Two items of interest.
1) A new poll looks at conservative and liberal views of science. The findings are not especially unexpected, but the details are interesting. The image above is from this infographic, and the details are given here.
Yes, the detail are quite interesting.
2) If you care, there is some information on what the 2016 GOP candidates stand on climate change.
This is put together by CBS and is here.
Human caused climate change is changing the size and location of major climate zones, according to a new study.
Climate is complex, and a classic, widely used effort to wrangle that complexity into a sensible form is the Köppen classification system (and variants). We need not speak of the details here, but within this scheme there are five climate groups that include all of the possibilities for the Earth’s land surface. They are:
This is sort of like a large scale version of the famous planting zone classification you use to determine when to plant your radishes or take in the last of the green tomatoes. The classifications are based on the idea that plants are indicators of the complex mix of factors that determine regional climate. Average temperatures matter, but high and low temperatures, when they occur (during the day and across the march of seasons) matter more, with key values such as frost mattering a lot. Average precipitation matters, but the distribution of precipitation across the year which might result in dry seasons matters a great deal. Ultimately, the local expression of global temperature, moisture, elevation, latitude, and the physical proximity to large bodies of water (most notably the oceans) and mountain ranges result in regional or local climate. The five classifications reflect zones that are mostly distributed across latitude (A on the Equator, E on the Poles) but that are also heavily influenced by altitude.
As humans add greenhouse gasses to the atmosphere the climate changes. We therefore expect these major classifications of regional climate to change as well, both in their relative sizes and in their locations with respect to latitude and altitude.
They do.
A new paper, “Significant anthropogenic-induced changes of climate classes since 1950” by Duo Chan and Qigang Wu, in Nature’s Scientific Reports journal, looks at Köppen classes under global warming, and also attempts to parse out underlying natural variation.
The paper is Open Access so you can go read it yourself. It is very clearly written and interesting. Here, I’ll just give you the key conclusions.
The research uses several data sources to conduct the analysis. All of the data are gridded across the globe, but some grids don’t have their own data because they are in remote areas with little or no instrumentation across the study period. Some data sets interpolate values into these grid squares, and those that do use different methods. One major data set leaves those grid squares blank and treats them as missing data. By using all of the data sets, the researchers were able to avoid coming up with results that were influenced by specific interpolation methods. Most importantly, though, they discovered that using the missing data approach did not change results because the missing data squares are mostly in the most A-like of Group A climate areas or the most E-like of Group E climate areas. Group A climate zones are growing, so being in the middle of those zones does not influence the analysis. So, not knowing what was going on in the middle of the Congo Raiforest does not change anything. Group E climate zones are shrinking, but those areas that are deep wihtin those zones (at the poles, on top of Mount Everest, etc.) don’t matter either.
Group D is “continental” and includes places like Chicago, Seoul, Salt Lake City, Ottawa, Flagstaff, and Faribanks. It is a very large zone that transits places that have real winters and those that have whimpier winters. Even though Group D is huge and significant, it also acts a bit like an ecotone or transition between Group C (Seasonally dry or arid, like Los Angeles, Cape Town, Beirut) and Group E (Tundra, ice caps, etc.). For this reason Group D is divided along the 55th parallel.
There are some complexities in how the data change over time which I will skip here (see the original paper). The point is, the zones do change significantly, with anthropogenic global warming being the primary cause. There is nothing particularly surprising in the results, but details can be important. Most importantly, the study also uses modeling to look at both past and future changes, and predicts an acceleration in change.
This graphic shows changes in climate types over the period 1950 to 2003 using one of the data sets (the data they chose for most of the analysis).
Tropical areas are expanding in space, moving north, and moving up in elevation. Not a lot, but a little. Why not a lot? The study does not say but I’ll guess. The tropical heat and moisture associated with this climate group are rapidly dispersed by air and water circulation systems and become part of the rest of the climate system quickly.
Arid and semi-arid areas (Group B) expand dramatically in area, and also move north and up hill. Why to they expand so much? There are probably two reasons. One is that more heat means more evaporation as well as more holding potential for water in the air. So ground moisture is sucked into the air at a greater rate, and stays there longer. Another (but closely related) reason may be the clumping of moisture we see in certain emerging weather patterns. Clumping means more arid conditions, even if that clumped water all falls eventually, on average, where it might have fallen anyway. A given amount of water falling uniformly in time and space across a region may provide a non-arid climate zone. The same amount of water falling non-uniformly in space, or especially, time, may result in a semi-arid zone.
Arid, semi-arid, subtropical Group B expands at the expense of Group C, while Group C is busy moving north but not up in elevation. The norther parts of Group D (ie, much of Canada) diminishes in area and moves north and uphill.
Group E, the cold bits, decline in area, move north, and retreat uphill.
The most important thing in this graphic is probably the expansion of Group B, where we can and do grow some food but under somewhat difficult conditions, and the loss of Group C area. The breadbasket, it is shrinking.
The paper concludes,
… major Köppen climate types since 1950 have occurred worldwide and are almost entirely attributed to the observed anthropogenic increase in greenhouse gas concentrations. Model runs project accelerating anthropogenic-induced major climate type changes in the next decades. As the Köppen climate classification links the Earth’s climates with the qualitative features of the vegetation, results here indicate that observed climate changes might already be causing significant impacts on vegetation in areas where the major climate class has changed, and model projections imply increasing future impacts.
This is a problem.
John Abraham is a scientist at St Thomas University in the Twin Cities. John is famous for doing battle with a famous science denialist (that’s what the meme above refers to), for his blog at the Guardian, for his research in several areas such as ocean heat, and for keeping track of month by month increases in global surface heat caused by anthropogenic global warming.
Sunday, I had the honor of interviewing John Abraham about current developments in climate change. It was Sunday morning so you were probably either sleeping or in church, but don’t worry, there’s a podcast!
You can listen to the podcast here:
Or here.
Here’s a partial list of other Atheist Talk interviews I’ve done, in case you were looking to spend several hours listening to me asking interesting people questions.
Emily Cassidy
Sheril Kirshenbaum
Anastasia Bodnar
Shawn Lawrence Otto on “Sins of Our Fathers”
Michael Mann
Paul Douglas
Me talking about the 5th IPCC report (Interviewed by Stephanie Zvan)
Me talking about science denialism (Interviewed by Stephanie Zvan)
John Hawks
Shawn Lawrence Otto on Science Policy
Shawn Lawrence Otto on his book “Fool Me Twice.”
