Yes, we inevitably see these evidence-free claims of intentional shortages, but it almost never makes economic sense for the manufacturer. The release date is likely to be a balance between producing enough product to meet your most optimistic projections, and getting the product onto the market in a timely manner. Internet pre-sales are not even a particularly good way to build buzz. In fact, there were news reports last time around along the lines of "iPhone 4 released to short lines" because most of the sales were pre-orders, giving customers no reason to join long lines out of concern that stocks would run out. If Apple really wanted to generate buzz, they wouldn't have had pre-orders at all, but made everyone line up on release day where the world could see them. Apple did this with the iPad2, but the iPhone is an established market. Apple doubtless had a good idea that there was enough pent-up demand to sell as many units as they'd managed to build (even if the pundits hadn't managed to figure it out).
Then tell me this, how would you discern between something acting as a feedback, and something acting as a forcing. Be specific.
"Feedback" vs. "forcing" is not something that is written into the models, but rather a qualitative description of the way it behaves, based upon its fundamental physics (which is what the models are based upon). An explanation of what the terms mean may be found here.
Yes, there *is* a correlation between temperature and CO2, and the historical record clearly shows CO2 changing *after* temperature. It is a novel assumption that suddenly, this behavior has changed, and as for causality, until you get a time machine, causes have to come before effects:)
This is nonsense. In physical systems, it is most commonly observed that coupling is two way. Like a see-saw. Which is cause and which is effect, the left side of the see-saw or the right side of the see-saw? Does the right side go up because you are pushing down on the left side, or does the left side go down because you are pushing up on the right side? It depends upon what the forcing is (which side you are pushing on). Has the fundamental behavior of a see-saw changed depending upon what side you pushed upon? Perhaps to a cargo cult scientist, it might seem so.
In climate models, the linkage between CO2 and temperature emerges naturally from the fundamental physics: either can lead, depending upon which side you are "pushing" on. If you push on the CO2 side, by adding CO2 to the atmosphere (from a temperature-independent source) then temperature subsequently follows by rising. If you push on the temperature side (by adding energy by a mechanism not dependent on CO2, such as an increase in solar radiation then temperature, then CO2 will follow by rising. This has been explained to you before. Which part of it do you not understand?
Note that this has nothing to do with "null hypotheses." Once you acknowledge that there is a correlation of any kind between CO2 and temperature, the null hypothesis has been rejected. A hypothesis about why there is a correlation cannot be can never be a null hypothesis. So if you want to propose that there is a "natural" mechanism that can account for these changes, you face the same challenges that climate scientists have met: develop a physically realistic model, show that it is consistent with historical data, test it by observation.
One does not need a competing model to demonstrate problems with an existing one.
No model is perfect. That's why we call them "models." The question is whether it is good enough to make useful predictions. For example, our soldiers calculate their trajectories using a physical model that has problems--it uses incorrect equations that do not properly deal with relativity. Yet it turns out that these problems are inconsequential with respect to targeting artillery shells. So nitpicking a model is easy to do, but has little scientific value--the challenge is to criticize a model in a meaningful way. That's why real scientists (unlike cargo cult scientists) always think in terms of competing models. To criticize a model in a scientifically meaningful way, you have to show that the "problem" that you have imagined that you have identified actually makes a difference in the conclusions. How do you do that? Fix the problem, and show your improved models is superior in terms of its ability to predict the results of real-world observations.
What you're proposing here is cargo cult science, with the demand that unless I can create a better model than the coconut radio transmitters and the bamboo landing fields, that I have no right to insist that you're barking up the wrong tree.
And indeed, that's one way we know that the coconut radio transmitters and bamboo landi
You keep saying that, but it doesn't make it any more true. GCMs are programmed with the basic assumption that CO2 drives global average temperature, more specifically through assumed feedback effects on water vapor (which is a much stronger greenhouse gas). I welcome you to show me any existing GCM which does not assume this.
