1 match paper 1: contributions to climate change sb-23 17 may 2006 niklas höhne

1

MATCH paper 1: contributions to climate change

SB-23 17 May 2006Niklas Höhne

2

MATCH paper #1Analysing countries’ contribution to climate

change: Scientific uncertainties and methodological choices

– Michel den Elzen (RIVM, Netherlands)– Jan Fuglestvedt (CICERO, Norway)– Niklas Höhne (Ecofys, Germany)– Cathy Trudinger (CSIRO, Australia)– Jason Lowe (Hadley, UK)– Ben Matthews (UCL, Belgium)– Bård Romstad (CICERO, Norway)– Christiano Pires de Campos (Brazil)– Natalia Andronova (UIUC, USA)

Modelling and assessment of contributions to climate change

M. den Elzen, J. Fuglestvedt, N. Höhne, C. Trudinger, J. Lowe, B. Matthews, B. Romstad, C. Pires de Campos, N. Andronova, 2005: “Analysing countries’ contribution to climate change: Scientific uncertainties and methodological choices”, Environmental Science and Policy, 8 (2005) 614–636

3

Cause-effect chainEmissionsRegion A

EmissionsRegion B

EmissionsRegion C

EmissionsRegion D

Concentrations

Radiative forcing

Global average temperature

change

Impact in Region A

Impact inRegion B

Impact inRegion C

Impact inRegion D


4

Temperature increase

Unattributed

Attribution start date,e.g. 1900

Region A

Region B

Region C

Region D

Time

Attribution period

Total temperature increase

Attributed temperature increase

Attributed effects

Today

5

Choices• Policy choices (values can not be based on objective ‘scientific’ arguments) :

– Indicator (e.g. temperature increase, radiative forcing, …)– Timeframes– Mixture of greenhouse gases– Attribution method

• Scientific choices– Choice of the dataset on historical emissions– Choice of the representation of the climate system (different

models)


6

Main objective of paper #1• Summarise the studies and results so far (i.e. the contributions

to the UNFCCC initiated process)

• Present new attribution calculations with non-linear carbon cycle and climate models using non-linear attribution methodologies and updated historical emissions datasets

• Investigate the effect of a range of scientific, methodological and policy-related choices on the attribution, but not the full range by all uncertainties.


7

Models used


1

Model Carbon cycle (CO2)

Atmospheric chemistry (non-CO2)

Sulphate aerosols

Radiative forcing

Temperature and sea level rise

ACCC (default): ECOFYS-ACCC IVIG-ACCC UIUC-ACCC

IRF (Bern) fixed lifetimes Hadley IPCC-TAR IRFs (Hadley)

CSIRO-ACCC ACCC* ACCC No ACCC ACCC

RIVM-ACCC ACCC ACCC or IPCC-TAR ACCC ACCC ACCC or IRFs

UCL-ACCC ACCC ACCC ACCC ACCC UDEBv

CICERO-SCM Non-linear v IPCC-TAR IPCC-TAR ACCC EBC/UDO model

UCL-JCM Bern non-linear IPCC-TAR IPCC-TAR ACCC UDEBv

2

8

Model show similar outcomes


temperature increase

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

1900 1950 2000 2050 2100

°C

JCM-JCM (1)

Hadley (2)

CICERO-SCM (3)

CSIRO-ACCC (4)

RIVM-ACCC (5)

ECOFYS-ACCC (6)

UCL-ACCC (7)

IVIG-ACCC (8)

UIUC-ACCC (9)

123,4

5678,9

9

Models used


Policy choices Indicators Radiative forcing, GWP-weighted cumulative emissions, weighted

concentrations, temperature increase, integrated temperature, sea level rise Attribution start dates 1765, 1890, 1950 and 1990 Timeframes Attribution end dates 1990, 2000, 2050 and 2100

Evaluation dates 2000, 2050, 2100, 2500 Attribution methods Normalised marginal, residual, time-sliced Attributed greenhouse gases (GHGs)

