Image. And another example of alarmist nonsense not rooted in reality: Climate change may be escalating so fast it could be ‘game over’, scientists warn
From the ‘scare tactical modeling’ department comes this press release today, which has been circulating to news media until the embargo lifted this morning. You’ll see all sorts of caterwauling from the usual media outlets about how global warming is even worse now, and the future looks grim.
Of course, the back story is pretty much the business as usual scenario; activist scientists, in this case Patrick Brown and Ken Caldiera, who work for the think tank Carnegie Institute have taken the Representative Concentration Pathways (RCP) climate model set, tweaked it a bit with some observational data from the CERES dataset, and declared warming is going to be worse than even the worst-case RCP 8.5 model, which is quickly losing favor as being out of sync with reality.
Basically, it’s a headline-grabber paper.
You can read more about the ‘nightmare scenario’ that is RCP 8.5 here.
Here is the press release:
Climate science: Warmer future forecast
The global warming projection for the end of the twenty-first century could be about 15 per cent greater than the steepest emissions scenario from the Intergovernmental Panel on Climate Change (IPCC), reports a study published in this week’s Nature.
Climate models indicate that human-caused emissions of greenhouse gases will continue to warm the global climate. However, the projected warming varies extensively among different climate models, complicating efforts to mitigate and adapt to climate change.
Patrick Brown and Ken Caldeira assess the many available climate models and constrain them with observational data of the energy budget at the top of Earth’s atmosphere. Focusing on those that realistically simulate observations, the authors find that the observationally informed warming projection to the end of the twenty-first century for the steepest emissions scenario is about 15 per cent warmer than reported by the IPCC and the uncertainty of the previous projections is reduced by a third.
The results add to a broadening collection of research indicating that when models are constrained by observations, they tend to project more global warming for the remainder of the twenty-first century. Therefore, achieving any given global temperature stabilization target will require steeper greenhouse gas emissions reductions than previously calculated.
Greater future global warming inferred from Earth’s recent energy budget
Climate models provide the principal means of projecting global warming over the remainder of the twenty-first century but modelled estimates of warming vary by a factor of approximately two even under the same radiative forcing scenarios. Across-model relationships between currently observable attributes of the climate system and the simulated magnitude of future warming have the potential to inform projections. Here we show that robust across-model relationships exist between the global spatial patterns of several fundamental attributes of Earth’s top-of-atmosphere energy budget and the magnitude of projected global warming. When we constrain the model projections with observations, we obtain greater means and narrower ranges of future global warming across the major radiative forcing scenarios, in general. In particular, we find that the observationally informed warming projection for the end of the twenty-first century for the steepest radiative forcing scenario is about 15 per cent warmer (+0.5 degrees Celsius) with a reduction of about a third in the two-standard-deviation spread (−1.2 degrees Celsius) relative to the raw model projections reported by the Intergovernmental Panel on Climate Change. Our results suggest that achieving any
given global temperature stabilization target will require steeper greenhouse gas emissions reductions than previously calculated.
First, a definition:
Climate sensitivity is the equilibrium temperature change in response to changes of the radiative forcing. … The climate sensitivity specifically due to CO2 is often expressed as the temperature change in °C associated with a doubling of the concentration of carbon dioxide in Earth’s atmosphere. -Wikipedia
I have to laugh at the phrase in the abstract “When we constrain the model projections with observations…“. What the authors are really saying is that they are using the CERES data to create a greater feedback in the model, and thus increase the worst-case scenario by 15%. “Constrained” should actually be “amplified” but in the double-speak of climate modeling, the choice of words is all about making you think they are being conservative with the numbers. In figure 2, note the “observationally informed” plots of the model spread and the Equilibrium Climate Sensitivity whisker plot which suggests an ECS of about 3.7C. Note also the red line in figure 2, which is what their paper predicts.
We find that the observationally informed ECS prediction has a mean value of 3.7 °C (with a 25–75% interval of 3.0 °C to 4.2 °C) and that 68% of the observationally informed distribution of ECS is above the raw model mean of 3.1 °C (Fig. 2e).
3.7C is well above many other observationally-based estimates of ECS, but then again Caldiera is well-known for being a climate alarmist.
Below, I’ve added the Brown-Caldiera ECS estimate to the collection of ECS estimates that we have previously published on WUWT, with a hat tip to Pat Michaels at CATO who originally started this graph:
The important thing to note about the above graph is that it represents a range of opinion. Clearly, climate science doesn’t know exactly what the response of the atmosphere is to a doubling of CO2, but we have a range of opinions published in the literature.
