Analysis: How well have climate models projected global warming?.
Scientists have been making projections of future global warming using
climate models of increasing complexity for the past four decades.
Analysis: How well have climate models projected global warming?
These models, driven by atmospheric physics and biogeochemistry, play
an important role in our understanding of the Earth’s climate and how
it will likely change in the future.
Carbon Brief has collected prominent climate model projections since
1973 to see how well they project both past and future global
temperatures, as shown in the animation below. (Click the play button to
start.)
While some models projected less warming than we’ve experienced and
some projected more, all showed surface temperature increases between
1970 and 2016 that were not too far off from what actually occurred,
particularly when differences in assumed future emissions are taken into
account.
How have past climate models fared?
While climate model projections of the past benefit from knowledge of
atmospheric greenhouse gas concentrations, volcanic eruptions and other
radiative forcings
affecting the Earth’s climate, casting forward into the future is
understandably more uncertain. Climate models can be evaluated both on
their ability to hindcast past temperatures and forecast future ones.
Related articles
Hindcasts – testing models against past temperatures – are useful
because they can control for radiative forcings. Forecasts are useful
because models cannot be implicitly tuned to be similar to observations. Climate models are not fit to historical temperatures, but modellers do have some knowledge of observations that can inform their choice of model parameterisations, such as cloud physics and aerosol effects.
In the examples below, climate model projections published between 1973 and 2013 are compared with observed temperatures from five different organizations. The models used in the projections vary in complexity, from simple energy balance models to fully-coupled Earth System Models.
(Note, these model/observation comparisons use a baseline period of
1970-1990 to align observations and models during the early years of the
analysis, which shows how temperatures have evolved over time more
clearly.)
Sawyer, 1973
One of the first projections of future warming came from John Sawyer at the UK’s Met Office in 1973. In a paper published in Nature
in 1973, he hypothesised that the world would warm 0.6C between 1969
and 2000, and that atmospheric CO2 would increase by 25%. Sawyer argued
for a climate sensitivity – how much long-term warming will occur per doubling of atmospheric CO2 levels – of 2.4C, which is not too far off the best estimate of 3C used by the Intergovernmental Panel on Climate Change (IPCC) today.
Unlike the other projections examined in this article, Sawyer did not
provide an estimated warming for each year, just an expected 2000
value. His warming estimate of 0.6C was nearly spot on – the observed
warming over that period was between 0.51C and 0.56C. He overestimated
the year 2000’s atmospheric CO2 concentrations, however, assuming that
they would be 375-400ppm – compared to the actual value of 370ppm.
Broecker, 1975
The first available projection of future temperatures due to global warming appeared in an article in Science in 1975 published by Columbia University scientist Prof Wally Broecker. Broecker used a simple energy balance model
to estimate what would happen to the Earth’s temperature if atmospheric
CO2 continued to increase rapidly after 1975. Broecker’s projected
warming was reasonably close to observations for a few decades, but
recently has been considerably higher.
This is mostly due to Broecker overestimating how CO2 emissions and
atmospheric concentrations would increase after his article was
published. He was fairly accurate up to 2000, predicting 373ppm of CO2 –
compared to actual Mauna Loa observations of 370ppm. In 2016, however,
he estimated that CO2 would be 424ppm, whereas only 404 pm has been observed.
Broecker also did not take other greenhouse gases into account in his model. However, as the warming impact from methane, nitrous oxide and halocarbons has been largely cancelled out by the overall cooling influence of aerosols since 1970, this does not make that large a difference (though estimates of aerosol forcings have large uncertainties).
As with Sawyer, Broecker used an equilibrium climate sensitivity of
2.4C per doubling of CO2. Broecker assumed that the Earth instantly
warms up to match atmospheric CO2, while modern models account for the
lag between how quickly the atmosphere and oceans warm up. (The slower
heat uptake by the oceans is often referred to as the “thermal inertia” of the climate system.)
You can see his projection (black line) compared to observed temperature rise (coloured lines) in the chart below.
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Projected warming from Broecker 1975 (thick black line) compared to observational temperature records from NASA, NOAA, HadCRUT, Cowtan and Way, and Berkeley Earth (thin colored lines) from 1970 to 2020. Baseline period of 1970-1990. Chart by Carbon Brief using Highcharts.
Broecker made his projection at a time when scientists widely thought that the observations showed a modest cooling
of the Earth. He began his article by presciently stating that “a
strong case can be made that the present cooling trend will, within a
decade or so, give way to a pronounced warming induced by carbon
dioxide”.
Hansen et al, 1981
NASA’s Dr James Hansen and colleagues published a paper
in 1981 that also used a simple energy balance model to project future
warming, but accounted for thermal inertia due to ocean heat uptake.
They assumed a climate sensitivity of 2.8C per doubling CO2, but also
looked at a range of 1.4-5.6C per doubling.
<br />
Projected warming from Hansen et al 1981 (fast growth–thick black
line–and slow growth–thin grey line). Chart by Carbon Brief using Highcharts.