Fossil CO2, CO2, [CO2, CH4, N2O], Kyoto-gases (including F-gases, i.e. HFCs, PFCs and SF6), Kyoto gases and ozone precursors

Scientific choices Historical emissions CDIAC database (fossil CO2

a, land-use CO2b), EDGAR (Kyoto-gases and

ozone precursors) c, IVIGd

Representation of the climate system

See table 2

1

10

Model show similar outcomes


39.3 38.3 40.5 39.5 41.2 39.5 37.8 39.6

14.8 15.3 13.2 14.7 14.9 14.3 14.4 14.3

23.5 23.8 24.9 23.5 21.0 23.8 25.8 23.7

22.4 22.7 21.5 22.4 22.8 22.4 22.0 22.4

0%

20%

40%

60%

80%

100%

EC

OF

YS

-AC

CC

IVIG

-AC

CC

UIU

C-A

CC

C

CS

IRO

-AC

CC

RIV

M-A

CC

C

UC

L-A

CC

C

CIC

ER

O-S

CM

UC

L-S

CM

ALM

ASIA

EEUR&FSU

OECD90

11

Policy choices

1. Indicator

2. Timeframes

3. Attribution method

4. Mixture of Greenhouse gases


12

1. Indicators


Source: Ecofys-ACCC

Historical emissions

Time

ACB

Time

Time

Present

D

Emissions

Radiative forcing

Temperature change

E

Time

FSea level rise

Time

Concentrations

Attribution end date

Evaluation date

Incr

easi

ng c

erta

inty

Incr

easi

ng r

elev

ance


Time

ACB

Time

Time

Present

D

Emissions

Radiative forcing

Temperature change

E

Time

FSea level rise

Time

Concentrations


Evaluation date

Incr

easi

ng c

erta

inty

Incr

easi

ng r

elev

ance

Time

AACB

Time

Time

Present

D

Emissions

Radiative forcing

Temperature change

E

Time

FSea level rise

Time

Concentrations


Evaluation date

Incr

easi

ng c

erta

inty

Incr

easi

ng r

elev

ance

Time

E

Time

Time

Time

Present

Emission pulse Historical emissions

Emissions

Concentrations

Radiative forcing

Temperature change


Time

ACB

Time

Time

Present

D

Emissions

Radiative forcing

Temperature change

E

Time

FSea level rise

Time

Concentrations


Evaluation date

Incr

easi

ng c

erta

inty

Incr

easi

ng r

elev

ance


Time

ACB

Time

Time

Present

D

Emissions

Radiative forcing

Temperature change

E

Time

FSea level rise

Time

Concentrations


Evaluation date

Incr

easi

ng c

erta

inty

Incr

easi

ng r

elev

ance

Time

AACB

Time

Time

Present

D

Emissions

Radiative forcing

Temperature change

E

Time

FSea level rise

Time

Concentrations


Evaluation date

Incr

easi

ng c

erta

inty

Incr

easi

ng r

elev

ance

13

1. Indicators


Name of indicator Backward discounting

Forward looking

A Radiative forcing X -+

B GWP-weighted cumulative emissions - X

C Weighted concentrations X X

D Temperature increase X* -

+

E Integrated temperature increase

X X

F Sea level rise X* -+ *: Also discounting most recent emissions

+: Can be made forward looking, when evaluating at a date after attributed emissions end. In such case also a time horizon is required

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1. Indicators

0

10

20

30

40

50

60

70

Fossil CO2 Forestry CO2 CH4 N2O

%

Radiative Forcing (100%=2.00 W/m2)GWP w eighted cummulative emissions (100%=160)Weighted concentrations (100%=67)Temperature increase (100%=1.19°C)Integrated Temperature increase (100%=84°Cy)Ocean Heat Content (100%=3.8E+9 J/m2)


Relative contributions using different indicators

05

101520

2530354045

OECD90 EEUR&FSU ASIA ALM

%

Radiative Forcing (100%=2.00 W/m2)GWP w eighted cummulative emissions (100%=160)Weighted concentrations (100%=67)Temperature increase (100%=1.19°C)Integrated Temperature increase (100%=84°Cy)Ocean Heat Content (100%=3.8E+9 J/m2)

Source: Ecofys-ACCC

15

1. Indicators


Conclusions• Two main factors:

• Whether a source emitted ‘early’ versus ‘late’• The share of emissions of short-lived / long-lived gases.

