Ch8 Climate Cycles
Instructor Guide
INSTRUCTOR GUIDE
Chapter 8 Climate Cycles
SUMMARY
This exercise explores cyclic climate change from the geologic record and the explanation of
that change using astronomical theory. In Part 8.1, you will examine a variety of records displaying cyclic climate change, calculate the periodicities of these records, and reflect on sources and
implications of scientific uncertainty. In Part 8.2, you will reflect on your knowledge of seasonality. Then you will be introduced to the long-term orbital variations of eccentricity, obliquity, and
precession and connect these orbital drivers to the periodicities in the climate proxy records from
Part 8.1. In Part 8.3, you will dissect the CO2 record of the last 400 kyr to characterize greenhouse gas levels during past glacial–interglacial cycles and today. You will identify a distinct break
in the cyclicity and develop hypotheses to explain this change in climate.
FIGURE 8.1. The Earth and Sun. Image from NASA;
http://www.nasa.gov/centers/goddard/news/topstory/2008/solar_variability.html.
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Goal: to explore evidence of cyclic climate change from the geologic record and explain those changes using astronomical theory.
Objectives: After completing this exercise your students should be able to:
(1) Describe the variety of ways that climate cycles are recorded in sedimentary
records.
(2) Calculate the periodicities of climate proxy records.
(3) Discuss sources and implications of scientific uncertainty.
(4) Explain why seasons exist.
(5) Differentiate among eccentricity, precession, and obliquity.
(6) Use orbital theory to explain the cause of climate cycles, including glacialinterglacial cycles.
(7) Identify a distinct break in the glacial-interglacial cycle, and develop hypotheses to explain this change in climate.
I. How Can I Use All or Parts of this Exercise in my Class?
(based on Project 2061 instructional materials design.)
Title (of each part)
How much class time will I need? (per
part)
Can this be done independently (i.e., as
homework)?
Part 8.1
Part 8.2
Part 8.3
Patterns and
Periodicities
60 min
Orbital Metronome
60 min
A Break in the
Pattern
20 min
Yes, but would
Yes
need follow-up
presentation
and discussion
in class
What content will students be introduced to in this exercise?
Science as human endeavor
X
X
How do you know about earth history? Types
X
of archives outcrops, cores
Where do you go to learn about earth hisX
tory? Land vs. sea vs. ice
Geographic awareness
X
Stable isotopes
X
Subdivisions of geologic time
X
X
Fossils as age Indicators
X
Magnetism as an age Indicator
X
Climate change can be cyclic
X
X
Glacial-interglacial cycles
X
Orbital periodicity, Milankovitch, insolation
X
variability
Climate changes on human timescales
Synchronous vs. asynchronous change geoX
X
graphically
Ocean-atmosphere-biosphere-cryosphere
X
system interactions/feedbacks
High latitude climate change sensitivity
X
What types of transportable skills will students practice in this exercise?
Make observations (describe what you see)
X
X
Yes
X
X
X
X
X
X
X
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Ch8 Climate Cycles
Recognize trends (abrupt vs. gradual vs.
patterns)
Form questions
Interpret graphs, diagrams, photos, tables
Make hypotheses or predictions
Synthesize/integrate & draw broad conclusions
Perform calculations (rates, averages, unit
conversions) & develop quantitative skills
Work with diverse perspectives
Written communication
Oral communication
Make persuasive, well supported arguments
Identify assumptions & ambiguity
Levels & types of uncertainty (quantitative
vs. qualitative)
Significance/evaluation of uncertainties &
ambiguity
Information literacy (use of primary literature)
What general prerequisite knowledge &
skills are required?
What Anchor Exercises (or Parts of Exercises) should be done prior to this to
guide student interpretation & reasoning?
What other resources or materials do I
need? (e.g., internet access to show on-line
video; access to maps, colored pencils)
Instructor Guide
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Math - working
with word
problems;
definition and
use of stable
oxygenisotopes;
geologic time;
definition of
climate rchives
and proxies
Intro to Cores
(Ch 1);
Cenozoic
Overview (Ch
6; or lecture
on oxygen isotopes)
Calculators;
document
camera or over
head projector
for student
presentations;
optional videos
suggested in
the supplemental resources would
require internet access to
watch and listen to these
online videos
None
None
None required,
but helpful to do
Part 8.1
None required,
but helpful to
do Parts 8.1 &
8.2
None
None
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What student misconception does this
exercise address?
Any uncertainties in science
make scientific
conclusions
useless
What forms of data are used in this?
(e.g., graphs, tables, photos, maps)
What geographic locations are these
datasets from?
graphs, table,
photos
Global distribution of data
How can I use this exercise to identify
my students’ prior knowledge (i.e., student misconceptions, commonly held
beliefs)?
How can I encourage students to reflect
on what they have learned in this exercise? [Formative Assessment]
How can I assess student learning after
they complete all or part of the exercise? [Summative Assessment]
Where can I find more information on
the science in this exercise?
Cause of Earth’s
seasonality (variety of misconceptions on this
topic); Earth’s
geometry in
space does not
vary over time
(e.g., fixed tilt
angle and direction).
table, photos
Global climate
change today
is simply part
of another
regular interglacial period
Graphs
Global distribuSynthesis retion of data
cord, therefore
(same data as
global
Part 8.1)
All parts of this exercise include questions or tasks
that can help identify student prior knowledge and
misconceptions. In particular Part 8.2 begins with
questions on seasonality, a topic that is often misunderstood by students.
Each exercise part can be concluded by asking: On
note card (with or without name) to turn in, answer:
What did you find most interesting/helpful in the
exercise we did above? Does what we did model
scientific practice? If so, how and if not, how not?
See suggestions in Summative Assessment section
below.
See the supplemental materials and reference sections below.
II. Annotated Student Worksheets (i.e., the ANSWER KEY)
This section includes the annotated copy of the student worksheets with answers for each Part of
this chapter. This instructor guide contain the same sections as in the student book chapter, but
also includes additional information such as: useful tips, discussion points, notes on places
where students might get stuck, what specific points students should come away with
from an exercise so as to be prepared for further work, as well as ideas and/or material
for mini-lectures.
Part 8.1. Patterns and Periodicities
Introduction
This exercise examines paleoclimate records from a variety of archives, locations, proxies, and
geologic epochs. However, they all have something in common – the data display cyclicity or
the repetition of some distinct pattern. Cyclicity in the time dimension (vs. space dimension) is
termed periodicity. Your instructor will assign one or more of these records to you to examine
and ultimately determine the periodicity of the observed cycles. As an introduction to periodicity,
examine the hypothetical data below (Figure 8.2). These data show three cycles (high-low-high)
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Instructor Guide
in some variable over approximately 30 million years. Thus, the cycles have a periodicity of approximately 10 million years. Note periodicity (time/cycle) is the inverse of frequency (number
of cycles/time). Furthermore, when determining periodicity in a record it is important to identify
the number of full cycles, rather than simply counting the number of peaks (or troughs) in the
curve. The importance of this distinction is apparent in the example below as there are four
peaks (highs), yet only three full cycles.
