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PUBLISHED ONLINE: 26 OCTOBER 2012 | DOI: 10.1038/NCLIMATE1562

Communication of the role of natural variability infuture North American climate
Clara Deser1*, Reto Knutti2, Susan Solomon3 and Adam S. Phillips1
As climate models improve, decision-makers’ expectations for accurate climate predictions are growing. Natural climate
variability, however, poses inherent limits to climate predictability and the related goal of adaptation guidance in many places, as
illustrated here for North America. Other locations with low natural variability show a more predictable future in which anthropogenic forcing can be more readily identified, even on small scales. We call for a more focused dialogue between scientists, policymakers and the public to improve communication and avoid raising expectations for accurate regional predictions everywhere.

Evidence is clear that Earth’s global average climate has warmed
over the past century 1. However, a science communication
challenge is to better explain where, how and how much natural
climate variability may obscure anthropogenic climate change ontimescales of a few decades and spatial scales smaller than continental2–7. (Here, the term ‘natural climate variability’ refers to unforced
variability internal to the real or simulated climate system.) For
example, natural phenomena such as the Interdecadal PacificOscillation and the Atlantic Multidecadal Oscillation substantiallymodify the rate of warming in many regions of the globe8,9. Despite
clear evidence for the importance of such phenomena, some news
articles10 imply that uncertainties in climate change projections
are due to model shortcomings, and it is sometimes confidently
asserted that those can be overcome. For example, a recent modelling summit 11 concluded that “a vigorous Climate Prediction Project… would ensure that the goal of accurate climate predictions at theregional scale could begin to aid the global society in coping withthe consequences of climate change”. Should such assertions be
more targeted, rather than global?
Uncertainty in climate projections is due to three main factors:
emissions-scenario uncertainty, model-response uncertainty andnatural variability 3. The choice of emissions scenario can be specified and model-response uncertainty can potentially be reduced.
But given the inherently unpredictable nature of unforced climate
fluctuations beyond a few years12 to at best a decade13,14, uncertainty in future climate change due to natural variability is unlikely
to be reduced as climate models improve or as projections ofgreenhouse-gas concentrations become more accurate. It is critical to consider how the amplitude of natural variability differs withlocation. Several recent studies15–17 have shown that a ‘signal’ of
locally significant summertime warming is already emerging or
will emerge from the ‘noise’ in the next two decades in a numberof tropical areas owing to low natural variability. Here we provide
simple figures based on one climate model and with a specificfocus on a timescale of the next 50 years to illustrate that althoughclimate change and climate projections could be inherently uncertain in many parts of North America owing to natural variability,
not all places and climate variables are subject to the same limitations, requiring a more focused approach to adaptation and science communication. North America is chosen as an example toillustrate the argument, but the conclusions qualitatively apply to
all continents.

Modelling natural variability and climate change

To span the range of internal climate variability, a 40-member
ensemble of climate change simulations for the period 2000–
2060 was conducted with a comprehensive coupled atmosphere–ocean–sea ice–land general circulation model — the
National Center for Atmospheric Research Community Climate
System Model version 3 (CCSM3) — at a horizontal resolutionof approximately 2.8° latitude and 2.8° longitude4. Each ensemble
member undergoes the same external forcing, the main components of which are the Special Report on Emissions Scenarios 18 A1B
greenhouse-gas scenario (in which carbon dioxide concentrations
increase from approximately 380 ppm in 2000 to approximately
570 ppm in 2060) and stratospheric ozone recovery by 2060, as
well as smaller contributions from sulphate aerosol and black-carbon changes19. Each ensemble member begins from identical initial conditions in the ocean, land and sea-ice model components(taken from the conditions on 1 January 2000 from a single twentieth century CCSM3 integration), and slightly different initialconditions in the atmospheric model (taken from different days
during December 1999 and January 2000 from the same twentiethcentury CCSM3 run).
The different members of the model ensemble show how muchthe climate can vary in the model world as a result of random
internal variations. To the extent that the model captures the relevant physical processes, its range provides insight into what could
happen in the single realization that will occur in the real world. The
predictability of air temperature and precipitation changes in thesemodel runs is limited to a few years12. Thus, the 40 realizations are
all plausible outcomes of climate change over the next 50 years. This
set-up can be thought of as an idealized decadal prediction experiment in which one member is reality and the others are initialized
predictions. Because all simulations are performed with the samemodel and are identical until 2000, twenty-first century differences
cannot be ascribed to model errors, biases or initialization shocks.
The spread therefore represents the irreducible uncertainty of theprediction. This 40-member ensemble of climate change realizations
represents the largest such ensemble with a single state-of-the-art
coupled climate model so far. The spatial patterns and magnitudes
of internal climate variability on decadal and longer timescales are
generally well represented by CCSM3, although some locationsin North America show enhanced variability (by approximately
15–25%) compared with nature4.