• Choosing the right indicator is ultimately a policy choice that also depends on the purpose of use of the results.

• Temperate increase: use evaluation date after the attribution end date

• ‘Backward discounting’ and ‘forward looking’: ‘weighted concentrations’ or ‘integrated temperatures’

• Not ‘backward discounting’: GWP-weighted cumulative emissions could be an option, which is simple and approximately represents the integrated impact on temperature.

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2. Timeframe• Start date emissions 1890,

1950 and 1990

• End date emissions 1990, 2000, 2050 and 2100

• Evaluation date of attribution 2000, 2050, 2100, 2500


Temperature increase

Unattributed

Attribution start date,e.g. 1900

Region A

Region B

Region C

Region D

Time

Attribution period

Total temperature increase

Attributed temperature increase

Today

17

Start-date

• Choosing a shorter time horizon (e.g. 1950 or 1990 instead of 1890) reduces the contributions of OECD90 countries ('early emitters') to

temperature increase.

Contribution to temperature increase in 2000

0

5

10

15

20

25

30

35

40

45


%

1765 (100% = 1.13)1850 (100% = 1.04)1890 (100% = 0.99)1950 (100% = 0.78)1990 (100% = 0.21)


Source: RIVM-ACCC


0

5

10

15

20

25

USA LatinAmer

Africa OECDEurope

FSU SouthAsia

EastAsia

%

18

End-date

• A late end-date increases non-Annex-I contributions, because it gives more weight to their larger future emissions.

• Impact of emissions scenarios (error bars) can be large


05

1015

202530

3540

4550


%

1990 (100% = 0.43°C)2000 (100% = 0.53°C)2050 (100% = 1.54°C)2100 (100% = 4.00°C)


Source: RIVM-ACCC


0

5

10

15

20

25

USA LatinAmer

Africa OECDEurope

FSU SouthAsia

EastAsia

%

19

Evaluation-date

• A later evaluation-date raises OECD contributions due to: (1) their large share in historical CO2 emissions (long residence time) (2) and their small share of methane emissions (short residence time)

Contribution to temperature increase in:(end date 2000)

05

101520253035404550


%

2000 (100% = 0.99°C)2050 (100% = 0.68°C)2100 (100% = 0.53°C)


Source: RIVM-ACCC

Contribution to temperature increase in:(end date 2000)

0

5

10

15

20

25

USA LatinAmer

Africa OECDEurope

FSU SouthAsia

EastAsia

%

20

3. Attribution methods


• Normalised marginal method - Attributes responsibility using total sensitivities determined "at the margin".

• Residual (all-but-one) method - Attributes responsibility by leaving out the emissions of each region in turn.

• Time-sliced - determines the effect of emissions from each time as if there were no subsequent emissions.

21



• The Residual method, although simple to implement and explain, can be rejected on scientific grounds (not additive).

• The Normalised marginal and Time-sliced methods are harder to implement and explain. These methods differ in how they treat early vs. late emissions.

22


• The differences between methods are fairly small compared to the effects of many of the other choices already considered.


Source: CSIRO-SCM


0

5

10

15

20

25

30

35

40

45

OECD90 EEUR & FSU Asia ALM

% Contribution to temperature increase in 2000

0

5

10

15

20

25

USA LatinAmer

Africa OECDEurope

FSU SouthAsia

EastAsia

%

N. Marg (100% = 1.24°C)T. Sliced (100% = 1.24°C)N. Resid (100% = 1.24°C)

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0

5

10

15

20

25

30

35

40


% Contribution to temperature increase in 2100

0

5

10

15

20

25

USA LatinAmer

Africa OECDEurope

FSU SouthAsia

EastAsia

%

N. Marg (100% = 4.04°C)T. Sliced (100% = 4.04°C)N. Resid (100% = 4.04°C)

• Differences between methods are greater for later evaluation date (2100)• In general, the results of the different methods vary most for regions with emissions that differ

most from the average in terms of early versus late emissions, i.e. India and EU.

