Summary of Workshop on Summary of Workshop on GHG Stabilization - - PowerPoint PPT Presentation

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Summary of Workshop on Summary of Workshop on GHG Stabilization Scenarios GHG Stabilization Scenarios (22 (22-

• 23 January, 2004, Tsukuba)

23 January, 2004, Tsukuba)

Junichi Fujino

The 9th AIM International Workshop; 12-13, March 2004 National Institute for Environmental Studies, Tsukuba, Japan

IV-2

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Overview

• SRES (2000) and Post SRES (2001)

– SRES: long-term(-100yr) social and environment baseline emission scenario – Post SRES: stabilization scenarios target on

• Reduce CO2 emissions
• Stabilize concentration (450, 550, 650, 750ppm…)
• EMF21 (since 2002)

– Multi-gas (CO2, CH4, N2O, HFC, PFC, SF6) control – Stabilize radiative forcing (4.5W/m2 after 2150)

• Workshop on GHG Stabilization Scenarios (2004)

– What should be the stabilization levels? – Downscaling of scenarios – Fully integrated scenarios

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Components

Economy/Emission Models Climate Models Impact Models Stabilization Target

Nakicenovic # Nakicenovic #4 4 I I AS A&TU W 20 4 I I AS A&TU W 20 4

INTERGOVERNMENTAL PANEL ON CLIMATE CHANGE (IPCC)

Next Steps on Urgent Issues from IPCC/TAR

• Limitations of downscaling need to be considered

(need for scaling methods; other to proportional)

• Emissions modeling community could be asked to

include all GHGs and particulates in multigases baseline scenarios

• Role of additional GHGs and particulates to be

considered in stabilization scenarios (e.g. burden- sharing; uncertainties)

Neboj Nebojš ša a Naki Nakić ćenovi enović ć

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EMF21 scenarios EMF21 scenarios for long for long-

• term model

term model

Modeler’s reference (B2-like) (1) BaU Stabilize radiative forcing at 4.5 W/m^2 by 2150 relative to pre-Industrial times (2) Long-term stabilization scenarios (2-1) CO2 only (2-2) multi gas global mean temperature change to an average decadal rate of 0.20ºC (3) Long-term stabilization scenarios with rate of temperature change (3-1) CO2 only (3-2) multi gas

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2 4 6 8 10 12 14 16 20 20 10 20 20 20 30 20 40 20 50 20 60 20 70 20 8 20 90 210 Anthr

• pogeni

c G H G em i ssi

• ns

( G tC -eq/yr ) CO2 CH4 N 2O CO2( BaU ) CH4 ( BaU ) N 2O( BaU ) 2 4 6 8 10 12 14 16 20 20 10 20 20 20 30 20 40 20 50 20 60 20 70 20 8 20 90 210 Anthr

• pogeni

c G H G em i ssi

• ns

( G tC -eq/yr ) CO2 CH4 N 2O CO2( BaU ) CH4 ( BaU ) N 2O( BaU ) 2 4 6 8 10 12 14 16 20 20 10 20 20 20 30 20 40 20 50 20 60 20 70 20 8 20 90 210 Anthr

• pogeni

c G H G em i ssi

• ns

( G tC -eq/yr ) CO2 CH4 N 2O

Anthropogenic Anthropogenic GHG emissions GHG emissions

BaU CO2 only multi gas

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Discussions from Emission Modeling

• The inclusion of non-CO2 gases has important

implications for stabilization.

• Limiting the change in radiative forcing at 4.5W/m2

implies stabilizing CO2 concentrations at 500 ppm and temperature at 2 degree.

• Uncertainty in climate sensitivity has huge

implications for a 2oC limit on GMT change:

– Low climate sensitivity means no mitigation until the second half

• f the century

– High climate sensitivity means immediate, radical emissions mitigation.

• An improved technology portfolio could reduce the

cost substantially; e.g. demand reduction, fuel switching, carbon capture and storage, bio-technology, hydrogen and advanced transportation systems.

Based on Dr. Jae Edmonds’ presentation

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Topic of Climate models

AOGCM

• Downscaling, High resolution
• Earth system modeling for the carbon cycle and

chemical mass transport

• ENSEMBLE – The European climate modeling

project

• Probability density functions of temperature

change Simple climate models

• revised MAGICC carbon cycle model
• Climate sensitivity

9 Chemical Mass Transport Ozone CMT Aerosol CMT Carbon Cycle Ice Sheet and Glacier

Global MRI-CGCM2 300km/250km Asian Regional Climate model 60km Coupled Regional Climate Model 20km/20km Cloud Resolving Regional Climate Model 5km Global AGCM 20km

Climate Modeling at MRI

Akira Noda

Stott and Kettleborough, 2002

Probability density functions of temperature change simulated with the Hadley Centre model

