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Computer Modeling Failed During the Ebola Outbreak
the_newsbeagle writes: Last fall, the trajectory of the Ebola outbreak looked downright terrifying: Computational epidemiologists at Virginia Tech predicted 175,000 cases in Liberia by the end of 2014, while the CDC predicted 1.4 million cases in Liberia and Sierra Leone. They were way off. The actual tally as of January 2015: A total of 20,712 cases in Guinea, Liberia, and Sierra Leone combined, and in all three countries, the epidemic was dying down. But the modelers argue that this really wasn't a failure, because their predictions served as worst-case scenarios that mobilized international efforts.
Garbage in ... Garbage out - GIGO
That computer simulation failed simply because all the input that the program got fed with were erroneous
Well, IF there hadn't been a very robust response, it could easily have been that bad.
People who work in population dynamics know that the models are based on a very crude understanding of the disease and ultimately general epidemiological assumptions. The fact that there are basic assumptions is sometimes disguised in the process of making fancy computer models.
These models may be the best predictions that people can make. However, GIGO (garbage in, garbage out) still applies. However, sometimes the best predictions are not good enough since they can be very misleading.
(I used to work on similar models and became disenchanted; I need to post anonymously.)
I've been involved in contracts that had public health modeling components. Being "way off" is not necessarily a proof the model is no good when you're modeling a chaotic process which depends on future parameters that aren't predictable. In our case it was the exact timing of future rainfall. In their case it probably had to do with human behavior. A small thing, like an unseasonable rainstorm, or an infected person showing up in an unexpected place, can have immense consequences.
You look at all the data you have, and you think, "Hey, this is a lot of data, I should be able to predict stuff from it," but the truth is while it looks like a lot of data it's a tiny fraction of all the data that's out there in the world -- and not even a representative sample. So you have to guess "plausible" values, and if they're wrong you might not see the kind of result that eventually happens, even after many model runs.
So in most cases you can't expect a computer model to have the power to predict specific future events. It can do other things, like generate research questions. One of our models suggested that having a lot of infected mosquitoes early in the season reduced human transmission of a certain mosquito borne disease later in the season, which was a surprising result. When we looked at it, it turned out that the reason was that the epidemic peaked in the animal population early in the season before people were out doing summer stuff and getting bit. Does that actually happen? We had no idea, but it sounded plausible. The model didn't give us any answers, it generated an interesting question.
Post may contain irony: discontinue use if experiencing mood swings, nausea or elevated blood pressure.
"Its not a bug...... Its a feature!"
This is like a car manufacturer claiming that their car will have 1,000 horsepower, and after several months/years the people who have preordered it finally get theirs and find out it has 20 horsepower and the manufacturer says its a good thing because it makes the car safer.
The problem with blaming prediction models after the fact is that the models were based on the assumption of current and continued support. Ebola just like the Y2K bug was everything the disaster it may have been had it not been for the efforts involved in preventing it.
End result, all the people who did the hard work making the world aware of the problem are blamed for crying wolf.
To quote my beloved Bryan Caplan (http://econlog.econlib.org/archives/2015/06/the_sum_of_all.html):
"I didn't think there was anything more to say about infamous doomsayer Paul Ehrlich. Until he decided to justify his career to the New York Times. Background:
'No one was more influential -- or more terrifying, some would say -- than Paul R. Ehrlich, a Stanford University biologist... He later went on to forecast that hundreds of millions would starve to death in the 1970s, that 65 million of them would be Americans, that crowded India was essentially doomed, that odds were fair "England will not exist in the year 2000." Dr. Ehrlich was so sure of himself that he warned in 1970 that "sometime in the next 15 years, the end will come." By "the end," he meant "an utter breakdown of the capacity of the planet to support humanity."'
Okay, here's Ehrlich's side of the story:
After the passage of 47 years, Dr. Ehrlich offers little in the way of a mea culpa. Quite the contrary. Timetables for disaster like those he once offered have no significance, he told Retro Report, because to someone in his field they mean something "very, very different" from what they do to the average person.
