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- ItemHistorical and idealized climate model experiments: An intercomparison of Earth system models of intermediate complexity(München : European Geopyhsical Union, 2013) Eby, M.; Weaver, A.J.; Alexander, K.; Zickfeld, K.; Abe-Ouchi, A.; Cimatoribus, A.A.; Crespin, E.; Drijfhout, S.S.; Edwards, N.R.; Eliseev, A.V.; Feulner, G.; Fichefet, T.; Forest, C.E.; Goosse, H.; Holden, P.B.; Joos, F.; Kawamiya, M.; Kicklighter, D.; Kienert, H.; Matsumoto, K.; Mokhov, I.I.; Monier, E.; Olsen, S.M.; Pedersen, J.O.P.; Perrette, M.; Philippon-Berthier, G.; Ridgwell, A.; Schlosser, A.; Schneider von Deimling, T.; Shaffer, G.; Smith, R.S.; Spahni, R.; Sokolov, A.P.; Steinacher, M.; Tachiiri, K.; Tokos, K.; Yoshimori, M.; Zeng, N.; Zhao, F.Both historical and idealized climate model experiments are performed with a variety of Earth system models of intermediate complexity (EMICs) as part of a community contribution to the Intergovernmental Panel on Climate Change Fifth Assessment Report. Historical simulations start at 850 CE and continue through to 2005. The standard simulations include changes in forcing from solar luminosity, Earth's orbital configuration, CO2, additional greenhouse gases, land use, and sulphate and volcanic aerosols. In spite of very different modelled pre-industrial global surface air temperatures, overall 20th century trends in surface air temperature and carbon uptake are reasonably well simulated when compared to observed trends. Land carbon fluxes show much more variation between models than ocean carbon fluxes, and recent land fluxes appear to be slightly underestimated. It is possible that recent modelled climate trends or climate–carbon feedbacks are overestimated resulting in too much land carbon loss or that carbon uptake due to CO2 and/or nitrogen fertilization is underestimated. Several one thousand year long, idealized, 2 × and 4 × CO2 experiments are used to quantify standard model characteristics, including transient and equilibrium climate sensitivities, and climate–carbon feedbacks. The values from EMICs generally fall within the range given by general circulation models. Seven additional historical simulations, each including a single specified forcing, are used to assess the contributions of different climate forcings to the overall climate and carbon cycle response. The response of surface air temperature is the linear sum of the individual forcings, while the carbon cycle response shows a non-linear interaction between land-use change and CO2 forcings for some models. Finally, the preindustrial portions of the last millennium simulations are used to assess historical model carbon-climate feedbacks. Given the specified forcing, there is a tendency for the EMICs to underestimate the drop in surface air temperature and CO2 between the Medieval Climate Anomaly and the Little Ice Age estimated from palaeoclimate reconstructions. This in turn could be a result of unforced variability within the climate system, uncertainty in the reconstructions of temperature and CO2, errors in the reconstructions of forcing used to drive the models, or the incomplete representation of certain processes within the models. Given the forcing datasets used in this study, the models calculate significant land-use emissions over the pre-industrial period. This implies that land-use emissions might need to be taken into account, when making estimates of climate–carbon feedbacks from palaeoclimate reconstructions.
- ItemThe PMIP4 contribution to CMIP6 - Part 3: The last millennium, scientific objective, and experimental design for the PMIP4 past1000 simulations(Göttingen : Copernicus GmbH, 2017) Jungclaus, J.H.; Bard, E.; Baroni, M.; Braconnot, P.; Cao, J.; Chini, L.P.; Egorova, T.; Evans, M.; Fidel González-Rouco, J.; Goosse, H.; Hurtt, G.C.; Joos, F.; Kaplan, J.O.; Khodri, M.; Klein Goldewijk, K.; Krivova, N.; Legrande, A.N.; Lorenz, S.J.; Luterbacher, J.; Man, W.; Maycock, A.C.; Meinshausen, M.; Moberg, A.; Muscheler, R.; Nehrbass-Ahles, C.; Otto-Bliesner, B.I.; Phipps, S.J.; Pongratz, J.; Rozanov, E.; Schmidt, G.A.; Schmidt, H.; Schmutz, W.; Schurer, A.; Shapiro, A.I.; Sigl, M.; Smerdon, J.E.; Solanki, S.K.; Timmreck, C.; Toohey, M.; Usoskin, I.G.; Wagner, S.; Wu, C.-J.; Leng Yeo, K.; Zanchettin, D.; Zhang, Q.; Zorita, E.The pre-industrial millennium is among the periods selected by the Paleoclimate Model Intercomparison Project (PMIP) for experiments contributing to the sixth phase of the Coupled Model Intercomparison Project (CMIP6) and the fourth phase of the PMIP (PMIP4). The past1000 transient simulations serve to investigate the response to (mainly) natural forcing under background conditions not too different from today, and to discriminate between forced and internally generated variability on interannual to centennial timescales. This paper describes the motivation and the experimental set-ups for the PMIP4-CMIP6 past1000 simulations, and discusses the forcing agents orbital, solar, volcanic, and land use/land cover changes, and variations in greenhouse gas concentrations. The past1000 simulations covering the pre-industrial millennium from 850 Common Era (CE) to 1849 CE have to be complemented by historical simulations (1850 to 2014 CE) following the CMIP6 protocol. The external forcings for the past1000 experiments have been adapted to provide a seamless transition across these time periods. Protocols for the past1000 simulations have been divided into three tiers. A default forcing data set has been defined for the Tier 1 (the CMIP6 past1000) experiment. However, the PMIP community has maintained the flexibility to conduct coordinated sensitivity experiments to explore uncertainty in forcing reconstructions as well as parameter uncertainty in dedicated Tier 2 simulations. Additional experiments (Tier 3) are defined to foster collaborative model experiments focusing on the early instrumental period and to extend the temporal range and the scope of the simulations. This paper outlines current and future research foci and common analyses for collaborative work between the PMIP and the observational communities (reconstructions, instrumental data).