Date: Friday January 17, 2014
Subject: “The Global Warming Hoax” and “War on Carbon” Clips
From: Bob Tisdale
To: Jon Stewart
I am an independent climate researcher and regular contributor at the award-winning science blog WattsUpWithThat. I am also the author of three ebooks on global warming, climate change and the poor performance of climate models. I am writing to you about your January 6, 2014 episode (full episode here) of The Daily Show. It began with “The Global Warming Hoax” and “War on Carbon” clips, which ran consecutively when aired.
First, let me say that I applaud you and your staff for making The Daily Show a massively entertaining political satire. I enjoy the show thoroughly.
During your January 6th episode, however, you expressed beliefs in climate models and in the climate science community…the human-induced global warming wing thereof. Unfortunately, the climate models used to hindcast past climate and to project future climate are so flawed that they are not fit for their intended purposes. And the climate science community under the direction of the IPCC (Intergovernmental Panel on Climate Change) has specialized in only one aspect of global warming, which is why the models perform so poorly. I’ll provide evidence for those statements in the following, including data and peer-reviewed scientific studies.
MUCH HAS CHANGED IN 7 YEARS
For most people, their understanding of climate science comes from the time around 2006-2007 when there was a lot of interest in global warming and climate change. Al Gore’s An Inconvenient Truth was getting press and the IPCC and Al Gore were awarded the Nobel Peace Prize. Things have changed drastically since then. Specialists in many fields of climate science are now writing papers about model failings, and they’re not small problems. They’re fatal flaws. Skeptics have become much better at presenting and illustrating those model failures, too, and describing why they’re important. And there has been a flood of peer-reviewed papers over the past two years, in which climate scientists are trying to explain the hiatus in global warming—with limited success and limited agreement; that is, there’s no consensus on the cause of the pause. Examples are discussed in the very recent Nature article Climate Change: The Case of the Missing Heat by Jeff Tollefson. Those scientists wouldn’t be writing those papers if the climate models had anticipated the current cessation of global surface temperature warming. Unfortunately, with the IPCC’s focus on manmade greenhouse gases, climate scientists still do not know how to model nature’s handiwork. More on this later.
THE DOCTORS ARGUMENT AGAIN
You presented a clip of Dan Weiss of the Center for American Progress who said:
If 97 doctors told you that that lump on your lung was something to worry about, and 3 scientists — er, doctors — told you not to worry about it, are you going to listen to the 97, or the 3? Sounds like you might listen to the 3, which would be sad.
(Quotes from the DailyKos transcript here.)
That argument has been used a lot recently.
You were right to point out the error in the logic of the response to it, which was to the effect of climate scientists are paid to… But the reality of the situation is something altogether different.
The climate science community has specialized in only one aspect of global warming and climate change, and as a result, they have overlooked other major contributors.
I’ve addressed this problem previously in two open letters—one to George Clooney and your associate Lewis Black here, and one to the Executive Producers of the upcoming ShowTime series Years of Living Dangerously here. As I wrote to Black and Clooney:
The climate science community, under the direction of the IPCC (Intergovernmental Panel on Climate Change), has only been tasked with determining whether manmade factors, primarily carbon dioxide, could be responsible for the recent bout of global warming, and what the future might bring if the real world responds to projected increases in manmade greenhouse gases in ways that are similar to climate models. They were not asked to determine if naturally caused, sunlight-fueled processes could have caused the global warming over the past 30 years, or to determine the contribution of those natural factors in the future—thus all of the scrambling by climate scientists who are now trying to explain the hiatus in global warming. Refer to the IPCC’s History webpage (my boldface):
Today the IPCC’s role is as defined in Principles Governing IPCC Work, “…to assess on a comprehensive, objective, open and transparent basis the scientific, technical and socio-economic information relevant to understanding the scientific basis of risk of human-induced climate change, its potential impacts and options for adaptation and mitigation…”
It is not the IPCC’s role to understand the scientific basis for naturally caused climate change, which the Earth has experienced all along. As a result, even after decades of modeling efforts, climate models still cannot simulate naturally occurring ocean-atmosphere processes that contribute to global warming or stop it. So a “doctors” example falls flat because it relies on experts whose understandings of climate are extremely limited in scope.
The response to “97 doctors” argument should have been: “Would you see a podiatrist or proctologist for that lump on your lung?”
CLIMATE SCIENTISTS ABOUT THE IPCC’s FOCUS ON MANMADE GREENHOUSE GASES
The climate science community now understands the problems caused by limiting their research to the increased emissions of manmade greenhouse gases, primarily carbon dioxide.
The Royal Netherlands Meteorological Institute (KNMI) is concerned about the IPCC’s focus. See their document titled Submission by The Netherlands on the future of the IPCC. Under the heading of “The IPCC needs to adjust its principles”, KNMI begins:
We believe that limiting the scope of the IPCC to human-induced climate change is undesirable, especially because natural climate change is a crucial part of the total understanding of the climate system, including human-induced climate change.
This failure to properly account for natural factors also led a former lead author of IPCC reports (Kevin Trenberth of NCAR) to remark in David Appell’s 2013 article “W(h)ither global warming? Has global warming slowed down?”
“One of the things emerging from several lines is that the IPCC has not paid enough attention to natural variability, on several time scales,” he [Dr. Trenberth] says, especially El Niños and La Niñas, the Pacific Ocean phenomena that are not yet captured by climate models, and the longer term Pacific Decadal Oscillation (PDO) and Atlantic Multidecadal Oscillation (AMO) which have cycle lengths of about 60 years.
