Love him or hate him, it is worthwhile to understand where he is coming from, so I present this video: The emergent patterns of climate change
According to TED:
You can’t understand climate change in pieces, says climate scientist Gavin Schmidt. It’s the whole, or it’s nothing. In this illuminating talk, he explains how he studies the big picture of climate change with mesmerizing models that illustrate the endlessly complex interactions of small-scale environmental events.
Video follows, comments welcome.
The transcript is here: http://www.ted.com/talks/gavin_schmidt_the_emergent_patterns_of_climate_change/transcript
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A couple of final thoughts.
Thanks to our host for posting this, it is important to understand where guys like Dr. Schmidt are coming from.
We can quibble about what the word skill means, but I don’t think it matters here.
This statement of Dr. Schmidt is so blatantly misleading that to me it’s as inexcusable as an outright lie. What’s the use of having developed a science well enough to make predictions that haven’t happened if, in the end, all we’re willing to do is stand around and pretend the science is OK even though the projections have not matched observations would be a much better question IMHO.
The paid-for “Ted Talk” (as all Ted Talks are now) starts with a fake “crowd-applause-soundtrack” and then ends with the same fake “crown-applause-track”.
It would have been far more entertaining and far more accurate if there was also a “laugh-track” along with it after every sentence made by Gavin. Situation comedy is what it was.
His models are comedic. His talk needs a laugh-track (like when he said climate models haven’t move onto C programming yet – C was invented in 1969 – Fortran in 1959).
If you like your global warming, you like your climate models and you like your Gavin. If you like your evidence, then you do not get to work on climate science at a University or an Institute, If you like your evidence, you get fired. If you like your fake applause-track, you get promoted.
When I ask the models they just tell me to go away.
We certainly do have skilful models predicting weather and those excellent visual representations of models runs are displaying that. Frankly the BOM (in Australia) does an excellent job of predicting weather, several days in advance now.
What we dont have is skill in perturbing the system into unknown and previously unseen states because our understanding of the interactions is based on known combinations and our understanding on interactions with different states is obviously poor.
Skill with Weather simulations != Skill with Climate simulations
Gavin is trying to convince himself as much as anyone in that video. And in typical “team fashion” he oversold the models without acknowledging their weakness in anything other than an “it’ll be alright in the end, meanwhile trust us now” way.
TED is relentless Warmist and will not countenance skeptical contributions.
Therefore I will not watch TED stuff…even though I may be missing out on an opportunity to pillory Gavin as he writhes and wriggles and tries to claim that he’s right even though he is so clearly and spectacularly wrong!
I noticed the “skillful” model graphic animations stopped at the end of the 20th century.
Not so “skillful” since then, are they?
I still remember the video clip posted here a while ago, when Gavin appeared on a news program and slithered off the stage before (I believe) Dr. Spencer (or Christie) joined the panel. The man is a coward and a liar. It’s sad that people like him can a position a position of power and influence.
” We know what happened over the 20th century. Right? We know that it’s gotten warmer. We know where it’s gotten warmer. And if you ask the models why did that happen, and you say, okay, well, yes, basically it’s because of the carbon dioxide we put into the atmosphere. We have a very good match up until the present day. ”
That’s just it; we don’t know globally what happened over the entire 20th century. We only have half way decent global observations from the beginning of the satellite era.
Here’s the other thing, who still uses FORTRAN? I haven’t used FORTRAN since college. He might as well of said: trust us we’re on the cutting edge of science even though we’re 3 decades behind in technology.
Oh yeah, I cringed with Gavins thoughts on new fangled languages like “C”. Ouch. I think my last comment was probably meaningless to the climate modelling community. Allow me to rephrase
Skill with Weather simulations .NE. Skill with Climate simulations
😉
I sent the following email:
tedx@Alfred Ledner.com
Hello,
I note you have presented talks by several proponents of Global Warming/Climate Change. However, you have not given an opportunity to present the other side of the issue to climate skeptics. There are several notable, peer reviewed climate experts who present the skeptical view. Among them are Richard Lindzen at MIT, Willie Soon at the Harvard Smithsonian Observatory, Judith Curry at Georgia Tech, Roy Spencer and John Christy at the University of Alabama and a long list of other Ph.D. experts. Please invite one or more of these experts to take the stage at a future conference. Balance of scientific opinion is important.
Regards,
John Coleman
I think if would be excellent if they heard from many of the rest of you.
I thought it was fairly good.
Some false notes, but overall, an effective presentation.
