3.2: Future climate change and
climate forcing
Emissions of
greenhouse gases from human activity, particularly carbon dioxide, will largely
determine the magnitude of climate change over the next century. Therefore,
reducing human emissions will reduce future climate change.
Projections
of future climate change require projections of future climate forcing — the
external drivers of change such as GHGs and aerosols. These projections, in
turn, arise from scenarios of future GHG and aerosol emissions, which are based
on varying assumptions about how human activities, such as fossil fuel
consumption and land use, will change. Future emission scenarios are typically
developed using integrated assessment models, which combine economic,
demographic, and policy modelling with simplified physical climate models to
make projections of population growth, economic development, land use, and the
implications of different policy options on climate-relevant emissions. As
there is large uncertainty in the social and economic aspects of such
projections, a range of scenarios is generally provided, ranging from those in
which emissions are aggressively reduced to those with limited actions taken to
mitigate emissions.
The
projections described in the IPCC Fifth Assessment (see Chapter 1) were based
on a suite of future forcing scenarios called Representative Concentration
Pathways (RCPs) that cover the period from 2006 onward (van Vuuren et al.,
2011). The RCPs are identified by a number indicating the change in radiative
forcing — the imbalance between the solar radiation entering the climate system
and the infrared (longwave) radiation leaving it caused by greenhouse gases and
other external drivers (see Chapter 2, Section 2.3.1) — by the end of the 21st
century. RCP2.6 represents a low emission pathway with a change in radiative
forcing of roughly 2.6 W/m2, RCP4.5 and RCP6 represent intermediate
emission pathways, and RCP8.5 represents a pathway with continued growth in GHG
emissions, leading to a radiative forcing of roughly 8.5 W/m2 at the end
of the century. In this report, we will refer to climate scenarios based on
RCP2.6 as “low emission scenarios,” those based on RCP4.5 and RCP6 as “medium emission
scenarios,” and those based on RCP8.5 as “high emission scenarios.” For each
RCP, the integrated assessment models provide a comprehensive time series of
emissions and concentrations of individual GHGs (CO2, methane [CH4], nitrous
oxide [N2O], chlorofluorocarbons, etc.), along with aerosol emissions and
land-use change. All of these forcings are inputs to Earth system models, which
then simulate the future response of the climate system, including
biogeochemical feedbacks, to these external forcing scenarios.
The RCPs
supersede the so-called “SRES scenarios” (Nakicenovic et al., 2000), which
served as the basis for model runs reported in the IPCC Fourth Assessment
Report. Although there are differences in detail, the SRES A2 forcing scenario
is roughly comparable to RCP8.5, the SRES A1B scenario is roughly midway
between RCP6 and RCP8.5, and SRES B1 is roughly comparable to RCP4.5 (e.g.,
Burkett et al., 2014). There was no SRES forcing scenario comparable to RCP2.6.
These forcing scenarios are updated every few years, and new shared
socioeconomic pathways (building upon the RCPs) will be used in model runs that
will feed into the upcoming IPCC Sixth Assessment (e.g., Riahi et al., 2017).
In all
cases, CO2 is the largest contributor to the historical and projected change
radiative forcing, followed by CH4 and N2O (Myhre et al., 2013; Collins et al.,
2013). This means that future changes in human emissions of CO2 will largely
determine future climate.
An
illustration of aspects of the RCPs is shown in Figure 3.1. It is important to
note that no likelihoods are ascribed to these future forcing scenarios — they
are all deemed plausible, although, as emissions continue to increase, low
emission pathways become more difficult to achieve (e.g., Millar et al., 2017).
The spread across the RCPs represents some measure of our uncertainty about how
socioeconomic factors may change in the future, especially how aggressively
humans will pursue emission mitigation, and therefore the pace at which humans
will continue to drive climate change. The low emission (RCP2.6) scenario is
consistent with limiting global temperature increase to roughly 2ºC above the
pre-industrial value (see Section 3.3.3) and is therefore roughly compatible
with the global temperature goal agreed to in the Paris Agreement (UNFCCC,
2015). This scenario requires global CO2 emissions to peak almost immediately
and reduce to near zero well before the end of the century. Global annual CO2
emissions reached about 10 Gt of carbon (about 37 GtCO2) in 2017 (Le Quéré
et al., 2017)
3.3: Modelling the response of the
climate system to external forcing
In the near
term (to approximately 2040), projected warming will be similar under all
emission pathways. But by the late 21st century, the differences between possible
emissions pathways will have a considerable effect. Available estimates
indicate that the global climate will warm by an additional 1ºC (for a low
emission scenario) to 3.7ºC (for a high emission scenario). Scenarios that
would limit warming to an additional 1ºC or less require rapid and deep
emission reductions.
