Sensitivity of Surface Temperature to Oceanic Forcing via q-Flux Green’s Function Experiments. Part I: Linear Response Function

Liu, Fukai; Lu, Jian; Garuba, O. A.; Leung, L. Ruby; Luo, Yiyong; Wan, Xiuquan

doi:10.1175/jcli-d-17-0462.1

Cited by 38 publications

(38 citation statements)

References 65 publications

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“…This contrasts with the AOGCMs, in which we found evaluated from a single integration to be biased low by the presence of unforced variability (Appendix C), and comparably large values are attained only in the multimodel mean. We speculate that there are coupled atmosphere-ocean feedbacks which reinforce this SST pattern in the real world but are lacking in models (McGregor et al 2014(McGregor et al , 2018Raedel et al 2016;Yuan et al 2018;Liu et al 2018).…”

Section: Sst and Effcs Since 1975mentioning

confidence: 95%

How accurately can the climate sensitivity to $$\hbox {CO}_{2}$$ be estimated from historical climate change?

et al. 2019

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The equilibrium climate sensitivity (ECS, in K) to CO 2 doubling is a large source of uncertainty in projections of future anthropogenic climate change. Estimates of ECS made from non-equilibrium states or in response to radiative forcings other than 2 × CO 2 are called "effective climate sensitivity" (EffCS, in K). Taking a "perfect-model" approach, using coupled atmosphere-ocean general circulation model (AOGCM) experiments, we evaluate the accuracy with which CO 2 EffCS can be estimated from climate change in the "historical" period (since about 1860). We find that (1) for statistical reasons, unforced variability makes the estimate of historical EffCS both uncertain and biased; it is overestimated by about 10% if the energy balance is applied to the entire historical period, 20% for 30-year periods, and larger factors for interannual variability, (2) systematic uncertainty in historical radiative forcing translates into an uncertainty of ± 30 to 45% (standard deviation) in historical EffCS, (3) the response to the changing relative importance of the forcing agents, principally CO 2 and volcanic aerosol, causes historical EffCS to vary over multidecadal timescales by a factor of two. In recent decades it reached its maximum in the AOGCM historical experiment (similar to the multimodel-mean CO 2 EffCS of 3.6 K from idealised experiments), but its minimum in the real world (1.6 K for an observational estimate for 1985-2011, similar to the multimodel-mean value for volcanic forcing). The real-world variations mean that historical EffCS underestimates CO 2 EffCS by 30% when considering the entire historical period. The difference for recent decades implies that either unforced variability or the response to volcanic forcing causes a much stronger regional pattern of sea surface temperature change in the real world than in AOGCMs. We speculate that this could be explained by a deficiency in simulated coupled atmosphere-ocean feedbacks which reinforce the pattern (resembling the Interdecadal Pacific Oscillation in some respects) that causes the low EffCS. We conclude that energy-balance estimates of CO 2 EffCS are most accurate from periods unaffected by volcanic forcing. Atmosphere GCMs provided with observed sea surface temperature for the 1920s to the 1950s, which was such a period, give a range of about 2.0-4.5 K, agreeing with idealised CO 2 AOGCM experiments; the consistency is a reason for confidence in this range as an estimate of CO 2 EffCS. Unless another explosive volcanic eruption occurs, the first 30 years of the present century may give a more accurate energy-balance historical estimate of this quantity.

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Section: Sst and Effcs Since 1975mentioning

confidence: 95%

How accurately can the climate sensitivity to $$\hbox {CO}_{2}$$ be estimated from historical climate change?

et al. 2019

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“…However, models have trouble simulating the correct relationship between the AO and tropical forcing (L'Heureux et al 2008;Ding et al 2019). A recent study (Liu et al 2018) further suggests that the circulation pattern that is optimal for Arctic warming, such as a negative AO phase, could own an origin from an intrinsic mode excitation in the high latitudes, tending to be efficiently forced by an oceanic flux in the eastern equatorial Pacific. It is very likely that the relationship between the AO and tropical forcing is not well captured in the pacemaker experiments and may be an additional cause of some of the discrepancies between our experiment and observations.…”