FIGURE 8.2. Hypothetical data displaying cyclicity.
The records you will work with contain real data from natural climate archives and therefore
will not be as “clean” as the simple sine curve in this example. Nevertheless, one or more cycles
are present in each record you will work with.
To do:
Answer the questions for your record. Next, add information about your record to Table 8.1.
Then be prepared to present your record to the class and explain how you determined the periodicity and any other observations or questions you have about your record.
The following records vary in the math required to determine periodicity. Some records (Records
4, 5, 6, and 7) are already plotted against age and therefore periodicity may be calculated fairly
easily in 1 step. However, other records are plotted against depth and will require students to
use the average (linear) sedimentation rate to convert the depth scale to an age scale. In most
cases the linear sedimentation rate is provided (e.g., Records 2 and 3), whereas in one case
students will need to determine the average sedimentation rate based on the ages given for 2
levels within the core (e.g., Record 1).
Given the range of math skills in a class it is probably useful for students to have the option to
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Instructor Guide
work in small groups on the records they are assigned. Be sure to have the students complete
the appropriate row in Table 8.1 for their assigned record. Short class presentations on each of
the 7 records by the students will enable a fruitful class discussion on the global nature of climate cycles, the common periodicities, the sources and implications of uncertainties in these
data, and speculation on the potential causes for the observed cycles. These same points should
be addressed by students when they answer the synthesis questions.
TABLE 8.1. Data summary
Record
(Key
Figures)
What
Type of
Archive is
It?
Where is
the Record
From?
What type
of Data
(Proxy) is
It?
What
Geologic
Time
Span
Does
This Record
Cover?
What is the
Periodicity
That You
Determined?
[This column to
be completed in
Part 8.2]
What Orbital Cycle Best Matches
the Climate Cycle?
1
(Figure
8.3)
Marine
sediments
Shatsky
Rise, NW
Pacific
Ocean
lithology
(digital
photo),
color reflectance, bulk
density
Pleistocene
~44 kyr to
~46 kyr
Obliquity
2
(Figure
8.4)
Marine
sediments
Lomonosov
Ridge,
central
Arctic
ocean
Pollen,
spores, micro-fossils,
ice-rafted
debris
Eocene
~37 kyr to
~40 kyr
Obliquity
3
(Figures
8.5 &
8.6)
Outcrop
of paleolake
Teruel Basin, NE
Spain
Lithology
and color
reflectance
Miocene
~20 kyr to
~22.7 kyr
Precession
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Instructor Guide
Record
(Key
Figures)
What
Type of
Archive is
It?
Where is
the Record
From?
What type
of Data
(Proxy) is
It?
What
Geologic
Time
Span
Does
This Record
Cover?
What is the
Periodicity
That You
Determined?
[This column to
be completed in
Part 8.2]
What Orbital Cycle Best Matches
the Climate Cycle?
4
(Figures
8.7 &
8.8)
Marine
sediments
57 sites
from world
ocean
Benthic
oxygenisotopes
HolocenePliocene
~91 kyr
and 44 kyr
Eccentricity and
obliquity
5
(Figure
8.9)
Ice cores
Vostok,
East Antarctica
CH4, CO2,
oxygenisotopes
(temperature and ice
volume)
HolocenePleistocene
~102 kyr
(and 41
and 23 kyr
but difficult
to ID visually)
Eccentricity (and
obliquity and
precession)
6
(Figure
8.10)
Loess and Central
soils
China
Magnetic
susceptibility
Pleistocene
~117 kyr
Eccentricity
7
(Figure
8.11)
Marine
sediments
Freshwater
diatom
abundance
Pleistocene
~19 kyr
Precession
Equatorial
Atlantic
ocean
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Ch8 Climate Cycles
Record 1: Shatsky Rise, North Pacific Ocean (Figure 8.3)
Instructor Guide
SUGGESTED EXTENSION: We
recently obtained (thanks to the
Gulf Coast Repository staff) two
additional datasets for this core:
XRF (elemental) data and magnetic
susceptibility data. These data are
saved in excel files in the online
supplemental material for
instructors and students. Have
students plot the following to see
fantastic examples of cyclicity.
Good elements to plot (as that
element’s area vs cumulative
length) include: Fe, Al, Ti to
represent eolian input from land, Ca
to represent the calcareous
biogenic input. See what the Si
input is doing – is this a biogenic or
terrigenous signal? Have students
correlate different datasets
(including the color reflectance and
core photo to the left) to see what
changes synchronously and
asynchronously over the same
depth interval. Note that the lighter
colored sediment is calcareous ooze
(greater biogenic input), while the
darker colored sediment is
calcareous clay (greater
terrigenous input). Then let them
propose hypotheses as to what is
causing the cyclicty in those
elements and the magnetic
susceptibility. Given that the
sediments are mid-Pleistocene in
age (see question 2 below),
students may interpret these as
glacial-interglacial cycles. They can
also calculate the periodicity (as is
asked in questions 1-2 below).
Have they try and figure out which
elements would be in higher
abundances during glacial and
which would be higher abundances
during interglacials. This is great
science that can become a class
project!
FIGURE 8.3. Composite digital photograph, color reflectance, and bulk density for Core 198-1208A-8H. This core is
composed of nannofossil ooze and nannofossil clay of Pleistocene age from Shatsky Rise, NW Pacific Ocean. Ages in this
core were determined using magnetostratigraphy. From Shipboard Scientific Party, 2002.
1 (a) What evidence is there of cyclicity in the digital core image?
The core image shows a repeated color pattern of light and dark sediment layers (that corresponds to the highs and lows in the reflectance data – see next question)
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(b) The reflectance (Figure 8.3) of visible light from the sediment cores was measured using a
spectrophotometer. This quantitative measurement provides a high-resolution stratigraphic record of color variations for visible wavelengths (400–700 nm). Notice that light colored sediments have high reflectance values, whereas dark colored sediments have low reflectance values. What evidence is there of cyclicity in the reflectance data?
The reflectance data displays a repeated pattern, with reflectance levels oscillating between ~
35 nm and 15 nm. Students should recognize a repeated color pattern in the core that corresponds to the highs and lows in the reflectance data.
(c)Approximately how many meters of sediment were deposited within a typical cycle (Figure
8.3)?
Estimated by eye, there are ~1.8 m of sediment deposited within a typical cycle. This can also
be determined by recognizing there are 5 full cycles in the core:
~71.5m - 61.8m = 9.4 m
9.4 m/5 cycles = 1.88 m/cycle
2 If the age at 62 m below seafloor (mbsf) in this core (Figure 8.3) is determined to be 1.21 million years (Ma) and the age at 85 mbsf is 1.77 Ma, and if we assume a constant sedimentation
rate between these two age control points, what is the likely periodicity of the cyclicity represented in this core? Show your work.
