7. Quantitative Scenarios and Modeling Approaches
Box TS-2: The Six Modeling Teams that
Quantified the 40 SRES Scenarios
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
- Mini Climate Assessment Model (MiniCAM) from the Pacific Northwest
National Laboratory (PNNL) in the USA (Edmonds et al., 1994,
1996a, 1996b).
These six models are representative of emissions scenario modeling approaches
and different IA frameworks in the literature and include so-called top-down
and bottom-up models. For a more detailed description of the modeling
approaches see Appendix IV.
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The storylines were essentially complete by January 1998. After determining
the basic features and driving forces for each of the four storylines, the six
modeling groups represented on the writing team (on a voluntary basis) began
quantifying them. The six modeling groups that quantified the storylines are
listed in Box TS-2. Each model quantification of
a storyline constitutes a scenario, and all scenarios derived from one storyline
constitute a scenario family. The six models are representative of different
approaches to modeling emissions scenarios and different integrated assessment
(IA) frameworks
The storylines were essentially complete by January 1998. After determining
the basic features and driving forces for each of the four storylines, the six
modeling groups represented on the writing team (on a voluntary basis) began
quantifying them. The six modeling groups that quantified the storylines are
listed in Box TS-2. Each model quantification of
a storyline constitutes a scenario, and all scenarios derived from one storyline
constitute a scenario family. The six models are representative of different
approaches to modeling emissions scenarios and different integrated assessment
(IA) frameworks in the literature and include so-called top-down and bottom-up
models. The writing team recommends that IPCC or a similar international institution
should assure participation of modeling groups around the world and especially
from developing countries in any future scenario development and assessment
efforts. Clearly, this would also require resources specifically directed at
assisting modeling groups from developing countries. Indeed, a concerted effort
was made to engage modeling groups and experts from developing countries in
SRES as a direct response to the recommendations of the last IPCC scenario evaluation
(Alcamo et al., 1995).
The six models have different regional aggregations. The writing team decided
to group the various global regions into four "macro-regions" common to all
the different regional aggregations across the six models. Box
TS-3 indicates that 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, 1992), although the correspondence
is not exact because of changes in the countries listed in Annex I of UNFCCC
(1997).
Box TS-3: SRES
World "Macro-Regions" Used by All Six Modeling Teams
The six models have different regional aggregations. The writing team
decided to group the various global regions into four "macro-regions"
common to all the different regional aggregations across the six models.
The four macro-regions (see Appendix III) are
broadly consistent with the allocation of the countries in the United
Nations Framework Convention on Climate Change (UNFCCC, 1992), although
the correspondence is not exact due to changes in the countries listed
in Annex I of UNFCCC (1997):
- The OECD90 region groups together all countries belonging to the Organization
for Economic Cooperation and Development (OECD) as of 1990, the base
year of the participating models, and corresponds to Annex II countries
under UNFCCC (1992).
- The REF region stands for countries undergoing economic reform and
groups together the East European countries and the Newly Independent
States of the former Soviet Union. It includes Annex I countries outside
Annex II as defined in UNFCCC (1992).
- The ASIA region stands for all developing (non-Annex I) countries
in Asia.
- The ALM region stands for rest of the world and includes all developing
(non-Annex I) countries in Africa, Latin America, and the Middle East.
In other words, the OECD90 and REF regions together correspond to the
developed (industrialised) countries (referred to as IND in this report)
while the ASIA and ALM regions together correspond to the developing countries
(referred to as DEV in this report). The OECD90 and REF regions are consistent
with the Annex I countries under the Framework Convention on Climate Change,
while the ASIA and ALM regions correspond to the non-Annex I countries
(UNFCCC, 1992).
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All the qualitative and quantitative features of scenarios belonging 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 global population and GDP (gross domestic product) development (a few
that also share common population, GDP, and final energy trajectories at the
level of the four SRES macro-regions are called "fully harmonized," see Section
4.1. in Chapter 4). Thus, the harmonized scenarios are not independent within
each of the four families. However, scenarios within each family vary quite
substantially in such characteristics as the assumptions about availability
of fossil-fuel resources, the rate of energy-efficiency improvements, the extent
of renewable-energy development, and, hence, 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).
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 development compared to "harmonized"
scenarios and also stem from the differences in the underlying modeling approaches.
Each of the 40 quantifications of one of the storylines constitutes a SRES scenario.
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 four distinct scenario
groups. They are based on four 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. This
further increased richness in different GHG and SO2 emissions paths, because
this variation in the structure of the 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. It
should be noted that future energy systems variations could be applied to the
other storylines, but 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, where differences in alternative technology developments
translate into large differences in future GHG emission levels. Altogether the
40 SRES scenarios fall into seven groups: the three scenario families, A2, B1,
and B2, plus four groups within the A1 scenario. In the SPM, two of these groups,
the coal and gas and oil intensive groups, were merged into one fossil-intensive
group, leading to six groups.
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 the others belonging to the same family. Initially, for
each storyline, one modeling group was given principal responsibility, and the
quantification produced by that group is referred to as the "marker" scenario
for that storyline. The four preliminary marker scenarios were 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 in 1998. The four marker scenarios
were posted on the SRES web site (http://sres.ciesin.org/)
in June 1998 and were subsequently revised to account for comments and suggestions
received through this open scenario review process that lasted until January
1999. In addition to many revisions, the marker scenarios were also harmonized
along with the other 26 scenarios that adopted common assumptions for the main
driving forces within the four respective families. The choice of the 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
best;
- preference of some of the modeling teams and features of specific models;
- use of four different models for the four markers.
As a result the 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 match 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 the closest scrutiny
of the entire writing team and via the SRES open process compared to other scenario
quantifications. The marker scenarios are also those 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 four scenario groups (merged into three in the SPM) that constitute
different interpretations of the A1 storyline with different models.
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. This also means that the 40 scenarios are not independent
of each other as they are all based on four storylines and subdivided into seven
scenario groups (after merging two groups, six in the SPM) that share many common
assumptions. In addition to many revisions of the marker and other harmonized
scenarios, other alternative scenarios were formulated by the six modeling teams
within each of the four scenario families. The result is a more complete, refined
set of 40 emissions scenarios that reflects the broad spectrum of modeling approaches
and regional perspectives. However, differences in modeling approaches have
meant that not all of the scenarios provide estimates for all the direct and
indirect GHG emissions for all the sources and sectors. In addition to the marker
scenarios, two scenarios were also selected in the SPM to illustrate the alternative
energy systems developments in the A1 family. Hence, this report has an illustrative
scenario for each of the six scenario groups in the SPM. The four SRES marker
scenarios and the two illustrative scenarios (selected in the SPM) 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 four markers and the two additional
illustrative scenarios selected in the SPM from the A1 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 and the
two additional illustrative scenarios selected in the SPM, should always be
used together, and that, in general, 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. Combination of policies might
shape the future development in the direction of certain scenarios.
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