In the video interview, Ehrlich elaborates:
'I was recently criticized because I had said many years ago, that I would bet that England wouldn't exist in the year 2000. Well, England did exist in the year 2000. But that was only 14 years ago... One of the things that people don't understand is that timing to an ecologist is very very different than timing to an average person.'"
...maybe the crazy predictions opened enough eyes to get the ball rolling on containment...therefore nullifying the predictions?
The media love it because scary headlines attract eyeballs, but scare tactics can backfire: Researchers might get more funding, but they also might get their research banned: http://victimsofdsto.byethost3...
So the ends justifies the means. Got it.
Stupid sexy Flanders.
I think computer models only work when the target data is too far out to verify.
I would rather we end up with fewer losses than expected, than more. We learned something from this problem, and the cost was not as bad as it would have been had the error been in the other direction.
Damn_registrars has no butt-hole. Damn_registrars has no use for a butt-hole.
If math errors by computers due to hardware or software make us take the wrong assumptions? Especially in physics or other high end math fields.
"If any question why we died, Tell them because our fathers lied."
Sounds glorious, a reduction of population by at least 6 billion.
"If any question why we died, Tell them because our fathers lied."
The way the model results are reported needs to change. The worst case results were presented to the public as the expected outcome. This is something between highly deceptive and unethical. (think yelling "Fire!" in a crowded movie theater.) The best, worst and average outcomes from the model need to be reported. Perhaps even two sets of best, worst and average outcomes. One with large scale intervention and one with zero intervention.
A very simple way to think about when you know the model has failed: The model has failed when it makes 100 predictions with 95% certainty and more than 5 of the actual outcomes are outside the bounds defined by the best and worst outcomes. Note: I said SIMPLE.
The modelers need to be careful about what they say. Next time they predict armageddon, no one will take them seriously.
What a bunch of idiotic posts. Model results are associated with predicted range of probabilities (eg 80 percent chance of rain). We depend on weather reporting even when they are wrong on occasion. Why? ...because our weather models are pretty good(despite chaos).
A Good Troll is better than a Bad Human.
Computer modeling is vastly overrated. It is mostly based on the abstraction of trend lines. Which is the assumption that existing trends will continue. That is less a prediction of hte future than a picture of the present.
Look at the growth trend line of a six year old... then graph that out... in 10,000 years think how big he'll be!
Right?... that's what trend lines do... They're only useful if people that know what they are and how they work use them. Often as not, people that aren't educated or knowledgeable enough to deal with them get put in positions where they can make determinations about stuff using those trend lines.
And it generally leads to a shitstorm of stupidity.
I've decided to stop wasting my time responding to AC trolls/sockpuppets... so if you want a response from me... login.
if we let things go to shit like we normally do. Because of this we didn't let things go to shit and so the model was wrong...? How is this a bad thing, or a failure of the model. This is like when people say regulations aren't needed anymore because the abuses they were put in place to stop have stopped. They stopped for a reason people. Figure it out, it's not that difficult.
Hi! I make Firefox Plug-ins. Check 'em out @ https://addons.mozilla.org/en-US/firefox/addon/youtube-mp3-podcaster/
No, it doesn't show that. The point of the computer models is not to predict exactly how bad the outbreak will be. What good would that do? All you have to do to find out how bad the outbreak will be is wait. What computer models do is give us some kind of idea of how seriously we should take the situation. For that, the models did a fine job. They probably shouldn't have been bandied about so much on the news, but that's not a problem with the science--that's a problem with the science reporting, which is a well known problem.
But it's really, really frustrating when people predict a possible bad outcome and suggest steps be taken to prevent it, and then steps are taken, and then the bad outcome doesn't happen, possibly because the steps were taken (it's never possible to know for sure) and then somebody says "you cried wolf." No. Crying wolf is when you lie about a threat you know doesn't exist. The Y2K threat wasn't crying wolf, and this wasn't crying wolf. What both things were were attempts to mitigate a very real risk the severity of which was uncertain. The fact that we didn't have a massive breakdown in 2000, and that we didn't have an Ebola pandemic, are both really good outcomes.