Don Prothero
Me, John Abraham and Kevin Zelnio talking about climate change
Me and Desiree Schell talking about skepticism
Martin Rundkvist and Yusie Chou
Neil deGrasse Tyson
Me and PZ Myers talking about controversy
Me, Maggie Koerth-Baker, Steve Borsch, Will Steeger and Lynn Fellman
Ed Brayton
Lynn Fellman and me talking about fossil hominins
Me talking about missionaries (Interviewed by Mike Haubrich)
Me and Genie Scott talking about creationism (interviewed by Mike Haubrich)
Me talking about the evolution of the human diet
Me talking about academic freedom
I don’t care that the director or CEO of an advocacy organization concerned with poverty is an active academic. Indeed, my view of active academics is that many are largely incompetent in areas of life other than their specialized field. If that. So really, if you told me there is this great advocacy organization out there run by a well established active academic I’d figure you had that wrong, or I’d worry a little about the organization. On the other hand, everyone should care that university positions be given to active academics with credentials. So, when the University of Western Australia got paid off (apparently) to give Bjørn Lomborg a faculty position everyone looked at the UWA and said, “WUT?”
That was a situation up with which the members of that university community would not put, to coin a phrase, and the public outcry put a quick end to it. This is appropriate, because according to a new post by Stefan Rahmstorf at RealClimate, “… apart from one paper in 1996, Lomborg has never published anything in any field of science that was interesting or useful to other scientists, or even just worth the bother of contradicting in the scientific literature.”
I’ve talked about Lomborg here before. Here I noted,
There is currently a twitter argument happening, along with a bit of a blogging swarm, over a chimera of a remark made by John Stossle and Bjorn Lomborg. They made the claim that a million electric cars would have no benefit with resect to Carbon emissions. The crux of the argument is that there is a Carbon cost to manufacturing and running electric cars. When we manufacture anything, we emit Carbon, and when we make electricity to run the cars, we emit Carbon, etc. etc.
Lomborg is wrong, wrong, wrong, wrong, wrong. But here I want to focus on one aspect of why he is wrong that applies generally to this sort of topic….
We also talked about how Lomborg is wrong on electric cars here. Lomborg has been stunningly wrong on climate change, which is mainly what he is known for these days (being wrong on climate change, that is). And his wrongness on sea level rise and Bangladesh is not only stunning as well, but also, downright dangerous.
Stefan’s post looks in detail at two things (and in less detail at many other things). First, is the question of whether or not Lomborg is an actual practicing academic with a good publication record and all that. He is not. Stefan’s analysis is clear.
Second, is a more detailed look at Lomborg, sea level rise, Bangladesh, and all that. This is especially interesting because Stefan is one of the world’s leading experts on sea level rise. He has two peer reviewed papers on the “top ten most cited” on the Web of Science (which has well ove 40,000 sea level rise related papers), which are heavily cited. Stefan’s post is a must-read because of Stefan’s overview of sea level rise, aside from the stuff about Lomborg. Go read it.
So go read the post, learn about Bjørn Lomborg’s academic qualifications, how wrong he has been about sea level rise, and some other good stuff.
I suspect we are not going to see much more about Bjørn going forward.
Just a few pointers to some of today’s interesting climate stories.
First, this is the tenth anniversary of Hurricane Katrina. After ten years, the costs of that hurricane are still being paid. See this overview. Also, astonishingly, or perhaps totally expectedly, one third of Louisiana blame a Democratic Senator from the Midwest for the lousy response to Katrina by the Republican executive branch.
Meanwhile, wildfires out west are really bad. A friend of mine drove way into the rocky mountains over the last few days and noted that for a long time he couldn’t even see any mountains the smoke was so bad. I suppose we’re lucky here in Minnesota. We get a LOT of smoke from fires in the Canadian Rockies and Alaska, but now most of the smoke is passing to our south.
Anyway, there are now tens of thousands of people fighting the fires, including many brought in from other regions, and even other countries. At the moment there are no fire fighters left. If you live out there in the chaparral and a fire starts near your house, you might not be able to get help. Check it out.
A quick update on sea ice melt. This time I decided to display, on a graph produced using the interactive tool made available by the NSIDC, the first 20 years for which there are data (to get the background) and the current year so far, of Arctic Sea ice extent:
The meme at the top of the post is available in higher resolution HERE if you want.
A new paper examines what is behind the ~2% of climate change related peer reviewed research that run contrary to widely accepted scientific consensus on climate change to see why those papers are wrong.
There is a scientific consensus that increasing greenhouse gas concentration in the atmosphere causes surface warming, and that CO2 is a major greenhouse gas. This consensus is based on physics. We don’t need to observe the effects of human greenhouse gas pollution to know this. There is consensus that human burning of fossil fuel causes an increase in CO2 in the atmosphere. We don’t need to observe this to know it, because we know how combustion works. But it is relatively simple to measure, and it has been measured, and it is true. There is consensus that the planet’s surface has warmed. This is expected from the physics and the fact that we are increasing atmospheric CO2, but it is also relatively easy to measure, it is measured, and it is true. There are varying levels of understanding the effects of this process, and varying degrees to which the effects of surface warming are thought to cause specific effects. One could probably characterize the scientific consensus as a widespread understanding that surface warming has had and will have a range of effects, with many of those effects being changes in weather patterns or regional climatology (how warm/cool/dry/wet a region generally is across he seasons) arising from a combination of “natural variability” (what would happen without greenhouse gas pollution) and anthropogenic global warming.
It is interesting, then, to see the results of various studies of scientific consensus related to climate change. Two kinds of studies have been done. One asks scientists what they think, the other reviews the scientific literature to see what the peer reviewed papers that address climate change say. In both cases we see a number between 90 (or, really, 95) and 100 percent agreement on the stuff in the paragraph above. It is not surprising that the vast majority of scientists, and the vast majority of research papers, have very similar things to say about climate change. This is not new science, and while climate is very complex, the basics of anthropogenic global warming are well understood. The results of empirical research closely match expectations derived from the physics. It all hangs together pretty well.
