The six models have different regional aggregations. The writing team decided
to group the various global regions into four "macro-regions" common to all
different regional aggregations across the six models. The four macro-regions
(see Appendix III) are broadly consistent with the
allocation of countries in the United Nations Framework Convention on Climate
Change (UNFCCC, 1997) although the correspondence is not exact because of changes
in the countries listed in Annex I of UNFCCC.
All the qualitative and quantitative features of scenarios that belong to the
same family were set to conform to the corresponding features of the underlying
storyline. Together, 26 scenarios were "harmonized" to share agreed common assumptions
about population and gross domestic product (GDP) developments (a few that also
share common final energy trajectories are called "fully harmonized," see Section
4.1. in Chapter 4). Thus, the harmonized scenarios are not independent of
each other within each family, but they are independent across the four families.
However, scenarios within each family vary quite substantially in characteristics
such as the assumptions about availability of fossil-fuel resources, the rate
of energy-efficiency improvements, the extent of renewable-energy development,
and, hence, the resultant GHG emissions. Thus, after the modeling teams had
quantified the key driving forces and made an effort to harmonize them with
the storylines by adjusting control parameters, there still remained diversity
in the assumptions about the driving forces and in the resultant emissions (see
Chapter 4).
Box 6-2: SRES Modeling Teams
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In all, six models were used to generate the 40 scenarios:
- Asian Pacific Integrated Model (AIM) from the National Institute of
Environmental Studies in Japan (Morita et al., 1994);
- Atmospheric Stabilization Framework Model (ASF) from ICF Consulting
in the USA (Lashof and Tirpak, 1990; Pepper et al., 1992, 1998;
Sankovski et al., 2000);
- Integrated Model to Assess the Greenhouse Effect (IMAGE) from the
National Institute for Public Health and Environmental Hygiene (RIVM)
(Alcamo et al., 1998; de Vries et al., 1994, 1999, 2000),
used in connection with the Dutch Bureau for Economic Policy Analysis
(CPB) WorldScan model (de Jong and Zalm, 1991), the Netherlands;
- Multiregional Approach for Resource and Industry Allocation (MARIA)
from the Science University of Tokyo in Japan (Mori and Takahashi, 1999;
Mori, 2000);
- Model for Energy Supply Strategy Alternatives and their General Environmental
Impact (MESSAGE) from the International Institute of Applied Systems
Analysis (IIASA) in Austria (Messner and Strubegger, 1995; Riahi and
Roehrl, 2000); and the
- Mini Climate Assessment Model (MiniCAM) from the Pacific Northwest
National Laboratory (PNNL) in the USA (Edmonds et al., 1994,
1996a, 1996b).
For a more detailed description of the modeling approaches see Appendix
IV.
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The remaining 14 scenarios adopted alternative interpretations of the four
scenario storylines to explore additional scenario uncertainties beyond differences
in methodologic approaches, such as different rates of economic growth and variations
in population projections. These variations reflect the "modeling teams' choice"
of alternative but plausible global and regional developments compared to those
of the "harmonized" scenarios; they also stem from the differences in the underlying
modeling approaches. This approach generated a large variation and richness
in different scenario quantifications, often with overlapping ranges of main
driving forces and GHG emissions across the four families.
In addition, the A1 scenario family branched out into different distinct scenario
groups, based on alternative technological developments in future energy systems,
from carbon-intensive development to decarbonization. Similar storyline variations
were considered for other scenario families, but they did not result in genuine
scenario groupings within the respective families. However, if future energy
systems variations were applied fully to other storylines, they may evolve differently
from those in A1. They have been introduced into the A1 storyline because of
its "high growth with high technology" nature, for which differences in alternative
technology developments translate into large differences in future GHG emission
levels. The A1 groups further increased the richness in different GHG and SO2
emissions paths. Indeed, this variation in the structure of future energy systems
in itself resulted in a range of emissions almost as large as that generated
through the variation of other main driving forces, such as population and economic
development. Altogether the 40 SRES scenarios fall into seven groups: the three
scenario families A2, B1, and B2, plus four groups within the A1 scenario (see
footnote 2).
As in the case of the storylines, no single scenario - whether it represents
a modeler's choice or harmonized assumptions - was treated as being more or
less "probable" than others belonging to the same family. However, one preliminary
harmonized scenario from each family, referred to as a "marker," was used in
1998 to solicit comments during the "open process" and as input for climate
modelers in accordance with a decision of the IPCC Bureau. The four marker scenarios
were posted on the IPCC web site (sres.ciesin.org) in June 1998, and the open
scenario review process through the IPCC web site lasted until January 1999.
The choice of markers was based on extensive discussion of:
- Range of emissions across all of marker scenarios.
- Which of the initial quantifications (by the modelers) reflected the storyline.