Feedback effects of are not "assumed," but are based upon established physical properties of CO2 and water, such as the effect of temperature on CO2 solubility and evaporation of water.
You're really stretching yourself thin here. The null hypothesis is the assertion that there is no relationship (causal or otherwise) between to things. It is not the "zero hypothesis".
Yes it is: The "no relationship" hypothesis is that the derivative dy/dx = 0 (where x and y are two different measurements) . Nothing to do with causality--simply that a plot of y vs. x has a true slope of zero. Of course, if the slope is zero, then there is no evidence upon which to base a causal hypothesis relating x to y. But the converse is not true: a nonzero slope does not establish a causal relationship. In the case of CO2 and temperature, the null hypothesis of zero slope is readily excluded by simple statistics. There is a correlation between temperature and CO2; the question is why. For this question of causality, there is no null hypothesis, because the null hypothesis has already been excluded.
Pray tell, what would the "zero hypothesis" of "smoking causes lung cancer" be? That there is no difference between the measurement of smoking and the measurement of lung cancer?
I've answered this question before. Did you miss it? Of course, there is no null hypothesis about "smoking causes cancer," because null hypotheses apply only to statistics, and statistics does not address questions of causality. But there are certainly null hypotheses that can be formulated regarding the relationship between smoking and cancer. Examples would be: "There is zero difference in the incidence of lung cancer in smokers and nonsmokers" or (for more quantitative data regarding smoking) "the derivative dy/dx (where y is the incidence of lung cancer and x is the number of cigarettes smoked)" is equal to zero."
Again, you're not fighting with a competing model here, you're competing with the null hypothesis that there is no causal relationship between CO2 and global average temperature. Trying to put your model above strict scrutiny is clever, but not convincing.
Again, you are back to special pleading based upon your failure to understand that a question of causality cannot be a null hypothesis. The null hypothesis of no statistical relationship between temperature and CO2 is excluded. A causal model, whether "natural" or otherwise, must indeed be subject to strict scrutiny--which means you must do what climate scientists have done (and what the self-styled "skeptics" have so far failed to do): define a specific model of climate that makes definite predictions, and carry out observations to test those predictions.
You lie like a dog. Throughout this entire conversation, you have completely been unable to make any specific statement of what observation of CO2 and global average temperature, on any time scale, would falsify your hypothesis. Having a mathematical model that cannot hind cast such events as the MWP, or LIA, or Holocene optimum, much less forecast within any sort of error range, is no great feat.
There have been numerous papers published on the quality of hindcasts from the models (a good summary can be found in the IPCC report)--but you are hardly equipped to criticize the quality of those hindcasts unless you can offer a model that does a better job. Once again,
Which essentially is an admission that the underlying, basic assumption, that CO2 drives global average temperature, is not falsifiable in GCMs.
For about the fifth time, it is not assumed that CO2 drives global average temperature. That is a conclusion, not an assumption. The assumptions are with respect to things like thermodynamics or the fundamental physics of CO2. These are potentially falsifiable, but it's not even remotely likely--it's in the category of "If things start falling up, then gravity will be falsified." So what could be falsified are the details--how fine-grained the model needs, how it deals with things like ocean currents and clouds, etc. In a model of a complex system, there is always potentially room for improvement.
"For example, the null hypothesis might be that there is no relationship between two measured phenomena or that a potential treatment has no effect."
Yes, this simply rephrases what I told you: "Null" means "zero" and the null hypothesis is the hypothesis of zero difference between two measurements. Note the word "cause" does not appear. So burn it into your brain so you don't sound ridiculous when you talk to actual scientists: A hypothesis about causes cannot be a null hypothesis
kPrecautionary principle fallacy. You have no idea whether or not your prescribed mitigations are going to cause more harm than good, and it's arguable that we already know they will cause more harm than good.
