Carbon emission metrics for climate stabilization and the implications to metrics for non co2 ghgs
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Carbon emission metrics for climate stabilization and the implications to metrics for non-CO2 GHGs. Michio Kawamiya Research Institute for Global Change Japan Agency for Marine-earth Science and Technology. Introduction: limitation of single basket approach.

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Carbon emission metrics for climate stabilization and the implications to metrics for non-CO2 GHGs

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Carbon emission metrics for climate stabilization and the implications to metricsfor non-CO2 GHGs

MichioKawamiya

Research Institute for Global Change

Japan Agency for Marine-earth Science and Technology


Introduction: limitation of single basket approach

Forcings for these two lines have the same value of GWP.

“Methane+640GtC” and “1280GtC, No Methane” have the same forcing in terms of GWP.

-> “Single basket approach” does not work for discussing stabilization levels. (Eby et al., 2009; Solomon et al., 2011)

GTP is superior when discussing stabilization


Different roles of short-lived and long-lived agents

  • Short-lived: “trim” the peak

  • Long-lived: determine the stabilization level

“Two-basket approach” is proposed ( Solomon et al., 2011)

-> GTP for short-lived agents

Cumulative emission for long-lived agents


CO2 concentration has been often used as a carbon emission metrics…

IPCC AR5 WG3 (2007)


… then concentration metrics is converted to socio-economic scenarios.

CO2 emission paths to achieve CO2 concentration stabilization

IPCC AR5 WG3 (2007)


Cumulative carbon emission as a metric for climate stabilization level and transient climate response

Matthews et al. (2009)


Notifications

CCR = T/CE = (T/CA)(CA/CE) = αA

CCR: Climate-carbon response (matthews et al., 2009)

α(=T/CA): Temperature rise per unit airborne carbon

A(=CA/CE): Airborne fraction

Cf. Climate sensitivity: λ=T/F

F: Radiative forcing

CCR may be regarded as “earth system sensitivity”, with the forcing being anthropogenic carbon emission rather than radiative forcing.


CCR may be independent of scenario

1%/year increase

Instanteneous x2 & x4


MIROC-ESM: a GCM-basedEarth System Model

MIROC-ESM

Atmosphere

MIROC-AGCM

SPRINTARS (CHASER)

AGCM

CCSR/NIES/FRCGC

T42(~2.8ºx2.8º)

L80 (TOA:80km)

OGCM

COCO (CCSR/FRCGC)

Curvilinear grid system

(0.5-1.0)º x 1.4º

Ocean

Land

COCO

MATSIRO

NPZD

SEIB-DGVM


Global warming projection with MIROC-ESM under RCP scenarios


MIROC-ESM結果

Temperature Rise averaged over 2090’s relative to 1980-1999 average


Climate Carbon Response in MIROC-ESM

(1) With all anthropogenic forcings

(2) non-CO2 GHG corrected CCR

RCP2.6

R2.6

RCP4.5

R4.5

RCP8.5

R6.0

RCP6.0

R8.5


Another possible cause for scenario dependence of CCR

Efficiency of ocean heat uptake

Changes in ocean heat uptake:

DQ = DSW + DLW

+DSH + DLH

= kDT

Scenario A

Scenario B

Atmosphere

Atmosphere

Ocean heat uptake

Scenario A

Scenario B

Ocean

Ocean

Global temperature

change


(3)Ocean-heat-uptake (OHU) corrected CCR

CCR is moderately scenario dependent in our case, but can be corrected in terms of OHU.


Airborne CO2 is again not a good metrics…

(1) With all anthropogenic forcings

(2) non-CO2 GHG corrected

(3) Ocean heat uptake corrected


Implications for establishing metrics for short-lived and long-lived GHGs

  • It is important to recognize the difference between short-lived and long-lived GHGs with the same GWP, in particular for discussing climate stabilization.

  • For stabilization issues, cumulative emission (CE) of long-lived GHGs may be more desirable than concentration.

  • There may be a moderate scenario dependence of CE, especially for fast scenarios due to that of ocean heat uptake (OHU).

  • Constraining OHU efficiency may improve the validity of CE as a metrics.


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