Hansen and colleagues presented a number of different scenarios,
varying future emissions and climate sensitivity. In the chart above,
you can see both the “fast-growth” scenario (thick black line), where
CO2 emissions increase by 4% annually after 1981, and a slow-growth
scenario where emissions increase by 2% annually (thin grey line). The
fast-growth scenario somewhat overestimates current emissions, but when
combined with a slightly lower climate sensitivity it provides an
estimate of early-2000s warming close to observed values.
The overall rate of warming between 1970 and 2016 projected by Hansen
et al in 1981 in the fast-growth scenario has been about 20% lower than
observations.
Hansen et al, 1988
The paper published
by Hansen and colleagues in 1988 represented one of the first modern
climate models. It divided the world into discrete grid cells of eight
degrees latitude by 10 degrees longitude, with nine vertical layers of
the atmosphere. It included aerosols, various greenhouse gases in
addition to CO2, and basic cloud dynamics.
Hansen et al presented three different scenarios associated with
different future greenhouse gas emissions. Scenario B is shown in the
chart below as a thick black line, while scenarios A and C are shown by
thin grey lines. Scenario A had exponential growth in emissions, with
CO2 and other GHG concentrations considerably higher than today.
<br />
Projected warming from Hansen et al 1988 (scenario B–thick black
line–and scenarios A and C–thin solid and dashed grey lines). Chart by
Carbon Brief using Highcharts.
Scenario B assumed a gradual slowdown in CO2 emissions, but had concentrations of 401ppm in 2016 that were pretty close to the 404ppm observed.
However, scenario B assumed the continued growth of emissions of
various halocarbons that are powerful greenhouse gases, but were
subsequently restricted under the Montreal Protocol of 1987. Scenario C had emissions going to near-zero after the year 2000.
Of the three, scenario B was closest to actual radiative forcing, though still about 10% too high.
Hansen et al also used a model with a climate sensitivity of 4.2C per
doubling CO2 – on the high end of most modern climate models. Due to the
combination of these factors, scenario B projected a rate of warming
between 1970 and 2016 that was approximately 30% higher than what has
been observed.
IPCC First Assessment Report, 1990
The IPCC’s First Assessment Report
(FAR) in 1990 featured relatively simple energy balance/upwelling
diffusion ocean models to estimate changes in global air temperatures.
Their featured business-as-usual (BAU) scenario assumed rapid growth of
atmospheric CO2, reaching 418ppm CO2 in 2016, compared to 404ppm in
observations. The FAR also assumed continued growth of atmospheric
halocarbon concentrations much faster than has actually occurred.
The FAR gave a best estimate of climate sensitivity as 2.5C warming
for doubled CO2, with a range of 1.5-4.5C. These estimates are applied
to the BAU scenario in the figure below, with the thick black line
representing the best estimate and the thin dashed black lines
representing the high and low end of the climate sensitivity range.
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Projected warming from the IPCC First Assessment Report (mean
projection–thick black line, with upper and lower bounds shown by thin
dotted black lines). Chart by Carbon Brief using Highcharts.
Despite a best estimate of climate sensitivity a tad lower than the
3C used today, the FAR overestimated the rate of warming between 1970
and 2016 by around 17% in their BAU scenario, showing 1C warming over
that period vs 0.85C observed. This is mostly due to the projection of
much higher atmospheric CO2 concentrations than has actually occurred.
IPCC Second Assessment Report, 1995
The IPCC’s Second Assessment Report
(SAR) only published readily-available projections from 1990 onward.
They used a climate sensitivity of 2.5C, with a range of 1.5-4.5C. Their
mid-range emissions scenario, “IS92a”, projected CO2 levels of 405ppm
in 2016, nearly identical to observed concentrations. SAR also included
much better treatment of anthropogenic aerosols, which have a cooling
effect on the climate.
<br />
<br />
Projected warming from the IPCC Second Assessment Report (mean
projection–thick black line, with upper and lower bounds shown by thin
dotted black lines). Chart by Carbon Brief using Highcharts.
As you can see in the chart above, SAR’s projections ended up being
notably lower than observations, warming about 28% more slowly over the
period from 1990 to 2016. This was likely due to a combination of two
factors: a lower climate sensitivity than found in modern estimates
(2.5C vs. 3C) and an overestimate of the radiative forcing of CO2 (4.37 watts per square meter versus 3.7 used in the subsequent IPCC report and still used today).
IPCC Third Assessment Report, 2001
The IPCC Third Assessment Report
(TAR) relied on atmosphere-ocean general circulation models (GCMs) from
seven different modeling groups. They also introduced a new set of
socioeconomic emission scenarios, called SRES, which included four different future emission trajectories.