Depending on what the students count as full cycles this could vary.
62 mbsf = 1.21 Ma and 85 mbsf = 1.77 Ma. Therefore the average sedimentation rate between
these two age-depth datums is 23 m/0.56 Myr = 41.07 m/myr.
The reflectance peaks have a spacing of ~ 1.8 m (or 1.88 m depending on your answer to question 1.1).
Therefore 1.8 m x (1 myr/41.07 m) = 0.044 myr
0.044 myr x (106 yr/1 myr)= 44,000 yr periodicity.
If 1.88 m was used then:
1.88 m x (1/myr/41.07 m) = 0.46 myr = 46,000 yr
3 What additional information would you like to know to reduce the uncertainties in your periodicity estimate above? In other words, how could you test this hypothesis of periodicity?
Sources of uncertainty include the assumption of a constant sedimentation rate, when it may not
have been constant. In addition deciding by eye what to counts as a full cycle and what doesn’t
added uncertainty (visually smoothing data). Ideally, I would like additional age control data - a
high a resolution record as possible – to see if there are any hiatuses (gaps in the depositional
sequence), and if the depositional rate really was constant.
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Record 2: Lomonosov Ridge, central Arctic Ocean (Figure 8.4)
FIGURE 8.4. Records of the relative abundances of various “palynomorph” microfossils (i.e., angiosperm pollen and
spores, dinoflagellate cysts, bisaccate pollen, terrestrial palynomorphs) and the weight-percent of ice-rafted debris
(IRD, i.e., sediment transported from land by icebergs and/or sea ice) in samples from middle Eocene age sediments in
Core 302-2A-55X from the Lomonosov Ridge, central Arctic Ocean. Ages in this core were determined using
biostratigraphy (dinocyst and silcoflagellate index fossils). Both the “raw” data (gray lines), and the filtered data
(colored lines) are included. Data are filtered as part of the signal processing in spectral analysis. From Sangiorgi et al.,
2008.
4 (a) What evidence is there of cyclicity in the data (Figure 8.4)? (b) Approximately how many
meters of sediment were deposited within a typical cycle?
Each of the data curves display a rough sine-wave like pattern, oscillating from lower to greater
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abundance and back again. Estimating by eye, ~1 m of sediment was deposited within a full cycle. Alternatively the periodicity could be determined in the following way:
240.9 m- 236.3 m = 4.6 m/ 5 cycles = 0.92 m/cycle
5 Based on the age data, the sedimentation rate for this core was determined to be approximately
25 m/myr (assuming a constant sedimentation rate). What is the likely periodicity of the cyclicity
represented in this core (Figure 8.4)? Show your work.
Depending on what the students count as full cycles this could vary.
1 m (avg spacing of cycles) x 1 myr/25 m = 0.04 myr = 40,000 yr periodicity
Or if 0.92 m/cycle were used:
0.92 m x 1 myr/25 m = 0.037 myr = 37,000 yr periodicity
6 What additional information would you like to know to reduce the uncertainties in your periodicity estimate above? In other words, how could you test this hypothesis of periodicity?
Uncertainty stems from calculating the average sedimentation rate, smoothing data, and approximating the average spacing of the cycles “by eye”. Ideally, I would like additional age control data - a high a resolution record as possible – to see if there are any hiatuses (gaps in the
depositional sequence), and if the depositional rate really was constant.
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Record 3: Cascante outcrop, NE Spain (Figures 8.5 and 8.6)
FIGURE 8.5. Mudstone and limestone sediments in a Miocene age
outcrop of the Cascante sedimentary section in NE Spain. Age is
determined using magnetostratigraphy (the magnetic time scale).
Cycle numbers are listed from the base to the top of the outcrop (see
also corresponding cycle numbers in Figure 8.6). From Abels et al.,
2009.
FIGURE 8.6 (on right). Data and interpretation of the Cascante
sedimentary section (Figure 8.5). Gray shading in the magnetic
polarity record represents uncertainty intervals between samples with
certain polarity. Gray in the lithology column represent color
differences (white=limestone, light grey=green-yellow mudstone,
medium grey=red-orange mudstone, and dark grey=red-brown
mudstone). Cycles of dark mudstone and paler limeymudstone/limestone are numbered on the left of the column.
Locations of limestone samples collected for thin sections are also
indicated. The graph shows smoothed color reflectance data. Modified
from Abels et al., 2009.
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7 In Figure 8.6: (a) What evidence is there of cyclicity in the reflectance data? (b) In the lithology
column? (c) Approximately how many meters of sediment were deposited within a typical cycle?
The reflectance data displays a repeated pattern, with reflectance levels oscillating between
highs and lows. Students should recognize a repeated pattern of lithologies that corresponds to
the highs (limestones or paler limey mudstones) and lows (mudstones) in the reflectance data.
Estimated by eye, there are ~2 m of sediment deposited within a typical cycle.
8 Based on the magnetostratigraphy of this outcrop (Figure 8.6), the age at the top of Chron
C4Ar.2n is 9580 ka and the age at top of Chron C5n.2n is 9920 ka (ka  thousands of years
ago). Unlike core depths, the stratigraphic position (i.e., vertical scale) in this outcrop is numbered from the bottom up because field data collection started at the base of the outcrop and
the scientists worked their way up-section (and up the mountainside, see (Figure 8.5)). Assuming a constant sedimentation rate, what is the likely periodicity of the cyclicity represented in
this outcrop of ancient lake sediments? Show your work.
To make this process a bit more challenging the ages of the Chron boundaries could be removed
and students could be required to look these up themselves using the magnetic polarity time
scale (MPTS) in Chapter 4.
If one chooses to place the Chron boundaries such that none of the gray zone is included then:
(63 m-28.5 m)/ (9920 ka-9580 ka) = 34.5 m/340 kyr = 0.101 m/kyr linear sedimentation rate
There are 17 full cycles in about 36 meters. Therefore 1 cycle is 36 m/17 cycles= 2.1 m
2.1 m x (1 kyr/0.101 m) = 20,792 year periodicity
Alternatively students may use the data from 0 to 78 meters in the record and determine:
78 m /34 cycles = 2.29 m/cycle
2.29 m x (1 kyr/0.101 m) = 22,673 yr periodicity
9 What additional information would you like to know to reduce the uncertainties in your periodicity estimate above? In other words, how could you test this hypothesis of periodicity?
