I think this basically just represents the different timescales for the main causes of the effect. CO2 hangs around in the atmosphere for quite a long time. (People sometimes put a lifetime of ~100 years on it, but the truth is that the decay is not well-represented by a single exponential…so there are a whole range of timescales, with a significant fraction sticking around for a lot longer, see here). For an asteroid collision, I assume the main effect is (like for a volcano) the cooling effect of the aerosol particles ejected into the stratosphere. For a major volcanic eruption, most of that effect lasts just a few years before the particles get washed out. For a bigger effect, it may take a little longer and there may be some time for the climate to recover even once the particles are washed out, but it probably won’t be that much longer.
I will take a look.
My mind, and the mind of anyone else who looks at the prediction with an open mind.
By coincidence, a internet commentator prepared a graph to assess Hansen’s prediction:
http://rankexploits.com/musings/wp-content/uploads/2008/06/hansencomparedrecent.jpg
Note that the graph would appear to incorporate the most recent data, which apparently have not been kind to Hansen’s predictions.
You know what they say about having an “open mind”, don’t you?
Me, I’d still like an answer in that other thread about how PC politics is gagging your wife’s research…
If you are old enough to remember the “debates” on smoking and health in the '50s and '60s, you’ll remember that the tobacco companies and their captive scientists said that the link between tobacco and health wasn’t proven, that it was only a theory, and there wasn’t a mechanism to cause cancer. Sound familiar? Those who believed that brand of denier put themselves at risk for cancer. Someone waiting for “proof” might now be dead. That’s his or her right, but in this case we’re playing with the entire planet, not one life. Do you want to risk being as wrong as the deniers of the smoking - cancer link were?
And, it is worth noting that some of the same people who brought you doubt on the connection between smoking (particularly, but not exclusively, second-hand smoke) and health problems are now the same ones bringing you doubt on climate change, e.g., Fred Singer, the late Frederick Seitz, and Junkscience.com founder Steven Milloy. So, it’s not just the techniques being borrowed but even the actors.
If that’s true, then it supports my point that the climate is dominated by negative feedbacks.
Lol. It always comes down to simulations.
I don’t understand your point. Over the last 2 or 3 years, a wide gap has opened up between the prediction and “reality.”
Sure, if you ignore the last 2 or 3 years, the prediction doesn’t look as bad. But so what? Hansen made predictions about individual years. He was free to predict a trend but chose not to do so.
Anyway, I’m willing to bet that the gap will be even wider by 2010.
If you are listing people who have expressed skepticism about second-hand smoke, you may want to include Cecil Adams
Two and a half years of steady-ish and then briefly dipping temperatures are not going to change the overall trend lines since 1988 significantly from what they were at the end of 2005, when the trends were in very good agreement with Scenario B. They will be a bit lower now but still within the 2-sigma error bars. And, as I noted, this is for a model with a climate sensitivity on the high side of best current estimates. Care to estimate what trend would have been predicted if we assumed the climate sensitivity that, say, Richard Lindzen claims to be correct? (My best estimate is that if you really really stretch it, his climate sensitivity estimates might predict a rise close to 0.10 C per decade…but more realistically probably more like 0.05 C per decade, which is considerably lower than the trend actually seen over the past 20 years.)
It is also worth noting that although that plot that you linked to seems basically legit, there are a couple points to be cautious of: (1) Those monthly values are going to swing more dramatically than the yearly averages that Hansen’s predictions are based on…which tends to make the downturn in the early part of this year look much more dramatic than it will likely look for the full year. (2) Her choice to cut off the plots in 2010, while not an unreasonable choice for the data she wants to show, has the fortuitous advantage of catching a dramatic uptick in scenario B between 2009 and 2010 and then missing the quite flat period after that. See here for the full plot out to 2019.
I’m skeptical, but anyway I prefer to talk about what Hansen actually predicted. As opposed to what you wish he had predicted.
The suggestion in your statement is that Hansen’s model was right except that he overestimated CO2 sensitivity by a little bit. That’s certainly one interpretation. Another possibility is that he was wrong because there are other factors driving the climate which nobody understands.