National Center for Atmospheric Research, 1850 Table Mesa Drive, Boulder, Colorado 80305, USA, 2ETH ZÜrich, Institute for Atmospheric and Climate
Science, CHN N 12.1, Universitätstrasse 16, CH-8092 ZÜrich, Switzerland, 3Department of Earth, Atmospheric and Planetary Sciences, Massachusetts
Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, USA. *e-mail: cdeser@ucar.edu
1

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NATURE CLIMATE CHANGE DOI: 10.1038/NCLIMATE1562

a

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Phoenix, Arizona

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Figure 1 | Range of future climate outcomes. a, December–January–February (DJF) temperature trends during 2005–2060. Top panel shows the averageof the 40 model runs (all values are statistically significantly different from zero at the 5% confidence level); middle and bottom panels show the modelruns with the largest and smallest trends for the contiguous United States as a whole, respectively. b, DJF temperature anomaly time series for selected
cities (marked by open circles in the left panels), the contiguous United States and the globe (land areas only). Black curves show observed records from1910 to 2008 (minus the long-term mean); red and blue curves show model projections for 2005–2060 from the realizations with the largest and smallest
future trends, respectively, for each location or region. Dashed red and blue lines show the best-fit linear trends to the red and blue curves, respectively. For
visual clarity, the model projections are matched to observations averaged over their common period of record 2005–2008. Thus, projected values at theend of the simulation (2060) should be regarded in relative terms (see Supplementary Information). c, Distribution of projected DJF temperature trends(2005–2060) across the 40 ensemble members at the locations shown in panel b.

A range of future climate outcomes for North America

The projected changes in winter (December–January–February)and summer (June–July–August) temperatures, when averaged
over all 40 ensemble members, show familiar patterns: robust
warming at all locations, with the largest amplitudes at high latitudes in winter (4–6 °C over northern Canada and Alaska compared with 1–2 °C over the southern United States and the Rocky
Mountains in summer; top panels of Figs 1a and 2a, respectively).
Individual realizations, however, can look very different from thisaverage picture of climate change. For example, the model run
with the most warming over the contiguous United States in winter shows the largest temperature change (4–6 °C) over northeastern North America and the smallest change (1–3 °C) over western
Canada and Alaska (Fig. 1a, middle). On the other hand, the runwith the least warming over the contiguous United States in winterdisplays temperature changes that are limited to <1 °C over muchof the western United States and southwest Canada with someareas such as the northwest United States even experiencing cooling (Fig. 1a, bottom). These strikingly different climate outcomesoccur despite both model runs being subjected to identical external forcings. A similar story is evident in summer: one model run
shows temperature increases over the contiguous United States
776

that are approximately twice as large as the ensemble mean (4–5 °C
compared with 2–3 °C; Fig. 2a, middle), while another has only
limited warming (<1 °C) over the US Midwest (Fig. 2a, bottom).
The large differences between individual model realizations canbe traced back to multidecadal fluctuations in large-scale atmospheric flow patterns whose patterns are similar to those observedin daily weather and in interannual variability 4.
Figures 1b and 2b offer a complementary temporal perspective
on North American climate change as impacted by natural variability. Here, observed20 temperature records for 1910–2010 are
expanded with model projections to 2060 using the two ensemble
members with the largest and smallest future trends for each location or region (red and blue curves, respectively). In the global
terrestrial average, warming is evident over approximately the past
40 years, occurring at an average rate of 0.32 °C per decade in
winter and 0.29 °C per decade in summer during 1970–2008. The
model projects the rate of global warming to increase slightly
over the next 55 years, with a relatively small range of uncertainty
due to natural variability (0.38–0.45 °C per decade in winter and
0.35–0.42 °C per decade in summer during 2005–2060; see also
Figs 1c and 2c). However, the picture is different for the contiguous United States, where it is clear that in addition to fluctuations