What is surprising is to see that 3-6% or so disagreement. Who are those scientists, why do they disagree, what do those papers say?
I would assume that since consensus research takes time, and often looks at several years worth of papers, that some of that non-consensus reflects older thinking and older research. Also, there are climate contrarians, including some scientists, who oppose the consensus for reasons not based on the science. That sort of denial presumably comes from the simple fact that some corporations or wealthy individuals will see reduced profits as we make the inevitable shift away from fossil fuels. So some of that non-consensus may be bought and paid for self interested maneuvering.
Rasmus Benestad, Dana Nuccitelli, Stephan Lewandowsky, Katherine Hayhoe, Hans Olav Hygen, Rob van Dorland, and John Cook, in “Learning from mistakes in climate research” (Theoretical and Applied Climatology) looks at the non-consensus peer reviewed literature.
The paper is here, and author Dana Nuccitelli has a writeup on the paper here. From the abstract:
Among papers stating a position on anthropogenic global warming (AGW), 97 % endorse AGW. What is happening with the 2 % of papers that reject AGW? We examine a selection of papers rejecting AGW. An analytical tool has been developed to replicate and test the results and methods used in these studies; our replication reveals a number of methodological flaws, and a pattern of common mistakes emerges that is not visible when looking at single isolated cases. Thus, real-life scientific disputes in some cases can be resolved, and we can learn from mistakes. A common denominator seems to be missing contextual information or ignoring information that does not fit the conclusions, be it other relevant work or related geophysical data. In many cases, shortcomings are due to insufficient model evaluation, leading to results that are not universally valid but rather are an artifact of a particular experimental setup. Other typical weaknesses include false dichotomies, inappropriate statistical methods, or basing conclusions on misconceived or incomplete physics. We also argue that science is never settled and that both mainstream and contrarian papers must be subject to sustained scrutiny. The merit of replication is highlighted and we discuss how the quality of the scientific literature may benefit from
replication.
The researchers found that cherry picking was the most common explanation for the non-consensus papers contrary results. In other words, it is not the case that a small number of paper simply found the physics, or some other aspect of, global warming to be different than other researchers found, or that they were looking at a part of the system that acts differently. Rather, these papers were wrong, and for a specific reason.
We found that many contrarian research papers omitted important contextual information or ignored key data that did not fit the research conclusions. For example, in the discussion of a 2011 paper by Humlum et al. in our supplementary material, we note,
The core of the analysis carried out by [Humlum et al.] involved wavelet-based curve-fitting, with a vague idea that the moon and solar cycles somehow can affect the Earth’s climate. The most severe problem with the paper, however, was that it had discarded a large fraction of data for the Holocene which did not fit their claims.
The authors attempted a replication of that particular research, and found that the model they used only worked for part of the underlying data. The data that were ignored by Humlum et al contradicted their findings.
Another problem identified by Benestad et al is the lack of a consistent sensible alternative explanation for their alleged findings. “…there is no cohesive, consistent alternative theory to human-caused global warming. Some blame global warming on the sun, others on orbital cycles of other planets, others on ocean cycles, and so on. There is a 97% expert consensus on a cohesive theory that’s overwhelmingly supported by the scientific evidence, but the 2–3% of papers that reject that consensus are all over the map, even contradicting each other.”
Go read Dana Nuccitelli’s post in The Guardian for more discussion of this interesting new paper. Also, the lead author has a post on this paper at RealClimate.
What’s worse than months or years without rain? Rain, after months or years, at least under some circumstances.
For instance … it gets try, plants become vulnerable to fire. Fires happen denuding the dry landscape. Then it rains, and you get more severe floods together with landslides. You know the story because for years this has been the pattern in California.
But there is another roughly similar, or at least analogous, problem that is now being discussed. The levees that are mean to keep floodwaters contained in California were already in fairly bad shape. Prior to the drought, a significant number of levees were known to be at risk of failure should they actually get used. Many are thought unable to handle earthquakes as well.
But with the drought, several factors have probably made the levees weaker. This is an ongoing process and will continue as long as the drought continues.
From a letter to science, “Drought threatens California’s levees” by Farshid Vahedifard, Amir Aghakouchak, and Joe Robinson,
Prolonged droughts undermine the stability of levee systems by increasing water seepage through soil, soil cracking, soil strength reduction, soil organic carbon (SOC) decomposition, and land subsidence and erosion . The sand-clay mixtures, which form the body of the levees and consequently the entire structure, can lose a substantial amount of strength under dry conditions. Furthermore, levees in California are built on peaty soils, and the extreme drought leads to greater SOC decomposition in these soils. A large amount of the global carbon stock is found in peaty soils, and ~25% of this estimated stock is predicted to diminish under extremely dry conditions. Oxidation of SOC under a prolonged drought can also accelerate land subsidence. In fact, 75% of the land subsidence across California is accredited to oxidation of SOC. Land subsidence can increase the risk of water rising over the top of the levees.
This happened in Australia. Remember the big flooding a couple of years back? Some of that was made worse by levees failing, and those levees had been weakened by prolonged drought. So this is not theoretical.
We need to act urgently to reduce the amount of greenhouse gas pollution we humans create in order to slow down and eventually stop climate change. In the mean time we see case after case of something happening that seems unusual and that seems linked to global warming. We need not wait for the jury to return a verdict in every single case in order to act. We already know what many of the effects of climate change are, and we have a reasonably good idea of what effects will arise in the future. Even so, every now and then something happens that any reasonable person might guess is linked ultimately to greenhouse gas pollution, and we should pay attention to those cases.
Whales die, and sometimes their bodies wash up on shore. Over the last few months, the rate at which this happens seems to have increased about 300% in the Gulf of Alaska and maybe in other areas as well. One possible culprit is warming of northern waters (you may have heard of the Warm Blob), which in turn feeds the development of toxic microbes. Warming can also have other effects as well. This set of effects is thought to be a possible, maybe likely, cause of this alarming rate of whale deaths. Many of the whales are larger species.
From NOAA:
Since May 2015, 11 fin whales, 14 humpback whales, one gray whale, and four unidentified cetaceans have stranded around the islands of the western Gulf of Alaska and the southern shoreline of the Alaska Peninsula. To date, this brings the large whale strandings for this region to almost three times the historical average.