Uncertainty originates from placement of the chron boundaries, smoothing data, and approximating the average spacing of the cycles “by eye”. In addition, although all cycles include an
upward transition into carbonate-rich (paler) units, not all of the cycles include a true limestone
unit; this may suggest that some cycles are more complete than others in this sequence. Ideally, I would like additional age control data - a high a resolution record as possible – to confirm
my suspicion that there are some minor erosional surfaces (hiatuses; gaps in the depositional
sequence), and to determine if the depositional rate really was constant.
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Instructor Guide
Record 4: Global Ocean (Figures 8.7–8.8)
FIGURE 8.7. (a) Locations of
the 57 cores used in the Lisiecki
and
Raymo
(2005)
study.
Benthic oxygen isotope data
were obtained from core samples
from the Deep Sea Drilling
Program (DSDP) and Ocean
Drilling Program (ODP) sites
(crosses),
GeoB
sites
(diamonds), and others (circles).
(b) Graphically aligned benthic
oxygen isotope data from 57
sites, offset vertically, on the
page so that the variability within
each can be seen. These data
are compiled to make Figure
8.8.
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Instructor Guide
FIGURE 8.8. “Stacked” benthic oxygen isotope record constructed by graphically correlating and combining the 57
globally distributed benthic δ18O records shown in Figure 8.7. Ages are determined using magnetostratigraphy. The
magnetic polarity record is shown at the base of each panel in the figure. The numbering of peaks and troughs on this
curve represents marine isotope stage numbers with odd numbers representing warmer (interglacial or interstadial)
times and even numbers representing colder (glacial or stadial) times. Note ka = thousand years ago. From Lisiecki and
Raymo, 2005.
10 Describe any evidence of cyclicity in this record (Figure 8.8).
The repeated variation in oxygen-isotope values between 5 and 3‰ is evidence of cyclicity. Notice that the amplitude and frequency of the cycles is smaller in the older part of the record.
11
Notice that Figure 8.8 is a composite record of benthic oxygen isotope data obtained from
57 marine sites (Figure 8.7). What evidence is there that the cycles in these data are globally
synchronous? Explain.
These data are graphically aligned and offset vertically on the page so that the variability within
each can be seen, yet they can also be compared to each other. One can see that there is a
common pattern at each of these locations, however it isn’t a perfect match due to local influences. Stacking (or combining and averaging) the data provides a global perspective by removPage 15 of 33
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Instructor Guide
ing the local noise, however this process also adds some uncertainty since the individual records
are merged and local details are removed. That said, there is a clear, consistent pattern from
site to site, especially for the younger portions of these records (which are typically higher resolution, more complete data sets) that show the most extreme changes in amplitude.
12
What is the periodicity of the cycles (Figure 8.8) between 0 and 1000 ka (1 Ma)? Show your
work.
Depending on what the students count as full cycles this could vary.
11 peaks in 1000 kyr = 1000 kyr/11 = 91 kyr = 91,000 yr periodicity
13
What is the periodicity of the cycles (Figure 8.8) between 1000 and 2600 ka (1–2.6 Ma)?
Show your work.
Depending on what the students count as full cycles this could vary.
There are ~36 full cycles between 1000 and 2600 ka. Therefore, 1600 kyr/36 = 44.4 kyr =
44,400 year periodicity
Record 5: Vostok, Antarctica (Figure 8.9)
FIGURE 8.9. (a) Carbon dioxide (CO2) and (c) methane (CH4) concentrations measured in air bubbles trapped in the
Holocene to Pleistocene-age Vostok ice core, Antarctica. Ancient atmospheric air temperature (b) is calculated from the
oxygen isotope data measured from the ice. Ages are based on an ice-flow model and an ice accumulation model. From
Petit et al., 1999.
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14
Instructor Guide
Describe any evidence of cyclicity in this record (Figure 8.9).
All three records show a similar repeated pattern of change across this depth (age) interval. For
example the CO2 concentrations cycle from ~280 to ~180 and back to ~280 pmmv about every
100,000 years.
15
What are the likely periodicities of the cycles represented in this ice core (Figure 8.9)? Show
your work.
There are several different periodicities in this record, but they are not all easy to distinguish by
eye (spectral analysis would be required, see instructor notes on question 30). The easiest to
distinguish is based on the large amplitude peaks which occur at ~10 kyr, 120 kyr, 245 kyr,
335 kyr, and 420 kyr. This gives an average cycle length of 102.5 kyr = 102,500 yr periodicity.
Conforming this is the following calculation:
420 kyr – 10 kyr = 410 kyr
410 kyr/ 4 cycles = 102.5 kyr = 102,500 yr periodicity
16
What additional information would you like to know to reduce the uncertainties in your periodicity estimate above? In other words, how could you test this hypothesis of periodicity?
Assumptions must have been made in the ice-flow and ice accumulation models and these could
be sources of error. Also what counts as a peak and what doesn’t adds uncertainty (i.e., visually
smoothing data). Ideally, I would like additional age control data - a high a resolution record as
possible, and probably use spectral analysis to calculate periodicity (rather than doing it by eye).
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Record 6: Xifeng and Luochuan, central China (Figure 8.10)
FIGURE 8.10. Magnetic susceptibility of loess (wind blown dust) outcrops and interbedded soils at two locations
(Xifeng and Luochuan) in central China. The stratigraphic column on the left shows different loess (L1, L2...) and soil
(S1, S2...) units. The time scale was developed based on a model that assumes a constant deposition rate of
ferromagnetic minerals. This model was also compared with the established marine oxygen isotope time scale (but was
not astronomically tuned). Two thermoluminescence dates were used to constrain the ages of the upper units. Note ka
= thousand years ago. From Kukla et al., 1988.
17
Is the magnetic susceptibility higher in the loess or in the soils?
Higher in the soils. This is because the concentration of magnetic minerals is greater in the soils
than in the loess. The loess is wind-blown dust deposited during glacials and has a different
source than the soils that form during wetter times.
18
Describe any evidence for cyclicity in this record (Figure 8.10).
The magnetic susceptibility records show a repeated pattern of high-low-high concentrations, with
full cycles occurring about every 100,000 yrs.
19
What is the likely periodicity of the cyclicity represented in this sedimentary sequence (Figure 8.10)? Show your work.
Answers may vary depending on what students want to count as full cycles.
There are ~6 full cycles in 700 kyr. Therefore 700kyr/6 = 116.7 kyr = 116,700 yr periodicity.
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20
What additional information would you like to know to reduce the uncertainties in your periodicity estimate above? In other words, how could you test this hypothesis of periodicity?
There may be uncertainties in the age model. In addition, there is uncertainty in deciding what
counts as a full cycle and what doesn’t (i.e., visually smoothing data). ). Ideally, I would like additional age control data - a high a resolution record as possible, and probably use spectral
analysis to calculate periodicity (rather than doing it by eye).