Source: CSIRO-SCM

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4. Greenhouse gas mixtureWhich gases are attributed to the regions?

1. Fossil CO2

2. All anthropogenic CO2

3. CO2, CH4, N2O

4. Kyoto basket (CO2, CH4, N2O, HFCs, PFCs, SF6)

5. Kyoto basket + more O3 precursors (NOx, CO and VOC)


25

4. Greenhouse gas mixture

• Two main effects i) Going from fossil fuel CO2 emissions only to total anthropogenic CO2 emissions, ii) Inclusion of CH4 and N2O.


0%

10%

20%

30%

40%

50%

60%

OECD90 EEUR & FSU ASIA ALM

Fossil CO2 (100% = 0.58°C)Anthropogenic CO2 (100% = 0.74°C)CO2, CH4 and N2O (100% = 1.06°C)Kyoto gases (100% = 1.07°C)Kyoto gases & precursors (100% = 1.07°C)


Source: CICERO-SCM


0%

5%

10%

15%

20%

25%

30%

USA LatinAmer

Africa OECDEurope

FSU SouthAsia

EastAsia

26

4. Greenhouse gas mixture


Source: CICERO-SCM


0%

10%

20%

30%

40%

50%

60%


Fossil CO2 (100% = 3.11°C)Anthropogenic CO2 (100% = 3.26°C)CO2, CH4 and N2O (100% = 4.39°C)Kyoto gases (100% = 4.4°C)Kyoto gases & precursors (100% = 4.65°C)

• The effect is less pronounced on longer time scales (except for the shift from fossil CO2 to total CO2).

27

Scientific uncertainties1. Choice of the dataset on historical emissions

2. Choice of the representation of the climate system: carbon cycle and climate model and feedbacks


28

1. Historical datasets

• Fossil CO2 emissions: small differences in relative attribution• CO2 emissions from land-use changes: differences in estimates leading to large differences.

Data sets need to be compared and improved.• CH4 and N2O: Only one dataset is available (EDGAR)• IVIG Dataset estimate is outside IPCC range; almost zero for DCs in 1980s!


05

10152025

3035404550


%

FF+LUC:EDGAR (ref ) (100% = 0.68°C)FF:CDIAC; LUC:EDGAR (100% =0.62°C)FF:EDGAR; LUC:Houg (100% =0.74°C)FF:EDGAR; LUC:IVIG (100% =0.69°C)


Source: RIVM-ACCC


0

5

10

15

20

25

USA LatinAmer

Africa OECDEurope

FSU SouthAsia

EastAsia

%

29

2. Other scientific uncertainties

• The influence of other climate model parameters (e.g. IRFs), based on simulation experiments with nine GCMs and climate models is limited



0

5

10

15

20

25

30

35

40


%Hadley (ref ) (100% = 2.30°C)CSIRO (100% = 2.04°C)ECHAM (100% = 1.68°C)GFDL (100% = 2.36°C)


02468

10

1214161820

USA LatinAmer

Africa OECDEurope

FSU SouthAsia

EastAsia

%

Source: RIVM-ACCC

30

2. Other scientific uncertaintiesContribution to temperature increase in 2100

0

5

10

15

20

25

30

35

40


%

1: UCL-ACCC (linear carbon cycle) (100% = 3.8°C)2: 1 + non-linear carbon fertilisation (100% = 3.9°C)3: 2 + nonlinear oceanic chem is try (100% = 4.3°C)4: 3 + clim ate feedback ocean chem is try (100% = 4.4°C)5: UCL-JCM (= 4 + atm ospheric chem is try) (100% = 4.4°C)

