Uncertainties in absolute attribution of climate change SB-24 17 May 2006

Uncertainties in absolute attribution of climate change

SB-24 17 May 2006

Joyce PennerUniversity of Michigan

Overview of paper #2• Paper #1 examined the uncertainties associated with

methodological choices in attributing relative temperature change

• Here we assess scientific uncertainties in attributing absolute climate change

• We use a closure method to evaluate uncertainties:• Emissions to concentrations for long

lived greenhouse gases• Radiative forcing to temperature

change for attribution

• Attribution of OECD Annex I countries are used as an example because these (and their uncertainties) are available from UNFCCC reporting

Modelling and assessment of contributions to climate change

Overview of paper #2


Contributors:

Prather, Lowe, Raper, Stott, Höhne, Fuglestvedt, Romstad, Penner, Andronova, Kurosawa, Wagner, Jain, Pires de Campos, Meinshausen, van Aardenne

Method


Global inventories of GHG emissions

based on activities

Emissions derived from atmospheric

measurements

Match?

Emissions

Concentrations

Radiative forcing

Global average temperature

change

All sources of historical radiative

forcing

Observed temperature

increase

Match?

Total uncertainty of OECD Annex

I countries contribution


Emissions from inversemodel are well withinthe stated uncertainties of the EDGAR data base

Emissions of OECD Annex I countries fromEDGAR are within stateduncertainties fromUNFCCC inventories

Example: N2O


We estimate a pdffor OECD Annex I N2O emissionsusing UNFCCCuncertainties forthe next step(RF to T)

Example: CH4

Global emissions fromEdgar bottom-up inventory match wellthe emissions requiredto fit observations ofCH4.

But the Edgar OECDAnnex I emissions aresignificantly higher thanthe UNFCCC emissions.

The uncertainties for UNFCCC emissions mustbe increased in RF to Tcalculations



Uncertaintiesin OECD Annex I countries are widened forthe next step(RF to T) toaccount for mis-match betweenEDGAR andUNFCCC reportedemissions

CO2

The increase in CO2 concentration can be explained by the following factors: Measured

• Anthropogenic emissions from fossil fuels and industrial processes Well known

• Anthropogenic emissions/removals from land use change and forestry Unknown

• Natural removals by the biosphere Modelled• Natural removals by the ocean Modelled


Global LUCF emissions are highly uncertain due to land use change data

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Lan

d U

se (

Pg

C/y

r)

HH-Low

HH-Base

HH-High

HYDE-Low

HYDE-Base

HYDE-High

RF-Low

RF-Base

RF-High

Even so, OECD Annex I LUCF emissions from inverse method since 1990 are well known:

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d U

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r)

HH-LowHH-BaseHH-HighHYDE-LowHYDE-BaseHYDE-HighRF-LowRF-BaseRF-High

But UNFCCC LUCF emissions from OECD Annex I countries are outside the uncertainty range from inverse method: Need to increase range of uncertainty considered in RF to T

calculation! (not yet included)

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d U

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r) HH-Low

HH-Base

HH-High

HYDE-Low

HYDE-Base

HYDE-High

RF-Low

RF-Base

RF-High

UNFCCC OECD Annex 1

UNFCCCLUCF emissions

Method



based on activities


measurements

Match?

Emissions

Concentrations

Radiative forcing


change


forcing


increase

Match?



Radiative Forcing and uncertainty was estimated for all of the important climate factors *

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3Solar

Tropospheric ozone

CFCs, HCFCs andother ODSSF6

PFCs

HFCs

N2O

CH4

CO2

Vulcanic

Areosol forcingindirectCarbon aerosol

Sulfate aerosol

Stratospheric ozone

Total


Forcing (W/m2)

* Refers to preliminary assessment

Comparison of D and A (inverse model) aerosol forcing with bottom-up aerosol forcing

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Bottom up methodyields wider uncertaintyrange, but encompassesinverse method

Uncertainty in natural forcingdeduced using different reconstructions

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year

HOYT&SCHATTEN LEAN LEAN_II

Volcanic Solar

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sato Ammann03 Ammann06


Additional contributions from land use albedo change and dust – based on TAR

estimates

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year

forc

ing case 1

case 2

case 3


What will alter median and spread of bottom up forcing?

Uncertainty range in bottom up forcing

Median magnitude of bottom up forcing

Median magnitude

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GHG Trop O3 Bottom-upAP

D&A AP Other

Uncertainty range

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GHG Trop O3 Bottom-upAP

D&A AP Other

Forcing calculated to year 2000


Use uncertainties in individual components to define uncertainty in total forcing


Results space of modeled temperatures compared to observed warming since 1880

Observations are shown in black


Compare forcing from bottom up and forcing from inverse: not all forcing scenarios are consistent with the

observed temperature change*

Forcing from bottom up estimates* Forcing from inverse calculation


*Preliminary values

Method



based on activities


measurements

Match?

Emissions

Concentrations

Radiative forcing


change


forcing


increase

Match?