Record 7: North Atlantic Ocean (Figure 8.11)
FIGURE 8.11. Abundance of freshwater African diatom Melosira in sediment core V30-40 from the North Atlantic (b),
plotted alongside the oxygen isotope record (a) derived from a planktic foraminifera species Globigerinoides sacculifer in
the same core. Ages were determined based on correlation of this oxygen isotope record with the established marine
oxygen isotope (SPECMAP) time scale. Marine oxygen isotope stages (1-8) are shown to the left. From Pokras and Mix,
1987.
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Instructor Guide
Describe evidence of cyclicity in the diatom record (Figure 8.11b).
While the amplitudes of the diatom abundance data is not constant throughout this record, there
appears to be a regular spacing through time of high-low-high abundances.
22
Based on the diatom abundances (Figure 8.11b), what is the likely periodicity of the cyclicity represented in this core? Show your work.
There are 9 full cycles between ~75 and 250 kyr. Therefore (250kyr-75kyr)/9 = 19.44 kyr =
19,440 year periodicity.
23
What additional information would you like to know to reduce the uncertainties in your periodicity estimate above? In other words, how could you test this hypothesis of periodicity?
There may be uncertainties in the age model. In addition, there is uncertainty in deciding what
counts as a peak and what doesn’t (i.e., visually smoothing data). ). Ideally, I would like additional age control data - a high a resolution record as possible, and probably use spectral analysis to calculate periodicity (rather than doing it by eye).
Synthesis: Refer to Table 8.1 and the figures for each of the seven records.
24
Are cycles restricted to a certain type of archive, location, proxy, or geologic epoch?
No the cycles appear to be in different kinds of archives and proxies, are global, and occur in
different geologic epochs. Therefore cycles are pervasive in the geologic record.
Several examples are from the Pleistocene. Through lecture or discussion the instructor may
want to introduce the concept of glacial-interglacial cycles.
In addition all of these examples are from the Cenozoic Era. This can be a point of discussion
since it is generally difficult to obtain high resolution proxy records from older sedimentary sequences (usually lithified and/or diagenetically altered, or are incomplete sequences, or lack
sufficient age control).
25
In particular, compare the stacked deep-sea oxygen isotope record (Record 4) with the
Vostok ice core record (Record 5) for the interval 0–400 ka. What similarities do you see?
A distinct saw-toothed pattern is observed in marine oxygen isotopes, ice core temperature
proxies (which are based on oxygen isotope records in the ice) and atmospheric gases. In Part
8.3 students explore this pattern more and relate it to glacial-interglacial cycles.
26
What periodicities are “common”, in other words, occur in two or more of the seven records
(Table 8.1)?
If we round out the numbers we see the following common periodicities: ~20 kyr, 41 kyr, and 100
kyr.
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Instructor Guide
What factors introduce uncertainty in the periodicity calculations?
Methods of data collection, data reduction, eye balling the patterns, age models all introduce
uncertainty.
28
How much uncertainty do you think is acceptable? Explain.
This is an important discussion point and there will likely be a variety of opinions. Some may
feel that any potential for error means that the data lose its value. Others may conclude that
some uncertainty is unavoidable, that it should be kept at a minimum but that the data is still
useful for drawing logical, scientific conclusions. This could be an opportunity to lecture on the
topic of uncertainty in science and the social and political policy consequences of it. See the
section on Supplemental Materials for resource suggestions on the topic of scientific uncertainty. Pollack (2005, p.2-3) makes some important points about uncertainty that could contribute to a lecture or discussion on this topic:
•
“Uncertainty is always with us and can never be fully eliminated for our lives, either
individually or collectively as a society. Our understanding of the past and our anticipation of the future will always be obscured by uncertainty.”
•
“Because uncertainty never disappears, decisions about the future, big and small,
must always be made in the absence of certainty. Waiting until uncertainty is eliminated
before making decisions is an implicit endorsement of the status quo, and often an excuse for maintaining it.”
•
“Predicting the long-term future is a perilous business, and seldom do the predictions
fall very close to reality. As the future unfolds ‘mid-course corrections’ can be made that
take into account new information and new developments.”
•
“Uncertainty, far from being a barrier to progress, is actually a strong stimulus for,
and an important ingredient of, creativity.”
29
Speculate on what might have caused the cyclicity observed in this diverse collection of paleoclimate archives. List your ideas:
Students may come up with just about anything here, depending on their background. It is
unlikely that orbital forcing will be top on their list, unless they are already familiar with this
topic (it is the topic of Part 8.2). Some possible (and wrong) student answers might be:
•
changes in the Sun’s strength or Sun spot activity
•
volcanic eruptions
•
human-related greenhouse gas emissions
Encourage students to provide a rationale for their ideas. This way they practice making a hypothesis (even if it is proven wrong through discussion or future exercises).
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30
The records for which you estimated periodicities were fairly straightforward. Speculate
about how the periodicities of a more complex record, such as one of the wiggle plots in Figure
8.12, could be determined. List your ideas:
Students might say they would need to use a computer for some kind of signal processing of the
temporal patterns in the data (i.e., time series analysis). This is, in effect, what is done. Software
that performs spectral analysis (a technique for time series analysis) uses a numerical technique
for detecting and quantifying the distribution of regular (i.e., periodic) behavior in a complex signal (Ruddiman, 2001). See the supplemental materials section for resources on time series analysis.
FIGURE 8.12. Temporal variations of elements enriched in clay- and silt-sized minerals at ODP Site 1145, in the
northern South China Sea. From Sun et al., 2008.
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Part 8.2. Orbital Metronome
Annual Cyclicity
1 Are the Earth’s seasons a type of cyclic climate change? Why or why not?
The aim is to have students recognize that seasons are cyclic – a regular short-term (human
time scale) climate cycle that they can easily observe and relate to.
2 Why does the Earth have seasons? Explain as completely as possible and include a sketch.
The aim is to get students to draw on their prior knowledge to relate seasons to Earth’s changing
geometry in space relative to the Sun. This will also get at student misconceptions. The instructor may need to ask additional prompting questions. For example, if a student says “seasons exist because the Earth is tilted”, that is not enough. How is the Earth’s tilt oriented with respect to
the Sun throughout the year? Through discussion or lecture students should ultimately conclude
that “the main cause of seasons (as well as the solstices, and the changes in the length of day
and angle of incoming solar radiation) is the changing position of the tilted Earth with respect to
the Sun. During each yearly revolution around the Sun, Earth maintains a constant angle of tilt
(23.5 deg) and a constant direction of tilt in space. When a hemisphere (N or S) is tilted directly
towards the Sun it receives the more direct radiation of summer. When it tilts directly away from
the Sun, it receives the less direct radiation of winter. But at both times (and all times of the
year) it keeps the same 23.5 deg tilt.” (from Ruddiman, p. 175, Earth’s Climate 2001).