But the modelers argue that this really wasn't a failure, because their predictions served as worst-case scenarios that mobilized international efforts.
so.... how about those climate models out there????
So, you're saying that climate models that do not reflect the mobilization of international efforts mean that we should not attempt to push for international efforts to ensure that those worst-case predictions do not happen?
Climate science is always evolving. Scientists learn more about the planet and how different aspects of our planet's behavior interact, and they discover new aspects through this process. I don't think there's a lot of argument that humans are taking huge carbon deposits that are the result of plants using carbon from the air as building material in their structures and reintroducing that carbon into the atmosphere again. The debate is what that does to climate.
Do not look into laser with remaining eye.
TWENTY THOUSAND PEOPLE died and you claim this as 'crying wolf'???
If the international community hadn't jumped on this, it could have been way, way, way worse.
-WolfWithoutAClause
"Gravity is only a theory, not a fact!"Excuse me, it is politically incorrect to doubt the climate change models.
The OP didn't mention climate models nor provide any basis for doubting climate models.
Besides which most people who cast aspersions on the accuracy of climate models fail to recognise the consequences of that argument. If climate models are inaccurate than there can be no basis for the denialist claim that changing the concentration of greenhouse gases in the atmosphere won't impact the climate. Denialists need models, and they need those models to agree with them.
Whats the difference between a "computer model" and a theory? Nothing. The only difference is that people who don't understand them are making decisions based of theories that have not been fully vetted. Separation of science and state.
These kind of events often follow a power law for how bad they get. It's notoriously (maybe impossible) to guess the magnitude of a power law event in advance. Also, my guess is they are not able to accurately account for adaptation in behavior of normal people in the disease zone. That's the sort of factor that will almost by definition be under-predicted.
Play Command HQ online
done precisely in order to encourage behavior that would change the inputs to the model.
Nobody looks at cigarettes today and says, "Gosh, nobody smokes anyway and death rates are coming down, there was no need for all that worry, smoke away!"
The whole point of the data in that case (and in this one) was to encourage the world to change behavior (i.e. alter the inputs) to ensure that the modeled outcome didn't occur.
To peer at the originally modeled outcome after the fact and say that it was "wrong" make no sense.
When we tell a kid, "finish high school or you're going to suffer!" and then they finish high school and don't suffer a decade down the road, we don't say "well, you didn't suffer after all, guess there was no point in you finishing high school!"
That would be silly. As is the idea that the modeling was wrong after the modeling itself led to a change in the behavior being modeled.
STOP . AMERICA . NOW
spend their days posting, "Why in the hell do we vaccinate against polio? It's a scam! After all, how many people do *you* know that have ever had it? Hmmmm? Case closed!"
STOP . AMERICA . NOW
Do you think Y2K would have gone so quietly had the entire IT industry simply ignored the problems created during the prior four decades of programming? Do you think the ebola outbreak would have been stopped so quickly had the world's health care organizations simply ignored the problem?
So yes, it was Y2K all over again. Some people noticed a huge looming threat, they brought it to the attention of the world, the world eventually responded with enough resources to solve the problem.
John
I admit that this is off-topic.
I dissected a frog in school. I do not recall there being an entry hole large enough for a firecracker. I did not go on to study medicine or any icky biology field. But I have been curious for a long time (don't get me started on the raped ape thing) and have to ask. How, pray tell, does one actually go about sticking a firecracker into a frogs anus? Google is not forthcoming and I refuse to do an image search. This important, scientific (I believe), question has to be answered and we rely on you.
"So long and thanks for all the fish."
Clearly, you mean to say "hypothesis" instead of "theory".
You don't, and I don't, but it should be obvious from discussion here that a lot of people do!
