Steve Zadro - Climate Change Module
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School
Illinois State University *
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Course
102
Subject
Geography
Date
Jan 9, 2024
Type
docx
Pages
8
Uploaded by ProfMusicGorilla41
Project EDDIE: CLIMATE CHANGE
Student Handout
This module was initially developed by O’Reilly, C.M., D.C. Richardson, and R.D. Gougis. 15 March 2017. Project EDDIE:
Climate Change. Project EDDIE Module 8, Version 1.
http://cemast.illinoisstate.edu/data-for-students/modules/climate-
change.shtml
. Module development was supported by NSF DEB 1245707.
Learning objectives:
To analyze global temperature data to see if Earth’s average global temperatures are really
increasing
To analyze CO
2
data to see if atmospheric levels are really increasing
To correlate CO
2
data with global temperature to 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 this matters:
Current climate change is affecting many aspects of the environment, with 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.
Discussion of papers read for class and Power Point presentation
2.
Activity A: Determine current rates of air temperature and CO
2
change from modern datasets.
3.
Activity B: Explore whether temperature and CO
2
concentrations are related.
4.
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.
The Excel sheet posted in Canvas has ALL data downloaded for you!!
The steps that direct you to
download the data are for reference ONLY!!
You do NOT need to download any from this sheet.
1
Activity A:
How much are temperature and atmospheric CO
2
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 1880-2013.
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.
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.
1860
1880
1900
1920
1940
1960
1980
2000
2020
2040
12.80
13.00
13.20
13.40
13.60
13.80
14.00
14.20
14.40
14.60
14.80
f(x) = 0.01 x + 1.12
R² = 0.77
Tempature (C) vs Time
Years
Temp(C)
o
C
o
C
o
C
time
time
time
2
5.
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.
Equation for the line:
y = 0.0066x + 1.1197
b.
R
2
=
0.7662
c.
Rate of air temperature change (include units):
0.0066
d.
Given your analysis, is Earth warming? How do you know?
Yes, clearly since 1880 the
earth has been slowly rising in average temperatures but it has gone up faster since
the 1960’s and after.
6.
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 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.
Equation for the line:
b.
R
2
=
c.
Rate of air temperature change (include units):
d.
Compare the slopes of these two lines (1880 through mid-1900s versus mid-1900s
through 2013). Does your analyses support the hypothesis that the rate of global average
temperature is greater since the 1950s?
3
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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
that was available to Dr. Keeling and his colleagues, because your dataset extends up to current time.
7.
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.
Scroll down to the bottom of the page to ‘Data’. Select “Mauna Loa CO
2
annual mean data”
The data will appear as a .txt 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 mil, 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, you
need to makes sure you have that column highlighted, then go to ‘Text to Columns’ under the
Data tab in Excel. 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.
8.
As you did for air temperature, plot a graph of CO
2
vs time.
4
9.
1950
1960
1970
1980
1990
2000
2010
2020
0
50
100
150
200
250
300
350
400
450
f(x) = 1.54 x − 2702.36
R² = 0.99
CO2 vs Time
Time
Mean Co2
10. Determine the current rate of change for atmospheric CO
2
data by fitting a trend line, as you did
for air temperatures.
a.
Equation for the line:
y=1.5371x - 2702.4
b.
R
2
=
0.9852
c.
Rate of air CO
2
change (include units):
1.5371
d.
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
?
Yes, I can say that it has increased and it isn’t
stopping, it is an exponential growth over the years and it is increasing at a steady
pace for the last half a decade.
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.
Equation for the line:
y = 0.0094x + 10.945
b.
R
2
=
0.8744
c.
Based on your analysis, could atmospheric CO
2
concentration explain the increase in
average global temperature?
Yes it could explain a rise in temperature but not the
5
whole average, I believe there are a lot of other factors that increase the temperature
but this is definitely one of them.
Activity C:
How do current trends compare to pre-historic rates of change?
An exploration of the Vostok Ice Core -
When analyzing Earth’s climate, it is important to remember
that Earth is 4.54 billion years old. Our analyses so far have only looked at recent history. How can we
compare the recent data to pre-historic time? Are the current rates of change similar or different than
those the earth has experienced in the past? To explore this, we can use data taken from ice cores that
were drilled at the poles.