Long-Term Changes in Earth’s Geometry in Space Relative to the Sun
It may be surprising to learn that the shape of Earth’s orbit, the angle of Earth’s tilt, and the direction of Earth’s axis (with respect to fixed stars) is not constant over long time scales. The
variations of Earth’s geometry in space are known from contributions in the scientific fields of astrophysics and astronomy. These changes in the Earth’s orbit around the Sun (Figure 8.1) occur
in a cyclic or rhythmic way and therefore have particular periodicities. The three major orbital
cycles are eccentricity, obliquity, and precession. These cyclic changes in Earth’s orbital geometry largely result from gravitational pull from large planets in our solar system, especially
Jupiter, and from the Sun and moon. Each orbital cycle is briefly discussed below. See Ruddiman
(2001) for a more thorough description of orbital cycles.
Eccentricity describes the degree of deviation from a perfect circle (Figure 8.13 left); the
greater the eccentricity, the greater the elliptical deviation from a circle. A perfect circle has an
eccentricity of 0 and a flattened circle (i.e., a straight line) has an eccentricity of 1. Earth’s orbit
around the Sun has an eccentricity that ranges from 0.005 to 0.0607 with a mean of 0.028. The
eccentricity today is 0.0167. The eccentricity of Earth’s orbit varies at a range of periodicities (95
kyr to 136 kyr) with an average of approximately 100 kyr (100,000 years). There is also a long
eccentricity cycle with a periodicity of approximately 413 kyr and an even longer cycle with a period of 2.1 myr.
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3 (a) How would the Earth–Sun distance change in a highly eccentric orbit (Figure 8.13 left),
compared to a more circular orbit (Figure 8.13 right)?
Variations in eccentricity change the Earth-Sun distance. Greater differences in distance in a
highly eccentric orbit, as the Earth revolves around the sun.
(b) How would this affect the intensity of solar radiation striking the Earth’s atmosphere?
As the distance between the Earth and the Sun increases, the intensity of solar radiation reaching Earth decreases.
4 The Earth completes one revolution around the Sun each year regardless of the shape of the orbital path; however changing the shape of the orbital path (i.e., changes in eccentricity) will
have some affect on seasonality. Which orbital configuration would result in the greatest seasonal contrast (i.e., summer vs. winter temperatures): a highly eccentric orbit or a more circular orbit? Why?
The greater the eccentricity the greater the seasonal contrast because the distance from the
Sun (and therefore the insolation) will vary more throughout the year than it would when the
Earth’s orbit is more circular. This is NOT the primary control on seasonality, but a secondary influence on the intensity (and length) of the seasons. See instructor notes for Question 2 on the
cause of Earth’s seasons.
FIGURE 8.13. (left) Zero eccentricity and (right) 0.5 eccentricity, which greatly exaggerates Earth’s actual maximum
eccentricity. From http://en.wikipedia.org/wiki/Milankovitch_cycles
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Obliquity describes the Earth’s axial tilt with respect to the plane of the Earth’s orbit around
the Sun. Today this tilt is 23.5° and is estimated to vary from 22.1° to 24.5° through time (Figure 8.14). The periodicity of this variation is approximately 41 kyr.
5 Predict how a smaller tilt angle would affect polar climate in the summer and in the winter.
Less tilt would mean warmer winters and cooler summers (consider an extreme – if there were no
tilt there would be no seasonal contrast). However, more tilt would result in greater seasonal contrast.
Cooler summers in the high latitudes created by less tilt are more favorable for triggering an ice
age because the previous winter’s snow many not melt, thereby allowing snow to build-up and increasing the Earth’s albedo (reflectivity; a positive feedback).
6 Would high latitudes or low latitudes be more affected by changes in obliquity? Why?
High latitudes - the poles. While the poles are always cooler than the equator, slight differences in
solar radiation due to obliquity variations have the potential to cause ice to either accumulate or
melt.
FIGURE 8.14. Schematic diagram of different tilt angles. From http://en.wikipedia.org/wiki/Milankovitch_cycles
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Precession of the equinoxes has a cyclicity of 19 kyr to 26 kyr. This cycle exists primarily
because the spinning Earth wobbles like a toy top, which affects the direction of the Earth’s rotational axis (Figure 8.15), and with it, the position of solstices and equinoxes around the orbital
plane and the time of year that the Earth is closest to the Sun (owing to our slightly elliptical orbit around the Sun). Therefore the distance from the Earth to the Sun has varied with time for
each of the seasons. Today, we are closest to the Sun (perihelion) on January 3 (Northern
Hemisphere winter), and farthest from the Sun (aphelion) on July 4 (Northern Hemisphere
summer). About 11,000 years ago, the Northern Hemisphere was at its closest distance to the
Sun during the summer months.
7 How would the intensity of solar radiation striking the Northern Hemisphere in January been
different 11,000 years ago compared to today?
The Northern Hemisphere would have been farther from the Sun in January 11,000 years ago,
so the intensity would be less, and the Northern Hemisphere winter would have been cooler
11,000 years ago.
8 How would the intensity of solar radiation striking the Northern Hemisphere in July been different 11,000 years ago compared with today?
The Northern Hemisphere would have been closer to the Sun in July 11,000 years ago, so the intensity would be greater, and the Northern Hemisphere summer would have been warmer 11,000
years ago.
9 Based on your answers to questions 7 and 8, compare the seasonal contrast (i.e., summer vs.
winter temperatures) of 11,000 years ago to the seasonal contrast of today.
11,000 yrs ago the amount of solar radiation striking the Northern Hemisphere would have been
greater during the summer and lesser during the winter than it is today. Therefore the seasonal
contrast (summer vs winter temperatures) would have been greater 11,000 yrs ago than they
are today.
FIGURE 8.15. Schematic diagram showing the changing direction of Earth’s
spin axis. From http://en.wikipedia.org/wiki/Milankovitch_cycles
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Orbital Control of Earth’s Climate Cycles
The natural variations in the Earth’s orbit influence the amount of incoming solar radiation (insolation) received and therefore affect Earth’s climate in a cyclic way. Such orbitally driven climate cycles are called Milankovitch cycles, after the Serbian scientist who first made this connection between variations in the Earth’s orbit and changes in the Earth’s climate in the early
20th century.
10
Return to Table 8.1. In the last column labeled orbital cycle write down which orbital
variation (eccentricity, obliquity, or precession) has a periodicity that best matches the periodicity in that climate record. Note that some climate records exhibit more than one periodicity, so
you should list each corresponding orbital variation.
See answers in last column of Table 8.1.
11
It may be relatively easy to see how changes in insolation could directly cause changes in
temperature and indirectly cause changes ice volume (expanding ice during cold times and
melting ice during warm times), but what about some of the other proxy records of cyclic climate change? Speculate about how cyclic orbitally driven changes in insolation might have an
indirect effect on vegetation (Record 2), lake levels (Record 3), and greenhouse gas levels (Record 5). This is not an easy question (scientists are working on this question themselves), but
have a go at it!
