by Judith Curry

Here is a summary of some important new papers on the topics of climate sensitivity and attribution.

Time-varying climate sensitivity from regional feedbacks

Kyle Armour, Cecilia Bitz, Gerard Roe

Abstract. The sensitivity of global climate with respect to forcing is generally described in terms of the global climate feedback—the global radiative response per degree of global annual mean surface temperature change. While the global climate feedback is often assumed to be constant, its value—diagnosed from global climate models—shows substantial time-variation under transient warming. Here we show that a reformulation of the global climate feedback in terms of its contributions from regional climate feedbacks provides a clear physical insight into this behavior. Using (i) a state-of-the-art global climate model and (ii) a low-order energy balance model, we show that the global climate feedback is fundamentally linked to the geographic pattern of regional climate feedbacks and the geographic pattern of surface warming at any given time. Time-variation of global climate feedback arises naturally when the pattern of surface warming evolves, actuating regional feedbacks of different strengths. This result has substantial implications for our ability to constrain future climate changes from observations of past and present climate states. The regional climate feedbacks formulation reveals fundamental biases in a widely-used method for diagnosing climate feedbacks and radiative forcing—the regression of the top-of-atmosphere radiation flux on surface temperature. Further, it provides a clear mechanism for the ‘efficacies’ of both ocean heat uptake and radiative forcing.

Paper submitted to J. Climate [link]

Paul K has a guest post on this paper over at the Blackboard, some excerpts:

The implications of this paper are important and wide-ranging. It sends a number of sacred cows to the abattoir without being too concerned about the religion of the owners. In a certain sense it offers a unifying theory which should allow extremists on both sides of the climate sensitivity debate to moderate their views, and bring some calm reflection to the question of observation vs model results.

If one accepts that the curvilinear response is a real world phenomenon and that it is sufficient to bring into question the common assumption of constant linear feedback, one can reasonably conclude that a zero-dimensional linear feedback model should never be used by either skeptics or mainstream scientists – other than for local feedbacks or short-term feedbacks – and yet this is a common assumption that has been broadly applied to global response in hundreds of climate science papers. Here are just a few of the possible inferences to be drawn from Armour 2012:-

Effective climate sensitivity increases with time and temperature largely because of polar amplification and the relatively long response times of the high latitude regions.

The many previous papers which have sought to explain this phenomenon in terms of changing ocean heat uptake efficacy, changing forcing efficacy, varying negative cloud forcing or local non-linear temperature effects in feedback response are debunked or devalued.

Dozens of key papers which assume a linear global feedback to analyze the AOGCMs are just plain wrong or are heavily compromised (e.g. all of the landmark papers which partition and attribute feedbacks based on the assumption of a linear model and many of the regression methods applied to net flux and temperature from the GCMs).

Many other papers which estimate climate sensitivity directly from observational data are testing only a short-duration secant of the curvilinear flux response – valuable for comparative purposes over the same time and temperature scales perhaps, but underestimating the longer-term sensitivity.

The paper sets a new hurdle for assessing the reliability of estimates of ECS from the GCMs. As a necessary (but still not sufficient) condition the relationships between net-flux and temperature and between temperature and time in each latitude band need to be consistent with observed data; ideally this should be true for land and sea separately. Matching just global average temperature is revealed to be a very weak test of model validity.

JC comment: A light bulb went off in my head when I read this paper. A lot of my thinking about feedbacks and sensitivity have focused on the Arctic, and I have used a regional approach related to local temperature (or even sea ice conditions) that is conceptually similar to Armour et al. I find this formalism immensely useful, and explains how my blogospheric discussions about sensitivity with others using the conventional global energy balance approach seem to be talking past each other. I think this is a very important paper, and I find this approach to be vastly preferable and potentially much more informative than the conventional approach.

Using data to attribute episodes of warming and cooling in instrumental records

Ka-Kit Tung and Jiansong Zhou

Abstract: The observed global-warming rate has been nonuniform, and the cause of each episode of slowing in the expected warming rate is the subject of intense debate. To explain this, nonrecurrent events have commonly been invoked for each episode separately. After reviewing evidence in both the latest global data (HadCRUT4) and the longest instrumental record, Central England Temperature, a revised picture is emerging that gives a consistent attribution for each multidecadal episode of warming and cooling in recent history, and suggests that the anthropogenic global warming trends might have been overesti- mated by a factor of two in the second half of the 20th century. A recurrent multidecadal oscillation is found to extend to the preindustrial era in the 353-y Central England Temperature and is likely an internal variability related to the Atlantic Multidecadal Oscillation (AMO), possibly caused by the thermohaline circulation variability. The perspective of a long record helps in quantifying the contribution from internal variability, especially one with a period so long that it is often confused with secular trends in shorter records. Solar contribu- tion is found to be minimal for the second half of the 20th century and less than 10% for the first half. The underlying net anthropogenic warming rate in the industrial era is found to have been steady since 1910 at 0.07–0.08 °C/decade, with superimposed AMO-related ups and downs that included the early 20th century warming, the cooling of the 1960s and 1970s, the accelerated warming of the 1980s and 1990s, and the recent slowing of the warming rates. Quantitatively, the recurrent multidecadal internal variabil- ity, often underestimated in attribution studies, accounts for 40% of the observed recent 50-y warming trend.