To put that into more basic terms: There are naturally occurring multidecadal variations in surface temperatures of the Northern Hemisphere oceans (see the post here), and they were major contributors to the warming experienced since the mid-1970s. Climate models do not simulate those modes of natural variability. To compound the problems, the modelers had tuned their models during the naturally occurring upswings, failing to account for the peaking and downswings in cycles that would eventually occur (and are now occurring). I provided an overview of the potential impact of this in the post Will their Failure to Properly Simulate Multidecadal Variations In Surface Temperatures Be the Downfall of the IPCC?
That article by David Appell is also noteworthy, because it provides another example of the lack of consensus on the cause of the cessation of global surface warming. If climate scientists can’t agree on an explanation for why Earth’s surface stopped warming, it casts a lot of doubt on their consensus on the cause of the warming we had experienced from the mid-1970s to about 2000.
CLIMATE SCIENTISTS DISCUSS THE FLAWS IN CLIMATE MODELS
You mentioned climate models and peer-reviewed science in your clip, Jon. It appears you may not beaware of this, but there are a number of peer-reviewed papers that are very critical of climate model performance. I presented some of them recently in the post Questions Policymakers Should Be Asking Climate Scientists Who Receive Government Funding. Those papers served as references for the following questions, which all began with a common phrase:
After decades of climate modeling efforts…
- …why does the current generation of climate models simulate global surface temperatures more poorly than the prior generation?
- …why can’t climate models properly simulate sea ice losses in the Arctic Ocean or sea ice gains in the Southern Ocean surrounding Antarctica?
- …why can’t climate models properly simulate atmospheric responses to explosive volcanic eruptions?
- …why do climate models continue to poorly simulate precipitation and drought?
- …why can’t climate models simulate multidecadal variations in sea surface temperatures?
- …why can’t climate models simulate the basic processes that drive El Niño and La Niña events?
In that post (linked again here), I quoted portions of the peer-reviewed papers that supported those questions and I translated the science-speak into language that is more readily understood by readers who aren’t intimate with climate science.
BLOG POSTS THAT ILLUSTRATE THE PROBLEMS WITH THE MODELS
If you’re a visual person, Jon, over the past year I’ve presented a series of blog posts that illustrated and discussed many climate model failings, and for those posts, I’ve presented the average of all of the outputs of the current generation of climate models stored in an archive used by the IPCC for their 5th Assessment Report. Climate-related data and climate model outputs are available online to the public, in easy-to-use formats, through the web tool called Climate Explorer from KNMI (Royal Netherlands Meteorological Institute). I have also published posts that provide Step-By-Step Instructions for Creating a Climate-Related Model-Data Comparison Graph and a Very Basic Introduction To The KNMI Climate Explorer. It’s a relatively easy process. In fact, many middle school students could replicate my graphs. Some of the posts that illustrate the many flaws in climate models are linked below by subject. Basically, climate models do not properly simulate:
- Global Surface Temperatures (Land+Ocean) Since 1880
- Global Sea Surface Temperatures Since 1880
- Satellite-Era Sea Surface Temperatures
- Daily Maximum and Minimum Temperatures and the Diurnal Temperature Range
- Hemispheric Sea Ice Area
- Global Precipitation
Those posts and other examples are collected in my ebook Climate Models Fail, which is available in pdf and Amazon Kindle editions. Refer to the introduction here.
THE SHIP OF FOOLS
Back to your January 6th episode. You played a clip of Fox News’s Eric Bolling stating:
I gotta tell you, I think these scientists are laughing from their lavish laboratories, and their vacations up at the Arctic, in their nice boats that are well-equipped.
While first showing a image of an ice field and then showing a photo of the Akademic Shokalskiy caught in sea ice (screen cap below), you replied:
This Arctic? This lavish boat?
A minor problem: That “lavish boat” was not in the Arctic. The AkademicShokalskiy, one of the “Adventure Class” tour boats from Southern Explorations, was caught in the sea ice of the Southern Ocean surrounding Antarctica. And it was just after the start of the Southern Hemisphere summer a few weeks ago. Tours on that ship are not inexpensive. Rates range from “$5,720 to $21,590 per person”. The Mark Steyn: Global warming’s glorious ship of fools article at TheSpectator is a very humorous overview of the fiasco involving the Spirit of Mawson researchers, their families, tourists and reporters getting stuck in the sea ice…and the international rescue efforts. On the more technical side, Steve McIntyre of ClimateAudit has documented the sea ice conditions leading to the debacle, including where the data contradicts the claims made by the lead researcher. See Steve’s post Ship of Fools. Recall also that climate models simulate that sea ice should be decreasing in the Southern Ocean, but it has increased in area since 1979.
DATA SHOWS NO CHANGES IN EXTREME WEATHER OR RELATED INSURANCE LOSSES
Early in the show, Jon, you mentioned weather extremes (my boldface):
There you have it. War on Christmas is over, the War on Carbon begins. Global warming, just one more liberal conspiracy. Because even though there is a great deal of scientific data establishing climate trends, even though many of the models of global warming predict more extremes of weather — not just warming — apparently decades of peer-reviewed scientific study can be, like a ficus plant, destroyed in one cold weekend.
As presented earlier, climate models are flawed, likely to the point that they are not fit for purpose.
Data from the real world present an entirely different picture of extreme weather events. In my Open Letter to the Executive Producers of the Years of Living Dangerously, (also linked earlier) I included graphs of data from the testimony of Roger Pielke, Jr. at the U.S. House Subcommittee on Environment held on December 11, 2013: A Factual Look at the Relationship Between Climate and Weather. So please click on the link above to Dr. Pielke Jr’s testimony for graphs of the data. The following are the take-home points from his testimony, points that are supported by data (my boldface):
- Globally, weather-related losses have not increased since 1990 as a proportion of GDP (they have actually decreased by about 25%).