Actually, the argument you are making is an expression of the precautionary principle: if you can think of a bad outcome, no matter how unlikely, then you cannot act. This has always been my objection to the precautionary principle: ultimately, it is a prescription for paralysis--because if you are imaginative enough, one can always imagine some sort of scenario whereby things can go wrong. But there are many circumstances in life in which doing nothing can carry oven greater hazard than the risk of doing the wrong thing. So if you are headed for what looks very much like a cliff, it makes sense to jump out of the wagon, rather than tell yourself "Well, maybe the cliff is not as sheer as it looks, and I could sprain my ankle if I jump." In other words, we always have imperfect information, and we are often obliged to act on the best current knowledge. There is no guarantee that it will always yield the best outcome, but that way gives you the best odds.
Natural warming isn't magical, it's *natural*. Put another way, do you deny that natural warming happened in the past, without the benefit of humanity's existence and without a specified mechanism? Or can you explain every single climate change that ever happened in the past down to a specific mechanism?
An effect without a cause isn't natural, it is magical. In nature, effects have causes. Modern climate science accounts for past warming episodes in terms of causes (and as you've been told repeatedly, but still apparently fail to comprehend, there are multiple potential causes of warming considered by climate theory), but none of those causes are applicable to the current warming. If it's natural, it must have a cause--so what is it? What is your model? What testable predictions does it make?
Actually, your model needs to account for two things: it must explain why CO2 is not producing the warming predicted from basic physics, and it must come up with some other mechanism that is coincidentally producing warming similar to that predicted based upon knowledge of the physics of CO2
If you want to follow the money, the warmist industry stands to face substantial costs if the CO2 to global average temperature link is either not accurate, or not
If your scientific model predicts something specific regarding increased human CO2 emissions, and the resultant average atmospheric temperature over a specific period of time, and gives us some error bars, what are you going to say when reality diverges from your predictions? Will you abandon your model entirely, or insist on a never ending stream of ad hoc special pleadings?
Global Climate Models are based upon known physics, so no, if in the future the models diverge from prediction, as they have not done so far, scientists will not say, "Well, I guess we were wrong about the First and Second Laws of Thermodynamics, so we'll throw those out and start over." Rather, if discrepancies are found, the models will be improved to model the underlying physics with greater accuracy and detail.
You're completely misunderstanding the null hypothesis - it is not the "no change" hypothesis. Let's say you have a hypothesis "smoking causes lung cancer". The null hypothesis is not "there is no change in smoking" or "there is no change in lung cancer". The null hypothesis is "there is no causal relationship between smoking and lung cancer".
Don't try to teach your grandmother how to suck eggs. You are engaging in what Richard Feynman referred to as "cargo cult science", trying to sound "sciencey" and gain credibility by using scientific jargon the you don't understand. But these scientific terms have actual meanings. "Null hypothesis" has a very specific and unambiguous meaning in science--it is the hypothesis of "no change" or "zero difference." That's what the word "null" in "null hypothesis" means: zero. So the null hypothesis with respect to smoking and cancer is: "there is zero difference in the incidence of cancer between smokers and nonsmokers." Note that there is no mention of "cause." The concept of "null hypothesis" belongs exclusively to statistics, which does not address causality. Thus, any statement with the word "cause" in it cannot be a null hypothesis.
As Feynman writes, "The first principle is that you must not fool yourself--and you are the easiest person to fool." Scientific disciplines such as mathematical modeling and statistics were developed to help scientists protect themselves against the natural human vulnerability to wishful thinking and self-deception.
You are also mistaken in imagining that "GCM models which start with the assumption that CO2 drives global average temperature." In fact, GCMs start out by simulating the basic underlying physics. The conclusion that increasing CO2 would result in an increase in temperature was a prediction of these models, not a starting assumption. And in fact, the models indicate that many things can drive changes in global average temperature: changes in the earth's orbit, changes in other greenhouse gasses, changes in the sun's energy output. At this point, scientists have had to step away from the models and look at the real world to see what is actually changing: the earth's orbit hasn't changed; other greenhouse gasses have not increased enough to account for the warming; the sun's output hasn't changed; ENSO/PD has been around for a long time--there is no evidence that it has changed (even if there were some plausible mechanism whereby it could produce long-term warming, which there isn't).