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PERSPECTIVE

NATURE CLIMATE CHANGE DOI: 10.1038/NCLIMATE1562
a

b

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Mazatlán, Mexico

Phoenix, Arizona2
Temperature trend (°C per 55 years)

0Temperature anomaly (°C)–2

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–2

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Figure 2 | Range of future climate outcomes. As in Fig. 1 but for June–July–August.

on interannual-to-decadal timescales, even trends over 50 years
are subject to considerable uncertainty owing to natural variability. For the contiguous United States as a whole, future (2005–
2060) warming ranges from 0.8 °C to 3.4 °C in winter and 1.3 °C
to 3.4 °C in summer (recall the corresponding maps in Figs 1 and
2). The distribution of trends in Figs 1c and 2c shows the probability of warming of a particular magnitude. Higher warming
over the contiguous United States is compensated for by weakerwarming in other parts of the globe, particularly Canada, China
and portions of the tropical eastern Pacific Ocean, and vice versa(not shown).
Simulated temperature records at three selected western North
American cities (Mazatlan in Mexico, Phoenix in Arizona andSeattle in Washington) illustrate the latitudinal dependence of
uncertainty in the magnitude of future warming due to natural variability (Figs 1 and 2). A single model grid box is used for each city
location. At Mazatlan, where both the interannual variability andrelative uncertainty in future trends are smallest, projected warming ranges from 1.0 °C to 2.5 °C in winter and 0.8 °C to 1.8 °C insummer over the period 2005–2060. In comparison, Seattle shows
the largest interannual variability and greatest range of uncertainty
in future trends, with projected temperature changes varying from
−0.1 °C (that is, cooling) to as much as 4.1 °C in winter and from
1.5 °C to 4.2 °C in summer. The interannual variability and rangeof future trends at Phoenix (0.9–2.7 °C in winter and 1.4–3.0 °C insummer) lie in between those of Mazatlan and Seattle. The histograms shown in the figures illustrate how these extreme cases relate
to the range of the results across all realizations, demonstrating forexample the narrowness of the distribution of results for Mazatlan,
and the much broader spread across realizations for Seattle andthe mean across the United States. These results illustrate that at
many locations within North America and even at the regional
scale of the contiguous United States, natural variability of temperature trends over the next 55 years in both winter and summer
should be expected to be substantial. However, some places in thesouthwestern United States and Mexico are less subject to natural variability and may therefore be more predictable than otherlocations or even the United States as a whole: in other words,
regional averaging does not necessarily reduce the uncertainty inclimate change projections. Smaller levels of variability are generally found in summer compared with winter, and at lower latitudes
compared with higher latitudes; previous studies have shown such
behaviour to hold not only in a range of climate models but also
in observations16–18.
Compared with temperature, precipitation projections are evenmore subject to natural variability (Fig. 3). Although the ensemble
mean shows the familiar pattern of future precipitation increases athigh latitudes and decreases at low latitudes over North America inwinter, the changes over the midsection of the United States (indicated by stippling in the figure) do not exceed the range of modellednatural variability. As for temperature, individual realizations depict
a very different future for winter precipitation than that conveyed by
the ensemble mean. For example, one model run shows a wet future
for much of the contiguous United States, with trends exceeding
20–30% of the 2005–2060 mean over much of the southwest andKansas; whereas another shows a dry future with the largest rainfall

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NATURE CLIMATE CHANGE DOI: 10.1038/NCLIMATE1562ab
Seattle, Washington
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Figure 3 | | Range of future climate outcomes. a, As in Fig. 1 but for December–January–February (DJF) precipitation trends, expressed as a percentageof the model’s ensemble-mean climatology for 2005–2060. Top panel shows the average of the 40 model runs, with stippling where the values are notstatistically significantly different from zero at the 5% confidence level. The middle and bottom panels are based on the model runs with the wettest anddriest trends for the southern half of North America (south of 42° N), respectively. b, DJF precipitation anomaly time series, expressed as a percentage ofthe observed mean during 1910–2008 minus 100%. Northern and southern North American regions refer to averages north of 50° N and south of 42° N,
respectively. c, Distribution of projected DJF precipitation trends (2005–2060) across the 40 ensemble members at the locations shown in panel b.