The declaration of an unusual mortality event will allow NOAA and federal, state, and tribal partners to develop a response plan and conduct a rigorous scientific investigation into the cause of death for the stranded whales.
“NOAA Fisheries scientists and partners are very concerned about the large number of whales stranding in the western Gulf of Alaska in recent months,” said Dr. Teri Rowles, NOAA Fisheries’ marine mammal health and stranding response coordinator. “While we do not yet know the cause of these strandings, our investigations will give us important information on the health of whales and the ecosystems where they live. Members of the public can greatly assist the investigation by immediately reporting any sightings of dead whales or distressed live animals they discover.”
Ryan Schuessler has written about this in the Washington Post.
Predation, starvation, or disease could be behind the deaths, but researchers say there have been few signs of physical trauma to the whales. The more likely culprit is unusual water conditions.
Over the past two years, a large mass of warm water that climatologists have dubbed “the blob” has persisted in the north Pacific, and El Niño 2015 is pushing more warm water into the region.
The unusually warm and calm seas are believed to be behind a series of toxin-producing algae blooms – record-breaking in size and duration – stretching from southern California to the Aleutian Islands. Clams sampled near the town of Sand Point, Alaska were found to have toxin levels more than 80 times what the FDA says is safe for human consumption, said Bruce Wright, a scientist who studies toxic algal blooms for the Aleutian and Pribilof Islands Association. The levels were ten times anything Wright had previously recorded.
How do you explain a person seemingly legitimately trained in science drifting off and becoming more and more of a science denier?
In the case of Judith Curry I was unwilling to think of her as a full on science denier for a long time because her transition into denierhood seemed to be going very slowly, methodologically. It was almost like she was trying to drift over into denier land and maybe bring a few back with her. Like some people seem to do sometimes. But no, she just kept providing more and more evidence that she does not accept climate science’s concensus that global warming is real, caused by human greenhouse gas polution, involves actual warming of the Earth’s surface, and is important.
And lately she has added to this slippery sliding jello-like set of magic goal posts yet another denier meme. She is certain, after a convoluted review of “evidence” that one of the classic examples of deniers lying, deniers making stuff up to confuse and mislead policy makers, reporters, and the public, is real.
It is not real but she says it is real. If you were looking for a last straw required to place Judith Curry plainly and simply and undoubtedly in the category of Climate Science denier, this straw has fallen heavily on the camelid’s aching overburdened back. If you were looking for that one last fact that determines the balance of argument in favor (vs. against) Judith Curry being either nefarious (as all those who intentionally deny this important area of science must be) or just plain (and inexcusably) stupid (the only alternative explanation for pushing climate science denialism) than that fact has arrived.
What the heck am I talking about? This.
I’ve talked about it here. Go read that and the 100+ comments on it. In that post I contextualize and quote the following words from this source:
One e-mail Phil Jones of CRU sent to my coauthors and me in early 1999 has received more attention than any other. In it, Jones both made reference to “Mike’s Nature trick” and used the phrase “to hide the decline” in describing a figure … comparing different proxy temperature reconstructions. Here was the smoking gun, climate change deniers clamored. Climate scientists had finally been caught cooking the books: They were using “a trick to hide the decline in global temperatures,” a nefarious plot to hide the fact the globe was in fact cooling, not warming! …
The full quotation from Jones’s e-mail was …, “I’ve just completed Mike’s Nature trick of adding in the real temps to each series for the last 20 years (i.e. from 1981 onwards) and from 1961 for Keith’s to hide the decline.” Only by omitting the twenty-three words in between “trick” and “hide the decline” were change deniers able to fabricate the claim of a supposed “trick to hide the decline.” No such phrase was used in the e-mail nor in any of the stolen e-mails for that matter. Indeed, “Mike’s Nature trick” and “hide the decline” had nothing to do with each other. In reality, neither “trick” nor “hide the decline” was referring to recent warming, but rather the far more mundane issue of how to compare proxy and instrumental temperature records. Jones was using the word trick [to refer to] to an entirely legitimate plotting device for comparing two datasets on a single graph…
The reconstruction by Briffa, (see K. R. Briffa, F. H. Schweingruber, P. D. Jones, T. J. Osborn, S. G. Shiyatov, and E. A. Vaganov, “Reduced Sensitivity of Recent Tree-Growth to Temperature at High Northern Latitudes,” Nature, 391 (1998): 678–682) in particular …
…was susceptible to the so-called divergence problem, a problem that primarily afflicts tree ring density data from higher latitudes. These data show an enigmatic decline in their response to warming temperatures after roughly 1960, … [Jones] was simply referring to something Briffa and coauthors had themselves cautioned in their original 1998 publication: that their tree ring density data should not be used to infer temperatures after 1960 because they were compromised by the divergence problem. Jones thus chose not to display the Briffa et al. series after 1960 in his plot, “hiding” data known to be faulty and misleading—again, entirely appropriate. … Individuals such as S. Fred Singer have … tried to tar my coauthors and me with “hide the decline” by conflating the divergence problem that plagued the Briffa et al. tree ring density reconstruction with entirely unrelated aspects of the hockey stick.
In her most recent post, Judith Curry says:
In hindsight, the way the Climategate emails was rolled out, after very careful scrutiny by the targeted bloggers, was handled pretty responsibly. Lets face it – “Mike’s Nature trick” to “hide the decline” means . . . “Mike’s Nature trick” to “hide the decline.”
That statement by Curry is demonstrably wrong. That is a fact borne of logical and scientific examination of the information, and information is not lacking. Curry is wrong.
Beyond that, I think, as implied above, she is either doing something here that is morally wrong (lying to slow down action on climate change) or stupid (she is not smart enough to understand what she is looking at). Here, I want to be clear. The argument that Curry is wrong is logical. Ends there. She’s wrong. The idea that she is either immoral or stupid is both my opinion and NOT an argument about her wrongness. I am not making an ad hominem argument. If you think that is an ad hominem argument then you don’t know what an ad hominum argument is (and isn’t).
And yes, I understand that this is a rather insulting thing to say, that one is either immoral or a dumbass. But it is my children’s future that is at risk here. Expect insults.
See also this:
This is F@k1n’ brilliant.