Sent from my ASR33 using ASCII
This is almost a cliche, it's exactly what happened after Y2K. We saw a potential threat, a huge one, and a way to prevent it. We mustered great resources to prevent it - and succeeded. But unlike in the movies those who prevented the threats were not celebrated - immediately afterwards they were accused of having made up the threat to justify the resources.
It's a fundamentally stupid failure of logic, but it happens over and over. If you manage to prevent a threat from realizing, people claim the threat was never real.
Unicode killed the ASCII-art *
No, he didn't. The idea that true science obeys strict Popperian laws is false.
This is almost a cliche, it's exactly what happened after Y2K.
Some time back in 1996, an employee at a British supermarket handling deliveries of goods tried to enter the best-before date of a can of beans. Tinned beans can be stored safely for a very, very long time. The beans that had been delivered were the first goods that supermarket received with a best-before date in 2000. The employee couldn't enter that date.
It was obvious then that if no action was taken, the supermarket would be in bad trouble in December 1999 and in deep shit in January 2000. It's also obvious that they were not stupid enough to let that happen.
...and first among children and young adults (5 - 24) are cars, with 33804 deaths in 2013 alone.
6510 of those being in the 15 - 24 years of age range.
Now... Maybe you're out there, in the night, prowling garages and parking lots, killing all those cars in their sleep in order to prevent further deaths.
Which would explain why you missed OP's point.
Which was that those "worst-case scenarios that mobilized international efforts" predicting "175,000 cases in Liberia by the end of 2014... [and] 1.4 million cases in Liberia and Sierra Leone" could result in a "crying wolf effect" when the next epidemic comes around.
Mit der Dummheit kämpfen Götter selbst vergebens
It was the "worst case scenario" model, meaning what would happen if there wasn't a massive influx of help into the affected area. This model, as well as countless studies into the situation, prompted many governments and NGOs into action. That action meant the reality of the outbreak would not match this worst-case scenario, which is to be expected to be the case. Unless you think doctors and medicine and emergency infrastructure & logistics achieves nothing, in which case you are entirely correct.
You really don't know how any of this works, do you? This is becoming more and more obvious with every post you make. Learned the difference between sea ice and land ice yet? :)
1. People start dying from Ebola
2. Scientists model the outbreak, making predictions based on what is currently happening
3. The world's governments and NGOs see the model's predictions and decide that's not an acceptable outcome, and make an effort to reduce it
4. The effort is so effective that the outcome doesn't match the predictions which triggered the effort to be made in the first place
5. The prediction then doesn't match the outcome, so idiots on Slashdot think the models were inaccurate and useless
There wasn't a failure. They made a startling prediction which spurred action to reduce the very thing it modelled. Because the action was so great the model's predictions didn't happen.
You really don't know how any of this works, do you? This is becoming more and more obvious with every post you make. Learned the difference between sea ice and land ice yet? :)
:D, why don't you show the good people my errors.
Just wondering if the models came with a prediction score or some measure of their accuracy. As with climate predictions, the untold story is that the models are no more accurate than their inputs and the validity of the theories used to create them. You might expect models to come with warnings, but they don't, at least nothing that gets transmitted to the public.
As the world embraces 'big data' and the modeling it spawns, this should be a bit of a lesson. The worry should be: how many times can models be used to 'cry wolf' before people start ignoring them?
"Consensus" in science is _always_ a political construct.
I'd like to buy your rock, Lisa.
Denialists need models, and they need those models to agree with them.
No, they don't. All they need to do is take the model output and compare it to reality.
But the modelers argue that this really wasn't a failure, because their predictions served as worst-case scenarios that mobilized international efforts.
Sure, this worked this time in everyone's favor. But what about the next epidemic? Let's say the modeling is better next time (which it should be) and it predicts another disaster. What then? People will look to the modeling on Ebola and say "it's not going to be that bad" and regard the next warning more lightly. This does nobody any good.
