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DOI	10.1007/s00382-019-04991-y
	How accurately can the climate sensitivity to CO 2 be estimated from historical climate change?
	Gregory J.M.; Andrews T.; Ceppi P.; Mauritsen T.; Webb M.J.
发表日期	2020
ISSN	0930-7575
起始页码	129
结束页码	157
卷号	54 期号:2020-01-02
英文摘要	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 ±30to45% (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. © 2019, The Author(s).
英文关键词	Climate feedback; Climate sensitivity; Volcanic forcing
语种	英语
scopus关键词	accuracy assessment; anthropogenic effect; carbon dioxide; climate change; climate feedback; climate variation; historical perspective; radiative forcing; sensitivity analysis; volcanic eruption; weather forecasting
来源期刊	Climate Dynamics
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/145764
作者单位	National Centre for Atmospheric Science, University of Reading, Reading, United Kingdom; Met Office Hadley Centre, Exeter, United Kingdom; Grantham Institute, Imperial College London, London, United Kingdom; Department of Meteorology, Stockholm University, Stockholm, Sweden
推荐引用方式 GB/T 7714	Gregory J.M.,Andrews T.,Ceppi P.,et al. How accurately can the climate sensitivity to CO 2 be estimated from historical climate change?[J],2020,54(2020-01-02).
APA	Gregory J.M.,Andrews T.,Ceppi P.,Mauritsen T.,&Webb M.J..(2020).How accurately can the climate sensitivity to CO 2 be estimated from historical climate change?.Climate Dynamics,54(2020-01-02).
MLA	Gregory J.M.,et al."How accurately can the climate sensitivity to CO 2 be estimated from historical climate change?".Climate Dynamics 54.2020-01-02(2020).