Exercise #1: Global Warming
Exercise #2: The Dust Bowl
In this exercise, students examine temperature and precipitation data from North America to answer the following:
1) What happened climatologically during the Dust Bowl years?
2) Were heat and dryness confined to the classic “Dust Bowl” area of the High Plains or were the climate changes broader in scope?
To address these questions, students work in the same teams, analyzing monthly and annual precipitation and temperature data from 1890 to 1950 at stations across North America.
Students use Excel to calculate and plot mean annual precipitation, 5-year and 10-year moving averages of precipitation (Fig. 4), and summer precipitation (Fig. 5). Analysis of these graphs requires students to consider the temporal variability of data analysis. Instead of assuming that mean annual precipitation or mean annual temperature can account for all noted climate instabilities, students note the possibility that the frequency of high intensity rainfall, which would not be absorbed, changed during the Dust Bowl years. Students also plot the 5-year moving averages of precipitation and temperature in order to examine the combined effects of these factors in creating drought conditions (Fig. 5).
In this exercise, students examine temperature data from a global distribution of sites to evaluate the following
1) Has the earth been warming?
2) If so, is the warming rate steady over time?
3) Is warming uniform over the globe?
Students work in small groups (3-4) analyzing data from a wide distribution of climate stations, including those located at high latitudes. We attempt to assign stations that have long, complete records (Fig. 2).
To assess the issue of global warming using the available data sets, students use Microsoft Excel to calculate and plot the annual mean temperatures for individual stations. They also plot the 5-year moving average of temperature to clarify the relationships between long-term and short-term warming trends (Fig. 3).
Figure 2. Map showing approximate locations of climate stations selected for Exercise #1.
Annual Temperature Anomaly at Jakutsk
Te
mp
era
ture
An
om
aly
(o
C)
Year
-5.0
-3.0
-1.0
1.0
3.0
5.0
1829 1859 1889 1919 1949 1979
Figure 3. A) Average annual and 5-year moving average temperature anomalies, based on average temperature between 1951-1980, at Jakutsk; B) Mean annual temperature and 5-year moving average temperature at Jakutsk; C) Mean annual temperature and 5-year moving average temperature at Toronto; D) Average annual and 5-year moving average temperature anomalies, based on average temperature between 1951-1980, at Toronto. Anomalies based on mean temperature between 1951 and 1980 (a relatively stable climatological period). The records for Jakutsk extend from 1829 to 1993 and for Toronto from 1841 to 1993. These stations have fairly complete records. Jakutsk shows a general “warming” trend, while Toronto exhibits slightly more variability. Spurious peaks in the Jakutsk record are due to the averaging of years for which some monthly data is missing. Their effect, in this case, suggests that students should remove incomplete years from their plot records.
Te
mp
era
ture
(o C
)
MeanTemperature at Jakutsk
Year
-15.0
-13.0
-11.0
-9.0
-7.0
-5.0
1829 1859 1889 1919 1949 1979
Year
Annual Temperature Anomaly at Toronto
Te
mp
era
ture
An
om
aly
(o C
)
-4.0
-3.0
-2.0
-1.0
0.0
1.0
2.0
1840 1865 1890 1915 1940 1965 1990
Analyzing Historical Climatology Records in Introductory GeoscienceElizabeth A. Clark* and Mary E. Savina, Department of Geology, Carleton College
*Current affiliation: Department of Civil and Environmental Engineering, University of Washington; Email: [email protected]
(A) (B) (D)
Figure 5. 5-year moving average of precipitation and of temperature at Toronto (far left), and total summer (June + July + August) precipitation in Toronto (near left). Precipitation data span the years from 1840 to 1988 and temperature from 1841 to 1993. Note on the far left a period of high temperatures and moderate precipitation in the 1950s, lower temperatures and higher precipitation in the 1970s, and climbing temperatures accompanied by lower precipitation in the 1930s.
The NDP-041 Data Set
The NDP-041 data set, used in this exercise, is distributed by the Carbon Dioxide Information Analysis Center based in Oak Ridge National Laboratories, Tennessee. The data is available in two forms:
1) As a download from the CDIAC ftp site at ftp://cdiac.esd.ornl.gov/pub/ndp041
2) On CD-ROM (contact the CDIAC directly, see http://cdiac.esd.ornl.gov/ for further information).
Monthly temperature data (in tenths of degrees Celsius) and monthly precipitation data (in tenths of mm) are located in <temp.data.Z> and <precip.data.Z>, respectively. These files contain temperature data for 7533 stations and precipitation data for 6039 stations worldwide for the period spanning1693 to 1990. See <temp.statinv> and <precip.statinv> for corresponding station inventories, including station number, name, location, dates of record, and percent data missing.