A good example of this is Hurricane Katrina. The Weather Channel makes every weather event look like the apocalypse because it's the Weather channel and they really only have one story they can run. They have to keep eyes on their channel to sell advertising time. So they exaggerate everything. And people become numb to the warnings - and look what that got us with Katrina.
No, it's always better to call things for what they are. I think they would be better off to say the modeling was off, call a failure a failure, and keep people's trust intact.
Weaselmancer
rediculous.
Exactly. Do those asking the question "did the modelers get it wrong?" think that the models can actually account for the level of response there will be from every country in the world that has the ability to help mitigate the spread of the disease?
I can see it now... epidemiologists sit down, come up with a model of the outbreak based on what they know about how the disease spreads, and where it's starting from, and then ask themselves "OK, now what's the World Aid Fudge Factor?".
"I have no special gift, I am only passionately curious." - Albert Einstein
this shows just how bad an idea it is to put too much trust in computer models
What's this? What exactly did the output of their model harm?
If anything, it was a reality check reminding people who don't study the spread of disease just how bad things can get if something this harmful goes unchecked.
"I have no special gift, I am only passionately curious." - Albert Einstein
But the modelers argue that this really wasn't a failure, because their predictions served as worst-case scenarios that mobilized international efforts.
so.... how about those climate models out there????
So, you're saying that climate models that do not reflect the mobilization of international efforts mean that we should not attempt to push for international efforts to ensure that those worst-case predictions do not happen?
Climate science is always evolving. Scientists learn more about the planet and how different aspects of our planet's behavior interact, and they discover new aspects through this process. I don't think there's a lot of argument that humans are taking huge carbon deposits that are the result of plants using carbon from the air as building material in their structures and reintroducing that carbon into the atmosphere again. The debate is what that does to climate.
I think the more salient point is our call to action should take into account uncertainties within the models. If the actions we call people to are costly, people should reasonably expect that the evidence brought forward is certain enough to justify the cost...
Modelling climate is insanely challenging as the scope is our entire planet, and the components involved number in the hundreds or thousands, and the interactions between them are again almost universally dependant upon one another. Climate models are a great tool for us to investigate and test theories about those systems and their interactions. We are getting pretty good at sorting the important/dominant components from the less significant ones. That said, there IS still a long ways to go. I would strongly advocate for continued study and development of climate modelling. I would also strongly caution against placing high confidence in specific model projections out into the future. Evidence follows:
Climate models fail the conservation of energy test. That's pretty fundamental, and models very widely still 'leak' energy.
From Mauritsen et al.
Among the model simulations whose data were available at the time of this analysis, there is a tendency for drift in the CMIP5 models to be less pronounced than in some of the CMIP3 models, and there is a reduction in the number of warm and cold biased models in CMIP5. Only a few models are close to zero imbalance, or likely to relax to near-zero imbalance. If a model equilibrates at a positive radiation imbalance it indicates that it leaks energy, which appears to be the case in the majority of models, and if the equilibrium balance is negative it means that the model has artificial energy sources.
Climate model tuning today normally uses adjustments to cloud parameters to balance the Top of Atmosphere energy. The single central driving force behind climate change still gets tuned by hand and is not yet an emergent property of the underlying understanding or simulation of the system.
From Chapter 9 of the IPCC AR5, complete with more than a half dozen citations to articles on model tuning confirming exactly this.
For instance, maintaining the global mean top of the atmosphere (TOA) energy balance in a simulation of pre-industrial climate is essential to prevent the climate system from drifting to an unrealistic state. The models used in this report almost universally contain adjustments to parameters in their treatment of clouds to fulfil this important constraint of the climate system (Watanabe et al., 2010; Donner et al., 2011; Gent et al., 2011; Golaz et al., 2011; Martin et al., 2011; Hazeleger et al., 2012; Mauritsen et al., 2012; Hourdin et al., 2013).
