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3
Potentially Disruptive Climate Events
E
arth’s climate provides the environment in which humanity has
evolved and in which human societies have expanded and thrived.
It also periodically generates events that disrupt those societies—in
some historic cases, apparently causing the failure of entire civilizations, al-
though in many of those cases considerable dispute exists about the precise
cause (Butzer, 2012). Climate events are disruptive when they harm people
and the environmental, social, and economic assets that people depend on
and when societies are unable to cope, respond, and recover effectively. Dis-
ruption thus depends on the conjunction of events with human vulnerabil-
ity. However, major climate events are not always seriously disruptive. Past
civilizations have sometimes faced very serious stress from environmental
change without collapsing (Butzer, 2012; Butzer and Endfield, 2012).
When climate is changing, potentially disruptive climate events occur
at different rates, with different intensities, and perhaps in different places
from what people would expect from past experience. Those responsible for
anticipating the risks, including the intelligence and security communities,
turn to climate science in the hope of getting useful estimates of changing
overall risks of future events of interest and forecasts of when and where
such events will occur on time-scales longer than those of normal weather
forecasts.
This chapter focuses on climate events, a key element in the conceptual
framework presented in Chapter 2 for considering the connections between
climate change and outcomes of security concern. It briefly summarizes the
scientific bases for providing risk estimates and forecasts for potentially
disruptive climate events on time-scales up to a decade or so. We consider
53
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54 CLIMATE AND SOCIAL STRESS
the potential for major, abrupt climate change as well as for single climate
events and clusters and sequences of such events that could be sufficiently
disruptive as to raise concerns about U.S. national security. The next two
chapters examine how such events might disrupt social, political, and eco-
nomic systems sufficiently to raise national security concerns.
THE SCIENCE OF CLIMATE PROJECTION
The predictability of weather and climate varies with the time-scale;
moreover, predictive efforts face different challenges at different time-scales.
Weather forecasting focuses on predictions at time-scales up to about two
weeks and is based on the premise that the atmosphere behaves according
to a set of deterministic equations such that if the initial state of the atmo-
sphere is known, its evolution can always be determined. Changes or errors
in the initial state limit predictability on longer time horizons; two weeks is
normally considered the limit of atmospheric predictability.
Climate models are based on the same basic set of equations that
predict shorter-term weather variations, but they also include terms that
represent a coupling of the atmosphere with the ocean and land surfaces,
which inherently have memories of climate longer than the atmosphere
does. Climate models have a coarser resolution than weather prediction
models, which limits the level of accuracy in their simulations of atmo-
spheric and ocean dynamics and their interactions with climate. Instead of
forecasting actual day-to-day changes in weather over a period of a week or
more, climate models concentrate on simulating the processes that govern
the interannual and longer-term climate variability of the coupled ocean–
atmosphere–land system.
To date, climate prediction has focused mostly on two time-scales:
seasonal and centennial. Seasonal predictions, like weather forecasts, are
dependent on initial values, and thus their ability to make predictions
relies on information provided by initial ocean conditions (Latif et al.,
2010), particularly sea surface temperatures, which strongly influence at-
mospheric circulation. The greatest contributor to predictive skill on a
seasonal time-scale has been an understanding of the dynamics of the El
Niño–Southern Oscillation (ENSO), which influences the yearly variability
of rainfall and temperatures over broad sectors of the globe and even global
mean temperatures.
On centennial time-scales, the evolution of climate remains chaotic and
irregular and depends on external changes in radiative forcing (the influence
of a factor, such as solar radiation or anthropogenic changes in atmospheric
composition and land cover, on the balance of incoming and outgoing
energy in the Earth-atmosphere system). Thus on such time-scales, climate
projections are sensitive to assumptions about how future radiative forcing
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POTENTIALLY DISRUPTIVE CLIMATE EVENTS 55
will change as a function of energy consumption, land cover, and other driv-
ers of change in Earth’s radiation balance. On such time-scales, the system
loses its memory of the initial conditions, and the future trajectory of the
coupled climate system is strongly determined by the external forcing.
Recently observations and models have suggested that it might be
possible to make decadal climate predictions by using knowledge about
regularities in the natural climate system on that time-scale, especially
conditions involving the state of the ocean. However, climate projections
based on emission scenarios indicate that decadal-scale variability is also
influenced by the accumulated impacts of anthropogenic radiative forcing.
Decadal-scale predictions therefore require information both about radia-
tive forcing (e.g., levels of greenhouse gases and aerosols) and about the
current observed state of the atmosphere, oceans, cryosphere, and land
surface (Hurrell et al., 2010).
Understanding and making predictions of decadal variability is still very
much in its infancy, and evaluating these predictions is a major challenge.
It is straightforward to verify daily weather forecasts through statistical
and historical data, but verification is more difficult for decadal forecasts.
Observational records are simply not consistent enough or long enough to
quantify prediction skill. Even the basic characteristics and mechanisms
that describe climate on a decadal scale are poorly documented and not well
understood. Testing models against observed climate variability provides
some means of verification and thus can offer some confidence in using
these models to simulate future climate, but even those efforts are hindered
by a lack of subsurface ocean observations and satellite data.
As part of the work for the next Intergovernmental Panel on Climate
Change (IPCC) report, modeling centers have coordinated decadal hindcast
and prediction experiments covering the period from 1960 to 2035 in what
is known as the Coupled Model Intercomparison Project Phase 5 (CMIP5).
Part of the work involves an atmosphere–ocean general circulation model
with a resolution of approximately 50 kilometers (31 miles) being run to
make decadal predictions out to 2035. Lower-resolution versions of the
same model will be run with coupled carbon cycles and biogeochemical
processes to help quantify the magnitude of important feedbacks that will
determine the degree of climate change in the second half of the 21st cen-
tury (Hurrell et al., 2009).