Changes in pollen type could be explained by changes in the temperature or precipitation needs
of certain plants. However depending on student background the changes in the other proxies
could be a very challenging to explain, but worth considering. There are many internal Earth
system feedbacks (e.g., albedo, sea level, productivity) that are affected by changes in insolation-controlled temperature. There is considerable active research in identifying and understanding what the climate system feedbacks are and how they work.
Some feedbacks must include the carbon cycle, such that carbon is moved to and from the atmosphere (CO2 and CH4) and into other carbon reservoirs and in other forms (e.g., organic carbon in vegetation, dissolved carbon in the ocean, carbon in sediments and sedimentary rocks).
Some ways that insolation-controlled temperature changes may influence this carbon cycle as
the climate transitions from warm to cold (i.e., during the transition from an interglacial to a
glacial period) include the following (Ruddiman, 2001):
•
A colder ocean can hold more gas (e.g., CO2),
•
More biological productivity may occur in surface ocean waters (drawing down CO2) if
the ocean is fertilized by “dust” (implies greater wind strength during cold periods),
•
Less methane (CH4) is produced in wetlands if the climate is drier (because of a
weaker monsoon).
The specific hypotheses for the variability in the records included in Parts 8.1 and 8.2 of this exercise can be found in the primary literature from which the datasets were taken. Full reference
information can be found in the reference list at the end of this instructor guide.
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Part 8.3. A Break in the Pattern
Cyclic changes are part of the Earth’s climate history. In the Pleistocene, climate cycles produced
relatively cooler glacial intervals and relatively warmer interglacial intervals. As shown in Part
8.1, changes in temperature, ice volume, precipitation, and greenhouse gases all followed a
similar pacing. How do modern climate changes compare with this pattern? To put this question
into context, examine Figure 8.16 and answer the questions that follow.
I
I
I
G
G
I
G
I
G
FIGURE 8.16. Variations in the concentration of carbon dioxide (CO2) in the atmosphere during the last 400
thousand years. Data sources include: (blue) Vostok ice core, Antarctica (Fischer et al., 1999); (green) EPICA ice
core, Antarctica (Monnin et al., 2004); (red) Law Dome ice core, Antarctica (Etheridge et al., 1998); (cyan) Siple Dome
ice core, Antarctica (Neftel et al., 1994); (black) Mauna Loa Observatory, Hawaii (Keeling and Whorf, 2004).
Throughout most of the record, the largest changes can be related to glacial–interglacial cycles. Although the glacial
cycles are most directly caused by changes in the Earth’s orbit (i.e., Milankovitch cycles), these changes also
influence the carbon cycle, which in turn feeds back into the glacial system. This figure was originally prepared by
Robert A. Rohde from publicly available data and is incorporated into the Global Warming Art project
(http://en.wikipedia.org/wiki/File:Carbon_Dioxide_400kyr.png).
1 Glacials are times of extensive ice and relatively cold temperatures. The last glacial maximum occurred approximately 20,000 yrs ago. Interglacials are times of minimal ice extent
and relatively warm temperatures. Use your understanding of the relationship between CO2 and
temperature to label each of the glacial maxima with a “G” and each of the interglacials with an
“I” on Figure 8.16.
See labels on Figure 8.16. The glacial maxima occur when CO2 levels are at their minima (at
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~20 ka, 130 ka, 270, and 340 ka). The interglacials occur when CO2 levels are at their maxima
(0-10 ka, 120 ka, 250 ka, 320 ka, and 420 ka).
2 What was the typical atmospheric CO2 value during glacial maxima of the last 400,000 years?
~180 ppm
3 What was the typical atmospheric CO2 value during the interglacials (glacial minima) of the last
400,000 years?
~280 ppm
4 What was the atmospheric CO2 value in the year 2000? 380 ppm
5 Are the transitions from glacials to interglacials typically rapid or gradual? What about the transitions from interglacials to glacials?
glacial to interglacial: rapid deglaciation
interglacial to glacial: gradual and irregular ice build-up (saw-toothed pattern)
6 When did a break in the glacial–interglacial pattern occur?
Based on the inset graph the break occurs at ~1800 AD.
7 What scientific questions and/or hypotheses about climate change does this data raise? Make a
list your questions and/or hypotheses:
This should raise questions on the human influence of climate change – why the warming started,
how confident are we that humans play a role in the climate change, and how much of a role humans play.
Encourage students to provide a rationale for their idea. This way they practice making a hypothesis (even if it is proven wrong through discussion or future exercises).
III. Summative Assessment
There are several ways the instructor can assess student learning after completion of this exercise. Additional datasets from the primary literature that contain visually identifiable cycles
could be used to determine if students can transfer their knowledge and skills to a new dataset.
In addition students should be able to answer the following questions after completing this exercise:
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1. What reason might there be for including more than one type of age control data (e.g., paleomagnetic stratigraphy, dinocyst biostratigraphy) for constructing a plot of a climate proxy vs.
time?
a. Multiple lines of evidence reduce the uncertainty in the interpretation
b. All were used to see which one created the best fit line
c. The scientists couldn’t agree which data set they should use
d. All of the above
2. The Precession of the Equinoxes
a. Result from the wobble of Earth’s spin axis
b. Result from the rotation (shifting) of the actual orbital plane of the Earth
c. Result in a shifting of the position of the Earth along its orbit such that ~5000 years
from now the position of Earth at the Spring Equinox will be in the current position of
the Earth during the Winter Solstice.
d. All of the above
e. A and C only
3. Which
a.
b.
c.
d.
of the following causes variations in insolation?
Solar flares
Stages of glaciation
Changes in Earth’s orbital cycles
Changes in Earth’s albedo
4. Is the world today in an interglacial or a glacial stage?
interglacial
5. Transitions from glacials to interglacials are:
a. abrupt
b. gradual
c. saw-toothed
d. A and C only
e. B and C only
6. What is the dominent periodicity of the glacial-interglacial stages in the last million years?
a. 100 yrs
b. 10,000 yrs
c. 41,000 yrs
d. 100,000 yrs
7. Which of the following climate proxies have records that show a pattern that matches orbitial
cyclicity?
a. Ice core CO2
b. Ice core CH4
c. Pollen and spores (vegetation data) in lakes
d. Marine oxygen isotopes
e. All of the above
8. Short answer: Describe the variety of ways that climate cycles are recorded in sedimentary records.
9. Short answer: Explain why seasons exist.
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10.Short answer: Differentiate among eccentricity, precession, and obliquity. How do these influence climate?
11.Short answer: What orbital configuration(s) promote ice growth in the high latitudes? Why?
12.Short answer: When did a distinct break in the glacial-interglacial cyclic occur? Propose a hypothesis to explain this change in climate.