It's tempting to take the above and declare all climate models are bunk and toss them out, which would be very bad. Climate models are doing an important job of
Goes without saying that I haven't read the article, but that's my question. If the model was "this is what will happen if no action is taken" then the model may or may not have been right. But you certainly can't say that it's wrong because...action was taken. What's interesting is akin to what you say. Not a "fudge factor," but as another independent variable in the model. "Here's the outcome with no aid. Here's the outcome with these different types and quantities of aid."
We don't have a state-run media we have a media-run state.
If you keep making Chicken Little the sky is falling predictions with computer models as your proof to bring about some desired political change. Then eventually you will lose all credibility and no one will listen to you anymore. You damage the reputation of the sciences and certainly of computer models when you do this. Knock it off.
No, he didn't. It would appear that you're the one who is confused.
Required reading for internet skeptics
Exactly. They didn't do that because model in question was the worst-case scenario, not the best-case scenario.
Other models, which *did* take into account the mitigating work actively being done, accurately predicted the peak infection rate, when that peak would hit, and what the total number of infected would be *well* within those models margin of error.
A model which predicts how bad something can get if *nothing* is done to mitigate things, is not invalidated by future results when mitigation actions were taken.
A simplified example is this:
Many cars will use fuel levels, and rate of consumption to predict how many more miles you have before your tank is empty. They're actually fairly accurate, despite the fact that people don't regularly run out of gas every 400-500 miles, like they predict. Why? Because people take the output of that model into account, and implement mitigating actions. (They stop and fill the tank when it gets low.)
Shut up, FFS. You'll attract that Greek twat.
Luckily for them, nobody believes their lies.
.... and being downmodded to 'troll' proves my assertion.
Why?
.... and being downmodded to 'troll' proves my assertion.
There isn't a "-1 delusional fucking idiot" mod option on slashdot.
To have a right to do a thing is not at all the same as to be right in doing it
Software people are unable to understand the real world. But they're convinced we can build Mars colonizing spaceships based on decades-old fantasies...
I maintain our ancestors came from Mars after an environmental catastrophe and colonised Earth. Why are we trying to return to a dead planet from which we escaped?
It's always nice to see someone post a good, solid theory grounded in facts and confirmed observations on slashdot.
Maybe there'll be one tomorrow.
To have a right to do a thing is not at all the same as to be right in doing it
Because the Earth may explode and form a new asteroid belt at any moment.
You're thinking too small. The correct space fan argument is "because in just ten billion years the Sun will die and with it all life on Earth, so we need to have colonised other galaxies by then".
To have a right to do a thing is not at all the same as to be right in doing it
You're dead wrong because it is falsifiable. Just see what happens if nothing was done while controlling for likely impact (that means excluding anybody who were largely unaffected or who didn't need to act due to upstream efforts). That shows a different picture including one nuclear power plant that actually shut down.
There is very few legitimate examples. Most who did nothing were using systems like Unix which were never at risk. They did nothing because they didn't have to. Many of the rest got helped because hardware and software suppliers had made efforts and they gained from these through normal upgrade cycles.
The whole survivalist panic was overblown but not by the scientists. Thst was just people being idiots and they do that on their own.
In 1994 south African supermarkets couldn't keep up with demand for canned foods and survival gear. Many white people were convinced that the ANC takeover would be a doomsday event (same behaviour as before y2k). Rumors spoke of how the power stations would fail and murder gangs walk the streets. Nothing happened. And no politicians or scientists spread this. Just paranoid racist urban legends. You can't blame scientists for idiots who misquote them.
Unicode killed the ASCII-art *
It was a TERRIBLE failure. NEXT time, and there is always a next time, the response maay be insufficient because the prevailing "wisdom" will be that it is over-hyped via needlessly dire models. ANd THAT could be the one that wipes us out. The idiots tnat are calling it a "success" are either trying to put a good spin on it, at the future's expense, or they really are idiots and don't realize the terrible price that will be paid due to the previous modeling, during the next epidemic...