Prove me wrong by succinctly stating what observations of CO2 and global average temperature, over any time period you'd like to specify, would overturn the assumption that CO2 drive global average temperature.
The models predicted the modern warming before it happened. But of course, one can always say, "That's not good enough, what if it stops warming tomorrow, and the temperatures 100 years from now are the same as today?" Similarly, one could be a gravity skeptic, and say "What if objects stopped falling tomorrow? Wouldn't that disprove gravity?" And I suppose it would-
So if I found a rapid change in CO2 levels without a change in the earth's orbit or solar output (say, 280ppm - 380ppm over 1000 years) in the historical record, you'd admit your hypothesis is falsified?
No, obviously not, because there might be some other mechanism whereby CO2 could be released by natural sources--some sort of extraordinary period of intense volcanism, perhaps. But if there were a massive release of CO2 without warming, that would certainly falsify the hypothesis. However, given the massive amount of evidence already available to support the impact of CO2 on climate, that's a pretty thin straw to cling to, a bit like asking, "If I found a kind of rock that always falls up, would that falsify the theory of gravity?"
Well, I'll through out the Late Eocene for you - without a great difference in solar output or orbital variation, ocean currents (which carry orders of magnitude more heat content than our atmosphere) made a veritable temperate paradise out of Antarctica. Changes in ocean currents have led to the seasonality we currently experience at various latitudes.
Ocean currents move heat around, so it is possible to get warming in one area at the expense of another. That's why the theory's prediction is about the globally averaged temperature, which reflects the overall energy balance.
We already have fairly good science on El Nino and La Nina dramatically affecting global average temperature
Energy can take many forms, but from basic thermodynamics, we know that it all ultimately must end up as heat. So the model allows (and indeed predicts) short term fluctuations in temperature. The prediction of global warming is on a multi-decade time scale. So, obviously, observing short term fluctuations such as El Nino, which are in fact seen in global climate models, is not a challenge to the theory.
Looking over your list of predictions, I'll note that none of them seem to predict a specific level of CO2 and a specific temperature
Yes, this is a common crank objection to genuine science, one that has been applied to fields as diverse as climate science and quantum mechanics: "If your model can't predict what I want it to predict, then it must be wrong." But testing of scientific models does not require that a model be able to predict everything, merely that it makes testable predictions. This is something that climate science has done with flying colors. Meanwhile the vague hand-waving notions of "natural variation" cited by the self-styled critics have been unable to predict anything, and when challenged, they fall back upon special pleading: "It's not a theory, it's just a 'null hypothesis' (never mind that that makes no sense) so I don't have to subject it to the standard scientificdiscipline of creating a mathematical model that makes actual testable predictions."
Why do you consider AGW/CAGW the null hypothesis?
I don't. No actual scientist would make such a claim. As I've explained to you several times, a physical model such as AGW cannot be a null hypothesis. The term "null hypothesis" is only meaningful in the context of statistics and statistical models, and has a well-defined meaning, so nobody gets to choose what is the null hypothesis. The null hypothesis is the hypothesis of no change--and nobody seems to be crazy enough to claim that climate is unchanging.
AGW has more credibility with the scientific community not because it has some sort of nonsensical privileged "null model" status, but rather because it has been subjected to the standard scientific disciplines of "sanity checking" that any credible theory must conform to: it has been implemented in mathematical form consistent with known physics to derive definitive mathematical predictions, and those predictions have been tested against observation, yielding dramatic confirmation (of which the prediction of the modern warming trend before it occurred is just one). Here, once again, are some of the successful predictions of climate theory: http://bartonpaullevenson.com/ModelsReliable.html
I'l take that one further - the project increase in average temperature over the next 50 - 100 years is much smaller than the natural variance of annual average temperature
I'm skeptical, particularly since there is no single projection, but rather a series of scenarios depending upon how successful we are at controlling CO2. Over a single year, the difference between them is negligible, but over 100 years, it can make quite a bit. Please explain what specific model or models and scenarios you used for your projection (with appropriate citations), and describe (or provide a citation to) how the variance of annual temperature was calculated.