Section: Simulated Circulation Responses To Tropical Sst Change From mentioning

confidence: 99%

How Tropical Pacific Surface Cooling Contributed to Accelerated Sea Ice Melt from 2007 to 2012 as Ice Is Thinned by Anthropogenic Forcing

et al. 2019

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Over the past 40 years, the Arctic sea ice minimum in September has declined. The period between 2007 and 2012 showed accelerated melt contributed to the record minima of 2007 and 2012. Here, observational and model evidence shows that the changes in summer sea ice since the 2000s reflect a continuous anthropogenically forced melting masked by interdecadal variability of Arctic atmospheric circulation. This variation is partially driven by teleconnections originating from sea surface temperature (SST) changes in the east-central tropical Pacific via a Rossby wave train propagating into the Arctic [herein referred to as the Pacific–Arctic teleconnection (PARC)], which represents the leading internal mode connecting the pole to lower latitudes. This mode has contributed to accelerated warming and Arctic sea ice loss from 2007 to 2012, followed by slower declines in recent years, resulting in the appearance of a slowdown over the past 11 years. A pacemaker model simulation, in which we specify observed SST in the tropical eastern Pacific, demonstrates a physically plausible mechanism for the PARC mode. However, the model-based PARC mechanism is considerably weaker and only partially accounts for the observed acceleration of sea ice loss from 2007 to 2012. We also explore features of large-scale circulation patterns associated with extreme melting periods in a long (1800 yr) CESM preindustrial simulation. These results further support that remote SST forcing originating from the tropical Pacific can excite significant warm episodes in the Arctic. However, further research is needed to identify the reasons for model limitations in reproducing the observed PARC mode featuring a cold Pacific–warm Arctic connection.

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“…This large suite of CAM5 experiments will be referred to as the q-flux Green's function experiments in the sense that the response becomes a Green's function solution in the limit of the forcing patch approaching a Dirac delta function. See Liu et al 19,20 for further details about the experiment configuration. The approach herein should be distinguished from the similar sea surface temperature (SST) Green's function experiments performed to quantify the global radiative feedbacks to local SST perturbations 21,22 .…”

Section: Q-flux Green's Function Experimentsmentioning

confidence: 99%

Neutral modes of surface temperature and the optimal ocean thermal forcing for global cooling

Liu

Leung

et al. 2020

npj Clim Atmos Sci

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Inquiry into the climate response to external forcing perturbations has been the central interest of climate dynamics. But the understanding of two important aspects of climate change response-nonlinearity and regionality-is still lacking. Here a Green's function approach is developed to estimate the linear response functions (LRFs) for both the linear and quadratic nonlinear response to ocean thermal forcing in a climate model, whereby the most excitable temperature modes, aka the neutral modes, can be identified for the current Earth climate. The resultant leading mode of the nonlinear response is characterized by a polaramplified global cooling pattern, unveiling an intrinsic inclination of the modern climate towards cooling. Moreover, optimal forcing patterns are identified to most efficiently excite the corresponding neutral mode patterns. The forcing-response framework developed herein can be utilized to determine the optimal forcing patterns to inform solar geoengineering experiments and to interpret regional climate response and feedback in general.npj Climate and Atmospheric Science (2020) 3:9 ; https://doi.

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Sensitivity of Surface Temperature to Oceanic Forcing via q-Flux Green’s Function Experiments. Part I: Linear Response Function

Cited by 38 publications

References 65 publications

How accurately can the climate sensitivity to $$\hbox {CO}_{2}$$ be estimated from historical climate change?

How accurately can the climate sensitivity to $$\hbox {CO}_{2}$$ be estimated from historical climate change?

How Tropical Pacific Surface Cooling Contributed to Accelerated Sea Ice Melt from 2007 to 2012 as Ice Is Thinned by Anthropogenic Forcing

Neutral modes of surface temperature and the optimal ocean thermal forcing for global cooling

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