I liked the orders of magnitude paradigm, a very useful way to illustrate the difficulty of the problem
Surprisingly, he used only 14, with the size of the earth as the upper bounds – somewhat surprising as he clearly (despite some comments upthread) acknowledged the influence of the sun. The 4 down 14 to go was simply the artifact of a live presentation.
I see some chuckles about Fortran, and can only assume people are doing serious modeling.
In a recent role with my company, I worked with a moderately sophisticated financial model. It was written in Fortran, because we had to model interest rates, inflation, and the interactions as they affect bond prices and yields, not to mention stochastic insurance loss projections. Fortran was used because it is a suitable language to do very heavy duty number-crunching. It makes a nice sound-bite to treat it as antiquated, but only to those who don’t really do heavy duty modeling. (Which is not to say it is always the best option – I’ve modeled some processes in APL, some others in Excel,, the choice depends on how much number crunching is needed. One can have a highly sophisticated model that doesn’t require a lot of number crunching, but models of the financial world and models of the climate need to do a lot of brute force calculations)
The problem isn’t fortran. The problem is implementing different bits of math outside of a high level architecture that ensures quality and allows for measures of confidence. I’ve worked on problems of less complexity, that required far more effort from the coding side to even get past the initial reviews at the pentagon.
Gavin Schmidt is a self proclaimed expert in his climate modelling field. To protect his own authority to make expert statements his questionable skill, is avoiding direct and public debate with scientists who challenge that expertise.
In a court of law, an expert must submit to probing cross examination to establish that they are what they claim to be, in the knowledge of the court and, before their evidence as an expert will be accepted.
While Gavin and many of his colleagues shrink from public debate with other sceptical scientists, they cannot expect to be taken seriously!
Untested authority statements in those circumstances should not be used in determining public policy outcomes, or used only under suitable caution.
And let me say this “pal review” and setup “pal debates” with fellow nodding puppets do not qualify as a public honest debate. Especially so when dealing with political policies and responses that will impact on the rights, wellbeing or, economic circumstances of others.
Let the public debate take place.
If it can only be recognized “in the whole” then it can only be predicted in the whole.
Yet when the predictions in the whole prove wrong, we are told the effects are masked in the complex parts.
Any proposition about anything could be justified this way.
“The ability to predict retrospectively this slowdown not only strengthens our confidence in the robustness of our climate models”
It boggles the mind that someone could make the above statement and keep a straight face. ‘Retrospective prediction’ is a contradiction in terms. You can’t predict what has already happened. The fact that they can adjust the parameters that stand for lack of knowledge of how the underlying processes function (clouds, PDO, volcanism, etc) to mirror past events does not give me any confidence in the robustness of the models. That is a nonsense statement worthy of Lewis Caroll.
[b]Ocean Vents And Faulty Climate Models[/b]
http://quadrant.org.au/opinion/doomed-planet/2014/05/ocean-vents-faulty-models/
[blockquote][i]It hardly needs to be said that climate modelling is a far-from-settled science, despite what its practitioners would have us believe. Just how flawed becomes even more apparent when you consider that massive heat sources on the ocean floor have been entirely omitted from the warmists’ calculations[/i][/blockquote]
I don’t guess a CAGW skeptic or a lukewarmer has ever given a TED talk? At least I can’t find one.
Apologies, wrong syntax …
Putty in their hands as a “man of vision” leads them over the intellectual precipice. I wonder how impressed his audience would have been had they known that what record there is of climate model accuracy is the result of furious, after-the-fact hind-casting.
Schmidt’s talk tells me more about Schmidt than it does about his presentation. He is either convinced about what he spouting or in a state where he is so deeply entrenched that he dares not backtrack, and has closed his mind about any conflicting data or flawed underpinning that renders the climate models as merely cartoons of reality.
His definition, or more correctly his believe, that the climate models display “skill” is laughable as is Mr Mosher’s ridiculous ‘illustrative example”.
Well, I don’t know the man, and this is the first I have seen of him. A lot of hand waving, and he quickly whisked away the abstract and the cement ; excuse me, that’s the concrete, not the cement.
Well he impressed on us just how much minutiae goes into these models. The live models running in video were stunning. So this impressed on me, just how much of the fine detail goes into the models.
That leads me to believe; or at least presume, that the real climate in real time, is being depicted by these models running, which means that there aren’t appreciable, or at least significant, delays between what the model predicts, and the actual occurrence of the result.