Dr. Benny Peiser of The Global Warming Policy Foundation commented on this paper prior to publication:
The flood of conflicting global warming predictions for the 21st century — from harmless to alarmist — is evidence that climate modellers remain divided over the issue of climate sensitivity. Empirical observations are our best guide. They show that the warming trend over recent decades is much lower and much slower than models have predicted. As long as climate models fail the test of time and fail to replicate reality, they should be treated as GIGO.
Nic Lewis, who authored papers on ECS, shown in the above ECS chart, had this to say:
I am doubtful whether the predictor measures they use are that relevant to the multidecadal warming that they are seeking to predict. They use mean climatology, the magnitude of the seasonal cycle, and the magnitude of monthly variability. The last two are both short term measures, and it is well known that such short term behaviour is not a good guide to longer term warming behaviour under greenhouse gas forcing; or is mean climatology of direct relevance to it.
Their statisitical methodology is quite complex and it is possible that it may not be appropriate.
Of course, the caveats to the headline and headstrong ECS estimates are buried in the paper, and the paper is behind a paywall thanks to Nature. Don’t look behind the curtain!
From the discussion section of the paper:
The constrained global warming projections presented here come with a number of important caveats. First, the unconstrained model values of Δ T do not span the complete uncertainty range. This is because there is a finite number of models, they are not comprehensive, and they do not sample the full uncertainty space of physical process representation. For example, a rapid nonlinear melting of the Greenland and Antarctic ice sheets has some plausibility but is not represented in any of the models studied here and thus it has an effective probability of zero in both the raw unconstrained and observationally informed Δ T distributions.
Furthermore, the models used here cannot be considered to be independent and thus the effective number of models in the suite is less than the nominal number. Because of these considerations, the raw Δ T model spread is best thought of as a lower bound on total uncertainty and thus our observationally informed spread represents a reduction in this lower bound rather than a reduction in the upper bound. Second, the model suite used here is diverse in terms of the level of sophistication of the simulation of, for example, atmospheric chemistry, carbon cycle processes, vegetation dynamics, and so on (Supplementary Table 1). This makes it more difficult to pinpoint the reasons for the spread in Δ T than it would be in a documented perturbed-physics-like model ensemble where only one aspect of model structure is altered at a time. Our statistical results suggest physical mechanisms (as discussed above), but these mechanisms should be interpreted as speculative rather than definitive. Third, the CERES satellite observations used here to constrain the Δ T projections were used to some degree during the model development process.
Ideally, observational data used to evaluate models would be completely independent of any data used in the development of the models. Unfortunately, owing to the limited length of high-quality observations, this is generally not possible for climate model evaluation. Thus, the model spread in the predictor fields may be artificially small owing to explicit efforts to reduce discrepancies between models and observations. Nevertheless, the model spread in the simulated climatological energy budget components is much larger than observational uncertainty (Extended Data Fig. 2), indicating that it is possible to distinguish statistically between models that perform well and poorly.
The above caveats notwithstanding, our results indicate that observations of several diverse attributes of Earth’s global energy budget indicate both individually and collectively that global warming is likely to be greater than that suggested by the unconstrained model suite. In particular, we find that the observationally informed end-of-twenty-first-century warming projection for the RCP 8.5 scenario is about 15% warmer with a reduction of about 33% in spread relative to the raw model projections. Another implication of our observationally informed projections is that the emissions associated with the RCP 4.5 scenario are likely to produce global warming more in line with that previously associated with the RCP 6.0 scenario (Table 1).
Finally, it is sometimes argued that the severity of model-projected global warming can be taken less seriously on the grounds that models fail to simulate the current climate sufficiently accurately. Our study confirms important model-observation discrepancies, indicating ample room for model improvement. However, we do not find that model errors can be taken as evidence that global warming is over-projected by climate models. On the contrary, our results add to a broadening collection of research indicating that models.
The take-away lines are these:
Finally, it is sometimes argued that the severity of model-projected global warming can be taken less seriously on the grounds that models fail to simulate the current climate sufficiently accurately.
However, we do not find that model errors can be taken as evidence that global warming is over-projected by climate models.
You have to admire the sheer chutzpah of such a statement, while at the same time shake your head and laugh about it. Thank goodness these guys aren’t modeling mission-critical structures like bridges.
