Arguments
Climate scientists just debunked deniers' favorite argument
Posted on 28 June 2017 by dana1981
Whenever they hold one of their frequent hearings to reject and deny established climate science, congressional Republicans invariably trot out contrarian scientist John Christy, who disputes the accuracy of climate models. In doing so, Christy uses a cherry-picked, error riddled chart, but there’s a nugget of truth in his argument. Although the discrepancy isn’t nearly as large as Christy’s misleading chart suggests, atmospheric temperatures seem not to have warmed quite as fast since the turn of the century as climate model simulations anticipated they would.
Remote Sensing Systems estimate of the temperature of the middle troposphere compared to the CMIP5 multi-model average (top frame), and the difference between the two over time (bottom frame). Illustration: Santer et al. (2017), Nature Geoscience
How you react to this information is a good test of whether you’re a skeptic or a denier. A denier will declare “aha, the models are wrong, therefore we don’t need any climate policies!” A skeptic will ask what’s causing the difference between the observational estimates and model simulations.
There are many possible explanations. Maybe the tricky and often-adjusted estimates of the atmospheric temperature made by instruments on orbiting satellites are biased. Maybe there’s something wrong with the models, or our understanding of Earth’s atmosphere. Maybe the inputs used in the model simulations are flawed. The answer is likely a combination of these possibilities, but in congressional testimony earlier this year, Christy tried to place the blame entirely on the models, with a denier-style framing:
the average of the models is considered to be untruthful in representing the recent decades of climate variation and change, and thus would be inappropriate for use in predicting future changes in the climate or for related policy decisions.
And in testimony to Congress in December 2015, Christy offered his unsupported speculation that the discrepancy was a result of climate models being too sensitive to rising greenhouse gases:
Indeed, the theoretical (model) view as expressed in the IPCC AR5 in every case overestimated the bulk tropical atmospheric temperature response of extra greenhouse gases … indicating the theoretical understanding of the climate response is too sensitive to greenhouse gases.
New study tests and falsifies Christy’s assertions
The issue is that climate model simulations are run using specific scenarios. These scenarios assume specific changes in factors that influence global temperature and climate changes (known as “forcings”), like rising levels of atmospheric greenhouse gases and changes in solar and volcanic activity. Climate models don’t make “predictions;” rather, they make “projections” of how temperatures and other climatological factors will change in response to those forcing input scenarios. There’s also a random component known as “internal variability” due to factors like unpredictable ocean cycles.
An infamous example of deniers exploiting this wonky technical point to mislead policymaker happened in 1998. Congressional Republicans invited fossil fuel-funded Pat Michaels to testify ahead of the Kyoto international climate negotiations. In a shameless distortion of reality, Michaels evaluated a 1988 global temperature projection by James Hansen at NASA, but deleted all except the scenario that was the least like the actual forcing changes that had occurred over the prior decade. By only looking at Hansen’s model projection under a scenario where greenhouse gases rose much faster than they had in reality, Michaels deceptively made it appear as though Hansen’s climate model had vastly over-predicted global warming.
Santer’s team found a similar issue in comparing simulated and observed changes in atmospheric temperatures over the past few decades:
There are known systematic errors in these forcings in model simulations performed in support of the IPCC Fifth Assessment Report. These errors arise in part because the simulations were performed before more reliable estimates of early 21st century forcing became available. The net effect of the forcing errors is that the simulations underestimate some of the cooling influences contributing to the observed “slowdown”.
For example, were Christy right that models are too sensitive to rising greenhouse gases, they should be systematically wrong during the entire period for which we have observational data. On the contrary, aside from a small discrepancy in the late 20th century that can be explained by natural internal variability, Santer’s team showed that the difference between model simulations and observations only begins around 1998. A problem with model sensitivity would also show up in studies looking at global temperature changes in response to large volcanic eruptions, which create a big change in forcing and temperature. But those studies rule out the low climate sensitivities that Christy favors, and as Santer’s team notes:
there are no large systematic model errors in tropospheric cooling following the eruptions of El Chichon in 1982 and Pinatubo in 1991.
On the other hand, research has identified a number of real-world cooling influences in the early 21st century that weren’t accurately represented in the climate model simulation scenarios. The sun went into an unusually quiet cycle, there was a series of moderate volcanic eruptions, and the boom in Chinese coal power plants added sunlight-blocking pollution to the atmosphere. Using statistical tests, Santer’s team showed that those unexpected cooling effects combined with shifts in ocean cycles best explained the model-data discrepancy in atmospheric temperatures over the past 20 years.
Deniers respond by turning on the spin cycle
Unsurprisingly, in blogs and on Twitter, deniers tried to spin the results of this study in their favor. Some claimed that the paper admitted there was a “pause” or “hiatus” in global warming. In reality, the paper used neither term, but did use the phrase “slowdown” 15 times, including explicitly clarifying that it was a “temporary” slowdown. In other words, the study clearly rejected the myth that global warming “paused;” instead, the rise in atmospheric temperatures temporarily slowed due to the aforementioned decline in solar activity, increase in pollution from coal plants and volcanic eruptions, and shifts on ocean cycles.