- Insured catastrophe losses have not increased as a proportion of GDP since 1960.
- Hurricanes have not increased in the US in frequency, intensity or normalized damage since at least 1900.
- There are no significant trends (up or down) in global tropical cyclone landfalls since 1970 (when data allows for a comprehensive perspective), or in the overall number of tropical cyclones.
- Floods have not increased in the US in frequency or intensity since at least 1950.
- Flood losses as a percentage of US GDP have dropped by about 75% since 1940.
- Tornadoes have not increased in frequency, intensity or normalized damage since 1950, and there is some evidence to suggest that they have actually declined.
- Drought has “for the most part, become shorter, less frequent, and cover a smaller portion of the U. S. over the last century.”
I also addressed sea levels and Hurricane Sandy in that Years of Living Dangerously article.
A COUPLE OF QUICK MODEL-DATA COMPARISONS
Let’s return to climate models: how poorly they simulate global surface temperatures. The following graphs are very easy to understand. They are model-data comparisons of global surface temperatures for the past 3+ decades. The start time is dictated by the use of satellite-enhanced sea surface temperature data. The graph on the right compares global land air surface temperature data with climate model simulations of it. The models performed reasonably well on a global basis when simulating land surface air temperatures. Before we move to the graph on the left, you have to understand that the vast majority of the rise of land surface air temperatures in the real world is in response to the warming of the surfaces of the oceans. Land surface air temperatures mimic and exaggerate the variations in the surface temperatures of the oceans. Now, the graph on the left compares global sea surface temperature data with climate model simulations. The models doubled the rate of warming of the surface temperatures of the global oceans for the past 3+ decades. Doubled. That, in and of itself, is horrendous. Now consider that the modelers had to double the rate of warming of the surfaces of the oceans in order to get the land surface air temperatures near to where they needed to be.
(Click to enlarge.)
A BIG FLAW IN THE MODELS
I’m sure you’ve heard of the global warming hiatus, the pause, etc. I presented the following in a post that I linked earlier, but it should be repeated. Recently, there have been two very enlightening peer-reviewed studies on the topic of the recent cessation of the warming of global surface temperatures. The first is Von Storch, et al. (2013) “Can Climate Models Explain the Recent Stagnation in Global Warming?” They stated:
However, for the 15-year trend interval corresponding to the latest observation period 1998-2012, only 2% of the 62 CMIP5 and less than 1% of the 189 CMIP3 trend computations are as low as or lower than the observed trend. Applying the standard 5% statistical critical value, we conclude that the model projections are inconsistent with the recent observed global warming over the period 1998- 2012.
According to Von Storch, et al. (2013), both recent generations of climate models (CMIP3 used by the IPCC for their 2007 4th Assessment Report, and CMIP5 used by the IPCC for their recent 5th Assessment Report) cannot explain the recent slowdown in global surface warming. The models show continued global surface warming, while observations do not.
The second paper is Fyfe et al. (2013) “Overestimated global warming over the past 20 years.” Fyfe et al. (2013) write, requiring no translation from science-speak:
The evidence, therefore, indicates that the current generation of climate models (when run as a group, with the CMIP5 prescribed forcings) do not reproduce the observed global warming over the past 20 years, or the slowdown in global warming over the past fifteen years.
Looking at this realistically, if the climate models cannot explain the current slowdown or halt in global surface warming, then they cannot be used to explain the warming that had occurred from the mid-1970s to the late-1990s. In turn, they have little value as tools for making predictions of future climate. It’s unfortunate, but that’s the sad reality of the state of climate science today.
In closing, Jon, when people imagine climate models, maybe it’s best to think of early generations of CGI (computer generated imagery). A decade or two ago, we’d go to the movies and be amazed at the images on the big screen. And we probably thought some of the video games at that time were also impressive. Looking back at them now, they look hokey.
Climate models used by the IPCC for hindcasting and projections of future climate are at the hokey-looking phase of development. And the more you investigate them, the hokier they look.
Jon, if you have any questions, please feel free to leave a comment on any thread at my blog Climate Observations.
PS: If you should know of a comedian who’s tired of the tripe we’ve been seeing from the catastrophic manmade global warming wing of the climate science community, please let them know I’m looking for a co-author for my next book. Working title: The Oceans Ate My Global Warming. I’m looking for someone to help make it fun to read.
Great piece Bob. I hope Stewart takes this seriously, I’ve never seen his show.
The world is in the midst of a political war on this, and I must be blunt. You are entirely too respectful of peer-review and the “authorities” engaged in it–we are in this mess because it has failed to provide self-correction to the science, for 40 years now or more–and too wordy and specialized in your detailed enumeration of scientific details, that again are too respectful of the generally bad work being done by climate scientists, deluded as they are by the unphysical theories they have been brainwashed to accept without question. You even fail to call out the models for what they are: crude, and obviously wrong curve-fitting, using physical variables whose individual atmospheric effects are still largely unknown and hence wrongly applied, and whose supposed commingled and global effects are without any observational support whatsoever (because they are all addressed via a bogus “radiation transfer” theory that replaces real heat transport with “radiation”, and ignores the real processes of heat transport–to wit, conduction and convection, in addition to radiation–within the atmosphere). You haven’t put anything in your presentation that speaks to Jon Stewart the Widely Popular Entertainer, and would put his audience to sleep in less than a minute. And your referring to David Appell, who is a total fraud as a competent scientist (or a competent “science journalist”), marks you yourself as still deluded on who should be taken seriously in the climate debates. You’re a good, competent technical researcher, but you need to grasp the thorny political situation driving this mess, reject it out of hand, and communicate how badly real science is being served by consensus climate science now, after two generations of miseducation of the scientists themselves. As my Venus/Earth tropospheric temperatures comparison showed–over 3 years ago, but still 20 years after climate scientists should have been aware of it–the utterly stable Standard Atmosphere model of the troposphere truly represents our atmosphere, not the upside-down physics of the consensus view, of an atmosphere balanced on the razor’s edge of pretended “radiation forcings”.
