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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.

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Presentation on theme: "Carbon emission metrics for climate stabilization and the implications to metrics for non-CO2 GHGs Michio Kawamiya Research Institute for Global Change."— Presentation transcript:

1 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

2 Introduction: limitation of single basket approach “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) Forcings for these two lines have the same value of GWP. GTP is superior when discussing stabilization

3 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

4 CO2 concentration has been often used as a carbon emission metrics… IPCC AR5 WG3 (2007)

5 … then concentration metrics is converted to socio-economic scenarios. IPCC AR5 WG3 (2007) CO2 emission paths to achieve CO2 concentration stabilization

6 Cumulative carbon emission as a metric for climate stabilization level and transient climate response Matthews et al. (2009)

7 Notifications CCR = T/CE = (T/CA)(CA/CE) = α A 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.

8 CCR may be independent of scenario 1%/year increase Instanteneous x2 & x4

9 MIROC-ESM: a GCM-based Earth System Model 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 Atmosphere Ocean Land MIROC-AGCM SPRINTARS (CHASER) COCO NPZD MATSIRO SEIB-DGVM MIROC-ESM

10 Global warming projection with MIROC-ESM under RCP scenarios

11 MIROC-ESM 結果 Temperature Rise averaged over 2090’s relative to 1980-1999 average

12 Climate Carbon Response in MIROC-ESM (1) With all anthropogenic forcings (2) non-CO2 GHG corrected CCR RCP2.6 RCP6.0 RCP4.5 RCP8.5 R2.6 R6.0 R4.5 R8.5

13 Another possible cause for scenario dependence of CCR Global temperature change Ocean heat uptake Scenario A Scenario B Atmosphere Ocean Atmosphere Ocean Scenario A Scenario B Changes in ocean heat uptake:  Q =  SW +  LW +  SH +  LH =   T Efficiency of ocean heat uptake

14 (3) Ocean-heat-uptake (OHU) corrected CCR CCR is moderately scenario dependent in our case, but can be corrected in terms of OHU.

15 Airborne CO2 is again not a good metrics… (1) With all anthropogenic forcings(2) non-CO2 GHG corrected (3) Ocean heat uptake corrected

16 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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