Climate models projected stronger warming over the past 15 years than has been seen in observations. Conspiring factors of errors in volcanic and solar inputs, representations of aerosols, and El NiNo evolution, may explain most of the discrepancy

Schmidt, Gavin A.

Shindell, Drew T.

Tsigaridis, Konstantinos

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Reconciling warming trends
Gavin A. Schmidt, Drew T. Shindell and Kostas Tsigaridis
Climate models projected stronger warming over the past 15 years than has been seen in observations. 
Conspiring factors of errors in volcanic and solar inputs, representations of aerosols, and El Niño 
evolution, may explain most of the discrepancy.
Any divergence between real-world climate phenomena and prior expectations poses interesting 
science questions. The case of the 
apparent slow-down of warming since 
the record El Niño event in 1997/1998 is 
no exception. The global mean surface 
temperature trend was smaller1 between 
1997 and 2013 (0.07±0.08 °C per decade) 
than over the last 50 years (0.16 ± 0.02 °C 
per decade), highlighting questions about 
the mechanisms that regulate decadal 
variability in the Earth’s temperature. In 
addition, the warming trend in the most 
recent 15-year period is near the lower 
edge of the 5–95% range of projections 
from a collection of climate models 
that were part of the Coupled Model 
Intercomparison Project Phase 5 (CMIP5). 
Why most of the model simulations 
suggest more warming than has been 
observed is a second question that deserves 
further exploration.
Short-term fluctuations in global mean 
surface temperature anomalies have been 
a perennial focus of public discussions 
related to climate change. We should 
expect to see climate changes, by definition, 
only in the long-term trends that average 
over stochastic weather and year-to-year 
fluctuations such as those associated with 
the El Niño/Southern Oscillation (ENSO), 
which favoured a cool La Niña phase in 
the past few years. On decadal timescales, 
global mean surface temperatures are 
expected to vary, too. One cause might 
be the chaotic internal variability of the 
coupled system of oceans and atmosphere, 
for example in the tropical Pacific Ocean2, 
or in variability in deep ocean circulation3. 
Alternatively, decadal-scale temperature 
variations can be a response of the climate 
system to external influences, such as 
volcanic eruptions or the solar cycle. Both 
kinds of influence will continue to operate 
and be superimposed on any long-term 
warming trend from rising atmospheric 
greenhouse gas concentrations. For shorter 
time periods — and a 15-year interval 
may just about qualify as such — natural 
and externally driven fluctuations can, 
in principle, lead to a change in warming 
trend. But it is not obvious that either 
effect should lead to a discrepancy 
between climate model projections 
and observations. 
Here we argue that a combination 
of factors, by coincidence, conspired 
to dampen warming trends in the real 
world after about 1992. CMIP5 model 
simulations were based on historical 
estimates of external influences on the 
climate only to 2000 or 2005, and used 
scenarios (Representative Concentration 
Pathways, or RCPs) thereafter4. Any 
recent improvements in these estimates 
or updates to the present day were not 
Well-mixed greenhouse gases. We 
linearly interpolated observations of 
atmospheric concentrations of CO2, N2O, 
CH4 and chlorofluorocarbons (CFCs) 
between 2005 and 2012, and calculated 
the radiative effect of these greenhouse gas 
levels using standard simplified formulae. 
Concentrations of CO2, N2O and CH4 
were very slightly lower than used in the 
CMIP5 runs, whereas CFCs were a little 
higher, leading to a small cool bias in the 
models (Fig. 1a).
Solar irradiance. Because solar irradiance 
at the last solar-cycle minimum was 
lower and the present weak solar cycle 
started later12 than had been assumed in 
the CMIP5 simulations13, solar drivers 
were too positive in the CMIP5 runs. We 
multiplied the difference in total solar 
irradiance forcing by an estimated factor 
of 2, based on a preliminary analysis 
of solar-only transient simulations, to 
account for the increased response over 
a basic energy balance calculation when 
whole-atmosphere chemistry mechanisms 
are included.
Human-made tropospheric aerosols. Only 
two CMIP5 models include nitrate aerosol 
forcing, and half did not include aerosol 
indirect effects. Given the recent increases 
in Asian sources, nitrate effects amount 
to perhaps −0.04 W m−2 of additional 
forcing14. Exclusion of aerosol indirect 
effects15 might add another −0.06 W m−2 
globally since 2000. We assumed that this 
forcing increased slowly in the 1990s, and 
faster in the 2000s following Asian NO2 
emissions16, peaking at −0.1 W m−2 in 
2010. Underestimates of secondary organic 
aerosols are an additional missing factor, 
but are harder to quantify17.
Volcanic stratospheric aerosols. A 
reanalysis of satellite retrievals in the 
1990s and additional observations in the 
2000s has produced a record of aerosol 
optical depth9 (updated to version 2.0; 
ref. 10) that differs significantly from that 