Cherry-pickin’ a bit of temperature data
And tryin’ to claim that climate change is in hiatus
It’s not, the trends are still going straight up
But they ain’t tryin’ to change their minds once they’re made up
In 1992 my mama’s thesis
Was about CO2 and Svante Arrhenius
So if you try to tell me that climate change isn’t serious
You’re dissin’ my mama, yup I’m kinda cliquish
Also by Baba Brinkman:
Climate models employ piles of data and sophisticated computational techniques to predict what will happen in the future. Sometimes they predict what happened in the past as well. That is important to test the models (because we might know what happened in the past), or to fill in the blanks (we don’t always know exactly what happened in the past) or to understand complex climate systems better.
If you glance at the science denier rhetoric (mainly on blogs, you won’t find much in the peer reviewed literature because it isn’t good science) you’ll see repeated claims that climate models that try to predict global warming don’t match the actual observations of global warming. Most of the time, this claim is simply wrong. Perhaps an improper measurement of warming (like temperatures up higher in the atmosphere where we actually expect cooling rather than warming) is being used, which constitutes a lie. In other cases observed warming is within the model projections, but tracks off to one side (usually the low side) of the average expectation, but remains within the margin of error. This is either a misunderstanding of how the science works, or a willful misrepresentation. (Again, a lie.) But there are actually two legitimate areas where certain climate models seem to overstate observed warming. A recent post by John Abraham at the Guardian explores these areas.
First there is the question of where the warming is observed. We measure warming in several parts of the Earth’s surface. (See “What does “Global Warming” Mean?) One is surface temperatures at about head height, over land, via a gazillion weather stations many of which have been in operation since the 19th century. The other is at the surface of the sea, using a combination of older measurements taken from ships and more recent satellite observations. In addition, we have measurements of the deeper ocean itself, usually averaged out over some depth such as the top 700 meters, or the top 2,000 meters. This combines older and new ship our buoy measurements but tend to not go back in far in time as the land and sea surface measurements.
John Abraham has spent a lot of effort looking at ocean temperatures at depth. He and I recently published this item, and he’s done a lot of additional work on it. The total amount of heat added to the Earth’s surface from anthropogenic warming (caused mainly by greenhouse gasses such as carbon dioxide) is divided between the ocean and the surface, with the ocean taking up much of that heat. I liken the system to a dog with a wagging tail. The ocean is the dog, the surface temperatures, making up a small part of the overall system and being much more variable, is the tail.
In “The oceans are warming faster than climate models predicted,” Abraham notes:
We separated the world’s oceans into the Atlantic, Pacific, and Indian. All three of these oceans are warming with the Atlantic warming the most. We also calculated the ocean heating by using 40 state-of-the-art climate models. Over the period from 1970, the climate models have under-predicted the warming by 15%.
And here you can see a number of climate models superimposed over the observed heating in the top 700 meters of the ocean (the red line):
In a more recent post, Abraham asks the question, “ how have the models done at predicting the changes in air temperatures?”
As noted, global surface temperature is estimated in part from a bunch of thermometers around the globe, but these thermometers were not placed there for this purpose. They are weather stations set up to help track the weather, not to address questions of climate change. They are not evenly distributed, and there are huge gaps in the surface coverage, most notably in the Arctic and interior Africa, both regions where recent warming has probably been greater than elsewhere. In order for these temperature data to be used, they have to be carefully employed in a computational system that helps fill in the gaps. There are other complexities beyond our scope here. Suffice it to say that when a bunch of different groups of scientists (i.e., the British meteorology office, NASA, NOAA, the Japan Meteorological agency, and various university based groups) take on the task of estimating surface temperatures, they all do it a bit differently and thus turn up with slightly different curves.
This is true as well with sea surface temperatures. There is more than one way to measure sea surface temperature, or more exactly, to take existing data and turn it into a useful estimate of sea surface temperatures.
In addition, the data are cleaned up over time as mistakes are found, the basic computational approach used may be updated to make it more precise, and the overall approach to computation may be changed to make it more accurate.
Over time, two clear patterns have emerged. First, if you take all of the different measurements of surface temperature over time spanning from the 19th century to the present, lay them all out in front of you and step back about two meters and squint slightly, you can’t see the difference among them. They all look the same, they all tell the same story. They all have a handful of notable ups and downs along the generally upward march of surface temperatures with industrial pollution. You have to look at the graphs all on the same axes, together, to see the differences, and the differences are minor. This tells us that all the different approaches to processing a largely overlapping set of data end up with the same basic result. So many smart minds working with the best available science all produce the same result. How boring. But also, how reassuring that the science is being done right.
The second pattern emerges when we look at these graphs as they are produced over time. Various groups have said, “hey wait a minute, we’re missing this” or “we’re missing that” factor. Urban heat island effects may change the data! What about the Arctic! Interior Africa! Our satellites were recalibrated what does that do? Etc.
Over time, and honest, well informed, diligent effort by many groups to improve the measurement of the Earth’s surface temperature has resulted in a series of slightly different graphs, and in each and every case of which I’m aware, the resulting, more recent and better done graphs show more warming, and various periods of relative flatness have become steeper (going upwards).
So, what John Abraham has done is to take some of the more recently processed, better quality data and compared it to the usual models to see how well the models have done. They did well.
He based his discussion on a comparison of the most recent climate model simulations with actual global surface temperature measurements as numerically summarized by NASA’s Gavin Schmidt, shown here:
John has superimposed 2015 so far (the star).
This shows the most current computer model results and five current temperature data sets. The dark line is the average of the models, and the various colored lines are the temperature measurements.
The dashed line is slightly above the colored markers in recent years, but the results are quite close. Furthermore, this year’s temperature to date is running hotter than 2014. To date, 2015 is almost exactly at the predicted mean value from the models. Importantly, the measured temperatures are well within the spread of the model projections.
This is the year of the heatwave. We’ve had heat waves off and on for the last few years, but it seems that there are more now than ever before. While some have tried to argue that global warming can’t really cause warming (sometimes expressed as heat waves), it does.
Climate Scientist Stefan Rahmstorf has a blog post, in German, about a current heat wave in Europe. He notes (rough translation):
Europe is currently experiencing the second major heat wave this summer. On 5 July, according to the German Weather Service , a never before measured in Germany temperature reached 40.3 ° C in Kitzingen. But a month later, on August 7, this century record has been revised…One might speculate that a single heat wave could be simply due to chance. If you look at the temperature data, however, in their entirety it is immediately clear that extreme heat has become more common over several decades. (Apologies for errors in translation.)
