Climate sensitivity is one of the most important metrics for future climate projections. In previous studiesthe climate of the last glacial maximum has been used to constrain the range of climate sensitivity, andsimilarities and differences of temperature response to the forcing of the last glacial maximum and to idealized future forcing have been investigated. The feedback processes behind the response have not, however, been fully explored in a large model parameter space. In this study, the authors first examine the performance of various feedback analysis methods that identify important feedbacks for a physics parameter ensemble in experiments simulating both past and future climates. The selected methods are then used to reveal the relationship between the different ensemble experiments in terms of individual feedback processes. For the first time, all of the major feedback processes for an ensemble of paleoclimate simulations are evaluated. It is shown that the feedback and climate sensitivity parameters depend on the nature of the forcing and background climate state. The forcing dependency arises through the shortwave cloud feedback while the state dependency arises through the combined water vapor and lapse-rate feedback. The forcing dependency is, however, weakened when the feedback is estimated from the forcing that includes tropospheric adjustments. Despite these dependencies, past climate can still be used to provide a useful constraint on climate sensitivity as long as the limitation is properly taken into account because the strength of each feedback correlates reasonably well between the ensembles. It is, however, shown that the physics parameter ensemble does not cover the range of results simulated by structurally different models, which suggests the need for further study exploring both structural and parameter uncertainties.
Studies of climate change 6,000 years before present using atmospheric general circulationmodels (AGCMs) suggest the enhancement andnorthward shift of the summer Asian and Africanmonsoons in the Northern Hemisphere. Althoughenhancement of the African monsoonal precipitationby ocean coupling is a common and robust feature,contradictions exist between analyses of the role of theocean in the strength of the Asian monsoon. Weinvestigated the role of the ocean in the Asian monsoonand sought to clarify which oceanic mechanismsplayed an important role using three ocean couplingschemes: MIROC, an atmosphere-ocean coupledgeneral circulation model [C]; an AGCM extractedfrom MIROC coupled with a mixed-layer ocean model[M]; and the same AGCM, but with prescribed seasurface temperatures [A]. The effect of ‘‘oceandynamics’’ is quantified through differences betweenexperiments [C] and [M]. The effect of ‘‘ocean thermodynamics’’is quantified through differences betweenexperiments [M] and [A]. The precipitationchange for the African and Asian monsoon area suggestedthat the ocean thermodynamics played animportant role. In particular, the enhancement of theAsian monsoonal precipitation was most vigorous inthe AGCM simulations, but mitigated in early summerin ocean coupled cases, which were not significantlydifferent from each other. The ocean feedbacks werenot significant for the precipitation change in latesummer. On the other hand, in Africa, ocean thermodynamicscontributed to the further enhancement ofthe precipitation from spring to autumn, and the oceandynamics had a modest impact in enhancing precipitationin late summer.
The effect of bias on control simulation is asignificant issue for climate change modeling studies. Weinvestigated the effect of the sea surface temperature (SST)bias in present day (0 ka) Atmosphere-Ocean CoupledGeneral Circulation Model (AOGCM) simulations onsimulations of the mid-Holocene (6 ka, i.e., 6,000 yearsbefore present) Asian monsoon enhancement. Becausechanges in ocean heat transport have a negligible effect onthe 6 ka Asian monsoon (Ohgaito and Abe-Ouchi in ClimDyn 29(1):39-50, 2007), we used an Atmospheric GeneralCirculation Model (AGCM) rather than an AOGCM.Simulations using the AGCM coupled to a mixed layerocean model (MLM) were conducted for 0 and for 6 kawith different ocean heat transport estimated from theclimatological SST of the 0 ka simulations from ninePaleoclimate Modeling Intercomparison Project (PMIP)phase 2 (PMIP2) AOGCMs (henceforth ‘‘MA’’ is used torefer to experiments using the AGCM coupled with theMLM). No correlation between MA and the correspondingPMIP2 was seen in the 0 ka precipitation and it was notvery strong for the 6 ka precipitation enhancement. Thus,the influences from the different AGCMs play a substantialrole on the 0 ka precipitation and the 6 ka precipitationenhancement. The sensitivity experiments indicated that itwas the pattern of the 0 ka SST bias which played adominant role in the 0 ka precipitation and the 6 ka precipitationenhancement, not the difference in the mean value of the SST bias. The distributions of the 6 ka precipitationenhancements for the nine PMIP2 AOGCMs andnine MA experiments were compared. These showed thatthe effects of SST bias on 6 ka precipitation enhancementamong the AOGCMs were not negligible. The effects ofbiases among the AGCMs were not negligible either, but ofcomparable size. That is, improvements in both the SSTbias and the AGCM contribute to simulate better 6 kamonsoon.