6: 5 + soil respiration feedback (100% = 4.8°C)7: 6 + high clim ate sens itivity (100% = 6.7°C)8: 3 + high clim ate sens itivity (no feedbacks) (100% = 5.7°C)9: 6 excl. F-gas , trop.O3, solar&volcano (100% = 4.9°C)10 =4 + high carbon fertilisation (100% = 4.2°C)11 =4 + fas t ocean diffus ivity (100% = 4.4°C)



0

5

10

15

20

25

USA Latin Amer Africa OECD Europe FSU South Asia East Asia

% Source: UCL-SCM

31

Deviation f rom default calculations

-15

-10

-5

0

5

10

15

20

25

OECD EEUR&FSU ASIA ALM

perc

enta

ge p

oint

s

GWP w eighted cummulative emissionsOcean Heat ContentAttribution start date 1990Only fossil fuel CO2All Kyoto gases and precursorsAll Kyoto gases and SO2Other LUCF data: Houghton

Overall conclusions• Policy choices (values can not be based on

objective ‘scientific’ arguments) :– Indicator important– Timeframes important– Mixture of GHG important– Attribution method less

important


• Scientific choices– Choice of the dataset on historical emissions important– Choice of the representation of the climate system

(different models) less important for relative contr.

32

Overall conclusions• First summary of the work undertaken so to date

• Not a full assessment of the uncertainty range, but an evaluation of the influence of different policy-related and scientific choices

• The influence of scientific choices is notable. Therefore research is ongoing (see paper #2)

• However, the current work suggests, that the impact of policy choices, such as time horizon of emissions, climate change indicator and greenhouse-gas mix is larger than the impact of scientific uncertainties

• Impact of uncertainties on the relative contributions is smaller than impact of uncertainties on the absolute changes in temperature.

• Research needs: Historical emission datasets


33

Backup slides

34

Policy choices


Indicators Radiative forcing, GWP-weighted cumulative emissions, weighted concentrations,temperature increase, integrated temperature, sea level riseAttribution startdates

1890, 1950 and 1990Timeframes

Attribution end dates 1990, 2000, 2050 and 2100Evaluation dates 2000, 2050, 2100, 2500

Attributionmethods

Normalized marginal, residual, time-sliced

Attributedgreenhousegases (GHGs)

Fossil CO2, CO2, CO2, CH4, N2O, Kyoto-GHGs (including F-gases), all GHGs(including the other halocarbons (CFCs))

Data Historical emissions CDIAC database (fossil CO2, land-use CO2), EDGAR (allKP-GHGs), IEA (fossil CO2)

Future emissions IPCC SRES B1, A2 and A1F emission scenario

Regions Four regions (Nakicenovic et al. 2000): OECD90; Eastern Europe and Former SovietUnion (REF); Asia (ASIA); Africa and Latin America (ALM), and 13 world regions:Canada, USA, Latin America, Africa, OECD Europe, Eastern Europe, FormerUSSR (FSU), Middle East, South Asia, East Asia, South East Asia, Oceania andJapan

35

Models are calibrated


36

1900 1950 2000 20500

5

10x 10

4

Gg

P uls e emis s ions of 1E5 Gg CO2 - proportional

1900 1950 2000 20500

0.01

0.02

ppm

1900 1950 2000 20500

2

4x 10

-4W

/m2

1900 1950 2000 20500

0.5

1x 10

-4

°C

Years

1900 1950 2000 20500

5

10x 10

4

Gg

P uls e emis s ions of 1E5 Gg CO2 - res idual

1900 1950 2000 20500

0.01

0.02

ppm

1900 1950 2000 20500

2

4x 10

-4

W/m

2

1900 1950 2000 20500

0.5

1x 10

-4

°C

Years

1900 1950 2000 20500

5

10x 10

4

Gg

Pulse emissions of 1E5 Gg CO2 - proportional

1900 1950 2000 20500

0.01

0.02

ppm

1900 1950 2000 20500

2

4x 10

-4

W/m

2

1900 1950 2000 20500

0.5

1x 10

-4

°C

Years

=1

=0.6

37

Table 3

No. Name of the indicator 1900 1950 1990 2000 CO2 0.29 0.36 0.56 1* CH4 0.015 1.0 28 64* A Radiative forcing due to increased