Other contrarians have exhibited their confirmation bias by claiming the paper is an admission that climate models are wrong. As statistician George Box said, “all models are wrong, but some are useful.” Declaring that climate models are wrong and tossing them in the waste bin is a brain-dead denial move. What any skeptical scientific mind should want to know is why they’re imperfect – what’s causing the difference between simulations and reality, and what can we learn from that?
Christy: "the models... would be inappropriate... in predicting future changes in the climate or for related policy decisions." Compared to what? Christy's intuition? Lamar Smith's faith that the future will be unlike the past? Inhofe's 'God is still up there'? The models are all policymakers have because the 'other side' of this debate steadfastly refuses to put together any models (or refuses to share the knowledge that they put them together, i.e. Exxon 1980). You would think an industry with a 22 trillion dollar stake in the outcome of this debate would be able to afford a better pointer to our climate future than James Inhofe's snowball.
Recommended supplemental reading:
Study: Why troposphere warming differs between models and satellite data by Zeke Hausfather, Carbon Brief, June 21, 2017
I don't think I have ever seen a model projection for the upper and intermediate ocean temperatures. Does one exist? Since that is where 90% of the heat goes, and it seems rather immune to internal variation and other non-radiative forcings (possibly due to the ginormous mass involved) it would seem like this would be easier to predict. In general, I think this data should be presented to the public more frequently.
rocketeer - how would extract those ocean temperatures from the modelling grid in a useful way and present compare them? One way is instead to extract global OHC over various depth ranges from models and compare, but I understand that is not trivial and not routine.
Anyway, data from models available here.
The models diverge from reality after about 2005, but only slightly. This is short term, so is most likely short term natural variation. As you say its not climate sensitivity and could be volcanic activity etc.
I would add natural variation like enso or pdo cycles could be difficult to 100% accurately incorporate into into models , as it's not perfectly regular, so you cannot read anything much into a divergence of temperatures over relatively short terms up to about 25 years.
In contrast sea level rise is slightly ahead of model estimates. Nothing from Christie on this. Again there's so much going on its hard to make completely 100% accurate predictions, but things can be more than predicted as well.
Do we do nothing on climate change because we don't as yet have 100% accuracy? It's like saying lets not treat this very sick patient, because we dont 100% understand how the body works, and can't 100% accurately predict outcomes of surgery or drugs. We would obviously treat the patient.
I should also say looking at straight temperature of any layer in ocean in most certainly not immune to internal variability. However, I do agree that OHC 0-2000m globally averaged is indeed a more stable measure of climate than surface temperature. However, if you look at it:
you see that still quite a lot of variability from ocean-atmosphere exchange. That is where heat from El nino comes from.
How can presentation of anything that is unjustifiably contrary to 'a fuller better understanding of what is going on and the application of that understanding to help improve the future for all of humanity' become a legally punishable offense, with the presenter and everyone who tries to unjustifiably defend or excuse the misrepresentation of understanding being penalized, with the magnitude of the penalty being based on the severity of the implications of their misrepresentation for the future of humanity, and the penalty including Elected Representatives and Supreme Court members to be removed from their positions (not waiting for the next election or for a replacement Justice to be identified)?
The real treat of potentially Losing Big League may be the only way to limit the attempts of those who grow up believing they can get away with deliberately trying to get as much advantage as possible from behaving as unacceptably as they can get away with.
As I pointed out on hotwhopper where this was also raised - what Santer's team did was to effectively validate what Foster & Rahmstorf did earlier.
We don't have any ability to actually penalize lying and misrepresentation in the service of the people who think "greed is good". The penalty is eventually to the society as a whole, which will ultimately disintegrate. The losers are everyone not in that 0.5% winners circle and the real penalties are going to be rather harsher.
Just not on this generation.
I do agree it would be good to force the issue regarding truth, but as long as we have a media that is owned by the 0.5% , and news that has to be sold like soap powder, we are just as owned. So not happening. What needs to happen is the effective dissolution of the United States of America and the regions choosing their own paths as to whether to be independent nations and what laws to apply to each. I could not live on the same block as a Pruitt or a Lamar Smith. I am lucky that I don't have to.. but I am on the same planet so they aren't far enough away.
bjchip@8,
It is curious that in the USA and many other nations an advertiser who tries to present actual but unflattering facts about a competitor can be penalized or at least stopped from continuing to do it, and the penalty is worse if they misrepresent the facts about a competitor, yet no such penalties apply to government actions or election campaigns.
The absence of Good Reason Ethical standards for government activity, and the inconsistent application of things like the advertising penalties (used more to limit public awareness of unacceptably activity than to correct for deliberate unjustifiable wrongs being done), are indications of how incorrectly developed a nation has become.