What they SHOULD have said, instead, was that the models were CORRECT, and there was NO failure, rather than that they overestimated it. If they say the models were correct based on no intervention, and the intervention simply prevented the worst case scenario, then the future is safer. It's not too late to change their tune, but if they don't stop apologizing for bad models, the point i mentioned in the previous comment will come to pass.
.... and being downmodded to 'troll' proves my assertion.
There isn't a "-1 delusional fucking idiot" mod option on slashdot.
Thank you for your well-thought-out and courteous reply.
If you think it's politically correct to question climate change models (the converse of my assertion), try it and see what happens.
The Ebola they modeled and the Ebola on the ground were not at all the Te same. The incubation period was longer, the death rate lower, and it took the survivors longer to become non-infectious after they recovered. All these made it spread much worse.
Red
But how is that any different from moving the goalposts? If they predicted something that didn't come to pass they're still wrong. Now it might be that they caused more work to be done than would have been, but it's still an incorrect model.
I predict if a brick falls on your head it will hurt. If you move your head out of the way I'm still correct. You seem to have some comprehension problems. In another model I predict if you move your head the brick won't fall on it and you won't get hurt. Pick a model.
My memory differs. There was an article in Scientific American about a year before Y2K; it predicted that even if "great resources" were mustered, there would be severe problems on the day after, and continuing for several months. I don't believe "great resources" were actually mustered, certainly not in the third world countries where computers were even then being used by governments and corporations. That article (or another one) also mentioned computers that were inaccessible, and which therefore could not be fixed (I think the example was computers monitoring undersea wellheads, which for some reason were located on the wellheads). And on January first, 2000, there were around ten documented problems, world-wide. (BTW, I have been unable to find the article in SciAm's on-line database, but I'm certain that's where I read it. Perhaps I should go to the library some time. You know, that place with all that paper...)
Looking back, I felt the article was a call for governments and industry to pour money into a field--the field the author of that article (and many others) would benefit from. Which is partly why I am now a skeptic when someone says that a catastrophic problem is going to hit us unless we do s.t. about it, and where that s.t. always involves $ (ok, euros and yens and... but not rubles, maybe that's a hold-over from the USSR's successful 5 year plans).
There is of course a Wikipedia article on Y2K, which summarizes the debate over whether this would really have been "a potential threat, a huge one" (quoting silentcoder).
Sure it's falsifiable--in principle. But most of the time you only get to try that experiment in some alternative universe. How do you know if you're in that alternative universe? People there don't buy life insurance.
I suppose you might panic, but saying the models are wrong doesn't make me panic, because it appears the situation is much better than predicted.
I don't suppose anybody believes the lies, but we also don't believe you've stopped beating your wife. (Hint: presupposition failure.)
No, a theory (much less a hypothesis) need not have fully specified parameters; a model is based on a theory, but must have specified parameters. In practice, you run lots of models, and pick one that closely fits some set of observations.
The _theory_ that the Earth's average temp should go up with increasing CO2 is largely accepted, even by most skeptics. At question are some of the parameters that determine how much it will go up. Not the opacity of CO2 to IR (that can be measured in a lab); but by itself, that produces a rather small temp increase. Less well known are some of the feedbacks, and different values for those result in widely different temp responses.
Oh great resources WERE mustered in third world countries.
I was one of them, and I live in a third world country.
Unicode killed the ASCII-art *
I suppose you might panic, but saying the models are wrong doesn't make me panic, because it appears the situation is much better than predicted.
Feel free to point us to a reputable journal is which you've published your analysis of the present situation, including. specifically how you extrapolated from current observations to a prediction of future events.
I don't suppose anybody believes the lies,
That's quite possible.
I've engaged in conversations where denialists make an assertion, and when rebutted, come back a few days later and make the same assertion again. It's impossible to exhibit those behavioural traits without deliberately concealing that you know you are wrong.
You're right : it's quite possible that no denialist actually believes the basic assertions of denialism.