IV. Supplemental Materials
•
•
•
•
•
•
•
See the 198-1208A-8H XRF and magnetic susceptibility data in the excel files in the
online supplemental materials. Use these data to make your own graphs of the variations in elemental abundances and magnetic susceptibility in 198-1208A-8H to compare with Record 1 in this exercise. These data were collected at the Gulf Coast Repository: http://iodp.tamu.edu/curation/gcr/ and http://odases.tamu.edu/researchfacilities/xrf-request.
A Private Universe (Harvard-Smithsonian Center for Astrophysics, 1987, ISBN: 1-57680-4046) is an excellent 20-minute video that explores how we learn by using interviews with high
school students and Ivy League graduates as they attempt to explain the seasons.
Pollack (2005) provides a good general audience overview of uncertainty in science and addresses how scientists accommodate and make use of uncertainty, and how they reach conclusions in the face of uncertainty. The book specifically addresses uncertainty in climate science,
among many other examples.
For a short, informative, and entertaining video on orbital variations see Richard Alley’s National Geographic mini-video: http://video.nationalgeographic.com/video/national-geographicchannel/shows/naked-science/ngc-ice-age-cycles/
The following papers provide reviews and summaries of orbital variations. In addition, Pälike
(2004) also provides a summary of the analysis of the orbitally-driven cycles in complex geologic records. Pälike (2004) is written for an advanced audience. Lee (2009) is written for a
more general audience.
• Lee, Jeff (Lead Author); Stephen J. Reid (Topic Editor). 2009. "Milankovitch cycles." In: Encyclopedia of Earth. Eds. Cutler J. Cleveland (Washington, D.C.: Environmental Information
Coalition, National Council for Science and the Environment). [Published in the Encyclopedia
of Earth April 24, 2009; Retrieved May 29, 2009].
<http://www.eoearth.org/article/Milankovitch_cycles>
• Pälike, H., (2004). Orbital variation (including Milankovitch cycles). In: Encyclopedia of Geology (Eds. Selley, R.C. et al.), vol. 1, p.410-421, Elsevier, Amsterdam.
More information on time series analysis and spectral analysis at an introductory level can be
found in Ruddiman (2001) and at a more advanced level in Chapter 7 and Appendix C of:
Crowley, T.J., and North, G.R. (1991). Paleoclimatology, Oxford Monographs on Geology and
Geophysics #18, Oxford University Press, New York, 349 p.
A very entertaining and thought provoking online video uses an effective heuristic argument
for why society should take action on global warming. The original video (with the odd title of
“the most terrifying video you will ever see”) has been updated (title: “how it all ends”) to include counter arguments to criticisms. The videos are each <10 min in length. Both can be
found at: http://www.youtube.com/watch?v=zORv8wwiadQ. Greg Craven has also taken his
video presentations and written a general audience book titled What's the Worst That Could
Happen?: A Rational Response to the Climate Change Debate, (2009), Perigee Trade, 264 p.
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•
•
Instructor Guide
A video clip from National Geographic shows climate scientists Richard Alley explaining orbital
cycles eccentricity, obliquity, and precession. Video clip is 4.5 min in length and can be found
at: http://video.aol.com/video-detail/ice-age-cycles/3554270053 or at:
http://fr.truveo.com/Ice-Age-Cycles/id/3554270053
For information on orbital cycles, abrupt climate change, climate systems and feedbacks written for a general audience read Two-Mile Time Machine: Ice Cores, Aprupt Climate Change,
and Our Future, by Richard Alley (2002), Princeton University Press, 240 p.
V. References
Abels, H.A., et al., 2009, Shallow lacustrine carbonate microfacies document orbitally paced lakelevel history in the Miocene Teruel Basin (North-East Spain). Sedimentology, 56, 399–419, doi:
10.1111/j.1365-3091.2008.00976.x
Etheridge, D.M., Steele, L.P., Langenfelds, R.L., Francey, R.J., Barnola, J.M., and Morgan, V.I.,
1998, Historical CO2 records from the Law Dome DE08, DE08-2, and DSS ice cores, in Trends: A
Compendium of Data on Global Change, Carbon Dioxide Information Analysis Center, Oak Ridge
National
Laboratory,
U.S.
Department
of
Energy,
Oak
Ridge,
Tenn.,
U.S.A,
http://cdiac.ornl.gov/trends/co2/lawdome.html
Fischer, H., Wahlen, M., Smith, J., Mastroianni, D., and Deck, B., 1999, Ice core records of Atmospheric CO2 around the last three glacial terminations: Science, v. 283, p. 1712–1714.
Keeling, C.D., and Whorf, T.P., 2004, Atmospheric CO2 records from sites in the SIO air sampling
network, in Trends: A Compendium of Data on Global Change, Carbon Dioxide Information
Analysis Center, Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tenn.,
U.S.A., http://cdiac.ornl.gov/trends/co2/sio-keel-flask/sio-keel-flaskmlo_c.html
Kukla, G., et al., 1988, Pleistocene climates in china dated by magnetic susceptibility. Geology,
16, 811–14.
Lisiecki, L.E. and Raymo, M.E., 2005, A Pliocene-Pleistocene stack of 57 globally distributed benthic δ18O records. Paleoceanography, 20, PA1003, doi:10.1029/2004PA001071.
Monnin, E., Steig, E.J., Siegenthaler, U., Kawamura, K., Schwander, J., Stauffer, B., Stocker, T.F.,
Morse, D.L., Barnola, J.M., Bellier, B., Raynaud, D., and Fischer, H., 2004, Evidence for substantial accumulation rate variability in Antarctica during the Holocene, through synchronization of
CO2 in the Taylor Dome, Dome C and DML ice cores: Earth and Planetary Science Letters, v.
224, p. 45–54. doi:10.1016/j.epsl.2004.05.007
Neftel, A., Friedli, H., Moor, E., Lötscher, H., Oeschger, H., Siegenthaler, U., and Stauffer, B.,
1994. Historical CO2 record from the Siple Station ice core, in Trends: A Compendium of Data on
Global Change, Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, U.S.
Department of Energy, Oak Ridge, Tenn., U.S.A., http://cdiac.ornl.gov/trends/co2/siple.html
Petit, J.R., et al., 1999, Climate and atmospheric history of the past 420,000 years from the
Vostok Ice core, Antarctica. Nature, 399, 429–36.
Pokras, E.M. and Mix, A.C., 1987, Earth’s precession cycle and Quaternary climate change in
tropical Africa. Nature, 326, 486–7.
Pollack, H.N., 2005, Uncertain Science…Uncertain World, Cambridge University Press, 243 p. DOI:
10.2277/0521619106.
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Instructor Guide
Ruddiman, W.F., 2001, Earth’s Climate Past and Future, Freeman and Co., New York, 465 p.
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