A better knowledge of the initial conditions needed to initialize the
models properly should increase the skill of predictions of the climate
system on varying time-scales. An increased understanding of the physical
mechanisms that govern climate variability is also critical. In sum, although
physical climate science is able to project climate trends based on scenarios
for increases in greenhouse gases (GHGs) and to estimate changes in the
likelihoods of occurrence for some kinds of climate events in the coming
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56 CLIMATE AND SOCIAL STRESS
decade, the ability to anticipate specific climate events on that time-scale is
still in its infancy. Improving our understanding of the ENSO cycle and its
broader climatic implications currently offers the best route for extending
our ability to make skillful forecasts of the risks of climate events from the
current limit of a few weeks into the future to a few months or even one or
two years. It will also be important to improve understanding of how the
GHG-forced changes in climate might change the characteristics of climate
variability, such as ENSO.
Despite their inability to predict specific events for the coming decade,
climate models can still provide useful information about the range of plau-
sible climate outcomes that could result from the combination of external
forcing and variability of the climate system due to internal processes over
the next decade. For example, several recent studies have evaluated the
distribution of 10-year trends within model simulations that were forced
with increasing concentrations of greenhouse gases (Easterling and Wehner,
2009; Santer et al., 2011). The purpose of these studies was to address
claims that the lack of a significant positive global temperature trend over
the 10-year period following 1998 refutes projections from climate models.
And, indeed, the models did show that even under scenarios with relatively
high greenhouse gas emissions, decades with a zero or negative temperature
trend occur in more than 10 percent of the individual 10-year segments
within models.
Figure 3-1 displays the probability distribution functions of 10-year
trends from Easterling and Wehner (2009) for global mean temperatures,
and it extends their method to look at the probability distributions of 10-
year trends for a number of regions for the future (see Appendix C for
an explanation of the method used for the regional projections). These
functions were calculated using model simulations from the CMIP5 data-
base under a scenario for the first half of the 21st century that assumes a
“business as usual” rate of greenhouse gas increase of about 1 percent per
year (known as the RCP8.5 scenario). The functions represent differences
between projected average annual surface temperature, globally and for
various regions, for the coming decade and the average temperature at the
start of the decade, expressed in degrees Celsius. The estimates apply to
any decadal start date up to 2040. Much as Easterling and Wehner (2009)
found for global temperatures, each region has a reasonable chance of cool-
ing over a period of a decade because of natural variability that can act to
counteract the warming trend. At the same time, the upper tails of these
distributions show that the increase in average global temperature could be
as high as 1.8°F (1°C) in a single decade and the increase in average regional
temperatures could be as high as 3.6°F (2°C) or more in a single decade—
for example, about a 40 percent chance of an increase of at least 1.8°F
(1°C) and about a 10 percent chance of an increase of at least 3.6°F (2°C)
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POTENTIALLY DISRUPTIVE CLIMATE EVENTS 57
FIGURE 3-1 Distributions of probabilities for average annual surface temperature,
globally and for the regions shown, for the coming decade, relative to the average
temperature at the start of the decade, expressed in degrees Celsius. Although the
most likely 10-year trend in each region is for warming (that is, most of the area
under each curve is to the right of the zero degree line), each region has a reasonable
chance of overall cooling for the coming decade. Each region also has a reason-
able chance of warming by more than 1.8°F (1°C) and some chance of warming
more than 3.6°F (2°C) in the coming decade.
SOURCE: Committee analyses.
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58 CLIMATE AND SOCIAL STRESS
in the U.S. corn belt. Although the scenarios of strong and rapid warming
over a decade have low probability, the potential implications for society
are large enough to deserve much more consideration by climate and secu-
rity analysts. To our knowledge, similar work has not yet been published
for plausible decadal trends at regional scales or for climate variables other
than surface temperature.
Although the foregoing analysis suggests very useful predictive skill for
changing likelihoods of some kinds of events, even projections that have
relatively low predictive skill can be useful to the security community. Low
predictive skill is especially likely to be characteristic of projections of cli-
mate parameters with low signal-to-noise ratios (e.g., with high interannual
variability) and for very low-frequency events, including the most extreme
events. Such events deserve special consideration by security analysts when
and where the fundamental science suggests that they will increase in likeli-
hood and the data are not yet adequate to rule out this possibility. In such
situations, it may be wise for security analysts to consider what-if scenarios
involving increased frequencies of occurrence for such events.
ABRUPT CLIMATE CHANGE
Climate models currently used to project climate change over the 21st
century generally indicate that there will be a gradual response to increased
greenhouse gases and other climate forcing, suggesting quite a low likeli-
hood that major changes will occur within the coming decade. Neverthe-
less, the simulations do show that abrupt changes are possible in various
regions where a particular variable crosses a threshold (for example, if
precipitation lowers sufficiently to cause a transition from forest to grass-
land, or grassland to desert, or if temperature increases enough to cause a
transition from snow- or ice-covered surfaces to snow- or ice-free ones).
The observed climate record, particularly the paleoclimate record, shows
that abrupt or step changes in climate do occur, even within a time span of
a decade or less. The possibility of rapid step changes in climate is of great
concern in terms of social and political stresses because, with less time to
adjust, it is usually harder for societies to cope and respond effectively.
Abrupt climate change is generally defined as occurring when some
part of the climate system passes a threshold or tipping point resulting in a
rapid change that produces a new state lasting decades or longer (Alley et
al., 2003). In this case “rapid” refers to timelines of a few years to decades.
Abrupt climate change can occur on a regional, continental, hemispheric,
or even global basis. Even a gradual forcing of a system with naturally oc-
curring and chaotic variability can cause some part of the system to cross a
threshold, triggering an abrupt change. Therefore, it is likely that gradual or
monotonic forcings increase the probability of an abrupt change occurring.