Here, Carbon Brief examines the A2 scenario,
though all have fairly similar emissions and warming trajectories up to
2020. The A2 scenario projected a 2016 atmospheric CO2 concentration of
406 ppm, nearly the same as what was observed. The SRES scenarios were
from 2000 onward, with models prior to the year 2000 using estimated
historical forcings. The dashed grey line in the figure above shows the
point at which models transition from using observed emissions and
concentrations to projected future ones.
<br />
Projected warming from the IPCC Third Assessment Report (mean
projection–thick black line, with upper and lower bounds shown by thin
dotted black lines). Chart by Carbon Brief using Highcharts.
TAR’s headline projection used a simple climate model that was
configured to match the average outputs of seven more sophisticated
GCMs, as no specific multimodel average was published in TAR and data
for individual model runs are not readily available. It has a climate
sensitivity of 2.8C per doubling CO2, with a range of 1.5-4.5C. As shown
in the chart above, the rate of warming between 1970 and 2016 in the
TAR was about 14% lower than what has actually been observed.
IPCC Fourth Assessment Report, 2007
The IPCC’s Fourth Assessment Report
(AR4) featured models with significantly improved atmospheric dynamics
and model resolution. It made greater use of Earth System Models – which
incorporate the biogeochemistry of carbon cycles – as well as improved
simulations of land surface and ice processes.
AR4 used the same SRES scenarios as the TAR, with historical
emissions and atmospheric concentrations up to the year 2000 and
projections thereafter. Models used in AR4 had a mean climate
sensitivity of 3.26C, with a range of 2.1C to 4.4C.
<br />
Projected warming from the IPCC Fourth Assessment Report (mean
projection–thick black line, two-sigma upper and lower bounds shown by
thin dotted black lines). Chart by Carbon Brief using Highcharts.
The figure above shows model runs for the A1B scenario (which is the
only scenario with model runs readily available, though its 2016 CO2
concentrations are nearly identical to those of the A2 scenario). AR4
projections between 1970 and 2016 show warming quite close to
observations, only 8% higher.
IPCC Fifth Assessment Report, 2013
The most recent IPCC report – the Fifth Assessment
(AR5) – featured additional refinements on climate models, as well as a
modest reduction in future model uncertainty compared to AR4. The
climate models in the latest IPCC report were part of the Coupled Model Intercomparison Project 5
(CMIP5), where dozens of different modeling groups all around the world
ran climate models using the same set of inputs and scenarios.
<br />
Projected warming from the IPCC Fifth Assessment Report (mean
projection–thick black line, two-sigma upper and lower bounds shown by
thin dotted black lines). Dashed black line shows blended model fields.
Chart by Carbon Brief using Highcharts.
AR5 introduced a new set of future greenhouse gas concentration scenarios, known as the Representative Concentration Pathways
(RCPs). These have future projections from 2006 onwards, with
historical data prior to 2006. The grey dashed line in the figure above
shows where models transition from using observed forcings to projected
future forcings.
Comparing these models with observations can be a somewhat tricky exercise.
The most often used fields from climate models are global surface air
temperatures. However, observed temperatures come from surface air
temperatures over land and sea surface temperatures over the ocean.
To account for this, more recently, researchers have created blended
model fields, which include sea surface temperatures over the oceans and
surface air temperatures over land, in order to match what is actually
measured in the observations. These blended fields, shown by the dashed
line in the figure above, show slightly less warming than global surface
air temperatures, as models have the air over the ocean warming faster
than sea surface temperatures in recent years.
Global surface air temperatures in CMIP5 models have warmed about 16%
faster than observations since 1970. About 40% of this difference is
due to air temperatures over the ocean warming faster than sea surface
temperatures in the models; blended model fields only show warming 9%
faster than observations.
A recent paper in Nature by Iselin Medhaug
and colleagues suggests that the remainder of the divergence can be
accounted for by a combination of short-term natural variability (mainly
in the Pacific Ocean), small volcanoes and lower-than-expected solar
output that was not included in models in their post-2005 projections.
Below is a summary of all the models Carbon Brief has looked at. The
table below shows the difference in the rate of warming between each
model or set of models and NASA’s
temperature observations. All the observational temperature records are
fairly similar, but NASA’s is among the group that includes more
complete global coverage in recent years and is thus more directly
comparable to climate model data.
Conclusion
Climate models published since 1973 have generally been quite
skillful in projecting future warming. While some were too low and some
too high, they all show outcomes reasonably close to what has actually
occurred, especially when discrepancies between predicted and actual CO2
concentrations and other climate forcings are taken into account.
Models are far from perfect and will continue to be improved over
time. They also show a fairly large range of future warming that cannot easily be narrowed using just the changes in climate that we have observed.
Nevertheless, the close match between projected and observed warming
since 1970 suggests that estimates of future warming may prove similarly
accurate.
Methodological note
Environmental scientist Dana Nuccitelli helpfully provided a list of past model/observation comparisons, available here. The PlotDigitizer software
was used to obtain values from older figures when data was not
otherwise available. CMIP3 and CMIP5 model data was obtained from KNMI Climate Explorer.
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