And he shows this graph:
Percentage of global land area where the temperatures over a month were two or three standard deviations above the average from 1950 to 1980. Two standard deviations (orange) could be described as “very hot”, three standard deviations (dark red) as “extremely hot”. Source: Coumou and Robinson 2013
Meanwhile, in Egypt, there is another heat wave. According to ABC News,
Egypt’s state news agency says 21 more people have died due to a scorching heat wave, raising this week’s death toll to more than 60.
The official MENA news agency said Wednesday that the latest deaths are from the previous day, mostly elderly people. It says 581 people are in hospital for heat exhaustion.
The Mideast has been hit by a heat wave since late July. Egyptian summers are usually hot, but temperatures this week soared to 46 degrees Celsius (114 degrees Fahrenheit) in the south.
At least 40 people had died on Sunday and Monday, including detainees and patients in a psychiatric hospital, according to officials. It wasn’t immediately clear whether Tuesday’s death toll includes a German national living in the southern city of Luxor who died from heatstroke.
Additional items of interest:
It is not the sun: Corrected sunspot history suggests climate change not due to natural solar trends
It is not just the editorial page: Study Finds WSJ’s Reporting On Climate Change Also Skewed
It is not a hiatus or pause: The alleged hiatus in global warming didn’t happen, new research shows
It is not just the heat, it is also sea level rise: Catastrophic Sea Level Rise: More and sooner
We are expecting a major Carbon Dioxide sink to eventually stop grabbing CO2 and, possibly, to start releasing it: Global Warming: Earth, Wind, Fire, and Ice
Bill Maher and Penn State meteorology professor Michael Mann discuss the “settled science” of climate change and the lack of public engagement on the issue. Dr. Mann is the co-author of “Dire Predictions: Understanding Climate Change.”
There are two new scientific research papers looking at variation over the last century or so in global warming. One paper looks at the march of annual estimates of global surface temperature (air over the land plus sea surface, not ocean), and applies a well established statistical technique to ask the question: Was there a pause in global warming some time over the last couple of decades, as claimed by some?
The answer is, no, there wasn’t.
The paper is open access, is very clearly written so it speaks for itself, and is available here. One of the authors has a blog post here, in German.
The other paper looks at the so called global warming “pause” and interrogates the available data to see if the pause is supported. It concludes that it isn’t. The paper is written up in a blog post by one of the authors, here.
I’ll give you an overview of the findings below, but first, a word from the world of How Science Works.
No, I’m not calling you stupid. Probably. I’m just paraphrasing Bill Clinton to underscore the importance of variation in science. The new paper examines variation in the global surface temperature record, so this is an opportunity to make this point.
Much of the time, science is about measuring, understanding, explaining, and predicting variation. This is a point non-scientists would do well to grasp. One of the reasons non-scientists, especially those engaged in policy making (from voter to member of Congress to regulatory agent to talking head) need to understand this better is because variation is one of the most useful tools in the denier tool kit. If your objective is to deny or obfuscate science, variation is there to help you.
Global warming, the increase in the Earth’s surface and ocean temperatures caused by the human caused increase in greenhouse gas, is a system with plenty of variation. The sources of variation are myriad, and the result is that the measurement of air temperature, sea surface temperature, and deeper ocean temperature appears as a set of squiggly lines.
In many systems, variation exists at more than one scale.
So, at the centennial scale, we see global surface temperatures not varying much century by century for a thousand years, then the 20th century average is higher than the previous centuries, and the 21st century average, estimated by 15% of the years of a century, is higher still. That is the effect of industrialization, where we shift from using energy from human and animal work, together with a bit of wind and water power, to using energy stored in carbon bonds in fossil fuels. This combined with population increase and increasing demands to support a consumer-driven comfort-based lifestyle have caused us to release fossil carbon into the atmosphere at an alarming rate.
At the decadal scale, we see a few recent decades that stick up above the others, and a few that are lower than others or at least don’t go up as much as others. Over the last 100 years, the decadal average temperatures have gone up on average, but with variation. The primary explanation for this variation is two fold. First, there is an increase in the absolute amount of greenhouse gas, and the rate at which we are adding greenhouse gasses to the atmosphere, so over time, greenhouse gasses have become the main determinant of temperature change (causing an increase). Earlier on, when greenhouse gas concentration was lower, other factors had a bigger impact. The second (and related) explanation is variation in aerosols, aka dust, in the atmosphere from various industrial processes, volcanoes, and such. Decadal or multidecadal variation over the last century has been mainly caused by aerosols, but with this effect diminishing in its importance as it gives way to the increasingly important role of greenhouse gas.
At a finer scale, of a year or a few years, we see variation caused mainly by the interaction of the surface (the air and the sea surface) and the upper ocean (this is sometimes examined for the top, say, 700 meters, other times, for the top 2000 meters, etc.) When we look at just ocean temperatures or just surface temperatures, we see a lot of squiggling up and down on an ever increasing upward trend. When we look at both together, we note that the squiggles cancel out to some extent. The ocean warmed considerably during recent years when the surface warmed more slowly. This is because heat is being exchanged back and forth between the surface and the deeper sea in a away that itself varies.
That is the simple version. In reality things are more complex. Even though ocean and surface temperatures vary from year to year, with the major variations caused by El Nino and La Nina events in the ENSO cycle, there are longer term variations in how this exchange of heat trends. This time scale is in the order of several decades going in one direction, several decades going in the other direction. (see this post) Then, this sort of variation may have much larger scales of change, at century or even millennial time scales, as ocean currents that facilitate this exchange, undergo major changes, which in turn alters the interaction of the surface and the sea. And, of course, both sea and ocean temperature can affect the major ocean currents, so there is a complex causal interaction going in both directions between those two sources of variation.
Have you ever been annoyed by someone who makes a claim about the health benefits, or negative effects, of some kind of food or other ingestible substance? You know, one of those totally non-scientific “findings” from the usual internet sources. Here is a little trick you can do if you want to challenge such a claim.