So how in the hell, is there virtually NO correspondence whatsoever, between just one important aspect of the climate; the “global average temperature anomaly” predicted by the model, and that actually measured by a multibillion dollar monitoring system of the real “GATA”.
So Gavin says, there’s 14 orders of magnitude to the range of this system, and they are modeling four orders of magnitude.
Which one are you modeling Gavin; and are they contiguous ??
So we saw micron sized aerosols, and we hear a lot about how important they are. So I’ll be generous, and say that scale is 100 microns; and that’s where they start. That’s their (h) in the equivalent to E = h nu.
So 10^4 x 100 microns, is 10^6 microns; roughly one meter. So that’s about from my front door to down the first step , or thereabouts.
Nope, that doesn’t work; not nearly global climate.
Earth’s circumference is 21,600 nautical miles (a mile a minute), so 10^-4 of that is 2.16 nautical miles x 1852 = holy cow; 4000.32 meters !
So if I’m happy with a one dimensional globe model, and four orders of magnitude, I need one “weather” station every 4 km, and maybe it can be about 0.32 meters square; about the size of one of those smaller boxes with the incandescent light bulb in it , to keep the snow off the thermometer.
Well that doesn’t work either; Dr. Hansen, is only putting one every 900 km or so.
And what if I want a two, or even a three dimensional climate model; well a two on curved space will do. Do we have that many thermometers on this planet.
Well Dr Roy, and Prof Christy have a time shared one that they loan around the world, so it seems to be almost everywhere
I’m really having a hard time trying to imagine which four orders of magnitude Gavin is modeling. I wonder if Peter Humbug, knows which ones ??
If I take for granted, that the climate models say the climate is changing rapidly; I didn’t hear one word from Gavin, about what exactly is going to happen, when the fat hits the shin, and all that model clay comes to pass.
We’re supposed to all jump.
Which way Gavin ?? Why don’t you go first.
I will let y’alls have the Fortran lollypop; darn things get stuck in my teeth.
What the heck does it matter, what computer language you program in.
I would be paying more attention to the actual mathematical formulas that they are encoding in that Fortran; not the language.
So long as they are not programming those equations in Bill Gates personal kindergarten Excel language; it is fine with me.
In M$ excel math, earth’s volume is given by: V = (4/3)*PI()*(POWER(R,3))
Gavin flashed some fancy math by us too quickly to read; so why bother showing it.
Didn’t anybody ever teach him, you never write more than three lines of text on any one presentation slide ??
Who or what is Ted ??
Actually THERE’S the #1 stupid skeptic argument.
I might believe he had a valid model for predicting the future when he can zero the model for whatever base time he chooses. Then run it backwards for 2000 years prior to his base time. If he matches what the weather actually was in that past period, then he has a chance of predicting to future. But I doubt that he understands why the magnetic poles are drifting, or why the poles flip and flip back, or how that effects the climate. Why do we keep having ice ages, and why do they start and end. The most his model can say is if things remain the same in the future as they were in the test period then this is what we think will happen. Unless something happens that we did not account for, or there is a Black Swan Event, like a super volcano, or an asteroid hit or an EMP even from the sun, or the poles reverse.
I thought it extremely interesting and would happily sit through a longer lecture by Dr Schmidt.
I may not agree with his conclusions but the talk certainly allows you to see where he is coming from. Note that he admits the models are “wrong” and should, can and hopefully will be improved. However he thinks that they are good enough for a “reasonable” projection of the future and that future improvements in the models will refine the projection but not fundamentally change it.
If you had a model that you thought gave a reasonable projection and the results of that projection gave you cause for concern, wouldn’t you speak loudly too? Dr Schmidt models climate and the results have convinced him that there are grounds for concern.
He spoke fairly from his point of view and that is the best that anyone can do.
I would like to hear more about “modeling”. (Really, aren’t these more realistically called SIMULATIONS? Aren’t these modelers striving to duplicate The Climate Matrix? Reality from a virtual world?)
I think Gavin’s talk had merit. The magnitudes of SCALE in BOTH time and size are extremely significant in simulating climate. Small scale events affect large scale events and vice versa. For example, cloud formation starts with microscopic (molecular?) particle behavior but clouds act on a global scale. How many orders of magnitude is that?
So these simulations with terabytes of information and code run on super computers with hundreds? of cores. And they strive to make the simulations ever more complex. Derived data is fed back into the simulation to derive more results. And how long does it take for a simulation to run at that level of complexity, even on a supercomputer? Is it really necessary? Perhaps not….. simple models are sometimes reflect reality just fine.
I repeat, I’d like to hear more about these models.