concentrations N2O 81 126 180 196* CO2 1 1 1 1+ CH4 20 20 20 20+ B GWP-weighted cumulative

emissions N2O 323 323 323 323+ CO2 0.29 0.36 0.56 1 CH4 0.005 0.31 8.6 20 C Weighted concentrations N2O 134 208 296 323 Max year CO2 3.44 3.92 4.45 1 1983 CH4 9 33 262 64 1991 D Temperature increase N2O 927 1290 1220 196 1976 CO2 0.90 0.93 1.03 1 1993 CH4 2.2 3.3 16 22 2000 E Integrated temperature N2O 189 260 327 324 1994 CO2 To be completed CH4 F Sea level rise N2O

*: Represent instantaneous GWPs. +: Represent GWPs. Values slightly different to those of IPCC-TAR due to use of different parameters.

38

Contribution to radiative forcing


jansf

"New science": Perhaps add a few words more about what you have in mind. Incorporate new knowledge, new estimates in the litterature, update models.....?

39

Aerosol forcing

• Inclusion of SO2 emissions reduces the contributions from ASIA and REF, but the effect disappear when there is a gap between attribution end date and evaluation date.

• Again effect is less less pronounced on longer time scales


Attributing SO2, attribution period 1890-2000

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

OECD90 REF ASIA ALM

KP3 2000 (dT=1.06)

KP6_SO2 2000 (dT=0.51)

Attributing SO2, attribution period 1890-2000

0%

5%

10%

15%

20%

25%

30%

Canad

aUSA

Japa

n

OECD E

urop

e

Oce

ania CIS

Easte

rn E

urop

e

China

regio

n

East A

sia

South

Asia

Africa

Latin

Am

erica

Mid

dle E

ast

KP3 2000 (dT=1.06)

KP6_SO2 2000 (dT=0.51)

Source: CICERO-SCM

jansf

Illustrate second half of bullet #1 by including 2050 fig? The point tha the aerosol issue disappers when there is a gap between emiss attribution end date and evaluation date could be important to communicate.

40

Overall conclusions


Region Def

ault

(te

mp

erat

ure

incr

ease

)

GW

P w

eigh

ted

cum

mul

ativ

e em

issi

ons

Wei

ghte

d co

ncen

trat

ions

Inte

grat

ed T

empe

ratu

re in

crea

se

Oce

an H

eat C

onte

nt

Def

ual

t: A

ttri

bu

tio

n s

tart

dat

e 18

90

Attr

ibut

ion

star

t dat

e 19

90

Eva

luat

ion

date

210

0

Dea

fult

: N

orm

aliz

ed m

arg

inal

Tim

e sl

iced

Dea

fult

: al

l CO

2, C

H4,

N2O

Onl

y fo

ssil

CO

2

Def

ault

with

con

stan

t CH

4 lif

etim

e

All

Kyo

to g

ases

and

pre

curs

ors

Def

ault

(al

l GH

Gs:

ED

GA

R)

Oth

er L

UC

F d

ata:

Hou

ghto

n

Def

ault

: E

DG

AR

IRF

: GF

DL

Def

ault

: A

CC

C s

imp

lest

Var

iant

7 (

sect

. 3.3

.3):