The paper is published by PNAS, link to abstract [here]. Link to complete papere [here]. Here are additional excerpts from the text:

The presence of multidecadal internal variability superimposed on the secular trend gives the appearance of accelerated warming and cooling episodes at roughly regular intervals. Below we give a consistent explanation of the four centuries of climate variation based on the assumption that much of the AMO is natural and recurrent.

Almost no sunspots were observed during a 70-y interval (1645–1715) called the Maunder Minimum (1). Large volcano eruptions—Huaynaputina (1600), Parker (1641), and Long Island (1660)—contributed to the cold LIA at the beginning of the CET record. An unusual series of five large volcano eruptions from 1660 to 1680 probably prolonged the cold into the Late Maunder Minimum. A negative phase of the AMO accentuated the cold further in Late Maunder Minimum, reported in Europe (1), although it was thought that the cold CET was only “locally representative” (37). Our current work argues that it is probably global because the AMO has in-phase global manifestations (Fig. 3). There were no major known volcanoes from 1680 to 1707 [although there were some unknown ones (38)], and it started to warm. Although commonly attributed to the Sun (1), the rapid warming of ∼1 °C at the end of Maunder Minimum is 10 times greater than our understanding of the solar radiation change (39) can explain but is within the range of a speculative theory (40) if we remove 0.4 °C as due to the AMO. The timing of the warming, however, appears to precede the increase in total solar irradiance (TSI) (39, 41) by 20–30 y and favors the reduced volcanic aerosol loading as the main cause for the warming—the rebound. The 20-y small dip in temperature near 1810 coincides with the solar Dalton Minimum, but is probably caused by a negative excursion of the AMO. The rising AMO cycle in the first half of the 19th century produced a warming, despite the eruption of Tambora (1815), the largest in the past four centuries. The next rising phase of AMO led to the often cited early 20th-century warming in the global mean (1910–1940) of 0.4 °C, but it happened to occur during a period of increasing mean solar irradiance, leading some to attribute it, incorrectly, to solar forcing. The observed warming rate for that period lies above the range of all model responses to combined anthropogenic and natural forcing com- piled by IPCC AR4, even after correcting for a discontinuity in the wartime data, corroborating the suggestion here that it is mostly caused by internal variability. The cooling experienced in the 1960s and 70s is seen as occurring in the negative phase of the AMO. The period after the 1970s shows a secular increase in global-mean temperature. The rising AMO half-cycle gives the appearance of an accelerated warming that lasted until 2005 (discounting the warm El Niño of 1998). Recently, there have been debates about the slowing of the warming rates since 2005, with explanations ranging from increases in stratospheric water vapor and background aerosol to increased coal burning in the emergent economy of China of the past 20 y. If one accepts the conclusion that the AMO is recurrent, and because this period coincides with the start of the descending phase of the AMO, one can suggest that the AMO is a more likely explanation.

For the first half of the 20th century, the solar contribution to the linear trend was less than 10%. It does not support the much larger role (>50%) for the Sun in the observed warming, obtained by Scafetta and West by attributing early 20th-century warming to solar forcing. The observed solar- cycle response suggests that it is a response to radiative effects of the TSI, amplified by the same climate feedback factors as for the greenhouse radiative forcing. There were no consecutive large volcanic eruptions in the 20th century, and none that could have caused the recent slowdown in the rate of global warming.

Various fitted linear trends in global-mean temperature up to 2005 were presented in the IPCC AR4, with the recent 25-y trend (at 0.177 °C/decade) larger than the 50-y trend (0.128 °C/decade), which is in turn larger than the 100- and 150-y trends (0.074 and 0.045 °C/decade, respectively). The phenomenon of “accelerating warming trends” is still present. The fitted 25-y trend is not robust, being sensitive to the addition or subtraction of a single-year end-point datum and so will not be discussed further here. A 50-y wavelet low-pass filter is applied to the data points. It is seen by eye that the smoothed curve captures the main episodes of warming and cooling in the past 162 y that are present in the raw data as it agrees with the simple running mean. In particular, one can see that there is a low-frequency oscillation present in the data. We reprocess the data after re- moving the oscillatory component, defined by the 50- to 90-y wavelet band, the AMO. The removal of the AMO in the determination of the anthropogenic warming trend is justified if one accepts our previous argument that this multidecadal variability is mostly natural. Linear trends are then fitted to the resulting data points in Fig. 4B in the same way as in the IPCC AR4. It is visually apparent in Fig. 4B that removing the oscillatory AMO from the raw data organizes the data points into a monotonic band and yields a more stable linear trend, converging to the 50-y trend of 0.08 °C/decade. We argue that this is the long-term anthropogenic trend, forced by greenhouse gas increases offset by tropospheric aerosol cooling, which also increased along with industrialization. Comparing Fig. 4B with Fig. 4A, we see that the internal variability accounts for 40% of the observed 50-y trend.