I wish you well, but the doors of real communication and understanding–particularly in the public discourse, where outright fraud reigns–are all closed now, and must be forced open by competent, honest scientists.
In October of last year I pointed out to you that you’re (unintentionally) misrepresenting what the KNMI meant with the passage you quoted. I used an explanation from Rob van Dorland who is part of the group that wrote that document, yet you dismissed this explanation. When you did that I mentioned that you could verify this explanation from the KNMI, I’m even willing to give you any details you need to contact them.
Considering you’re still making the same claim based on the quote from the KNMI document I can safely conclude you haven’t checked with the KNMI if your interpretation is correct? And thus also haven’t checked that I’m correct representing what they said to me?
Collin Maessen: We’ve been through this before. You claim an individual (one person) at KNMI disagrees with the official KNMI statement.
I have not misrepresented what KNMI wrote. I quoted KNMI’s statement. And I provided a link to their website so that my readers could see that I was NOT quoting KNMI out of context.
Good-bye, Collin. End of conversation. I’m not going to argue this with you AGAIN.
Appreciated your response to Jon Stewart. A great summary, too, given the range of areas you covered and the links provided.
Regarding your new book, you may wish to contact John Spooner who did the cartoons for, and provided some commentary in, the book “Taxing Air” with Bob Carter and others – see http://www.taxingair.com/. You may be able to contact John via the publisher, Kelpie Press, at email@example.com.
By the way, “Taxing AIr” is a good read, providing questions and answers to the hypothesis of dangerous global reading. Free postage internationally via Fishpond at http://www.fishpond.com/Books/Taxing-Air-Bob-Carter-John-Spooner-With/9780646902180.
Owen, thanks for the tip.
your assertion the models were flawed are based on only two articles, which seemingly support your argument. What about those that don’t, e.g. the one by Kosaka and Xie, Nature (2013), http://dx.doi.org/10.1038/nature12534? The article by von Storch et al. (2013) isn’t even a peer reviewed publication as far as I can see.
The quoted argument and the whole essay by von Storch et al. are flawed themselves. They compare only a single realization from the probability distribution of all possible trends in Nature for the given climate state with a distribution of modeled trends.
1. Why did they choose the period 1998-2012 for the observations, exactly the one that starts with a strong El Nino? They haven’t done any test whether their result is statistically robust. Just moving the data window by only one year to 1999 to 2013, inclusively, increases the trend in all surface temperature data sets.
2. von Storch et al. come to the conclusion of an inconsistency between model simulations and observations because the observed trend lies outside of the 95% range of the modeled trend distribution. However, there is a probability distribution of trends in Nature, and one of the trends in models. von Storch et al. did not randomly pick the period 1998-2012 from the distribution in Nature. They picked it with a priori knowledge that this trend lies in the left tail of the distribution. Assuming perfect models and perfect observations (which is just a thought experiment), 5% of the observed trends must lie outside the 95% probability range of the simulated distribution, i.e., every 1 out of 5 observed data points on average. Thus just simply finding such a trend would not be sufficient to conclude any inconsistency, even if the trend was randomly picked, which it even wasn’t.
3. The distribution of model trends is taken from model data projected in the future up to 2060 or so. The model simulations assume idealized scenarios after 2005, for instance a constant solar cycle. von Storch et al. didn’t account for a possible divergence between the variability of the climate drivers in the simulations and the variability of the climate drivers in Nature (e.g. the longer and deeper solar cycle minimum in the last decade). If there is a divergence between the change in time of the drivers in Nature and as prescribed for the model simulations, even the trend distribution simulated with perfect models would diverge from the observed trend distribution.
As for the Fyfe et al. (2013) paper. Are you aware that the study isn’t solely based on observations, but partially by applying a simplified model for the variability of the heat exchange between ocean and atmosphere due to El Nino/La Nina? According to the study, using this model, the contribution of the El Nino/La Nina distribution in time to the temperature trend is supposed to be about Zero, even for the period since 1998. I find this very implausible. Already the position of a very strong El Nino and the dominance of La Ninas at the end of the period will create a virtual downward temperature trend in the time series, subtracting from any positive trend forced by other climate drivers. Also, the claim that the contribution of El Nino/La Nina is about Zero is in contradiction to other studies, like the one by Foster and Rahmstorf , ERL (2011), http://dx.doi.org/10.1088/1748-9326/6/4/044022 or the Kosaka and Xie-study.
In summary, you have made your argument based on a biased and very limited selection of papers, of which only one was even a peer reviewed publication. In addition, the not peer reviewed essay is seriously flawed according to my assessment. And I see some serious question marks regarding the other one, the conclusions of which are not plausible and in contradiction to other papers. You are ignoring all the papers that do not share your conclusion or imply a different conclusion. One could suspect that you chose exactly those two papers and ignored the other ones because of a bias on your side regarding the conclusions desired by you. You have not presented any convincing argument for your assertions about the climate models in your letter to Jon Stewart.
I just see I wrote, “5% of the observed trends must lie outside the 95% probability range of the simulated distribution, i.e., every 1 out of 5 observed data points on average.”
I misspoke. It is supposed to say, “i.e., every 1 out of 20 observed data points on average.”
Thanks for stopping by to defend climate models, Jan. But I’ve also been documenting their shortcomings in dozens of blog posts over the past year.