- Preference of some of the modeling teams and features of specific models.
- Use of different models for the four markers.
Markers were not intended to be the median or mean scenarios from their respective
families. Indeed, in general it proved impossible to develop scenarios in which
all relevant characteristics matched mean or median values. Thus, marker scenarios
are no more or less likely than any other scenarios, but are those scenarios
considered by the SRES writing team as illustrative of a particular storyline.
These scenarios have received much closer scrutiny, not only from the entire
writing team, but also via the SRES open process, than other scenario quantifications.
The marker scenarios are also the SRES scenarios that have been most intensively
tested in terms of reproducibility. As a rule, different modeling teams have
attempted to replicate the model quantification of marker scenarios. Available
time and resources have not allowed a similar exercise to be conducted for all
SRES scenarios, although some effort was devoted to reproduce the scenario groups
that constitute different interpretations of the A1 storyline with different
models.
Figure 6-1: Schematic illustration
of SRES scenarios. The set of
scenarios consists of the four scenario
families A1, A2, B1, and
B2. Each family consists of a number of scenarios,
some of which
have "harmonized" driving forces and share the same prespecified
population and gross world product (a few that also share common
final
energy trajectories are called "fully harmonized"). These are
marked
as "HS" for harmonized scenarios. One of the harmonized
scenarios, originally
posted on the open-process web site, is called
a "marker scenario."
All other scenarios of the same family based
on the quantification of
the storyline chosen by the modeling team
are marked as "OS." Six modeling
groups developed the set of 40
emissions scenarios. The GHG and SO2
emissions of the scenarios
were standardized to share the same data
for 1990 and 2000 on
request of the user communities. The time-dependent
standardized
emissions were also translated into geographic distributions.
See
also footnote
2.
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Additional scenarios using the same harmonized assumptions as the marker scenarios
developed by different modeling teams and other scenarios that give alternative
quantitative interpretations of the four storylines constitute the final set
of 40 SRES scenarios. However, differences in modeling approaches mean that
not all the scenarios provide estimates for all the direct and indirect GHG
emissions for all the sources and sectors. The four SRES marker scenarios cover
all the relevant gas species and emission categories comprehensively and thus
constitute the smallest set of independent and fully documented SRES scenarios.
The scenario groups and cumulative emissions categories were developed as the
smallest subsets of SRES scenarios that capture the range of uncertainties associated
with driving forces and emissions. Together, the scenario groups constitute
the set of SRES scenarios that reflects the uncertainty ranges in the emissions
and their driving forces. Furthermore, the writing team recommends that, to
the extent possible, these scenarios, but at least the four markers, be used
to capture the range of uncertainties of driving forces and in addition, the
two additional illustrative scenarios in A1 be used to capture the range of
GHG emissions, and these should always be used together, and that no individual
scenario should be singled out for any purpose. Multiple baselines and overlapping
emissions ranges have important implications for making policy analysis (e.g.,
similar policies might have different impacts in different scenarios). Combinations
of policies might shape the future development in the direction of certain scenarios.
Box 6-4 (see later) summarizes the recommendations
of the writing team for consideration by the user communities within and outside
the IPCC.
Thus, there are three different types of scenarios within each family - one
marker (and two illustrative scenarios in the A1 family), a set of harmonized
scenarios, and a set of other (non-harmonized) scenarios. In addition, the A1
family of scenarios is subdivided into groups that describe alternative technological
developments in the energy system. Together with the other three scenario families
the SRES scenarios build seven distinct scenario groups (see footnote
2). Figure 6-1 illustrates this scenario terminology
schematically. The detailed descriptions of inputs and outputs (other than GHG
emissions) of the SRES marker scenarios, other harmonized scenarios, and all
other scenarios are presented in Chapter 4 and the Appendices,
while the emissions of GHGs and other radiatively important species of gases
are described in Chapter 5 and Appendices.
The writing team considers that the SRES scenario set (in all the richness
of scenario families, groups, markers, and illustrative and harmonized scenarios)
is based on a "neutral" choice of scenario drivers; no driver is unduly emphasized
as being more important than others. The scenarios do not suggest that future
population growth alone is the driver of future emissions, nor do they suggest
that technological change alone in any one sector could drive future emissions
in one way or the other. While recognizing the importance of any of these driving
forces per se, this report illustrates the critical role of relationships and
interdependencies between scenario driving forces. To an extent it is the nature
of these relationships that drives the future more than the possible evolution
of any individual driving forces by itself. In other words, the uncertainty
of the future is not simply parametric, but deeply functional; uncertainties
and incomplete understanding exist for both. Qualitative scenario storylines
add transparency and consistency to the relationships assumed in any particular
scenario. The storylines also allow for additional interpretation of scenario
results by different user communities.
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