The first step to "Getting Better Behaviour" is exposure and increased understanding that the current behaviour is unacceptable. The exposure is growing. Getting acceptance that the bahaviour is unacceptable enough to require effective significant penalties is likely not that far away (and understandably faces fierce opposition).
The most interesting aspect of this attack on climate science is the way the attackers/deniers appear to be unaware that their actions are shattering illusions/preceptions of special status and admiration for the wealthy and powerful today. It is becoming more apparant to more people that recognition and reward is not owed to someone because of the impression or image they create (their profitability and popularity may or may not be deserved). There actually is a reality that can be understood by everyone, the need to help others and help improve the future for all of humanity. And images or dogmas that are inconsistent with that understandable reality eventually get shattered (or there is no future for humanity).
Sadly, a lot of damage is usually able to be done before the shattering of unjustified impressions makes deserving losers of the ones who have been the biggest trouble-makers. There are many other exmples of how understandably unacceptable things are gotten away with in pursuit of personal benefit and profit. But climate science has unintentially produced a Huge Unmistakable Bad Example Response that everyone can understand to be Bad, even if they refuse to admit that it is bad.
BJChip says "I do agree it would be good to force the issue regarding truth, but as long as we have a media that is owned by the 0.5% , and news that has to be sold like soap powder, we are just as owned..... I could not live on the same block as a Pruitt or a Lamar Smith. "
I agree on both points.
Regarding the media, its not just the owners. I have seen a big change in our main newspapers over the last couple of years. They used to be at least moderately balanced, but now print far fewer articles critical of things like fossil fuel interests, food companies, sugar consumption etc and instead have now tended to become almost total corporate apologists. It's possibly fear of losing advertising to social media or other internet media.
It's reached crisis point, unfortunately right at the wrong time for getting facts out on climate change. I dont know what the answer is, but the mainstream media are turning to trash. It's not fake news in the flawed and ridiculous way Trump claims, its near total corporate capture.
I'm a very easy going guy who will normally talk to people of all ideologies and classes, but these days I would struggle to socialise with some of these climate denier people. And frankly I dont have to. It's not their beliefs as such, it's the underhanded distortion of so many issues, which I think is largely cynically deliberate.
New paper Mears and Wentz of RSS on new v4
https://www.carbonbrief.org/major-correction-to-satellite-data-shows-140-faster-warming-since-1998
As I understand it the authors of the recent paper in Nature Geoscience said that: "We conclude that model overestimation of tropospheric warming in the early twenty-first century is partly due to systematic deficiencies in some of the post-2000 external forcings used in the model simulations". As neither a believer or a denier, I think the logical view to take is that the model predictions were indeed wrong and due to wrong assumptions. I leave others to judge whether the wrong assumptions reflect shortcomings in our understanding of how the climate works. But I would plead for more humility on all sides in this debate.
Mike Evershed: The models are not used to make "predictions," they are used to make "projections." Whereas in typical English those terms might be synonyms, in technical climatological language "prediction" means asserting both that a set of specific values of climate forcings will occur, and that the climate will respond in a particular way. Climatologists rarely use "prediction," because rarely do they assert that a particular set of values of forcings will occur.
Climatologists usually use "projection," because they make merely a working assumption about the values of the forcings, which they give as inputs to climate models. The models themselves do not "contain" those forcing values, but merely respond to them. For example, the climate models do not make predictions about the amount of energy the Sun will deliver to the Earth's top of the atmosphere. The climate models instead "predict" the Earth's climatological response to whatever solar energy is input to the models.
For climate models to produce those estimates, they must be given those forcings as inputs. Each set of such forcing inputs is called a "scenario" or a "Representative Concentration Pathway." Models' accuracies properly can be judged only by comparing their projected responses to the forcing scenarios that actually happened. In the absence of a time machine, that must be done after the fact. "Hindcasts" of the models are exactly that: "projections" using the values of the forcings that actually happened, up to the most recent year for which the forcings are known. When models are run for years in the future, scientists input to them one or multiple scenarios as what-ifs.
Mike Evershed: GoogleMaps is a computer model of traffic. It "predicts" when I will arrive at my office, given my home departure time. I run that model multiple times, each time with a different input of my departure time (a different "scenario"), and each such run "predicts" the resulting arrival time. GoogleMaps does not predict when I will depart, so it does not predict when I will arrive.
GoogleMaps can be "wrong" about my arrival time if I input the wrong departure time. GCMs can be "wrong" about the climate if I input the wrong forcings. Such "wrong" outputs do not in any way reflect poorly on GoogleMaps or GCMs. To help keep that distinction clear, scientists use the term "projection" for what GCMs output, as a more concise term than "prediction given a particular set of input assumed forcings."
Mike - I have responded to your comment on a more appropriate thread.
Mike, perhaps you could point us to a statement in IPCC science report or published paper which you think does reflect the necessary humility?