When the facts refute one’s hypothesis, do you adjust the hypothesis so that you can keep the part you like? Or do you question the entire hypothesis?
So look at the moving averages. They are all well below Scenario “B.”
brazil84, firstly, the only thing you’ve succeeded at is getting us off course. The proof of a simulator has nothing to do with it’s predictive ability. If you don’t understand why, start a GQ question asking.
It’s what you decided to talk about. You don’t want to talk about simulators, don’t ask about them. You don’t want to understand simulators, don’t ask ask about them. If you don’t want to believe what simulators come out with, learn how they work and how they’re tested and confirmed first.
You don’t have the basic skills or knowledge to be arguing about this, and I’m not even talking about climatology, since you don’t even understand the basics of simulations and graphs and margins of error. You might as well try arguing whether or not 80 + 42 = 122 with a guy who can’t count higher than 2 for all the usefulness your presence brings to the debate on AGW.
(bolding added)
No, he published the output of the simulator. That’s not a yearly prediction. It’s just the form that the data output took. It churns through data, adding in slightly random elements that simulate unpredictable real life things (like El Nino events or volcanic eruptions) and spits it out as it is. It’s not intended to be a future predictor on a year to year basis since there are several factors that are entirely unpredictable and will effect the global weather at an unknown quotient for an unknown period of time which can run into the decades. But it’s good to have the output data so you can go back and see how well it tracks against other people’s simulators given the same random events of the same amplitude at the same times, and see what their result is. Or simply just to eyeball to see if the “wobbliness” of the line is within the same range as the real live wobbliness–as that’s a measure of the quality of the simulator.
Data is useful for data’s sake even if it isn’t representing something immediately useful to the layman viewer (i.e. you.) Getting pissed off because there’s more data contained in the graph than is useful to yourself as a 3rd party is silly. It wasn’t made for you, and if you don’t have the knowledge to understand the meaning of the data, then you have no place to contend it.
Still if you would feel joyous in averaging out the years into larger segments then let’s go ahead and see if the lines don’t become more similar to one another as the years are compacted (using the blue and black lines from here:
Averages of 16 year segments (The orange line is the actual and the prediction is yellow)
Hansen et al was slightly high, but the up-slope change is at the same angle for both graphs. For one thing, Hansen got unlucky with real world volcanic eruptions, depressing the values somewhat:
But mostly the levels of various emissions didn’t track along any of the A, B, or C scenarios. You have to make assumptions to make predictions, and the world ended up having different emissions levels than were assumed. This doesn’t make the simulator wrong, but there’s no expectation in anybody’s mind who understands the basics of such tests that the simulator will track with reality. It just tells us (roughly) what will happen if emissions do go along a certain course.
It’s like my bean machine and hammer example. If you set up your simulator with the presupposition that the hammer will strike once every 3 seconds, but in real life it ends up occurring every 2.8, you’ll get different results between prediction and observed. That doesn’t mean that the simulator doesn’t work as a simulator. And it definitely doesn’t mean that the hammer is having no effect on the outcome. It might, but it’s unlikely. But once you’ve discovered what the actual rate of hammer strike is, you can set the simulator to 2.8 and see if it lines up what did happen in real life. That’s the real test of a simulator.
If you were to take the 1988 Hansen simulator and give the actual values (and simulate the Pinatuba eruption), it’s likely that it would come a significantly closer to what actually happened globally than any of the scenarios in the graph. And we’ve done things like that. We know the simulators work to within X% accuracy, and they all show that anthropogenic emissions have caused change already and will continue to do so.
The proof of a simulator isn’t in its predictive capabilities, but in it’s being able to simulate the past and have it match up.
I don’t understand what you mean by “proof of a simulator” Do you mean proof that a simulation models something in a reasonably accurate way?
Of course it’s what I decided to talk about. My point early in the thread iwas that the main evidence for the CAGW hypothesis is that it’s possible to construct simulations which are consistent with some aspects of the climate and also consistent with high climatic sensitivity to CO2.
Nonsense.