Hundreds of ice cores have been extracted from polar ice because they contain valuable data on
atmospheric chemistry over pre-historic time. These valuable data exist in tiny air bubbles that are
trapped in the ice. These air bubbles contain the same gases in the same ratios as the atmosphere at the
time when the ice formed. The data you will be analyzing today are from ice cores extracted from the
Vostok research station in Antarctica. As you have probably assumed, the depth of the ice core is related
to how old the ice is; deep ice is older. There are two other variables that you will be analyzing from the
ice cores. The first is temperature, which is reflected by isotopic ratios in the ice of the core so that these
isotopic ratios can be converted into air temperatures. The second variable you will analyze is CO
2
concentration, which has been measured from air bubbles trapped in the ice. We can use these data to see
what rates of change were like during this pre-historic period, during which human activity has been
minimal.
This step is already done for you on the Excel sheet!
1.
The Vostok ice core data is available through the Carbon Dioxide Information Analysis Center
(CDIAC)
http://cdiac.esd.ornl.gov/
. Under the Data dropdown menu, select Climate. Then select
Temperature. Then down at the bottom of that page there is a link called “Historic isotopic
temperature record from the Vostok Ice core, Antarctica”. Select this link, which provide
information about the core location, and then select ‘Digital Data’ on the top of the page. Similar
to the CO
2
data, you need to highlight the column headings and then down all the rows,
excluding all the text in the starred box. Download the Vostok ice core data to Excel and save it
as a new Excel workbook on the desktop.
2.
Begin with the temperature data, and graph it using ice age as the independent variable. Create a
Scatter graph with straight lines between the points. Keep in mind that the x axis refers to how
many thousands of years ago, so the time axis moves in the opposite direction as what you are
accustomed to based on previous analyses. This is the custom for research that investigates
patterns over long time periods.
Adjusting the y axis will make the data be more prominent on the graph.
To help you orient to these plots, address the following questions:
6
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a.
Do you think these data are a good representation of pre-historic rates of change?
It
shows how the temperature during the ice age was stagnating between -450 and -480
and sometimes going under and over but usually stayed in that range, I would say
it’s a good way to show the temperature but not a good way to show change since it
rarely does.
b.
Are we currently in a glacial or interglacial period?
Interglacial
c.
How long does a glacial and interglacial period last?
Glacial:
70,000 – 90,000 years
Interglacial:
10,000 – 15,000 years
3.
Add a trend line to the ice core temperature data and look at the R
2
value. Do you think this line
is a good representation of long-term rates of temperature change?
No
4.
The next step is to calculate what the fastest rate of change might be. To do this, you want to
identify a section of your data where the temperature is changing very rapidly. If you hover your
mouse over a data point, it will tell you the data values for that particular point. Make note of the
data point values at the beginning and end of the time period segments that you think have the
steepest slopes:
Then make a new graph of only that time period, and determine the rate of change by fitting a
trend line and looking at the slope.
a.
Rate of pre-historic temperature change (with units). Write your answer on the board to
compare with others.
5.
To download the Vostok ice core CO
2
data, under the CDIAC website
http://cdiac.esd.ornl.gov/
select ‘Atmospheric Trace Gases & Aerosols’. Then select ‘Carbon Dioxide (CO2)’. On the next
page there is a link to ‘Vostok, Antarctica (Baronla et al.).’ You can then download the data and
convert it into Excel columns in the same way you did previously. Prepare a plot of CO
2
concentration as a function of (gas) age. Plot (gas) age on the x axis and CO
2
on the y axis.
a.
According to the CO
2
data from ice cores, during which time frame(s) was there the
greatest rate of change in atmospheric CO
2
concentration? How does this change in
atmospheric CO
2
concentration correspond to what you see in the ice-core temperature
record?
The greatest change was in between 10,000-15,000 around 12,500.
7
b.
How do CO
2
concentrations recorded over time in the ice core compare to the current
values for today, which you can see on the Mauna Loa web site?
Comparing the two it
clearly shows that nowadays the Co2 count is a lot higher and only seems to be
rising while back during the ice age the Co2 count was stagnating a lot but always
was consistent in going up and down while the Mauna Loa information shows that
our Co2 ppm is only going up.
6.
Now make a new graph focused only on a time period of rapid change in CO
2
. Determine the
rate of change by fitting a trend line and looking at the slope.
a.
Rate of pre-historic atmospheric CO
2
change (with units)
0.3539
8