Climate_change_module_assignment
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Dec 6, 2023
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CLIMATE CHANGE PROJECT
Student Name___________________________
Class Time____________
This module was initially developed by O’Reilly, C.M., D.C. Richardson, and R.D. Gougis. 15 March 2017. It has been modified for
this project.
Learning objectives:
To analyze global temperature data and see if the Earth’s average global temperatures are increasing.
To analyze CO
2
data and see if atmospheric levels are increasing.
To correlate CO
2
data with global temperature and see if there is a relationship.
To compare current trends with rates of change during pre-historic periods using ice core data
To interpret what these results mean for understanding current climate change
To learn basic shortcuts and graphing in Excel
Why does this matter?
Current climate change is affecting many aspects of the environment, with varying socio-
economic consequences. For example, a warmer climate can allow new diseases to be introduced and persist
(e.g. West Nile became established in the United States after an unusually warm winter allowed the mosquitos
that carry the virus to survive and spread). We are concerned not only with the actual temperature, but also with
the rate that the temperature changes. Very rapid changes make it more likely that species (maybe even
including humans!) cannot adapt and will go extinct.
Outline:
1.
Activity A: Determine current rates of air temperature and CO
2
change from modern datasets.
2.
Activity B: Explore whether temperature and CO
2
concentrations are related.
3.
Activity C: Compare current rates to pre-historical rates of change using data from an ice core to
investigate how climate has changed in the past.
Activity A:
How much are temperatures and atmospheric CO
2
concentrations changing?
Changes in air temperature -
Scientists from the Goddard Institute for Space Studies, NASA, compiled
temperature datasets from weather stations all over the world to create the dataset you are going to be working
with today to answer the question: Is earth “warming”? The data you will use are from years 1880-2014.
1.
Before you conduct your analysis, you should first make your predictions. What slope would indicate a
warming Earth? What slope would indicate Earth’s average global temperature was not changing? What
slope would indicate a cooling Earth? Sketch lines in the axes below to show what the expected slopes
would be in these different scenarios.
1
cooling
warming
no change
2.
Getting the air temperature data: These data are compiled by the Goddard Institute for Space Studies,
NASA, and are made available via the Earth Policy Institute.
http://www.earth-policy.org/data_center/
Select Climate, Energy and Transportation. The dataset you are looking for is called something similar
to “Average Global Temperature, 1880-2014 (Celsius)”, about 15 rows down. Download this excel file
and save on your computer in a location where you can find it again (the Desktop is a good option).
3.
Open up the dataset. Make a scatter plot of temperature change over time.
4.
Now, determine the rate of change. Determining rates of change graphically is straightforward. The
average rate of change is just the change in temperature divided by the change in time, or change in y
divided by the change in x, or the slope of a line that fits through the data. These are all the same thing.
Luckily, Excel can calculate the slope of a line very easily. So, to determine the rate of change (slope)
add a trend line. When you do this, make sure to select the options to show the equation of the line and
the R
2
value. The equation is written in the form
y = mx + b
, where
m
is the slope and
b
is the intercept.
The value for
m
is the rate of change.
The R-squared (R
2
) is a statistic resulting from a linear regression analysis, which is the statistical name
for what you just did by adding a trend line. It describes the proportion of variation in the dependent
variable explained by the independent variable. When R
2
~1, the data form a perfectly straight line. As
the data become more scattered from the line, R
2
decreases toward 0. Higher R-squared values indicate a
stronger relationship between the two variables. Record your R
2
value down with your slope.
a.
Snip or paste the scatter plot to this file making sure the graph includes axis with the appropriate
units.
b.
Equation for the line:
c.
R
2
=
d.
Rate of air temperature change (include units):
e.
Given your analysis, is Earth warming? How do you know?
5.
Many scientists claim that drastic changes in global temperature began in the mid-1900s when fossil-
fuel-powered transportation became a mainstay for most families. Test this hypothesis by adjusting your
o
C
o
C
o
C
time
time
time
2
trendline so that it only looks at the most recent decades, after personal transportation became common.