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POTENTIALLY DISRUPTIVE CLIMATE EVENTS 59
Many cases of rapid change in climate have been observed in the instru-
mental and paleoclimatic records. The instrumental record is short—only
about 130 years in length—and as a consequence does not adequately
sample the full spectrum of climate variability. However, even with this
limited sampling some examples of rapid regional change can be found in
the observed record. For example, strong warming (greater than 4oC) oc-
curred in parts of the Arctic during the 1920s, with most of the warming
occurring in the late 1920s (Alley et al., 2003). The Dust Bowl years of
the 1930s in the central United States provide another example of a rapid
shift, in this case with the reversal also occurring in less than a decade. On
a much larger geographic scale, the climatic effects of the abrupt shift in
1976–1977, mainly in sea surface temperatures in the Pacific Ocean, have
been documented in a number of global and hemispheric analyses (Alley
et al., 2003).
The paleoclimatic record indicates that numerous rapid changes oc-
curred in the period after the last deglaciation (i.e., the past 10,000 years).
Many of these changes were larger than those recorded in the instrumental
record. Examples include abrupt shifts to large-scale drought that were
similar to, but more intense and longer lasting than, what was experienced
during the 1930s Dust Bowl years. Tree ring records of drought in the
western United States show abrupt, long-lasting mega-droughts that came
on rapidly and lasted for a decade or more, covering most of the region. It
has been argued that large-scale mega-droughts were responsible, at least
in part, for the decline and collapse of the Mayan civilization in Mexico
(Hodell et al., 1995), the Tang Dynasty in China (Yancheva et al., 2007),
and the Anasazi civilization in the southwest United States (U.S. Climate
Change Science Program and Subcommittee on Global Change Research,
2008). Such conclusions are hard to support conclusively, however. For ex-
ample, Butzer and Endfield (2012) judge the Mayan case to be controversial.
What can cause rapid climate change? Some rapid changes are initiated
by a cooling process, others by a warming process. Some rapid changes
are temporary and reversible, others cause one-way shifts that persist for
decades or longer. One recurring cause is massive releases of sulfate aero-
sols into the atmosphere, which can result in substantial regional or global
cooling. Historically the main cause of such releases has been volcanic erup-
tions. Large volcanic eruptions, such as the 1815 Tambora eruption that
led to the world-wide cooling event called the “year without a summer”
in 1816, occur on average about once every 1,000 years. Super-eruptions
occur on average about once every 10,000 years, with the last two having
been in Toba in Indonesia 74,000 years ago and Oruanui in New Zealand
26,000 years ago. It is thought that the Toba super-eruption led to a global
“volcanic winter” lasting for several years that was approximately 7.6°F
(4°C) colder than today and up to 27°F (15°C) colder in the high latitudes.
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60 CLIMATE AND SOCIAL STRESS
Some theories suggest that the Toba eruption and ensuing volcanic winter
wiped out most of our human ancestors, leaving only a small population
of perhaps a few thousand (Self, 2006).
The above examples of rapid climate change do not fully meet the
definition of abrupt climate change given by Alley et al. (2003) because
after each of these rapid changes, the climate returned to its previous
state. However, it is possible for a monotonic change in certain aspects of
the Earth system to cross a tipping point so that climate change not only
would be rapid but also would shift the system to a different baseline. For
example, as the area covered by Arctic summer sea ice decreases, exposing
more ocean surface, the result is an overall darkening and loss of reflectivity
for Earth’s surface in that region, which leads to an increase in the absorp-
tion of solar radiation; this in turn warms the ocean waters, which tends
to increase melting, creating a positive feedback loop. Thus the result of a
loss of summer sea ice could be a lasting change in the energy balance of the
planet. However, because there are feedbacks that lead ice extent to recover,
some analysts argue that a lasting change in the energy balance from this
mechanism is unlikely in the coming century (Tietsche et al., 2011).
Could significant and lasting abrupt climate change occur, either glob-
ally or regionally, in the next decade or so? The possible scenarios most fre-
quently mentioned include the loss of Arctic summer sea ice, GHG release
from melting permafrost, the melting of Greenland glaciers, the breakup
of the West Antarctic ice sheet, and a change in the strength of the Indian
summer monsoon (e.g., Lenton et al., 2008). At a smaller spatial scale, the
loss of specific mountain glaciers or glacier systems, the drying of lakes, and
shifts in biomes are likely types of abrupt changes for particular regions.
The likelihood of any of these events occurring by the mid-2020s is
difficult to estimate for a number of reasons, including the fact that global
climate models do not simulate abrupt climate shifts well, which makes it
hard to project when a change in some part of the climate system that might
induce a broader abrupt change (e.g., regional or hemispheric temperature
or precipitation) will reach a critical value. Lenton et al. (2008) provide
estimates of critical values for a number of “tipping elements,” which are
defined as features of the Earth system large enough (at least subcontinental
in scale) to have pronounced impacts on the climate system if an abrupt
change occurs in that feature. Examples would include the Greenland ice
sheet and the Amazon rain forest. Even for those tipping elements where
critical values are defined (e.g., for rapid melting of the Greenland ice sheet,
approximately a 5.4°F [3°C] increase in the local air temperature), estimat-
ing a probability that the critical value will be reached in the next couple
of decades is difficult if not impossible. Most climate scientists would
probably judge the likelihood of an abrupt change that would have large
and long-lasting destabilizing impacts on climate and human society by the
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POTENTIALLY DISRUPTIVE CLIMATE EVENTS 61
mid-2020s to be quite small. However, because of gaps in knowledge about
the mechanisms and tipping points for the processes involved, it is difficult
to assign a level of confidence to judgments about the preconditions for, or
timing of, an instability affecting, for instance, a major section of a large ice
sheet. Moreover, there may be other processes in the Earth system, not yet
identified, that have tipping points that could lead to abrupt climate change.
Because of such gaps in knowledge, the possibility of such events occurring
in the next decade or so cannot be totally discounted.