3.3.1: Earth system models
Earth system
models are based on a mathematical representation of the behaviour of the
atmosphere, ocean, land surface, and cryosphere. They simulate a virtual planet
using powerful supercomputers, allowing scientists to probe the connections
between various physical and biogeochemical processes, e.g., how the ocean
takes up heat and carbon, stores and then redistributes it. Two main ways such
models are used are (1) to compare simulations with and without historical
forcings to determine human versus natural forcing effects, and (2) to simulate
future climate in response to various forcing scenarios.
Earth system
models have some features in common with global weather-prediction models (used
to make daily weather forecasts) but do not depend on the use of observations
as inputs and typically operate at somewhat lower spatial resolution (i.e., the
level of spatial detail is often limited to features with scales of a hundred
kilometres or larger). The lower resolution is necessitated by the computing
demand of the long simulations that are required. Simulations begin with the
historical period (from 1850 to present), driven by observationally based
climate forcing (e.g., historical changes in GHG concentrations), and then
continue into the future, using different forcing scenarios (such as those
described in the previous section) out to year 2100 or further.
Earth system
models represent an evolution from earlier physical climate models
(representing the coupled atmosphere, ocean, land, and sea ice components of
the climate system) to models that go beyond this with explicit representation
of the carbon cycle (Flato, 2011; Flato et al., 2013). Including carbon and
other biogeochemical cycles in the models allows simulation of global
interactions among ecosystems, carbon, and climate, as well as several
terrestrial processes that occur at high latitudes. Changes to snow and sea ice
can cause positive (amplifying) snow/ice albedo feedbacks in the climate system
(Euskirchen et al., 2016; Kashiwase et al., 2017; see Chapter 2, Box 2.4). As
temperatures increase, the spatial extent of snow and sea ice declines,
reducing the reflectivity of land and oceans, allowing more solar radiation to
be absorbed, and hence further increasing temperatures. This feedback makes an
important contribution to the higher rate of warming in the Arctic region,
called Arctic amplification (FAQ 3.1; see Section 3.3.3). The models can also
simulate increased growth of vegetation at northern high latitudes in response
to a warming climate, an effect that may reduce the land surface albedo and
affect the exchange of energy and water between the land and the atmosphere
(Forkel et al., 2016). Changes in permafrost in response to changing climate —
leading to changes in hydrological conditions and CH4 release (Schuur et al.,
2008) — are also now included in some models.
How do we
know that models are accurately projecting future climate? One method of
measuring whether models can realistically represent the complex
interconnections among climate processes is to gauge their ability to reproduce
past changes. Simulations using observationally based historical forcing from
1850 onward provide the opportunity to directly compare model results to
observations. The IPCC Assessment Reports have traditionally included a chapter
devoted to this type of model evaluation (e.g., Flato et al., 2013), and these
provide a synthesis of the large number of scientific papers on model
performance. Figure 3.5 provides one example of model evaluation, comparing the
annual global mean surface air temperature from several different sources with
simulations from 36 different models that participated in the fifth phase of
the Coupled Model Intercomparison Project (CMIP5; see Box 3.1). Earth system models are able to reproduce the
observed long-term increase in temperature (heavy black lines), along with the
sporadic cooling that follows large explosive volcanic eruptions. The magnitude
of natural year-to-year variability is also well simulated (thin lines),
although one does not expect individual ups and downs to coincide (as each
model simulates its own internal variability). The heavy red line in the figure
shows the multi-model average, which is an approximation of the response of the
climate system to external forcing (changing GHG concentrations and aerosol
amount, land-use change, variations in solar irradiance, and volcanic aerosol),
upon which internal variability is superimposed. The difference between
observed temperature and the multi-model average from roughly 2000 onward has
been extensively analyzed (e.g., Fyfe et al., 2016) and is due to a combination
of small errors in the observational record, decadal timescale internal variability,
and incomplete early 21st century volcanic forcing in the models.
No comments:
Post a Comment