Transcript Lect10_ipcc

Intergovernmental Panel on Climate
Change (IPCC)
The IPCC is the leading international body for the assessment of
climate change. It was established by the United Nations
Environment Programme (UNEP) and the World Meteorological
Organization (WMO) to provide the world with a clear scientific
view on the current state of knowledge in climate change and its
potential environmental and socio-economic impacts.
The IPCC is a scientific body. It reviews and assesses the most
recent scientific, technical and socio-economic information
produced worldwide relevant to the understanding of climate
change. It does not conduct any research nor does it monitor
climate related data or parameters.
The IPCC is an intergovernmental body. It is open to all member
countries of the United Nations (UN) and WMO. Currently 194
countries are members of the IPCC.
Climate Scenarios and Emissions Scenarios
Future levels of global GHG emissions are the products of a very complex, illunderstood dynamic system, driven by forces such as population growth, socioeconomic development, and technological progress; thus to predict emissions
accurately is virtually impossible. However, near-term policies may have
profound long-term climate impacts. Consequently, policy-makers need a
summary of what is understood about possible future GHG emissions, and given
the uncertainties in both emissions models and our understanding of key driving
forces, scenarios are an appropriate tool for summarizing both current
understanding and current uncertainties.
Scenario Definition
• Image of future
• Neither forecast nor prediction
• Each scenario is one possible future– Set of scenarios possible future
developments of complex systems
• Useful tool for not fully understood complex systems, whose prediction is
impossible, e.g. population growth, use of fossil fuels and GreenHouse
Gases (GHG) emissions
• Emission scenario ≠ climate scenario
Scenarios can be viewed as a linking tool that integrates qualitative narratives or
stories about the future and quantitative formulations based on formal modeling. As
such they enhance our understanding of how systems work, behave and evolve.
How are scenarios formulated?
Scenarios are formulated with the help of numeric or analytic formal models.
Scenario development
1990 IPCC SA90 emission scenarios;
1992 IPCC IS92 emission scenarios
1999 IPCC Special Report on Emission Scenarios (SRES)
2007 IPCC AR4 uses SRES and IS92 scenarios
2009 Representative Concentration Pathways (RCPs)
2014 IPCC AR5 uses RCPs
Emission
SRES: Special Report on Emission Scenarios used in AR4
Main driving forces of future emissions:
1. Population prospects
2. Economic development
3. Energy intensities and demand, structure of its use
4. Resource availability
5. Technological change
6. Prospects for future energy systems
7. Land-use changes
different future developments
GHG total emissions
40 different scenarios
Storylines of scenarios
A1: • Rapid economic growth.
• Peak population mid-21st century, then,
declining.
• Rapid introduction of new and more
efficient technologies.
• Substantial reduction of regional
difference in per-capita income.
A2: • Regional solutions to environmental
and social equity issues.
• Continuously rising world population.
• Slow per-capita income growth
technological development
B1: • Rapid changes in economic structures.
• Peak population mid-21st century, then, declining, as in A1.
• Reduction in intensity of demand for materials.
• Introduction of clean and resource efficient technologies.
• Global solutions to environmental and social equity issues.
B2: •
•
•
•
Intermediate economic development.
Moderate population growth.
Less rapid and more diverse technological change than in the B1 and A1.
Regional solutions to environmental and social equity issues.
A1FI: Fossil fuel intensive
A1B: Balanced emphasis on
all energy sources
A1T: Non-fossil fuel intensive
A1B
A1FI
A1T
Uncertainties and Scenario Analysis
Uncertainties may be caused by socio-economic conditions, technology,
policy environment, representations of processes in assessment models,
‘rare’ events, …
Three types of uncertainties:
•
data uncertainties,
•
modeling uncertainties,
•
completeness uncertainties.
Data uncertainties arise from the quality or appropriateness of the
data used as inputs to models. Modeling uncertainties arise from an
incomplete understanding of the modeled phenomena, or from
approximations that are used in formal representation of the
processes. Completeness uncertainties refer to all omissions due to
lack of knowledge. They are, in principle, non-quantifiable and
irreducible.
CMIP: Coupled Model Intercomparison Project
• Program for Climate Model Diagnosis and Intercomparison
(PCMDI)
• Standard experimental protocol for coupled atmosphere-ocean
general circulation models (AOGCMs)
• Since 1995
• Phase 1: control runs (constant emissions)
• Phase 2: idealized global warming scenarios
• Phase 3: ‘realistic’ climate scenarios
– CMIP3 models used for IPCC AR4
• Phase 4: testing climate models for forecasting abilities
• Phase 5: improved Phase 3
– CMIP5 used for IPCC AR5
Range of global surface warming