In order to truly evaluate a health related claim, and have that evaluation be credible, you have to be able to do one of the following things, depending on the claim. Being able to do this is not enough to validate your expertise, but it is a starting point. It is a gate-keeper thought experiment. If you can’t do this, then you can’t really make the claim you are making with any credibility.
Describe, in detail, the digestive process, i.e., the process of food sitting on a plate being ingested and eventually being used by a human body, at the molecular level (for many claims about the beneficial or negative effects of certain foods, or the benefits of various dietary supplements).
All that stuff I said above about variation is the very simple version of what happens in the climate with respect to global surface temperature imbalance and global warming. If you read what I wrote and the whole time were thinking things like “yeah, but, he’s totally glossing this” or “no, it isn’t that simple, what really happens is…” then you might be a climate scientist.
If, on the other hand, this extensive tl;dr yammering on variation seemed senseless or a waste of time, or you didn’t find it interesting or don’t get the point, the you may not be prepared to evaluate claims like the one about the so-called “pause” or “hiatus” in global warming. More importantly, there is a good chance that a person making the claim that there has been such a pause is unprepared to do so, just as the person claiming that wearing a $50 fragment of a discarded circuit board around their neck will protect them from EMF can not really make that claim because they are a total dumb-ass when it comes to energy fields and cell biology.
Or, the person making the claim (most common in the area of global warming) is just trying to fool somebody. They are like the person who sells the fragment of the discarded circuit board.
The first paper is “Change Points of Global Temperature” by Niamh Cahill, Stefan Rahmstorf and Andrew Parnell, published in IOP Science Environmental Research Letters.
A long series of data may demonstrate the outcome of a set of variables where all the variables act in similar ways over time, and any trend plus or minus variation will be clear. But if the variables change in their level of effect over time, it may be that parts of the long term data series need to be treated separately. This requirement has led to the development of a number of statistical techniques to break a series of data up into different segments, with each segment having a different statistical model applied to it.
The statistical approaches to this problem initially arose in an effort to better understand variation in the process of making key electronic components in the telecommunications industry. An early method was the “Control Chart” developed by Walter A. Shewhart at Bell Labs. The method allowed engineers to isolate moments in time when a source of variation contributing to mechanical failure changed, perhaps because some new factor came into play.
More recently, the statistical method of “Change Point Analysis” was developed to provide a better statistical framework for identifying and assessing the statistical significance of changes in sources of variation. The process involves determining whether or not a change in the sources of variation has occurred, and also, estimating if multiple change points have occurred. The process is pretty complicated, numerically, but is automated by a number of available statistical tools.
The new paper attempts to assess the reality of a “pause” or “hiatus” in global surface temperature increase using change point analysis. The change point analysis used four of the major commonly used data sets reflecting surface temperature changes. In each case, they found three change points to be sufficient to explain the medium to long term variation in the data. Most importantly, the most recent detectable change point was in the 1970s, after which there is no detectable change in the trend of increasing global temperature.
The results of the analysis are summarized in this graphic:
Figure 1. Overlaid on the raw data are the mean curves predicted by the three CP model. The grey time intervals display the total range of the 95% confidence limits for each CP. The average rates of rise per decade for the three latter periods are 0.13 ± 0.04 °C, ?0.03 ± 0.04 °C and 0.17 ± 0.03 °C for HadCRUT, 0.14 ± 0.03 °C, ?0.01 ± 0.04 °C and 0.15 ± 0.02 °C for NOAA, 0.15 ± 0.05 °C, ?0.03 ± 0.04 °C and 0.18 ± 0.03 °C for Cowtan and Way and 0.14 ± 0.04 °C, ?0.01 ± 0.04 °C and 0.16 ± 0.02 °C for GISTEMP.
Those who claim that there was a pause in global warming point to certain dates as the origin of that pause. The authors tested that idea by forcing the change point analysis to assume that this was correct. The alleged starting points for a global warming hiatus failed the statistical test. They are not real. The authors determined that the change point analysis “…provides strong evidence that there has been no detectable trend change in any of the global temperature records either in 1998 or 2001, or indeed any time since 1980. Note that performing the CP analysis on the global temperature records excluding the 2013 and 2014 observations does not alter this conclusion.”
In addition, even though the alleged starting points for a global warming hiatus were found to be bogus, they were found to be more bogus in one of the four data sets, that developed by Cowtan and Way, which in turn is generally thought to be the data set that eliminates most of the biases and other problems found in this sort of information. In other words, using the best representation available of global surface temperature increase, the so called hiatus is not only statistically insignificant, it is even less significant!
But that wasn’t enough. The authors took it even a step further.
Finally to conclusively answer the question of whether there has been a ‘pause’ or ‘hiatus’ we need to ask: If there really was zero-trend since 1998, would the short length of the series since this time be sufficient to detect a CP? To answer this, we took the GISTEMP global record and assumed a hypothetical climate in which temperatures have zero trend since 1998. The estimated trend line value for 1998 is 0.43 °C (obtained by running the CP analysis on the original data up to and including 1998). Using this, we simulated 100 de-trended realizations for the period 1998–2014 that were centered around 0.43 °C. We augmented the GISTEMP data with each hypothetical climate realization and ran the four CP model on the augmented data sets. This allowed us to observe how often a fourth CP could be detected if the underlying trend for this period was in fact zero. Results showed that 92% of the time the four CP model converged to indicate CPs in approximately 1912, 1940, 1970 and a fourth CP after 1998. Thus, we can be confident that if a significant ‘pause’ or ‘hiatus’ in global temperature did exist, our models would have picked up the trend change with a high probability of 0.92.
Well, no. For one thing, as mentioned above, the overall pattern has been an increase in the importance of greenhouse gasses as the variable controlling surface temperatures. Whatever factors caused the flattish or downward trends many decades ago may still be in place but are relatively less important from now on, even if we quickly curtail CO2 output. Also, one of those factors, aerosols, is reduced permanently (we hope). Industrial pollution, in the past, caused a lot of aerosols to be released into the atmosphere. This has been reduced by changing how we burn things, so that source attenuation of surface temperatures is reduced. Also, as noted above, there are multi-decadal changes in the relationship between the surface (air and sea surface) and the ocean, and at least one major study suggests that over coming decades this will shift into a new phase with more surface heating.