Jan, PS: Come back when climate models (as evidenced by a CMIP multi-model ensemble mean) can simulate the multidecadal variability of North Pacific and North Atlantic sea surface temperature anomalies. If you’re not aware, the sea surface temperatures of the North Pacific also present multidecadal variations, similar in magnitude to the AMO, but slightly out of synch with it. And no, I’m not talking about JISAO’s PDO. To do that, you’ll need to be able to simulate the multidecadal variations in the strength, frequency and duration of ENSO events. Take your time, fewer and fewer people believe in climate models every year.
Before then, your models are nothing more than computer-aided speculation.
See ya in a few decades.
Bob, one can criticize something or exchange arguments or polemics in blog posts and blog comments, but at the end, they don’t matter. It’s all just opinion. They do not provide any scientific evidence.
Anyone can point out flaws in the models. All models have deficiencies. They always will have, since every model is based on idealizations. Perfect models do not exist. The only perfect model would be an exact copy of Nature. The real question is whether the features of the models that are deficient are essential for the scientific questions you want to answer. Answering this question requires a little bit more than just pointing out the presence of a flaw.
As for the multi-decadal variability. Are you talking about simulating the exact chronological succession of the multi-decadal variability or the statistical properties of this variability? On what scientific papers is your statement based that the models can’t simulate this? And do you have any scientific evidence that the ability to simulate this is required, and to what degree of accuracy it is, to make projections of the globally averaged multi-decadal climate change, within some range of uncertainty? The evidence points to that the overall changes of the global variables over the last century, particularly the global temperature, has mostly been controlled by the changes in the global energy balance due to the variability of the external climate drivers.
“Take your time, fewer and fewer people believe in climate models every year.”
Argumentum ad populum. A logically fallacious argument.
And I am still waiting for that AGW-“skeptics” present their first dynamic climate model with supposedly correct physics, since they like to claim that the physics of our models were flawed so much, with which they then can reproduce the observed variability of climate as well as we can, but for which an increase in the greenhouse gases from human activities wasn’t needed to do that. See you in: Never.
Jan, it may be argumentum ad populum, but the interest in climate science is close to a 10-year low. It’s not my fault. Look within your community.
With respect to your waiting for skeptics to “present their first dynamic climate model with supposedly correct physics”, I have a couple of questions for you. Would you share 50% of the GISS budget with skeptics? Do you think the other modeling agencies would share 50% their budgets? Can you think of a taxpayer-based funding agency that would provide the monies for skeptics to create dynamic climate models with the intent of determining the natural contribution to global warming and climate change? If your answer to any of these questions are no, then you understand the flaw in your argument.
Jan asks, “As for the multi-decadal variability. Are you talking about simulating the exact chronological succession of the multi-decadal variability or the statistical properties of this variability? On what scientific papers is your statement based that the models can’t simulate this?”
I plotted them and presented them years ago. The questions you should be asking is why there are so few studies highlighting the deficiencies in the models and why, if they are known to be imperfect, this hasn’t been better communicated to the public and policymakers.
Jan, the claimed climate science consensus is argumentum ad populum, so why’d you waste your time raising the fallacy?
Jan, one more that I DO have to go to work. Regarding multidecadal variability, maybe you should confer with Kevin Trenberth. According to David Appell’s article “W(h)ither global warming? Has global warming slowed down?”:
“‘One of the things emerging from several lines is that the IPCC has not paid enough attention to natural variability, on several time scales,’ he [Dr. Trenberth] says, especially El Niños and La Niñas, the Pacific Ocean phenomena that are not yet captured by climate models, and the longer term Pacific Decadal Oscillation (PDO) and Atlantic Multidecadal Oscillation (AMO) which have cycle lengths of about 60 years.
You can try to spin that any way you want, but it’s not gonna work
Excellent write-up. Much like your letter to Clooney, this letter exposes fundamental and undeniable deficiencies which are unspoken by MSM and thusly never passed onto the chattle and masses whom pay for every penny of the scare–from the models to the taxes.
Unfortunately, and I made this comment on your Clooney letter, your writing is as foriegn to the uneducated Hollywood bozos as hieroglyphics.
They do not have High School diplomas or GED’s. The only things they have done well are sex, drugs and alcohol.
Jan, on the other hand….”It’s all just opinion. They do not provide any scientific evidence.”……how appropriately stated in a conversation about failing models.
It’s somewhat funny when I hear the excuse that the recent hiatus is due to more La Niña events and when the El Niño events come back so will the warming. I think this is basically what Jan is claiming.
Of course, that misses the entire point. It was this ENSO variability that led to the warming in the first place. More El Niño events, increased global temperature. We are now the other side of the ENSO variability coin that is leading to the cooling. Yup, no argument there and it is not going to stop until the other half of the ~60 cycle completes.
Jan and the rest of the AGW true believers want to ignore the reality that most of the warming 1975-2005 was due to the ENSO. If they had properly modeled this variable then they would have realized that climate sensitivity is much less than they fudged. Most of the energy of the GHE goes into evapotranspiration. When Jan and friends finally figure that out and model ocean cycles properly, they might have a chance of getting the right answer. Instead, it appears all we will get is denial.
@Jan P Perlwitz
>Bob, one can criticize something or exchange arguments or polemics in blog posts and blog comments, but at the end, they don’t matter. It’s all just opinion. They do not provide any scientific evidence.
Model outputs are not scientific evidence, do you agree? I presume everyone here knows enough about the scientific method to know the difference between observations and the output of models.
The CAGW narrative depends wholly (not partly) on model outputs which project a significant rise in global temperature rise rooted in the idea that CO2 forcing and feedbacks overwhelm natural variation.