You can do this by:
Decide on the year in the mid-1900s that you want to begin the trendline. Scroll to that year and
select the data (year and temperature) from that year all the way to the most recent year.
Create a Scatter plot just as you did before, and add a trendline with the R
2
.
Write your answers for (a) and (c) on the board to compare with others.
a.
Snip or paste the scatter plot to this file making sure the graph includes axis with the appropriate
units
b.
Equation for the line:
c.
R
2
=
d.
Rate of air temperature change (include units):
e.
Compare the slopes of these two lines (1880 through mid-1990s versus mid-1990s through
2013). Does your analyses support the hypothesis that the rate of global average temperature is
greater since the 1950s?
Changes in atmospheric CO
2
-
In 1958, Dr. Charles David Keeling (1928-2005), who was a scientist at
Scripps Institute of Oceanography, began collecting data on atmospheric CO
2
concentration at the Mauna Loa
Observatory located in Hawaii. This dataset is what allowed us to understand the degree to which climate
change is human-caused through our burning of fossil fuels and release of CO
2
into the atmosphere. Due to his
scientific achievements, Dr. Keeling was awarded the National Medal of Science by President George W. Bush
in 2002. This is the highest award for lifetime scientific achievement that can be granted in the U.S. Today, you
get to analyze this same dataset, except that you have more data than was available to Dr. Keeling and his
colleagues, because your dataset extends up to current time.
6.
Getting the atmospheric CO
2
data: The longest measurements of atmospheric CO
2
concentrations have
been done in Mauna Loa, Hawaii. The simplest way to access the data is directly from the Mauna Loa
page.
http://www.esrl.noaa.gov/gmd/ccgg/trends/
You can already see some graphs plotted on this page, but since you want to analyze these data yourself
to determine a rate of change, you will have to download them. Select the ‘Data’ tab (second to the last
tab below the yellow text box). Then select the “Mauna Loa CO
2
annual mean data”
The data will appear as a .txt (CSV) web page. This is a common format for datasets that are relatively
small and easily downloadable. There is a lot of text at the top that describes the dataset. The data are
presented as a column of years, the mean CO
2
as ppm (parts per million, or micromoles per mol of air),
and the last column is the estimated uncertainty in the annual mean is the standard deviation.
Since you only need the data, the easiest way to do this is to highlight the data section of the web page,
including the headings (year, mean, unc). Copy. Then paste into Excel, on a new worksheet in the same
file that has the global temperature data. To convert from txt to Excel format, highlight the column, then
go to the Data tab and select ‘
Text to Columns
’. In the new window, you should be able to click through
as the default settings should work. You should be able to see the data in columns.
3
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7.
As you did for air temperature, plot a graph of CO
2
vs time.
8.
Determine the current rate of change for atmospheric CO
2
data by fitting a trend line, as you did for air
temperatures.
a.
Snip or paste the scatter plot to this file making sure the graph includes axis with the appropriate
units
b.
Equation for the line:
c.
R
2
=
d.
Rate of air CO
2
change (include units):
e.
Based on your analysis, has atmospheric CO
2
concentration increased? How confident are you in
these results? What phenomenon explains the matching patterns of average global temperature
and atmospheric CO
2
?
Activity B:
How related are the changes in temperature and CO
2
?
1.
To determine whether a change in CO
2
corresponds well with a change in air temperature, you can plot
temperature against CO
2
.To do this, highlight the CO
2
data from 1959 onwards, copy them, and then
paste them next to the temperature data from those years. Then make a graph with CO
2
on the x axis and
temperature on the y axis.
a.
Snip or paste the scatter plot to this file making sure the graph includes axis with the appropriate
units
b.
Equation for the line:
c.
R
2
=
d.
Based on your analysis, could atmospheric CO
2
concentration explain the increase in average
global temperature?
4