Lol. So his prediction wasn’t really a prediction after all. Well in that case, I come back to my original question:
Oh really? So even if a hypothetical simulation wildly diverges from reality (going forward) you would still accept it as “proven”? (assuming it matches up with the past, of course)
http://home.comcast.net/~jaswensen/machines/straight_edge/straight_edge.html
Welcome to the wonderful world of iterative processes.
Is that a “yes” or a “no”?
It’s a “Lurn how shit works. When come back, bring pie.”
If you want to learn stuff, ask in GQ and LEARN. It’s useless for me to write and rewrite the same thing countless times with you ignoring the meaning and learning nothing. You can’t teach someone who treats your lessons like a debate, and you can’t debate someone who hasn’t learned enough to know what he’s talking about.
Think upon the phrase “tools to build tools that build tools.” Try to grasp it’s meaning. Envision the progression of a factory which makes the parts for a factory that can make parts to within half the margin of error in size, which will make parts for a factory that can make parts to within half the margin of error in size. Try to grasp the relevance to the subject of how one even creates a simulator.
Welcome to the wonderful world of iterative processes.
Read posts #37 and #59. Chew and digest.
Simulators will always be wrong. Every time you run one, it will give you the wrong result. And yet we build massive structures in natural disaster zones based on the output of simulators and the structures do perfectly well! How do we achieve this, you ask? Well just keep thinking about “tools to build tools that build tools” until you don’t feel the need to ask.
i.e. you’ve decided to evade my question.
The fact is that you have no idea what you are talking about. Just like you had no idea about the concept of systematic error in the other thread.
And by the way, here is an interesting point, which apparently was published in a paper last year:
Remember, by the sage rat standard, all of these models have arguably been “proven” because they all simulate past temperatures reasonably accurately.
In my opinion, at least some of them must be wrong in the sense that their predictions will be very different from reality.
You have no idea what science modeling is all about. I’m not going to repeat myself in multiple threads, but read here
Sure, let’s take that as so.
Now, if I walk into a restaurant, see a lobster tank in the window with ten lobsters in it, lobster listed in the menu, and proceed to order lobster and it ends up that the waiter brings me steak–well does that mean I’m an idiot for believing that I can order lobster at that restaurant?
If the police get a 911 call giving very in-depth and believable information about a crime taking place, and they rush over in record time, and nothing is happening or appears to have happened–were the police a bunch of idiots for answering the 911 call?
If mankind has hundreds of years of experience and simulations stating that I will experience such and such a pressure differential as I dive X hundred feet under the surface of the ocean and I decide to ignore all that and go down and up really fast with no specialized equipment, because all of human experience and scientific knowledge very well might be wrong–am I an idiot?
“They might be wrong” is a stupid argument unless you have some sort of evidence beyond your personally inability to understand science to show that there is good reason to think that someone is wrong. And like I said in post #36, there’s no scientist who doesn’t admit that it’s entirely conceivable that all of our evidence and understanding and models may be wildly off due to some unknown or unexpected factor that no one has yet come up with. The models might be severely broken. They might end up being wildly wrong as we’ll discover 200 hundred years down the line. But WHY does that matter in any relevant way to the topic at hand?
And if I have a very complex machine made by aliens that regularly pulses either blue or green and I’ve had thousands of people split up into independent, competitive groups testing it regularly for 40 years and it’s never come up different, and they’ve studied and learned the internal workings of the alien machine and have come back to me to say that they’re decently sure that they understand the working of the machine and are 95% certain that the machine only can and will only continue to flash blue and green, well are they idiots? Sure, it’s a alien machine using foreign, complex technology. It might pulse red just because we missed some particular minor something. But, what would you personal vote would be the more likely?
No, I decided to make fun of the inanity of the question and revel in your inability to even understand how you’re being made fun of.
Yes, if the simulator is wildly wrong, it’s broken. But, short of evidence to support the idea that a simulator will break, and having lots and lots of experience showing that the simulator does model reality, supported by independently built rival simulators also all very well shown to model reality, dwelling on that is a very stupid and inane point.
No. So what?
No. So what?
Yes. So what?
Depends on the context. Besides, anyone and anything “might be wrong.”
A better question to ask is “how much confidence should I put in this model?”
No. So what?