Effect of group’s emissions


CO2

1.2

1.25

1.3

1.35

1.4

1.45

1.5

1.55

1.6

1.65

1.7

1990 1992 1994 1996 1998 2000 2002

W/m

2

Undisturbed forcing2.5th percentile5th percentile25th percentile50th percentile75th percentile95th percentile97.5th percentile

CH4

0.3

0.32

0.34

0.36

0.38

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0.42

0.44

0.46

0.48

0.5

1990 1995 2000

W/m

2


N2O

0.08

0.09

0.1

0.11

0.12

0.13

0.14

0.15

0.16

0.17

1990 1992 1994 1996 1998 2000 2002W

/m2

Undisturbed forcing

2.5th percentile

5th percentile25th percentile

50th percentile

75th percentile

95th percentile97.5th percentile

Combined effect of uncertainties on warming

from OECD Annex 1 countries due to CO2

Combined effect of uncertainty in global mean forcing, climate sensitivity, ocean diffusivity and OECD Annex 1 forcing uncertainty on warming from OECD Annex 1 countries due to CO2

A likelihood was estimated for the unperturbed case using agreement with observed warming. The prior probability for the OECD Annex 1 perturbations was also included.

The fraction of warming attributable to OECD Annex I countries is 0.23 with a 95% confidence interval of 0.08 to 0.38.

Combined effect of uncertainty on warming from OECD Annex 1 countries due to CO2, CH4 and N2O*

Combined effect of uncertainty in global mean forcing, climate sensitivity, ocean diffusivity and OECD Annex 1 forcing uncertainty on warming from OECD Annex 1 countries due to CO2, CH4, and N2O

A likelihood was estimated for the unperturbed case using agreement with observed warming. The prior probability for the annex 1 perturbations was also included.

The fraction of warming attributable to OECD Annex I countries is 0.34 with a 95% confidence interval of 0.23 to 0.53. (*preliminary analysis)

Conclusions• We examined uncertainties in emissions inventories

for both global mean values and OECD Annex I GHG emissions

• We examined the consistency between the emissions and observed concentrations

• We estimated forcing and forcing uncertainty from all other known climate factors

• We examined the implications of this uncertainty for predicted global average temperature change and the change associated with 1990 - 2002 OECD Annex I emissions


Contribution Low HighGWP weighted emissions 14160 MtCO2eq. -6% 16%Radiative forcing 0.32 W/m2 -28% 53%Temperature increase 0.10 °C -49% 139%

Backup slides

Closure for long-lived greenhouse gases

• Compare bottom-up inventories to those determined from inverse models to determine uncertainty in global emissions

• Define OECD Annex I emissions using UNFCCC reported emissions and reported uncertainties

• Compare OECD Annex I emissions from inverse model and adjust uncertainty in UNFCCC emissions if needed


Comparison of OECD Annex Iemissions with global emissions


OECD Annex 1 warming due to CO2, and effect of uncertainty in climate sensitivity


OECD Annex 1 warming due to CO2, and effect of uncertainty in ocean diffusivity


Uncertainties in global mean forcing


OECD Annex 1 warming due to CO2, and effect of uncertainty in global mean forcing


Uncertainty in OECD Annex 1 forcing from N2O


N2O

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1990 1992 1994 1996 1998 2000 2002

W/m

2

Undisturbed forcing

2.5th percentile

5th percentile25th percentile

50th percentile

75th percentile

95th percentile97.5th percentile

Combined effect of uncertainty on warming from

OECD Annex 1 countries due to N2O

Combined effect of uncertainty in global mean forcing, climate sensitivity, ocean diffusivity and OECD Annex 1 forcing uncertainty on warming from OECD Annex 1 countries due to N2O



Uncertainty in OECD Annex 1 forcing from CH4


CH4

0.3

0.32

0.34

0.36

0.38

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0.42

0.44

0.46

0.48

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1990 1995 2000

W/m

2


Combined effect of uncertainty on warming from OECD Annex 1 countries due to CH4

Combined effect of uncertainty in global mean forcing, climate sensitivity, ocean diffusivity and OECD Annex 1 forcing uncertainty on warming from annex 1 countries due to CH4



Comparison of aerosol forcing to year 2000 from bottom-up with D and A reconstruction

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Forcing

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Bottom-up reconstruction – used in subsequent analysis

D and A reconstruction

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Forcing

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Inverse model used to estimate forcing for 2 different values of climate sensitivities

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Annual valuesTime filtered forcing values

Inverse calculation showing plume of forcing curves for different climate sensitivity based on TAR GCM models.

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Would need to add other forcings to make all scenarios from bottom up estimates consistent with observed T

pdf from bottom uppdf from inverse

pdf of extra forcing that needs to be added to bottom up to achieve consistency with temperature record

Minus

Sample all combinations


Uncertainties in absolute attribution of climate change SB-24 17 May 2006

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Transcript of Uncertainties in absolute attribution of climate change SB-24 17 May 2006