Your excusing of the failure of models to perform well even for 15 or 16 years – citing the assumption that solar activity would remain constant until 2060 – is an inadequate response to the rather obvious gap between model forecasts and measured temperatures for nigh unto a generation. Would two generations of pause attract a different conclusion? I hope so.
Bob has done a marvelous job in dissecting the way ENSO events start, continue and terminate. I understand from reading about GCM’s that they assume ENSO is a cycle, i.e. self-cancelling in net effect over long periods. Bob has uncovered the fact this is simply not the case. It is not expectable therefore that GCM’s will do a good job of modeling them. Evidence they do not do a good job is in the difference between projections and measurements.
Further, the claim for models potentially being accurate (or meaningful) rooted in stable solar activity fails also for the period 1997-2006 when there was no evidence that solar activity was anything other than at the high level of the previous 50 years yet the temperature pause had started and was clear enough in the record for CRU staff to comment on it.
Why are so many scientists apologizing for the failed climate models? Apologetics belongs in the Vatican. Models don’t work well at predicting temperatures! The most obvious reasons are the overestimated CO2 forcing and positive feedbacks, and they (greatly) underestimate natural variation. That being the case, there remains little evidence connecting the 1976-1997 global temperature rise to AG CO2.
CO2 is a greenhouse gas, rising because of human activity. It has little effect on global temperatures, according to all the evidence: to wit, 14 data sets of global temperature measurements. It is not dangerous and based on known and suspected carbonaceous fuel deposits, cannot be doubled as a concentration in the atmosphere by human activity. The rest is noise. And there is a lot of it.
Bob, you wrote on January 20, 2014 at 6:50 am:
I suspect this is just correlated with the El Nino/La Nina distribution over time, and accordingly, with the short-term temperature trend, which is largely influenced by this distribution. Right now the trend is below average. In 2006/07 it was above average. However, since global warming continues, the interest will likely rise again.
As for the first dynamic, physics based model, developed by AGW-“skeptics”. I think you have a big misunderstanding how the development of Earth system models is done. You seem to think that somehow processes, which are influenced by humans are deliberately put in by the climate models, and other processes, which represent natural variability are left out during the development process. I suspect you are just projecting how you think AGW-“skeptics” would do it. That they somehow would try to artificially impose features of natural variability how they think those features should look like. But how would it even possible to do that. Model development is done with the aim to put the essential relationships between physical variables, based on the knowledge from theoretical and empirical physics, into the model. How would you separate human influenced physics from the physics underlying unforced internal variability in the model? There is only one set of physical equations. There are no two sets of equations, one for the human influence, and another one for natural variability. Features in the model that represent natural variability, like cycles in the ocean circulation, should emerge automatically in the model, when the model is based on the correct physical representation of the processes in the Earth system. The assertion that we weren’t interested in natural variability is nonsense too. A possible influence of human activity on climate can’t be understood without understanding natural variability, because the strength of a possible human induced signal in climate variables can only be established when there is also knowledge about natural variability. Also, there have been countless studies on natural variability in climate science, for which climate models have been a tool since they have been developed, including studies of natural variablity for past times, when the influence by human activity was small or absent. It’s the same climate models that are being used for these studies of natural variability as the ones being used for studying the influence of human acitivity.
Your claim that AGW-“skeptics” wouldn’t have the money available to develop their own climate models is a false excuse. How much money would you need for that? Nowadays, you can run climate models on laptops or PCs. The “skeptics” wouldn’t even necessarily have to start from scratch. A number of existing climate models is available in the public domain (e.g. GISS’s ModelE). You can download these models, evaluate their physics, and if you think some of the physics in there was wrong and the cause for false answers given by the models, you can throw it out and replace it with the supposedly correct physics. How many AGW-“skeptics” see themselves as incarnations of Galileo? If there are so many brilliant minds among you it should be a piece of cake to do that. And if you really need more money, why don’t you ask the Koch-brothers? If the AGW-“skeptics” can make a convincing case that they will be able to show with their own climate models that all the mainstream climate science was wrong, which use the models that are out there as tools, the brothers likely would be more than willing to support this purpose.
Jan P Perlwitz, regarding your lengthy January 20, 2014 at 3:56 pm comment: you quoted my comment about the decline in public interest in climate science, and you start rambling about ENSO. Have you been spending a lot of time at the local biergarten during your visit to Germany? I suggest you go to Google trends and type in global warming. You’ll find interest in global warming peaked in 2006/07 in response to Gore’s movie and the award of the Nobel Peace Prize to Gore and the IPCC. The long-term interest dropped since then, except in December 2009 when it spiked in response to Climategate and the achieved-nothing Copenhagen climate conference. But somehow you think it’s tied to an increase in La Niña events. That’s a curiously odd theory, Jan.
The remainder of your reply is as chock full of illogic. Climate science funding has only been directed at the assumed impacts of human factors, which is why the models still perform like crap, including the GISS Model-E.
Physics? I have no need to examine the physics of the models when the outputs indicate they have no relation to the real world.
Have a nice day.
Jan, if climate models did all the physics they would be called reality. Yeah, us dumb skeptics actually realize that is impossible. So, the amount of actual physics is simplified to get something meaningful in your lifetime. Once you start making assumptions you introduce potential errors. Sorry.
What happens when a person starts taking shortcuts is they put their efforts in things they believe are important. This is where researcher bias enters the process. There really is a reason medical science does double blind studies. The bias influences your results. The only way to move forward is to recognize the problem and admit models are not fit to make future projections at this time. Maybe someday but you need to accept that might not be for decades.