UC

L-JC

M

Canada 1.6 1.6 1.7 1.6 1.4 1.7 1.8 1.7 1.6 1.6 1.5 2.2 1.6 1.8 1.6 2.2 1.7 1.6 1.6 1.6USA 19.8 20.5 20.4 20.9 21.1 20.8 17.5 21.8 19.7 19.9 19.1 29.6 19.9 18.4 19.4 17.7 20.8 21.1 19.8 20.0Latin America 13.7 13.7 13.3 14.2 15.4 14.5 10.0 14.8 13.7 13.9 13.2 3.7 13.7 13.2 13.8 11.0 14.5 15.0 13.7 14.0Africa 6.5 6.3 6.2 6.2 6.6 6.3 6.5 6.0 6.6 6.6 6.8 2.4 6.6 7.9 6.7 5.6 6.3 6.3 6.6 6.6OECD Europe 13.8 14.7 14.5 14.9 15.2 14.7 11.0 15.8 13.9 14.0 13.2 21.3 14.1 12.8 13.6 13.2 14.7 14.9 13.9 14.2East Europe 4.1 3.9 4.0 4.1 3.6 4.2 3.4 4.2 4.0 4.0 3.9 5.8 4.0 3.7 4.2 4.0 4.2 4.2 4.0 3.9FSU 10.8 9.6 10.3 10.1 7.9 10.7 12.5 9.9 10.7 10.5 10.5 13.7 10.3 10.2 11.0 11.7 10.7 10.3 10.3 9.9Middle East 2.1 1.9 2.4 2.1 1.2 2.0 3.7 2.0 2.1 2.0 2.0 2.5 2.0 2.4 2.1 2.4 2.0 1.9 2.1 1.9South Asia (incl. India) 7.0 7.3 5.8 5.6 8.7 5.5 7.4 4.5 7.1 7.1 8.5 3.3 7.2 8.2 7.3 6.3 5.5 5.6 7.2 7.6East Asia (incl. China) 10.2 10.1 10.7 9.7 8.9 9.3 15.2 8.8 10.1 10.0 11.0 8.9 10.1 11.0 10.2 15.1 9.3 8.8 10.3 9.9South-East Asia 6.3 6.2 6.0 6.1 6.6 6.2 6.0 6.0 6.2 6.3 6.3 1.2 6.2 6.3 6.4 6.3 6.2 6.3 6.3 6.3Oceania 1.5 1.5 1.6 1.4 1.5 1.3 1.6 1.2 1.7 1.7 1.8 1.2 1.7 1.7 1.5 1.8 1.3 1.2 1.7 1.7Japan 2.6 2.6 3.0 2.9 1.9 2.9 3.5 3.1 2.5 2.5 2.3 4.3 2.5 2.3 2.5 2.8 2.9 2.7 2.5 2.4Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 0.0 0.0 100.0 100.0 100.0 100.0

OECD 39.3 40.9 41.3 41.8 41.1 41.2 35.3 43.6 39.5 39.6 37.8 58.6 39.8 37.0 38.6 37.7 41.2 41.6 39.5 39.9EEUR&FSU 14.8 13.5 14.4 14.2 11.6 14.9 15.9 14.1 14.7 14.5 14.4 19.5 14.3 13.9 15.1 15.7 14.9 14.5 14.3 13.8ASIA 23.5 23.6 22.5 21.4 24.2 21.0 28.6 19.4 23.5 23.3 25.8 13.4 23.6 25.6 23.8 27.6 21.0 20.7 23.8 23.9ALM 22.4 21.9 21.9 22.5 23.2 22.8 20.1 22.9 22.4 22.5 22.0 8.5 22.3 23.5 22.5 19.0 22.8 23.2 22.4 22.5Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0

100% = ... °C 1.2 160.4 67.4 84°Cy 3.8E+09 0.99 0.21 0.53 1.06 0.58 1.04 1.07 0.99 1.00 0.52 1.12

= More than 10% higher than default= More than 10% lower than default

RIVM -ACCC JCM-SCMECOFYS-ACCC CSIRO - ACCCRIVM - ACCC CICERO -SCM IVIG-ACCC

1 match paper 1: contributions to climate change sb-23 17 may 2006 niklas höhne

Documents

climate change slide

assessment of contributions

climate change source

climate change sb

climate models

region d modelling

region c impact

region b impact