I asked author Stefan Rahmstorf to comment on the possibility of a future “hiatus.” He told me that one is possible, but “I don’t expect that a grand solar minimum alone could do it (see Feulner and Rahmstorf ERL 2010). Maybe an exceptionally large volcanic eruption could do it but it would have to be far bigger than Pinatubo, which did not cause one.” He also notes that some IPCC climate models have suggested a future slowdown, and the possibility of cooling in not non-zero. The key point, he notes, is “it just has not happened thus far, as the data analysis shows.”
Author Andrew Parnell noted, “I think anybody who claims that these current data demonstrate a hiatus is mistaken.”
The second paper is “Lack of evidence for a slowdown in global temperature” by Grant Foster and John Abraham. Foster and Abraham start out by noting that there is a widely held belief, even among the climate science community, “…that the warming rate of global surface temperature has
exhibited a slowdown over the last decade to decade and a half.” They examine this idea “…and find no evidence to support claims of a slowdown in the trend.”
The authors note that most of the discussion of global warming involves reference to “ the relatively small thermal reservoir of the lower atmosphere” (what I refer to above as the “surface”), but since this is only a small part of the planets heat storage, this can be misleading. When the ocean is taken into account, we see no slowdown in warming. The paper by Foster and Abraham refers to the above discussed paper on change point analysis, so I’ll skip that part. The remaining thrust of the paper is to apply some basic statistical tests to the temperature curves to see if there is a statistically valid slowdown.
They derived residuals, using the GISS data set, for the last several decades, indidating the divergence of each year from an expected value given an upward trend. This looks like this:
They then took sets of adjoining residuals, and tested the hypothesis “This set of numbers is different from the other numbers.” If there was a statistically significant decrease, or increase, in temperature change for several years it would show up in this analysis. The statistical test of this hypothesis failed. As beautiful as a pause in global warming may seem, the idea has been killed by the ugly fact of ever increasing temperatures. To coin a phrase.
Then…
As a last attempt to find evidence of a trend in the residuals, we allowed for models in which not only the slope (the warming rate) changes, but the actual value itself. These are discontinuous trends, which really do not make sense physically … but because our goal is to investigate as many possible changes as is practical, we applied these models too. This is yet another version of change-point analysis, in which we test all practical values of the time at which the slope and value of the time series change. Hence it too must be adjusted for multiple trials.
Again, no statistical significance. If you look at the global temperature curve, and see a pause, what you are really seeing is noise.
Foster and Abraham conclude:
Our results show that the widespread acceptance of the idea of a recent slowdown in the increase of global average surface temperature is not supported by analytical evidence. We suggest two possible contributors to this. First, the natural curiosity of honest scientists strongly motivates them to investigate issues which appear to be meaningful even before such evidence arrives (which is a very good thing). Second, those who deny that manmade global warming is a danger have actively engaged in a public campaign to proclaim not just a slowdown in surface temperature increase, but a complete halt to global warming. Their efforts have been pervasive, so that in spite of lack of evidence to back up such claims, they have effectively sown the seeds of doubt in the public, the community of journalists, and even elected officials.
Men and women are different, on average, in a number of ways. It all probably starts with who has the physiology to have babies and who doesn’t, and the differences spread out from there, affecting both the body and the mind. Decades of research show us that many of the body differences (but not all) are determined by developmental processes while many of the mind differences (but maybe not all) are determined by culture, but culture still has men and women as being different, so those differences tend to be persistent and predictable, on average.
One of the differences which seems to meld body and mind, in the West anyway, is the tendency for women to be cold while men are comfortable across a certain range of temperature. It turns out that many decades ago a study was done that developed standards for installing and running air conditioning systems that, typically, set ambient in-room temperature levels to accommodate men. Damn the patriarchy, one more time. Since men are more comfortable on average at lower temperatures, this means a) air conditioners are set relatively low (which means high, in terms of energy use) and, b0 on average, women are doomed to wear sweaters or carry around blanket like objects while at work, at movies, at the mall, or anywhere where sexist air conditioning is operating.
This is important not only for comfort of half the population, but also for climate change. A large amount (about 30%) of the CO2 emmissions in the West are the result of energy use in the buildings we live and work in, and a good part of that is heating and cooling. A new study, just out in Nature Climate Change, addresses this issue. The study is by Boris Kingma and Wouter van Marken Lichtenbelt, and is called “Energy consumption in buildings and female thermal demand.” The authors point out that not only is a large amount of our energy used to heat and cool buildings, but that about 80% of the variation in that energy use is account for by variation in the behavior of the humans that live and work in those buildings.
The standard for setting ambient building temperatures is set by ASHRAE (American Society of Heating, Refrigerating, and Air-Conditioning Engineers).
ASHRAE founded in 1894, is a global society advancing human well-being through sustainable technology for the built environment. The Society and its members focus on building systems, energy efficiency, indoor air quality, refrigeration and sustainability within the industry. Through research, standards writing, publishing and continuing education, ASHRAE shapes tomorrow’s built environment today. ASHRAE was formed as the American Society of Heating, Refrigerating and Air-Conditioning Engineers by the merger in 1959 of American Society of Heating and Air-Conditioning Engineers (ASHAE) founded in 1894 and The American Society of Refrigerating Engineers (ASRE) founded in 1904.
And, according to Wikipedia,
ANSI/ASHRAE Standard 55 (Thermal Environmental Conditions for Human Occupancy) is a standard that provides minimum requirements for acceptable thermal indoor environments. It establishes the ranges of indoor environmental conditions that are acceptable to achieve thermal comfort for occupants. It was first published in 1966, and since 2004 has been updated periodically by an ASHRAE technical committee composed of industry experts. The most recent version of the standard was published in 2013.
According to the new study, the standard overestimates the “female metabolic rate by up to 35%” which “may cause buildings to be intrinsically non-energy-efficient in providing comfort to females.” The study suggests using actual metabolic rates to set the standard, and provides information on how to approach this. “Ultimately, an accurate representation of thermal demand of all occupants leads to actual energy consumption predictions and real energy savings of buildings that are designed and operated by the buildings service community.”
So, let’s turn the air conditioners up. Meaning down. Depending on what you mean when you say that.
I did an interview with JD Goodwin at at Blue Streak Science. It is here. Great science podcast, check out their other items.
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