used in CMIP5 (ref. 18). In particular, 
the magnitude of the impact of Pinatubo 
in the early 1990s is downgraded, and 
larger contributions are suggested for 
the twenty-first century. Radiative 
forcing is calculated by assuming no 
post-2000 volcanic aerosols in CMIP5 
and multiplying the difference in aerosol 
optical depth by −25 to derive a forcing 
in W m–2.
Box 1 | Adjustments to the CMIP5 external inﬂuences
A combination of factors, by 
coincidence, conspired to 
dampen warming trends in the 
real world after about 1992.
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taken into account in these simulations. 
Specifically, the influence of volcanic 
eruptions, aerosols in the atmosphere 
and solar activity all took unexpected 
turns over the 2000s. The climate model 
simulations, effectively, were run with the 
assumption that conditions were broadly 
going to continue along established 
trajectories. Additionally, the exact phasing 
of any natural fluctuations will not be 
captured in any specific model.
Updated estimates of climate drivers
To test this hypothesis, we have collated 
up-to-date information on volcanic aerosol 
concentrations, solar activity and well-
mixed greenhouse gases in the 1990s and 
2000s (Box 1). These updates include both 
newly observed data and also reanalyses 
of earlier 1990s data on volcanic aerosols 
based on improved satellite retrievals. 
Comparing the updated information 
with the data used in the CMIP5 climate 
model simulations (Fig. 1a) suggests that 
in the mid-1990s, cooling factors were 
overestimated (largely an effect of an 
overestimate of the stratospheric aerosol 
optical depth in the wake of the Mount 
Pinatubo eruption), making the models 
cooler than the real world. Conversely, in 
the 2000s, multiple cooling factors were 
underestimated, so the real world would 
be expected to have been cooler than in 
the models.
We estimate how simulated global 
mean surface temperature would have 
been different in the CMIP5 runs if two 
effects had been included: first, if ENSO 
in each model had been in phase with 
observations, and second, if the ensemble 
mean were adjusted using results from a 
simple impulse-response model5 with our 
updated information on external drivers 
(Fig. 1b). We find that this procedure 
reduces the differences between observed 
and simulated temperatures by a factor 
of 3. We conclude that the coincident 
underestimates of cooling factors in the 
2000s — that is, of volcanic aerosols, 
solar irradiance and effects of human-
made aerosols — have combined to bias 
the model ensemble. According to this 
estimate, about a third of the difference 
between simulated and observed trends 
(in the GISTEMP analysis6) between 
1997 to 2013 is a result of underestimated 
volcanic emissions; about one-seventh of 
the discrepancy comes from overestimates 
of solar activity and differences in ENSO 
phasing between climate models and 
the real world; and just under a quarter 
could be related to human-made aerosols. 
These estimates leave only a small residual 
between models and observations that 
can be easily accounted for by internal 
variability unrelated to ENSO, or to any 
further misspecifications of external 
influences. In comparison to an alternative 
temperature analysis7 the observed 
trend matches the adjusted simulated 
temperature increase even more closely 
(Fig. 1b).
Prediction
uncertainty 
GISTEMP LOTI
HadCRUT4 (inﬁlled)
CMIP5 ensemble (5–95%)
CMIP5 with obs. ENSO
and with updated forcings
Adjusted CMIP5 ensemble
Year
Year
Te
m
pe
ra
tu
re
 a
no
m
al
y 
(°
C
)
Global mean temperature anomalies
1992 1996 2000 2004 2008 2012
1992 1996 2000 2004 2008 2012
–0.4
–0.2
0.0
 0.2
 0.4
 0.6
 0.8
–0.4
–0.3
–0.2
–0.1
 0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
Ra
di
at
iv
e 
fo
rc
in
g 
(W
 m
–2
)
WMGHG
Solar
Aerosols
Volcanic
Updates to climate model driversa
b
Figure 1 | Updated external inﬂuences on climate and their impact on the CMIP5 model runs. a, The 
latest reconstructions of optical depth for volcanic aerosols9,10 from the Mount Pinatubo eruption in 
1991 suggest that the cooling effect of the eruption (1991–1993) was overestimated in the CMIP5 runs, 
making the simulated temperatures too cool. From about 1998 onwards, however, the cooling effects 
of solar activity (red), human-made tropospheric aerosols (green) and volcanic eruptions (pink) were 
all underestimated. WMGHG, well-mixed greenhouse gases. b, Global mean surface temperature 
anomalies, with respect to 1980–1999, in the CMIP5 ensemble (mean: solid blue line; pale blue 
shading: 5–95% spread of simulations) on average exceeded two independent reconstructions from 
observations (GISTEMP Land–Ocean Temperature Index (LOTI)6, solid red; HadCRUT4 with spatial 
inﬁlling7, dashed red) from about 1998. Adjusting for the phase of ENSO by regressing the observed 
temperature against the ENSO index11 adds interannual variability to the CMIP5 ensemble mean 
(dashed blue), and adjusting for updated external inﬂuences as in a further reduces the discrepancy 
between model and data from 1998 (black). The adjusted ensemble spread (dashed grey) clearly 
