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

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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  1. 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

  2. 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

  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. CO2 emission paths to achieve CO2 concentration stabilization IPCC AR5 WG3 (2007)

  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) = 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.

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

  9. 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

  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 R2.6 RCP4.5 R4.5 RCP8.5 R6.0 RCP6.0 R8.5

  13. 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

  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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