Although the likelihood of such abrupt climate change scenarios hap-
pening in the next decade or so appears to be quite small, it cannot be
estimated accurately. The consequences of some abrupt climate changes,
if they occurred, could be quite severe. For example, droughts are a recur-
ring event in the climate system, with a major drought occurring in some
part of the world at least yearly. Some drought conditions, such as those
that have continued off and on for the past decade in the western United
States, could be harbingers of a mega-drought. If that proved to be the
case in the western United States, the potential impacts on water supplies
as well on as ecosystems, both natural and managed, in that region would
be enormous. To the extent that the possible tipping elements leading to
such major changes are known, it would be important to monitor those
elements and the factors that affect them. It would also be important to
monitor changes in the social, economic, and political factors that affect
the size of the exposed populations, their susceptibility to harm, the ability
of the populations to cope, and the ability of their governments to respond.
Where potentially affected areas are important producers of key global
commodities such as food grains, it would also be important to assess the
effects of climate-induced supply reductions on global markets and vulner-
able populations.
SINGLE EXTREME EVENTS
The fundamental science of climate change suggests that continued
global warming will increase the frequency or intensity (or both) of a
great variety of events that could disrupt societies, including heat waves,
extreme precipitation events, floods, droughts, sea level rise, wildfires, and
the spread of infectious disease. Underpinning many of these extreme events
is an acceleration of the global hydrological cycle. For each 1.8°F (1°C)
increase in the global mean surface temperature, there is a corresponding
7 percent increase in atmospheric water vapor. Because warm air holds
more water vapor than cool air, this leads to more intense precipitation.
Essentially, warm air increases evaporation from the ocean and dries out
the land surface, providing more moisture to the atmosphere that will rain
out downwind. Water vapor is also a powerful naturally occurring green-
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62 CLIMATE AND SOCIAL STRESS
house gas. As such it is the source of a very strong positive feedback to the
coupled climate system that amplifies any external forcing by a factor of
approximately 1.6.
This section discusses trends in some extreme climate events over the
past half century, science-based expectations of the futures of these types of
events, and the prospects for using the science of climate change to estimate
the changing likelihood of such events and to forecast their occurrence.
Trends in Extreme Climate Events
The frequency of extreme high-temperature events driven by global
warming is increasing faster than would be the case if only the mean tem-
perature were increasing because the variance of the temperature distribu-
tion is increasing as well (see Figure 1-1). Extreme weather and climate
events have been responsible for a rapidly increasing loss of lives, well-
being, and economic assets in recent decades because of the confluence of
the events themselves with increases in the numbers of people and value
of property exposed and vulnerable to the events. It has been difficult to
determine conclusively whether damaging climate events themselves have
yet been increasing in frequency or intensity enough to be detected in trends
of damage, normalized for nonclimate factors. We discuss this issue further
in Chapter 4.
Climate Change and Extreme Climate Events in the Coming Decade
Effects of Climate Change on Extreme Events
The frequency and intensity of extreme events are particularly hard to
project because, among other things, there are by definition few of them,
which makes it hard to validate predictive models against experience (see
Appendix D for more detailed discussion of statistical issues and methods
for assessing the probabilities of occurrence of extreme events). Analyses
have, however, converged on a number of expectations for this century, as
noted in a recent National Research Council review (2010a). In this cen-
tury, it stated, “the frequency and intensity of heat waves is projected to
continue to increase, both in the United States and around the world,” and
“the frequency of cold extremes and the number of frost days will decline
in the middle and high latitudes” (p. 223). It is also projected that “the
fraction of rainfall falling in the form of heavy precipitation events will in-
crease in many regions” (p. 224). Furthermore, “[r]ecent model projections
indicate growing certainty that climate change could lead to increases in the
strength of hurricanes, but how their overall frequency of occurrence might
change is still an active area of research,” and “projections indicate that
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POTENTIALLY DISRUPTIVE CLIMATE EVENTS 63
the area affected by drought will probably increase in the decades ahead
and that the number of dry days annually will also increase” (p. 265). The
models are not highly specific about the timing of these changes, however.
A subsequent IPCC special report on extreme events (Intergovern-
mental Panel on Climate Change, 2012) summarized available evidence
on observed and projected extremes of a variety of important types of
climate events globally and at the regional level. Table 3-1 summarizes
observed trends in several of these.1 The level of confidence in an observed
trend neither implies nor excludes the possibility of changes in an extreme
at other geographic scales. The report also offers projections of trends in
these events, along with statements about the levels of confidence that the
scientific community places in the projections.
Considering the difficulty of validating projections of extreme climate
events, it would be a mistake to conclude from the lack of confidence in a
projection of change for any type of extreme event that one can prudently
act as if there will be no change. When there is good fundamental sci-
ence behind an expectation of change—for example, in the frequency of
extreme high-temperature and high-precipitation events or the likelihood
of droughts—combined with noisy data or a small number of events for
model validation, there may be sufficient reason for the intelligence com-
munity to develop and consider the security implications of scenarios in
which the extreme event parameter changes in the direction suggested by
the fundamental science.
Effects of Predictable Climate Variation on Extreme Events
Earth’s climate includes various regular cycles that may make it possible
to anticipate an increased likelihood of climate events of concern months or
longer in advance. Other than the succession of the seasons, the best under-
stood of these is the ENSO (see Box 4-1). ENSO affects weather on most of
Earth’s surface in cycles that last two to seven years. The largest and most
predictable impacts are in the tropics. The warm phase of ENSO “is usu-
ally accompanied by drought in southeastern Asia, India, Australia, south-
eastern Africa, Amazonia, and northeast Brazil, with fewer than normal
tropical cyclones around Australia and in the North Atlantic. Wetter than
normal conditions during El Niño episodes are observed along the west
1
The confidence levels used in Table 3-1 are based on three scales: evidence and agreement;
confidence; and likelihood (Mastrandrea et al., 2010). The summary terms used to describe the
available evidence were limited, medium, or robust, and the degree of agreement was described
as low, medium, or high. Levels of confidence were very low, low, medium, high, or very high.
