained. When doing the calculation do not include any years for which there is no record.

For example, suppose that it rained on that day 3 years out of 30, then

[latex]\dfrac{3}{30} \times 100\% = 10\%[/latex]

If on the other hand you only had 27 years of record and it rained on 3 of them then the probability would be

[latex]\dfrac{3}{27} \times 100\% = 11.1\%[/latex]

Your friend really doesn’t want it to rain on their wedding day, so even though the rain wasn’t measurable, count days with “Trace” rain as rainy days.

You also want to make sure that the temperatures aren’t too hot nor too cool. More specifically, your friend does not want the temperature to be over 30 °C, nor under 20 °C. To do the calculations you need to know how many days out of the 30-year record the temperatures were higher than 30 °C or were below 20 °C.

Use these guidelines to determine answers to the following questions. Show your work.

  1. Based on what has happened over the past 30 years, what is the probability of it raining on June 21 at
    1. Vancouver Harbour?
    2. Okanagan Centre?
  2. Based on what has happened over the past 30 years on June 21, what is the probability of temperatures
    1. exceeding 30 °C at Vancouver Harbour?
    2. being less than 20 °C at Vancouver Harbour?
    3. exceeding 30 °C at Okanagan Centre?
    4. being less than 20 °C at Okanagan Centre?
  3. Based on your responses to the above questions, what are your conclusions about where to hold the wedding? (2 – 4 sentences)

EX3: Have Precipitation and Temperature Changed Over the Past 30 Years?

When we calculate probabilities based on what has happened in the past, then we assume what statisticians call stationarity. Stationarity is an assumption that variations in measurements are due to random fluctuations, and are not associated with any systematic change. However, it is possible that there is some underlying pattern of climate change. One simple way of examining that is to graph the data over time. Here we will use bar graphs for precipitation and line graphs for temperature.

In this exercise, you will plot the total monthly precipitation and mean daily maximum temperature for June for Vancouver Harbour. Has it changed over the past 30 years? For your convenience, the data is listed in Table 5.2.

Table 5.2. Total June precipitation and mean daily maximum over 30 years at Vancouver Harbour
Year Total June Precipitation (mm) June Mean Daily Maximum Temperature (°C)
1991 53.6 25.5
1992 96.4 28.8
1993 72.2 23.3
1994 70.5 25.0
1995 43.4 28.6
1996 13.6 23.2
1997 94.8 23.5
1998 29.8 25.9
1999 83.1 27.4
2000 57.0 27.5
2001 60.4 25.4
2002 30.8 30.2
2003 12.8 26.6
2004 22.8 28.3
2005 49.6 24.3
2006 25.2 26.2
2007 80.0 27.4
2008 43.0 26.9
2009 10.8 25.9
2010 48.4 23.1
2011 41.0 22.1
2012 76.8 22.0
2013 45.8 31.2
2014 36.8 23.7
2015 11 28.3
2016 58.2 25.2
2017 46.4 26.2
2018 38.8 26.8
2019 26.2 29.9
2020 53.2 24.1
  1. Construct a bar graph of June precipitation at Vancouver Harbour for the period 1991 – 2020.
    1. Copy and paste Table 5.2 into Google Sheets or Excel.
    2. Select the Year and Total June Precipitation columns and click on Insert/Chart/Column.
    3. Check that your labels, title, and axis are correct using the checklist for graphs and copy and paste your graph into your Worksheet.
  2. Construct a line graph of June mean daily maximum temperature at Vancouver Harbour for the period 1991- 2020.
    1. Select the Year and June Mean Daily Temperature columns and click on Insert/Chart/Line.
    2. Check that your labels, title, and axis are correct using the checklist for graphs and copy and paste your graph into your Worksheet.
  3. Are there any trends here? Your opinion will be a little subjective, but try to be as objective as possible. There are world-wide datasets that show warming trends. Explain your results in this world-wide context. (2 – 4 sentences)
  4. In the context of climate change, is the average for the past 30 years a good way to estimate the probability of what will happen next year? On the basis of climate trends you identified, do you have any reason to adjust your thinking about the probability of rain or extreme temperatures in Vancouver? (2 – 4 sentences)

Reflection Questions

Please take 15 minutes to consider the following questions. You can type your responses into your Worksheet.

  1. Now that you have some experience calculating means, can you think of another use for this new skill of yours?
    1. Describe a scenario where calculating the mean could help you make a decision in your life. Include a description of the data you would need to collect to help inform your decision.
    2. How long would you need to collect the data for in order for the mean to be representative? Explain your reasoning.
  2. In EX3 you assessed trends in climate data based on one relatively small set of data. What type of data would you need to see larger trends?


Return to EX1