shows the decadal impact of the updated drivers. As an aside, we note that although it is convenient 
to use the CMIP5 ensemble to assess expected spreads in possible trends, the ensemble is not a true 
probabilistic sample.
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commentary
Reconciliation
We conclude that use of the latest 
information on external influences on the 
climate system and adjusting for internal 
variability associated with ENSO can almost 
completely reconcile the trends in global 
mean surface temperature in CMIP5 models 
and observations. Nevertheless, attributing 
climate trends over relatively short periods, 
such as 10 to 15 years, will always be 
problematic, and it is inherently unsatisfying 
to find model–data agreement only with the 
benefit of hindsight. We see no indication, 
however, that transient climate response is 
systematically overestimated in the CMIP5 
climate models as has been speculated8, or 
that decadal variability across the ensemble 
of models is systematically underestimated, 
although at least some individual models 
probably fall short in this respect.
Most importantly, our analysis implies 
that significant warming trends are likely to 
resume, because the dominant long-term 
warming effect of well-mixed greenhouse 
gases continues to rise. Asian pollution levels 
are likely to stabilize and perhaps decrease, 
although lower solar activity may persist and 
volcanic eruptions are unpredictable. ENSO 
will eventually move back into a positive 
phase and the simultaneous coincidence of 
multiple cooling effects will cease. Further 
warming is very likely to be the result. S
Gavin A. Schmidt, Drew T. Shindell and  
Kostas Tsigardidis are at the NASA Goddard Institute 
for Space Studies, 2880 Broadway, New York, New York 
10025, USA. Kostas Tsigaridis is also at the Center for 
Climate Systems Research, Columbia University,  
2880 Broadway, New York, New York 10025, USA. 
e-mail: gavin.a.schmidt@nasa.gov
References
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93, 485–498 (2012). 
5. Boucher, O. & Reddy, M. S. Energy Policy 36, 193–200 (2008). 
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7. Cowtan, K. & Way, R. G. Q. J. R. Meteorol. Soc. 
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10. Santer, B. D. et al. Nature Geosci. 7, 185–189 (2014).
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Bumpy path to a warmer world
Martin Visbeck
Decadal climate variability has long received limited attention. With the slow-down in surface warming 
since the late 1990s, the decadal scale has rightly become a focus of attention: for assessing climate 
change and its impacts, it is of critical importance.
A changing climate matters most to our generation on timescales from seasons to decades. Decadal climate 
information, in particular, is essential 
for societies in developing to become 
climate-resilient.
The developed world has established 
a wealth of adaptation mechanisms to 
cope with the effects of a changing climate 
on seasonal and interannual timescales. 
Advanced water management systems, 
capital reserves and widespread insurance 
all help to buffer the loss, damage and gains 
from short-term climate fluctuations. By 
contrast, a 10-year drought, or a decade 
of high tropical storm activity, may easily 
exhaust the coping strategies of even 
the most developed economies. In the 
developing world, coping mechanisms 
are less abundant, and the same change 
in the climate often leads to great 
societal hardship.
Beyond the decadal timescale, on the 
other hand, the world is developing long-
term adaptation strategies to cope with 
persistent climate change. These include the 
development of large-scale infrastructure 
such as seawalls and water reservoirs, 
alternative responses such as retreat 
from affected land, and adjustments in 
economic and legislative structures such as 
insurance frameworks.
Climate variability on scales of 10 to 
30 years — too long to sit out, yet too short 
to adapt to fully — is therefore particularly 
important to our generation. Nevertheless, 
the slow-down in warming over the 
past 15 years or so — despite unabated 
emissions of greenhouse gases and global 
climate model projections that suggest 
much steeper warming — has caught parts 
of the scientific community by surprise. We 
should have expected such decadal swings 
if more emphasis had been devoted to 
understanding the decadal scale.
Weak and regional
The most energetic frequency range in 
almost any long-term climate record is the 
annual cycle. In the tropics, the annual 
band is followed by climate variability on 
timescales of 3 to 7 years associated with 
the El Niño/Southern Oscillation (ENSO), 
a large-scale climate see-saw that is rooted 
Figure 1 | Ocean observations. Martin Visbeck 
deploying an Argo ﬂoat in the ocean from the 
research vessel MV Maria S. Merian. Argo is an 
international network of more than 3,000 robotic 
ﬂoats that measure the temperature and salinity of 
the ocean’s upper 2,000 m.
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© 2014 Macmillan Publishers Limited. All rights reserved


Reconciling Warming Trends

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