Likelihood (probability) was described as virtually certain (99–100%), very likely (90–100%),
likely (66–100%), about as likely as not (33–66%), unlikely (0–33%), very unlikely (0–10%),
and exceptionally unlikely (0–1%).
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TABLE 3-1 Observed Changes in Extreme Weather and Climate Events Since 1950
64
Event Global Change Confidence Regional Changes Confidence
Cold days and nights Decrease Very likely Decrease at the continental scale Likely
in North America, Europe,
and Australia
Warm days and nights Increase Very likely Increase at the continental scale Likely
in North America, Europe,
and Australia
Warming trend in daily Medium
temperature extremes in Asia
Warming trend in daily Low to medium, due to
temperature extremes in insufficient evidence
Africa and South America
Length or number of heat Increase in many regions with Medium
waves sufficient data
Heavy precipitation events More regions have experienced Likely
increases than decreases,
although there are strong
regional and subregional
variations
Tropical cyclone activity Unclear Low confidence after
(intensity, frequency, accounting for past changes
duration) in observing capabilities
Drought Intense and longer droughts in Medium
southern Europe, west Africa
Extreme coastal high water Increase related to an Likely, at global scale
increase in mean sea level
SOURCE: Adapted from Tables 3-1 and 3-2 in Intergovernmental Panel on Climate Change (2012).
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POTENTIALLY DISRUPTIVE CLIMATE EVENTS 65
BOX 3-1
The El Niño–Southern Oscillation Phenomenon
The El Niño–Southern Oscillation (ENSO) phenomenon is a multi-year cycle
marked by changes in relative atmospheric pressures at sea level across the tropi-
cal Pacific Ocean and changes in the strength of the Pacific trade winds and the
temperature of the ocean’s surface in the central and eastern Pacific. This mode
of climate fluctuation has been linked globally to devastating droughts, extreme
rainfall events, and the suppression of hurricanes in the Atlantic Ocean, among
other interannual climatic changes, and therefore has a significant impact on
global society. Recent studies have also linked ENSO to the natural variability of
the carbon cycle (Jones et al., 2001). An El Niño event (the warm phase of the
cycle, as indicated by sea surface temperature) is characterized by a weakening
of the Pacific trade winds, a warming of the ocean’s surface in the central and
eastern Pacific, and smaller differences in tropical sea level pressures between
the eastern and western tropical Pacific Ocean. Opposite conditions occur in the
cold phase, or La Niña. The warm events often last 12 to 18 months and histori-
cally occur every 2 to 7 years, although recent anthropogenic climate changes
may possibly contribute to more frequent and intense El Niño events. The term
ENSO is used to describe the full range of coupled ocean–atmosphere climate
variability in the tropical Pacific Ocean.
Over the course of many decades of research, great strides have been made
in understanding, monitoring, and predicting ENSO and its effects on climate.
During an El Niño event, the warmest waters of the ocean, usually west of the
international dateline, spread eastward into the eastern tropical Pacific, a distance
one-third the circumference of the planet, and significantly affect the global atmo-
spheric circulation. Via a process known as teleconnection, ENSO is often linked
to global extreme precipitation events, either drought or flooding, in many far-flung
places. ENSO also appears to play a large role in yearly and multi-year variations
in sea level rise, while larger ENSO events can affect decadal trends in sea level
by shifting the distribution of rainfall between land and the ocean. ENSO also af-
fects marine and terrestrial ecosystems. During a warm ENSO phase the primary
productivity in the eastern tropical Pacific is severely reduced because of weaker
upwelling off the coast of Peru. The reduction in productivity affects the population
and location of marine mammals, sea birds, and commercial fishing. Year-to-year
variability in global atmospheric carbon concentrations is dominated by the ENSO
cycle (Rayner et al., 1999). During El Niño, equatorial upwelling decreases in the
eastern and central Pacific, significantly reducing the supply of carbon dioxide to
the surface (Feely et al., 2006). As a result, the global increase in atmospheric
carbon dioxide noticeably slows down during the early stages of an El Niño.
Coastal regions are particularly affected by ENSO variability.
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66 CLIMATE AND SOCIAL STRESS
coast of tropical South America, subtropical latitudes of western North
America, and southeastern America” (Intergovernmental Panel on Climate
Change, 2012:155). The cold phase, known as La Niña, generally shows
opposite anomalies. The effects of ENSO can also be felt in the other ocean
basins and on all continents (Dai et al., 1998). Recent research has shown
that different phases of ENSO are associated with different frequencies of
short-term weather events such as heavy rainfall and extreme temperatures
in the affected regions (Intergovernmental Panel on Climate Change, 2012).
These regularities in the effects of ENSO on climate events allow for
skillful short-term climate predictions on time-scales from a season to a
year by coupling atmospheric general circulation models with ocean gen-
eral circulation models initialized with observations of the state of atmo-
sphere and ocean. Forecast skill decreases away from the equator, however.
This seasonal climate prediction has now become operational at many of
the world’s major weather prediction centers. (NOAA, for example, of-
fers seasonal outlooks online at http://www.cpc.ncep.noaa.gov/products/
predictions/90day/ [accessed November 13, 2012].) Prediction on time-
scales from years to decades is still very much in the research realm, so it
is not yet possible to estimate the eventual skill that might be achieved in
forecasting at these time-scales.
The fact that ENSO drives unusual weather patterns on several conti-
nents at the same time demonstrates that extreme weather patterns in dif-
ferent regions may not be independent in a statistical sense, suggesting the
possibility that extreme climate events may cluster in time, a topic discussed
more fully in the next section.
The question of whether and how anthropogenic climate change may
be altering the ENSO cycle is being actively examined by climate scientists
(Intergovernmental Panel on Climate Change, 2012). Dai et al. (1998)
noted a shift in ENSO events in the mid-1970s toward more warm events,
which coincided with record high global temperatures and drought anoma-
lies that were greater than expected. There is some evidence linking these
changes in ENSO events to intensified droughts in some drier regions since
the 1970s, while the extent of wet areas has declined during this period.