Industrial Fishing Of Sandeels Is To Blame For Seabird Declines, Not Climate Change
By Paul Homewood
Back to that RSPB report:
According to Yahoo:
The report went on: “The UK’s kittiwake population has declined by 70% since 1986 because of falling breeding success and adult survival.
“Climate change has reduced the availability of the sandeels they rely upon in the breeding season.
“Other species that feed largely on sandeels, such as Arctic skua, Arctic tern and puffin, are at high risk of climate-related decline.”
So let’s take a close look at puffins in particular.
The Joint Nature Conservation Committee (JNCC), published a report in 2011, based on the Seabird 2000 Census. They included two maps, showing the distribution of Atlantic puffins:
The first thing to note is that puffins are well distributed around the British Isles. Although there are many more around Scotland, this is due to the ready availability of suitable habitats.
Waters around the the south west of Wales and Ireland are much warmer than in the North Sea off the east coast of Scotland. Yet that seems to have no effect on the puffins which live in the former.
The map below showing population change also indicates that around Scotland there has been a mixed bag where some locations have seen increases at the same time as other areas close by have seen the opposite.
Since 2002, the puffins appear to have continued thriving in South Wales.
In 2009, the Telegraph reported:
Thousands of birds began leaving Skomer Island in Pembrokeshire over the weekend.
Unlike the rest of the UK, the number of puffins on the island has soared in recent years – leaving conservationists baffled.
The island currently has a puffin population of more than 13,500 – up from 10,000 last year – with more expected to arrive next March.
Jo Milborrow, from the Wildlife Trust of South and West Wales, said: “We’re delighted that the numbers keep growing but we don’t really know why.
“We think it may be because of the increased numbers of sandeels which the puffins feed on. “
And Latest estimates continue to show that puffins are thriving on Skomer.
Clearly there is no evidence here of a consistent climate change signal.
But there is a very real factor, which goes a long way to explain the decline in population in the North Sea.
Sandeels comprise a large proportion of the diet of Atlantic puffins, but since the 1970s they have been subject to heavy, industrial fishing in the North Sea, predominantly by Denmark.
Although attempts have since been made to restrict the harvest of sandeels, the horse has already bolted.
In 2013, a study by the British Trust for Ornithology (BTO) and the Joint Nature Conservation Committee found that fishing of sandeels was still having a significant impact on the population of birds such as the Arctic tern, little tern, common tern, sandwich tern, kittiwake, common guillemot, shag and fulmar.
Significantly they also found that seabirds breeding on the UK’s western colonies were faring better than those on the North Sea coast.
One more study of relevance came in 1998, “Status of the Puffin Fratercula Acrtica on the Isle of May National Nature Preserve” by Harris and Wanless, which stated:
“The history of the puffin on the Isle of May is well documented … in 1883 there were 30-40 pairs … the population was put at 5-10 pairs in the early 1950s but in 1957-58 at least 50 pairs attempted to form a colony. This attempt was brief and unsuccessful and in 1960 there were only a few pairs.”
[The Isle of May is in the Firth of Forth, which has been one of the main areas of concern in recent years.]
So this largest puffin colony in the UK barely existed until the 1970s when both global warming and the puffin population took off. Any population decrease since 1998 must be seen in this longer term context.
To be fair, this new RSPB study does admit that many species of birds are thriving because of a warmer climate.
Inevitably, rare species are, by definition, vulnerable to any environmental change, purely because their numbers are so small. But in these examples quoted, there is no evidence that they are under threat from climate change.
It is often claimed that animals are “forced” to migrate because the weather is too hot or not cold enough. In fact, this is usually a gross distortion of the truth. A warmer climate allows birds to populate areas previously too cold to live or breed in.
As such, the birds’ habitat range is generally expanded. When this happens, there may be a tendency to favour the new areas, where there is less competition for food. As a consequence, population levels may fall in some of the warmer regions previously inhabited.
Climate change may well see a redistribution of birds, with some species disappearing from certain regions to be replaced by others. But there is little evidence that any are under any direct threat as a result.
There is one more study of relevance, Decline in an Atlantic Puffin Population: Evaluation of Magnitude and Mechanisms, by Miles et al in 2015.
They studied puffins on Fair Isle in the Shetlands, and found that the decline in the puffin population coincided with an increase in the numbers of Great Skuas, who just so happen to prey on the poor puffins and other seabirds.
Great Skuas also like to eat other birds under threat, like Kittiwakes.
It may be that the Skua population took off as a result of the increase in the number of puffins already noted in the 1970s.