The same anthropogenic trend since 1979 of 0.17 °C/decade is obtained. However, one can see clearly that a 70-y oscillation is still present in the residual (see the orange running mean). In Fig. 5B, we add the AMO Index (16) to the multiple linear re- gression analysis. The 33-y net anthropogenic warming rate obtained, at 0.07 °C/decade, is less than half of Foster and Rahmstorf’s. In fact, the net anthropogenic warming trend has been remarkably steady for the past 100 y at 0.07–0.08 °C/decade.

Although there is a competing theory that the observed multi- decadal variability is forced by anthropogenic aerosols during the industrial era, our present work showing that this variability is quasi-periodic and extends at least 350 y into the past with cycles in the preindustrial era argues in favor of it being naturally recurrent and internally generated. This view is supported by model results that relate the variability of the global-mean SST to North Atlantic thermohaline circulation and by the existence of an AMO-like variability in control runs without anthropogenic forcing . If this conclusion is correct, then the following interpretation follows: The anthropogenic warming started after the mid-19th century of Industrial Revolution. After a slow start, the smoothed version of the warming trend has stayed almost constant since 1910 at 0.07–0.08 °C/decade. Superimposed on the secular trend is a natural multidecadal oscillation of an average period of 70 y with significant amplitude of 0.3–0.4 °C peak to peak, which can explain many historical episodes of warming and cooling and accounts for 40% of the observed warming since the mid-20th century and for 50% of the previously attributed anthropogenic warming trend (55). Be- cause this large multidecadal variability is not random, but likely recurrent based on its past behavior, it has predictive value. Not taking the AMO into account in predictions of future warming under various forcing scenarios may run the risk of over- estimating the warming for the next two to three decades, when the AMO is likely in its down phase.

The present finding that the low-frequency portion of the regional data agrees with the global mean (with a scaling that is slightly larger than 1) during the 162-y overlap period supports the notion (but does not prove) that a single time series can, in fact, be used to represent the global mean variation.

Using CET as supporting evidence, we have shown here that these same 2.5 cycles in the global data are a part of a recurrent oscillation going back at least 350 y, and it is unlikely that they can be attributed to volcanic aerosols, whose eruptions were not periodic nor aligned with the troughs.

JC comment. This paper seems to be the most advanced attribution analysis that I’ve seen that includes multi-decadal oscillations plus secular trend (see the previous thread Trends, Change Points and Hypotheses.) One critique is that the analysis seems overconfident of our knowledge of solar variability over this period. This paper also raises the issue of the representativeness of local measurements; in this instance the CET, but this assumption is also heavily used in global paleo reconstructions using only a few sites.

The upper end of climate model temperature projections is inconsistent with past warming

Peter Stott, Peter Good, Gareth Jones, Nathan Gillett and Ed Hawkins

Abstract. Climate models predict a large range of possible future temperatures for a particular scenario of future emissions of greenhouse gases and other anthropogenic forcings of climate. Given that further warming in coming decades could threaten increasing risks of climatic disruption, it is important to determine whether model projections are consistent with temperature changes already observed. This can be achieved by quantifying the extent to which increases in well mixed greenhouse gases and changes in other anthropogenic and natural forcings have already altered temperature patterns around the globe. Here, for the first time, we combine multiple climate models into a single synthesized estimate of future warming rates consistent with past temperature changes. We show that the observed evolution of near-surface temperatures appears to indicate lower ranges (5–95%) for warming (0.35–0.82 K and 0.45–0.93 K by the 2020s (2020–9) relative to 1986–2005 under the RCP4.5 and 8.5 scenarios respectively) than the equivalent ranges projected by the CMIP5 climate models (0.48–1.00 K and 0.51–1.16 K respectively). Our results indicate that for each RCP the upper end of the range of CMIP5 climate model projections is inconsistent with past warming.

Published in Environmental Research Letters, link [here].

JC summary: these papers are providing useful contributions to the methodologies of estimating climate sensitivity and attribution of climate change. Collectively they demonstrate the structural uncertainty, or ‘meta-uncertainty’ of the methodologies upon which our sensitivity and attribution analyses depend. This kind of structural uncertainty does not get included in IPCC confidence levels.

Moderation note: this is a technical thread; comments will be moderated for relevance.