These changes are qualitatively consistent with the observed increases in
greenhouse gases in the atmosphere, which act to enhance the hydrologi-
cal cycle. The IPCC special report on extreme events (Intergovernmental
Panel on Climate Change, 2012) describes systematic changes in ENSO
behavior that have been observed over the past 50 to 100 years, but it
concludes that it is not clear what role, if any, increased greenhouse gases
have played in this phenomenon. All models used in that assessment predict
continued ENSO interannual variability in the future no matter what the
change in average background conditions. However, the changes in ENSO
interannual variability differ from model to model based on subtle changes
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POTENTIALLY DISRUPTIVE CLIMATE EVENTS 67
in the physical parameterization schemes of the models (Collins, 2000).
The models are not consistent in their projections of ENSO amplitude or
frequency in the 21st century, and it is not yet possible to tell which models’
results are most credible. The IPCC study concluded that “it is not possible
at this time to confidently predict whether ENSO activity will be enhanced
or damped due to anthropogenic climate change” (Intergovernmental Panel
on Climate Change, 2012:157). Climate scientists continue to explore links
between increased greenhouse gas concentrations and ENSO because the
fundamental principles of atmospheric science indicate that greenhouse
warming will drive changes in ENSO.
It seems reasonable to infer from this research that ENSO is likely to
change in coming decades, even though we cannot at this point determine
which parameters will change or to what extent. In our judgment it would
be worthwhile for the intelligence community to consider the security im-
plications of a few of the scientifically plausible scenarios for how ENSO
might change because changes in the amplitude and nature of ENSO con-
stitute one of the few components of the coupled climate system capable of
having a global synchronized impact. However ENSO changes, there will
be simultaneous consequences in many places. For example, if the future
will bring stronger El Niño events, as some models project, the results will
likely include drought in Australia and excess precipitation across parts
of the southern tier of the United States occurring in the same year. Such
a confluence of events could affect global grain production in ways that
could be disruptive, depending on other conditions affecting food supply
and demand.
Conclusion
Over the next decade the most likely scenario for single extreme events
is a continuation of the trends of recent decades—probably a slow rate of
change for now, but with the possibility of a faster one later. Many of these
trends involve the continuation of trends that are already being observed,
such as those summarized in Table 3-1, such as a warming of days and
nights and a trend toward heavier precipitation, with wet areas tending
to get wetter and dry areas drier, and with more of the precipitation con-
centrated in heavy events, particularly in certain regions. The effects of the
ENSO cycle, superimposed on these longer-term climate trends, will exac-
erbate some extremes and dampen others in complex ways. In addition to
these events, there remains the possibility of unprecedented extreme events
that might occur as a result of abrupt climate change or other climatic
phenomena discussed later in the chapter.
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68 CLIMATE AND SOCIAL STRESS
CLUSTERS OF EXTREME EVENTS
By a cluster of extreme events we mean several extreme climate events
appearing close in time but not necessarily in space. Clusters of extreme
events are a concern from a national security perspective because U.S.
government resources and those of other international actors deployed to
deal with a security or humanitarian concern related to the first event in
a cluster might be unavailable or less available to deal with a second or
subsequent extreme event.
Clusters of extreme events may occur as a result of a random co-
occurrence of extreme events in different places that have different causes.
They may also result from large-scale climate processes that serve as com-
mon causes of events in disparate places that seem superficially to be un-
related. An example of such an event cluster was the conjunction of a heat
wave and drought in Russia and floods in Pakistan in 2010. In July and
August of that year, western Russia suffered from a major drought and heat
wave that resulted in a major loss of life and crops as well as large forest
fires. Simultaneously Pakistan was experiencing major flooding that also
resulted in a major loss of life and property. These two events were linked
by more than just their proximity in time. The meteorological pattern that
led to the Russian heat wave, in which the large-scale upper-level wind flow
developed a strong and persistent ridge, also contributed to the develop-
ment of the meteorological pattern that resulted in the Pakistani floods—a
downstream, leading trough (Lau and Kim, 2012). The fact that these two
extreme events corresponded in time with each other and with a single
larger meteorological pattern was unusual but not totally unexpected. Cir-
culation events like this one, which cause some event clusters, are known
to occur but are not well resolved in current climate models.
A key question for security analysis is whether such event clusters are
non-random, indicating a teleconnection phenomenon in which the events
in the cluster are intrinsically linked, making their joint probability of occur-
rence greater than the individual probabilities multiplied together. If so, when
one of these events occurs, the likelihood of the other is increased. Knowledge
of systematic connections of this type could be valuable for security analysis
because it could aid in the development of security risk scenarios.
Generally this sort of clustering of events can occur when the large-
scale atmospheric flow around the mid-latitudes of the northern and south-
ern hemispheres, which contains a series of about four to six meanders, or
waves (called Rossby, or planetary, waves), develops specific kinds of stable
patterns, resulting in the simultaneous occurrences of drought, drought
and flood, or flooding events in different parts of the globe. Herweijer and
Seager (2008) show that the simultaneous occurrence of drought in North
America, parts of Europe, South America, and Australia has resulted from
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POTENTIALLY DISRUPTIVE CLIMATE EVENTS 69
the development of Rossby wave patterns, likely a response to specific pat-
terns of cold sea surface temperatures in the tropical eastern Pacific Ocean
(La Niña). Much as with the recent Russian drought/Pakistani flooding
cluster, when drought has occurred over North America and Europe (in-
cluding western Russia), unusually wet conditions have occurred over Paki-
stan and northern India as well as over other parts of the globe (Herweijer
and Seager, 2008). The ENSO phenomenon creates systematic connections
of climate conditions that affect large parts of the planet more or less simul-
taneously, leading to predictable clusters of extreme climate events during
strong El Niño and La Niña phases (see Box 4-1). Such phenomena suggest
that the simultaneous occurrence of drought in parts of the northern and
southern hemispheres coincident with flooding in other regions is a distinct
possibility in the next decade or so. Other clusters of extreme weather or
climate conditions may also become more likely than in the past.