Ulrich Cubasch

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FOSSIL EMISSIONS FOR STABILIZATION PROFILES

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1 2 3 4 5 6 7 8 9 10 11 12 13 2000 2050 2100 2150 2200 2250 2300 2350 2400 YEAR FOSSIL CO2 EMISSIONS (GtC/yr) 650 550 450 350

It seems likely that overshoot pathways would reduce mitigation costs much more than they would increase climate-change damages – unless there are nonlinearities that lead to much larger damages if thresholds are passed Tom Wigley

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Topic of Impact models

• Impact analysis on water resource/

agriculture/ health/ natural vegetation/ biodiversity…

• Risk and robustness, Uncertainty,

Investment to avoid damage

• Critical impact thresholds

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Stabilization scenarios and climate scenario for impact assessment

GCM experiments driven by variety of stabilization scenarios

It is usually infeasible and unexciting work for GCM modelers to simply

repeat simulations.

Utilization of SRES-based (or other existing) GCM simulation as

substitution

Emission trajectory in 21st century may cause a significant difference on

spatial pattern of climate change.

Pattern scaling (SCM’s result + GCM’s spatially high-resolution info.)

Pattern scaling is based on the very rigid assumption. Pattern scaling which considers spatial difference of climate changes

caused by GHGs and Aerosols separately might be better for considering stabilization scenario.

It is difficult for majority of impact researchers to judge what is the

best way to develop climate scenarios.

Kiyoshi Takahashi

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Stabilization scenarios and adaptation

Socio-economic conditions assumed in the

background of stabilization scenarios affect adaptive capacity.

Socio-economic scenarios reported in

SRES scenario (4 regions in the world) was spatially too rough.

GDPpc is not the only factor of adaptive

capacity.

Kiyoshi Takahashi

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Stabilization scenario and resources

GHGs mitigation options assumed in some

stabilization scenarios may compete with adaptation options for the usage of limited resources.

Agricultural land for crop cultivation may be exploited

by land for biomass farm in some scenarios.

More comprehensive integrated assessment

framework seems required to treat this relation.

Kiyoshi Takahashi

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Climate impacts from IMAGE 2.2| Tom Kram et al.

Biodiversity: EUROMOVE/IMAGE

(Note: RIVM contribution to Nature article)

• EUROMOVE estimates presence of 1400 vascular

plant species in gridcells from 6 climate variables

• Calibration with Atlas Flora Europaeae (1989)
• Aggregated to 20 European regions
• Climate variables from IMAGE + GCM patterns
• Baseline (CPI) and stab.scenarios (S550, S450)
• Sensitivity to different GCM patterns

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Climate impacts from IMAGE 2.2| Tom Kram et al.

Stable Area in Europe

80% 83% 82% 64% 73% 78% 0% 25% 50% 75% 100% CPI S550 S450 CPI S550 S450

2050 2100

Source: Bakkenes & Eickhout, 2004 (in prep.)

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Issues in Designing Stabilization Scenarios

• Whether of Not to Use Stabilization Targets?

– Could Just Project Implications of Baselines & Baselines X Policies – Possible Ranges of Various Metrics Could Then Be Highlighted

• What to Stabilize (or Report) and When?

– Concentrations – Radiative Forcing – Temperature or Other Climate Changes – Climate Change Impacts – Rates of Change of Any of the Above

• What Range of Stabilization Targets to Consider?
• What Baseline Assumptions to Use?
• What Transition Pathways to Consider (Implementation

Uncertainty)?

• What Policy Options to Include (Implementation Feasibility)?

– Carbon Taxes – R&D, Technology Diffusion and Transfer – Non-CO2 Gases, Sinks, Etc.

John P. Weyant

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Issues in Designing Stabilization Scenarios

• How to Provide Hedging Relevant Information Via Scenarios?

– For “No Surprise, “Surprise” or “Not Implausible” Scenarios – Adaptation and Implementation as Risk Mgt. Tools

• What to Assume About International Trade?
• What Burden Sharing Assumptions to Make?
• What to Assume About Other “Climatically Important

Substances?”

• What Feedbacks to Consider?

– Land-Use – Carbon Cycle

• How to Provide Useful Input to Impacts Community?

– Down-Scaling of GCM Information – Down-Scaling of Socio Economic Information – Input to - And Input From - Adaptation Community

• What Outputs to Look At?

– Shorter Run “Metrics” – Meaningful “Longer Run” Metrics – Implementability Metrics

John P. Weyant

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– What should be the stabilization levels? – Uncertainty in climate sensitivity, technology, climate impact – Bridge short-middle term countermeasures and long- term ultimate target

Discussion will be continued intensively…

Develop and Enhance IAM IPCC new database

This workshop homepage can be browsed at “http://www-iam.nies.go.jp/aim/workshop.htm”