Dr? Perlwitz. (Sorry but I don’t know your correct title and don’t know you well enough to just use Jan).
You make the statement that; “Features in the model that represent natural variability, like cycles in the ocean circulation, should emerge automatically in the model, when the model is based on the correct physical representation of the processes in the Earth system.”
I understand that to mean that if the system is modeled properly then things like the PDO would emerge automatically in the models.
If that is the case then if the natural cycles do not automatically appear wouldn’t that indicate that the model is not a “correct physical representation of the processes in the Earth system”?
Bob Tisdale says:
January 20, 2014 at 6:36 am
That is a great argument!!!
Richard M says:
January 20, 2014 at 11:29 am
It’s somewhat funny when I hear the excuse that the recent hiatus is due to more La Niña events and when the El Niño events come back so will the warming. I think this is basically what Jan is claiming.
“somewhat funny” and yet it has reached well past the point of being funny.
Temperature trends for the recent 15 years:
GISTEMP: +0.093 K/decade
NOAA: +0.066 K/decade
HADCRUT4: +0.074 K/decade
BEST: +0.174 K/decade
NOAA: +0.138 K/decade
What “recent hiatus”? Earth’s surface is still warming. That is what I am claiming.
I am also saying: “Unfortunately, no one of the ones who claim the presence of a “hiatus” has given any scientifically based definition what even constitutes a “hiatus”. Or I must have missed it.”
I am also saying that there has been a longer-term warming trend over the about recent 40 years of about 0.17 K/decade, which is highly statistically significant with more than eight standard deviations.
I am also saying that the longer-term global surface warming trend is overlaid with short term natural variability, which at times can make short term trend estimates, like the ones over a time period of 15 years, lie under the average trend of the distribution of the trends for the same length, and at other times lie above the average trend. For instance, for the time period 1992 to 2006, the 15 year trend was larger than 0.26 K/decade.
As for El Nino/La Nina, which is a phenomenon of unforced internal variability in the climate system. The transition from El Nino to La Nina conditions subtracts from the average trend for the same length, the transition from La Nina to El Nino conditions adds to the average trend, accordingly. El Nino or La Nina by themselves can’t cause any warming or cooling trend in the climate system, respectively. It’s the transition between the two that adds or subtracts from the average trend. If the system went into a perpetual El Nino or a perpetual La Nina, those perpetual states would not cause any global warming or global cooling trend, respectively.
I am also saying that the decrease in the solar energy input into the system over the downward phase of cycle 23 from the solar maximum in 2000 to the solar minimum in 2008 by about 0.25 W/m^2 fully compensated the increased forcing from increasing greenhouse gases over the same time period. Thus, the net energy input change, after adding the two, was about Zero between the years 2000 and 2008. Considering that reflecting aerosols may have increased also somewhat, the net energy input change into the system over this time period may actually have been slightly negative, although the net change also depends on how the other greenhouse gases, besides CO2, have changed during this time period. One would have to examine in detail what the net energy input change into the Earth system has been after 1998. I don’t have the exact numbers at hand right now.
I am also saying that a longer term decrease in the solar input over multiple cycles, if it happens, will subtract from the global warming trend caused by the continuing increase in the greenhouse gases. By how much will depend on by how much the total solar irradiance will decrease over the solar cycle average over the next decades.
I hope that clarifies a little bit what I am saying.
Jan loves all his adjusted data while denying the best data available … satellite data. Why is that, Jan? Without UHI your belief system falls apart.
The trend since August of 1996 is almost a perfect zero. What you are demonstrating is exactly what I have talked about over and over again … researcher bias. Thanks for making it so obvious.
Why are satellite data “the best data available”? Please explain. Also, the satellite retrieved data are not measurements of Earth’s surface temperature. I was talking about surface warming.
Obviously, you are asserting that the surface data analyses are distorted by the urban heat island effect. However, you only asserting this, without providing any scientific evidence for your assertion.
1. The surface temperature analyses take the UHI into consideration, and the data are accordingly adjusted to remove this effect. For instance, the GISTEMP analysis uses night light data from satellite measurements to adjust for the UHI. And the comparison with the previously applied method to adjust for it, using the urban population number, shows very good agreement (Hansen et al. RG, 2010, http://dx.doi.org/:10.1029/2010RG000345)
2. Deriving the surface temperature change over land from other physical variables in the atmosphere, without using any temperature measurements from meteorological station, therefore excluding the possibility that artifacts of those measurements distort the analysis, provides results which are in close agreement with the surface temperature analyses using temperature measurements from meteorological stations. (http://climateconomysociety.blogspot.de/2013/09/an-independent-confirmation-of-global.html; Compo et al. GRL, 2013, http://dx.doi.org/10.1002/grl.50425). Therefore, there is a very low likelihood that the surface temperature analyses are significantly biased by any of the hypothesized artifacts of the temperature measurements from meteorological stations.
Now that takes some serious cherry-picking effort to find the exact month for which, chosen this month as start point, the trend is Zero. The 2-sigma value of the trend is 0.194 deg. C/decade for this time period. The trend in the RSS data set since 1979 amounts to 0.125 deg. C/decade.
And why did you choose the RSS data set as the one that supposedly shows the “true” picture, according to you? Why didn’t you choose the UHA data set, which is also a satellite based date set, provided by Roy Spencer and John Christy?
The temperature trend in the UHA data set since August 1996 is 0.101 deg. C/decade. The trend since the year 1999 amounts to 0.146 deg. C/decade, even larger than the trends in the surface data sets, which I had provided before, and even slightly above the longer-term trend of 0.138 deg. C/decade in the UHA data since the year 1979, but the two are actually not statistically distinguishable at all. If my choice of data was directed by “researcher bias” I would have chosen this one. If I had chosen the UHA data set to make my point, then it would have been OK, since satellite data were “the best data available”?