Related to the concept of event clusters is the notion of compound
events, which occur when different kinds of climate events are linked in
the same place. An obvious example is the conjunction of drought with
wildfires or crop failures. The first event drives the second, but they are
different in that different people or groups are susceptible to damage from
different parts of the compound event and different organizations may be
involved in response. In Chapter 5 we discuss an example of the conjunc-
tion of drought, heat wave, and forest fire in Australia in 2010.
If climate events and extremes were independent in a statistical sense,
the likelihood of a cluster or a compound event of any size could easily be
estimated mathematically. But as the above example makes clear, extreme
events in different parts of the world can be driven by common underlying
forces and thus have an intrinsic relationship such that when one such event
occurs, the likelihood increases that other extreme events linked to them
by common causes will also occur. In statistical language, such events are
called dependent.
We conducted two exploratory analyses in which we used data from
1901–2002 to examine statistical relationships between pairs of conditions
that climate science indicates may be dependent on underlying large-scale
climate patterns (see Appendix D for details). In one case, the correlation
between heat in Russia and heavy precipitation in Pakistan, we found no
general association between the two phenomena in the century-long record,
suggesting that the association in 2010 was without recent precedent. In
the other, an association between droughts in regions of the southwestern
United States and a region in Argentina and Uruguay, we estimated that the
probability of drought exceeding a 10-year return level in one of the regions
given a similarly serious drought in the other was almost three times what
it would be if the events were statistically independent and that for more
serious droughts, the dependence effect was even stronger.
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70 CLIMATE AND SOCIAL STRESS
These results are preliminary, and conclusions should be tempered by
questions about the accuracy of the data, the limited number of data points
(102 annual observations), and the small number of previous examples that
were extreme in both variables. The results suggest, however, that event
clusters of this sort could be increasing in likelihood more rapidly than the
underlying single events and that by combining climatological and statisti-
cal analysis, it may be possible to develop better estimates of the likelihoods
of occurrence of extreme event clusters of interest. However, the scientific
analysis on this matter is still in its infancy.
SEQUENCES OF EVENTS
A climate condition or event can sometimes precipitate or facilitate
a series of other physical and biological events, each linked to the oth-
ers through deterministic processes, that together promote conditions of
potential security concern. We can illustrate the concept of climate event
sequences, although not the potential national security implications, with
a sequence of events that took place recently in western North America.
The recent pine bark beetle outbreaks in western North America have
their roots in multiple mechanisms, but climate change is believed to be a
factor driving at least some of them (Bentz, 2008). Elevated temperatures,
particularly consecutive warm years and elevated minimum temperatures,
can speed up reproductive cycles and reduce cold-induced beetle mortality,
both of which increase beetle populations. Moreover, shifts in precipita-
tion patterns and associated drought can promote bark beetle outbreaks
by weakening trees and making them more susceptible to beetle attacks.
Droughts, combined with forest die-off from beetle outbreaks, in turn in-
crease the amount of fuel in forests, increasing the susceptibility of forests
to fire, especially during heat waves, which are likely to be longer and
more intense with climate change. The ongoing climate change, because of
its warming, also increases evaporation and thus intensifies the risk of fire
(see Figure 3-2). Dead forests provide an opportunity for fires to spread
more widely. The extreme forest fires in Colorado in the summer of 2012
occurred in one of the highest-risk regions in the western United States.
Severely burned forest lands are also more prone to erosion in storms (e.g.,
Benavides-Solorio and MacDonald, 2005), indicating that forest fires in-
crease the risks of soil degradation and of mudslides. Climate change may
thus be playing at least four different roles in this dynamic: It promotes
bark beetle infestations, weakens trees, dries the environment, and creates
weather conditions conducive to fire outbreak. These conditions, connected
in sequence, increase the risks of major forest fires and their hydrological
and human consequences.
The kinds of linkages involved in this example and in other plausible
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POTENTIALLY DISRUPTIVE CLIMATE EVENTS 71
FIGURE 3-2 Map of increased risk of fire in the western United States as a result
of rising temperatures and increased evaporation. The figure shows the percentage
increase in burned areas in the West for a 1.8°F (1°C) increase in global average
temperatures relative to the median area burned during 1950–2003. For example,
fire damage in the northern Rocky Mountain forests, marked by region B, is ex-
pected to more than double annually for each 1.8°F (1°C) increase in global average
temperatures. With the same temperature increase, fire damage in the Colorado
Rockies (region J) is expected to be more than seven times what it was in the second
half of the 20th century.
SOURCE: National Research Council (2011a).
event sequences are in general poorly understood and therefore not very
predictable. Nevertheless, the example suggests that there may be a very
large number of plausible ways by which climate change could set in mo-
tion a sequence of events in ecological, hydrological, or other deterministic
physical and biological systems that could become seriously disruptive and
that might create security concerns.
GLOBAL SYSTEM SHOCKS
Climate events occurring in one part of the world have the potential
to affect other parts of the world through important, globally integrated
systems other than climate itself. One example is the potential influence of
climate events on the world supply—and therefore the prices—of interna-
tional traded commodities, such as grains. By this mechanism an event such
as the 2012 drought in the central United States, still developing as this is
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72 CLIMATE AND SOCIAL STRESS
being written, could affect world corn or wheat prices in ways that make
essential foods unaffordable for populations in Africa or Asia. Another
example of a global system shock would be constraints on the availability
of humanitarian aid for a country because aid providers are responding to
situations elsewhere in the world. Yet another would be a climate event
that altered the distribution of a major pathogen affecting people or staple
crops. These examples, which are discussed in greater detail in Chapter 4,
indicate that there are numerous ways in which climate events could cre-
ate shocks to integrated global social, economic, health, or technological
systems and thus have effects far removed geographically from where the
events occur.