Formatting DataBecause the data files containing the NDP-041 are so large, users should open them in Microsoft Word (or similar) and then select and paste the data sets from specific stations into Excel. The “text to columns” command prepares the data for analysis. We have found it most convenient to replace the -999 (no data) code with blank cells. We complete the data formatting process to this point to allow students to focus on statistical analysis and graph interpretation, rather than preparation. Advanced students work directly with the original files.
Supplemental DataTo extend the time period of analysis, students download additional data from the IRI (International Research Institute)/LDEO (Lamont-Doherty Earth Observatory) Climate Data Library at http://ingrid.ldgo.columbia.edu/ . Stations can be located in the “Introduction to Climate Data: Station List” using the station ID number or station name as it appears in the NDP-041 data set. When saving the columnar data, users should change file type to “All files (*.*). This file contains the same data as the NDP-041 data set with some additional data. The dates are formatted as months since January 1960. Some months will be missing, so be check to ensure data formatting when adding this data to the NDP-041 list.
Objectives
Integrating Graphical Analysis and Historical Documentation
In response to the difficulties of introducing statistical data analysis into a broad-based introductory geology course, we have developed an exercise that exposes students to the types of climate data available and to the potential applications of these data. This exercise can be used as a stand-alone piece or incorporated in later coursework. For information on how this piece has been integrated into the course, see the section titled “Integrating Graphical Analysis and Historical Documentation.”
The exercise introduces students to the geographic and temporal limitations of data availability and the ways that these limitations affect our analyses. It also helps students to develop confidence in their ability to construct and interpret graphs. Students are given the opportunity to re-evaluate the significance of their findings when constructing original hypotheses for the cause of the Dust Bowl in a final paper.
The effectiveness of this exercise is evaluated during PowerPoint presentations of each group’s findings and when reading students’ final papers.
This exercise has been used in the context of a two-course “dyad” called “Agriculture and the American West” that combined American literature with geology. One theme that carried through the course was the question: “What caused the Dust Bowl?” Students were challenged to consider physical and societal factors: drought, soil types, land quality, capitalism, migrant farmers, and the Depression.
This question lent itself to the insertion of an information literacy portion of the project, as well as creating an opportunity for the development of writing and critical thinking skills.
To evaluate these factors, students consulted first-hand/contemporary accounts of the Dust Bowl from government documents, newspapers and periodicals. They also considered the depictions of the Dust Bowl in fiction, music, art, film, and photography. Information from the Excel exercise presented here was incorporated as evidence related to the role of climate/drought in the Dust Bowl.
Presentation of Results
After students have analyzed the data, they present their findings to the class. Two objectives met in this part of the exercise include:
1) Acquainting the entire class with spatial and temporal climate variability on a global-scale;
2) Building students’ confidence in their public speaking abilities.
We archive these presentations in a common course folder for students to refer to when building hypotheses about the role of climate change in the Dust Bowl (Fig. 1).
References
Boden, T. and Nelson, T., 1993, CDIAC’s numeric data package collection: Selected data sets relevant to studies of greenhouse gases and climate.
International Research Institute for Climate Prediction, 2003, IRI/LDEO Climate data library, http://ingrid.ldgo.columbia.edu/ (October 2003).
Figure 1. Examples of PowerPoint slides used to present findings. In this format graphs and conclusions can easily be archived for quick reference.
Data Availability
Record lengths are variable. Longer, more complete records are available for much of western Europe. Data availability for areas outside of western Europe has improved in the last 300 years.
Year
Pre
cip
itatio
n (
mm
)
Mean Annual Precipitation at Toronto
40
5060
70
80
90100
110
1840 1865 1890 1915 1940 1965 1990
3030
Annual Precipitation Anomaly at Toronto
YearPre
cip
itatio
n A
no
ma
ly (
mm
)
-20
-100
10
20
3040
50
1840 1865 1890 1915 1940 1965 1990
Mean Temperature at Toronto
Year
4.05.06.07.08.09.0
10.011.0
1840 1865 1890 1915 1940 1965 1990
Te
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(oC
)
Pre
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n (
mm
)
Te
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(o C
)
5-year Moving Average of Precipitation and Temperature at Toronto
50
60
70
80
90
100
1840 1865 1890 1915 1940 1965 1990
66.577.588.599.510
Year
5-year moving average precipitation5-year moving average temperature
Pre
cip
itatio
n (
mm
)
Total Summer Precipitation in Toronto
125
175
225
275
325
1840 1865 1890 1915 1940 1965 1990Year
Total summer precipitation5-year moving average summer precipitation
Mean annual5-year moving average
5-year moving averageMean annual
Figure 4. Mean annual precipitation and 5-year moving average precipitation in Toronto (top), and average annual and 5-year moving average precipitation anomaly, based on average temperature between 1951 and 1980 (bottom). Graphs generally show higher precipitation from 1845-1865 and an abrupt precipitation decline from 1928-1941.
(C)