deficits (30–40%) in California, Nevada, Kansas and parts of Mexico(Fig. 3a, middle and bottom).
The winter precipitation records21 shown in Fig. 3b illustrate
the high levels of uncertainty in future rainfall both locally andregionally. For example, individual locations such as Seattle (alsoPhoenix and Mazatlan; not shown) and areas as large as the southern half of North America may experience wetter or drier conditions in the future, with trends ranging from approximately −23%
to +17% of the 1910–2008 observed mean, in addition to considerable interannual variability. Winter precipitation over northern
North America, on the other hand, is projected to increase in all
ensemble members, with changes ranging from +9% to +18% of
the 1910–2008 observed mean. As for temperature, the range of
future terrestrial precipitation increases at the global scale is small(+6 to +8% over the period 2005–2060). Although the minimumto-maximum trend ranges given above depend on the ensemble
size, qualitatively similar results are obtained using ranges based on
95% confidence level estimates (for example, as Fig. 3c illustrates).

Climate change uncertainty and natural variability

Model projections are inherently uncertain. But the results shown
here suggest that often models may disagree because future changes
are within the natural variability 22. Such natural fluctuations inclimate should be expected to occur, and these will augment or reduce778

the magnitude of climate change due to anthropogenic forcing inmany parts of the world. Such intrinsic climate fluctuations occur
not only on interannual-to-decadal timescales but also over periods
as long as 50 years. Through an examination of a large ensemble oftwenty-first century projections produced by the CCSM3 climate
model, we have illustrated that even over the next 55 years, natural variability contributes substantial uncertainty to temperatureand precipitation trends over North America on local, regional andcontinental scales, especially in winter at mid and high latitudes.
Such uncertainty and regional variation in projected climate change
is largely a consequence of the chaotic nature of large-scale atmospheric circulation patterns, and as such is unlikely to be reduced asmodels improve or as greenhouse-gas trajectories become more certain4. Perhaps surprisingly, regional averaging does not necessarily
reduce uncertainty due to natural variability: the range of temperature change from one ensemble member to another over the next
55 years is larger for the contiguous United States as a whole thanfor a number of specific locations within the southwestern UnitedStates in summer and parts of Mexico in both winter and summer. It
is worth noting that downscaled information derived statistically or
dynamically from global climate model output will add local detail,but remains dependent on the overlying larger-scale field, and cannot mitigate the uncertainty of projected climate trends due to natural climate variability.

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PERSPECTIVE

NATURE CLIMATE CHANGE DOI: 10.1038/NCLIMATE1562
Planning for the future

Planning for future climate change thus requires not simply theapplication of regional or temporal averaging, but depends on a
deeper understanding of what drives the climate and its variability. Improvements in global and regional models are undoubtedly
critical, and will help climate prediction in many respects, and forsome places (such as parts of Mexico) better information on local
climate change and adaptation can be expected as models improve.
But to guide decisions in some locations, for example, the diameter of Seattle’s storm drain-pipes10, the models probably cannot be
expected to provide accurate projections. Whether projections subject to large and irreducible uncertainties remain helpful needs careful examination by the user 23,24.
Received 19 January 2012; accepted 2 May 2012; published online
26 October 2012; corrected online 14 November 2012

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Acknowledgements

The National Center for Atmospheric Research is sponsored by the National Science
Foundation. Model simulations and analyses were conducted by C.D. and A.S.P.; C.D.,
R.K. and S.S. contributed equally to the writing.

Additional information

The authors declare no competing financial interests. Reprints and permissions
information is available online at www.nature.com/reprints. Correspondence andrequests for materials should be addressed to C.D.

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Communication of the role of natural variability in future North American climate
Clara Deser, Reto Knutti, Susan Solomon and Adam S. Phillips
Nature Climate Change 2, 775–779 (2012); published online 26 October 2012; corrected after print 14 November 2012.
In the version of this Perspective originally published, the last label on the x axis of Fig. 3b should have read ‘2050’. This error has now
been corrected in the HTML and PDF versions.