SURPRISES ARISING FROM POORLY
RESOLVED CLIMATE DYNAMICS
Many extreme events, such as hurricanes, tornadoes, other severe
storms, floods, heat waves, and wild fires, occur on the time-scale of days
to about two weeks. A key question for climate research is how such ex-
treme events will change within a warming climate. With such warming
the statistics of weather are no longer stationary, and the linkage between
weather and climate emerges as a research priority. Today’s climate change
models are generally considered to provide an adequate representation of
the large-scale secular trend in climate. However, gaining a better insight
into how climate change will affect extreme weather requires that high-
resolution numerical weather prediction models (and their inherent fast
physics, such as cloud–radiation–precipitation interactions) be run in cli-
mate mode. This presents a major computational and resource challenge
and has been the reason for the call for a seamless approach to weather and
climate forecasting (World Climate Research Programme, 2009). Such a
unified approach was first implemented by the U.K. Met Office in 1993. In
the United States the National Centers for Environmental Prediction of the
National Oceanic and Atmospheric Administration developed the Coupled
Forecast System (CFS) in 2004 as a lower-resolution climate version of its
Global Forecast System, a weather forecast system for short-term seasonal
climate prediction. However, this system has yet to be run on decadal to
centennial time-scales in response to GHG forcing. Hence the behavior of
extreme events in a non-stationary climate cannot be fully described and
projected until climate change models are run with the spatial resolution
and physical processes of numerical weather prediction models. Until that
time, extreme climate surprises should be expected to be more the rule than
the exception.
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POTENTIALLY DISRUPTIVE CLIMATE EVENTS 73
CONCLUSIONS AND RECOMMENDATIONS
Physical climate science has developed some skill at estimating the
changing likelihoods of the occurrence of certain kinds of climate events,
such as heat waves and certain precipitation anomalies, at a decadal time-
scale and at a global and, in some cases, a continental or subcontinental
geographic scale. However, the ability to foresee specific climate events on
a decadal time-scale at the level of medium-sized countries is still in its in-
fancy. Predictive skill at such time horizons and levels of resolution depends
on having a more extensive observational system than currently exists and
on developing an improved understanding of interannual and decadal pro-
cesses of climate variability that can be incorporated into predictive models.
Estimating the risks of extreme climate events—and especially estimating
the places they will occur—is particularly challenging because predictive
skill is harder to acquire and to validate for infrequent events and because
the frequency and character of such events may change as climate trends
continue.
The current state of understanding does not suggest that the distribu-
tions of single climate event types in particular places will change sharply
in the coming decade, but neither can it preclude such a possibility with
high confidence. It is safe to say that extreme climate events will change in
their frequencies, intensities, and probably also their locations in the com-
ing decade. The most likely scenario is a continuation of the temperature
and precipitation trends of recent decades, probably with a slow rate of
change for now, but with the possibility of a faster one later. However,
the effects of the ENSO cycle superimposed on longer-term climate trends
will exacerbate some extremes and dampen others in complex ways. In
addition, there remains the possibility of unprecedented extreme events or
conjunctions of events that might occur as a result of abrupt climate change
or other climatic phenomena (for example, a more rapid rise in sea level if
the melting of ice sheets were to accelerate).
Conclusion 3.1: Given the available scientific knowledge of the climate
system, it is prudent for security analysts to expect climate surprises
in the coming decade, including unexpected and potentially disruptive
single events as well as conjunctions of events occurring simultaneously
or in sequence, and for them to become progressively more serious
and more frequent thereafter, most likely at an accelerating rate. The
climate surprises may affect particular regions or globally integrated
systems, such as grain markets, that provide for human well-being.
Some events or conjunctions of events may arise from connections
within the Earth system, such as aspects of the ENSO cycle and other
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74 CLIMATE AND SOCIAL STRESS
continental-level phenomena that are only beginning to be appreciated
and understood. Climate change has moved the physical Earth system into
conditions that are unprecedented in recorded history, and we do not un-
derstand the complexities of the relationships among the elements of the
system well enough to make skillful forecasts of specific events. It is there-
fore prudent to expect that the likelihoods of such events occurring will
increase in the coming decade in most places and that the rate of change
will continue subsequently to increase. Models are an increasingly power-
ful tool for examining the likelihood of changes in means, extremes, and
variability of climate.
It makes sense for the intelligence community to apply a scenario ap-
proach in thinking about potentially disruptive events that are expectable
but not truly predictable. For example, available climate models sometimes
disagree about the direction of a climate trend even when the fundamental
science strongly suggests that change is likely. In such situations it may
make sense to consider the security implications of two or more plausible
trends as a way to anticipate risks. It will also be valuable for the intel-
ligence community to have improved forecasting ability for subcontinental
climate events and for event clusters and sequences. An improved monitor-
ing of factors that might provide early warning of potentially disruptive
events would also be valuable. We discuss monitoring issues in Chapter 6.
Recommendation 3.1: The intelligence community should participate
in a whole-of-government effort to inform choices about adapting to
and reducing vulnerability to climate change. It should, along with
appropriate federal science agencies, support research to improve the
ability to quantify the likelihoods of potentially disruptive climate
events, that is, single extreme climate events, event clusters, and event
sequences. A special focus should be on quantifying risks of events and
event clusters that could disrupt vital supply chains, such as for food
grains or fuels, and thus contribute to global system shocks.
This research should include efforts by climate scientists to improve
fundamental understanding of the effects of climate change on the likeli-
hoods of extreme climate events and also efforts to apply the methods
of extreme value statistics to these problems, particularly the problem of
estimating the likelihoods of clusters of extreme climate events that are
dependent on the same underlying climatic processes. Having improved
likelihood estimates for single and clustered extreme climate events would
help in defining climate event scenarios for countries, regions, and systems
that could be used as the basis for the climate stress tests that we discuss
in Chapter 6.