You must be projecting. You have chosen the one data set, which deviates low from all the other data set, and deviates most from the other satellite data set, the one by Spencer and Christy. You have chosen the one data set that seems to be an outlier, but which gives the impression to support your assertions best. An apparent case of cherry-picking likely based on confirmation bias.
Pingback: Perlwitz before Swine? | Bob Tisdale – Climate Observations
I chose the RSS data because it shows a zero trend which is also what all the other data shows, that is, they are not statistically different from zero. So, why not just show zero. If I have to explain why satellite data is better than you obviously are so biased that anything I say will be ignored. GISS/NCDC/Hadcru continue to change historic data every month. Infilling, extrapolation, homogenization, questionable adjustments, changing station base, siting issues, UHI, AHI, etc. That alone disqualifies surface measures and it doesn’t even address the spacial problems. Sorry, you guys have been manipulating the data for so long you don’t even realize how silly it looks to use that data over satellites.
Now that your data is diverging more and more from satellite data all you want to do is ignore the technology that actually measures evenly across the oceans, mountains, deserts where few surface stations exist while covering the 3 dimensional troposphere. That surface data is still used at all is just another example of bias.
BTW, the reason UAH and RSS are different has more to do with UAH measuring low about a decade or so ago compared to RSS. The difference is likely due to UAH including more polar areas. Once again, the trend is still statistically not different from zero. You do understand what this means I hope.
As for your reference, here’s the method … “uses a time-varying weighting between pressure observations and an ensemble of 56 nine-hour forecasts made with a NOAA atmosphere/land general circulation model (AGCM) to estimate the three-dimensional state of the atmosphere every 6h (see supporting information).” I can only shake my head at using climate models that have been tuned to the surface record and then claim that verifies the surface record. Pure circular reasoning that any real scientist would simply discard without a second thought. The fact you mentioned it tells me quite a bit about your biases.
Thank you for admitting that your choice was based on confirmation bias. Some real honesty.
The scientific community doesn’t seem to have got your memo. Those silly ones, still using these data. Or they just don’t listen to you, because they are actually listening to scientific evidence. Your claims, however, about the bias in the surface data analysis, supposedly distorting the results from the analysis significantly, are still not based on any scientific evidence. It’s all just assertion and opinion.
Apparently, you want to claim that satellite data don’t have significant biases or inhomogeneities to worry about, making them so much better than surface data. Well, you are not well informed about this then. Satellite data do have significant biases, e.g., orbital drift, instrument degradation, there are jumps when the instruments are changed, and they have to be calibrated. Even more: The satellite instruments don’t even measure temperatures. They measure radiation coming from different layers of the atmosphere at ones. Then a model is being applied how those radiation measurements are to be translated into temperatures of a specific layer. And in the course of the short history of the satellite data, adjustments to previously provided temperature data had to be made again and again, because of all the biases in the satellite data that were revealed over time.
If there weren’t any strong biases in the satellite based temperature data, RSS and UAH data would closely agree, instead of being as different as they are, e.g. for the trends over the recent 15-year period. Both data sets are based on the same satellite instruments. However, the two groups use their own specific algorithms for bias correction and calculation of the temperatures from the radiation data. The result are data that provide such different trends (not for longer time periods, though).
If you want to get information on the troposphere, you will have to use those satellite data. But if you want to get information about the temperatures or their anomalies at the surface, those satellite data aren’t of much use.
Sorry about screwing up the blockquote closings at two points, apparently. Bob, feel free to fix it.
Jan……has been commenting about models and temp sets and how persons who do not accept the “evidence” of global warming as either being accurate wholly or as being far from zero.
Here are some of the persons on your side of the fence Jan, and I would like to know your position on this paper and the relevant comment I want you to see for yourself…..
Climate System Response to Stratospheric Ozone Depletion and RecoveryMichael Previdi1,*, Lorenzo M. Polvani1,2DOI: 10.1002/qj.2330
……..”robust modeling evidence…”
Models, in your realm, are evidence?
Pretty much what I expected from Jan. Denial, excuses and repetition of silly propaganda points. When someone is as biased as Jan obvious is, there is little use in having a discussion. They ignore valid points and simply repeat their talking points. Science has long since left the building.
This was made completely obvious by his completely ignoring my point that models were used in the reanalysis and the models themselves have been tuned to the temperature data.
His projection was made clear by this one statement …. “your choice was based on confirmation bias”. That in a nutshell is problem with Jan and likely is endemic at GISS. He is clearly not a scientist in any meaningful definition of the word. No real scientist would claim surface data is better than satellite data.
Where did you get the information that the models were tuned to the temperature data? You just keep repeating falsehoods. I quoted from the abstract where the authors of the study explicitly stated that no measured air temperature data were used. So you are asserting that the authors of the study were lying?
The rest of your comment, your attacks on my person, only serves to maintain your face after having utterly failed with refuting anything of what I said. That’s how fake skeptics do it.
Jan….do support research that propounds “robust modeling evidence” as propositioned in Climate System Response to Stratospheric Ozone Depletion and RecoveryMichael Previdi1,*, Lorenzo M. Polvani1,2DOI: 10.1002/qj.2330?
NOTE TO VISTORS: JAN PERLWITZ IS NO LONGER WELCOME HERE SO DO NOT EXPECT A REPLY FROM HIM TO YOUR COMMENTS.
PS: See the exchange between Jan and I on the thread here.
Pingback: If 99 Doctors Said… | Bob Tisdale – Climate Observations
Pingback: If 99 Doctors Said… | Watts Up With That?