And considering that a loss of $10 per unit could add up to substantial cost to Amazon when multiplied by millions of sales, while cutting the price by $10 will not sell appreciably more units relative to selling them at cost, it would be crazy for Amazon to sell them just $10 below cost.
Yes, this is clearly within error of break-even. Amazon is not going to sell appreciably more phone by taking a $10 loss per phone, so why do it? And since the main goal is not to make money on the hardware, but rather to sell Amazon's other products and contents, selling the tablet essentially at cost makes the most sense.
I think that he's an extremely good author. "Dying of the Light" was a very impressive novel. "Fever Dream" is also very strong. And the Wild Cards series was a lot of fun. I generally don't get into medievalist fantasy, but I've been impressed with the GoT series: it is intricately plotted and not predictable, with convincing characters who have some emotional depth. Considering how slowly the larger plot arc advances, I'm wondering if he plans for it so support him for the rest of his life (not that I begrudge him that; I'm just worried that he'll die and leave it unfinished). His prose isn't flashy or particularly poetic, but it conveys vivid images and is not repetitive. His dialog is good (as evinced by the fact that it works on the screen as well as on the page; a lot of written dialog sounds foolish when spoken by a live person).
As far as being a "sell out," if that's what he's done, it's on the best terms I've ever seen. The TV series was the most careful and faithful adaptation of a fantasy novel that I've encountered to date. It is virtually a scene by scene adaptation. The sets and costumes are pretty much exact. I've only seen one issue of the comic book, but it looks like the same will hold there. Either he has found adapters who genuinely respect his work, or else he has gotten a great deal of creative control. Writing can be a chancy living, and most writers, particularly of genre fiction do not make a great deal of money. Martin has been at it a long time, it seems terribly petty to begrudge him taking advantage of an opportunity to profit from his work.
Unsupportable assertion - expanding water can be a good thing. The assertion that any expansion of water, no matter how minuscule, is a problem is completely unfounded.
Obviously, there are some people who already live very close to the water line, for whom any increase in ocean level whatsoever will be a problem, even somebody else happens benefit (perhaps Al Gore's house in the hills of Montecito will increase in value by virtue of becoming oceanfront property).
The null hypothesis is that there is no causal relationship for a given factor
Sorry, but that's scientific gibberish. Read up on statistics. The null hypothesis has nothing to do with causal relationships. "Null" means one thing, and one thing only: it is the hypothesis that there is no difference in the true value of two measurements that are subject to error. Any hypothesis other than that cannot be considered a null hypothesis. The term has no meaning whatsoever in any other area of science.
Are you listening to yourself? You're putting *your* faith in GCMs
I am not impressed by self-styled skeptics who have subjected their ideas to the discipline of mathematical modeling. I am not impressed by those who dismiss the careful modeling of others, and yet have consistently failed to create a model of their own that is consistent with observational data and does not predict warming. And I am even less by those who try to excuse their failing by the statistically illiterate insistence that their ideas are a "null hypothesis" and therefore exempt from the type of scrutiny to which real scientists subject their scientific hypotheses.
Make a testable prediction for what the CO2 and temperature level will be like next year, and include your error range.
If I had a casino, I'd love to have you for a customer. If a mathematician told you, "You know, the roulette wheel is statistically weighted in favor of the house, and you will lose your money if you keep playing," you would doubtless insist, "Well if you think you know so much, make a testable prediction on the outcome of the next spin," and keep playing.
Climate models do not purport to accurately predict the temperature next year--or to put in in statistical terms, the projected increase in average temperature next year is much smaller than the variance of annual average temperature.
Let's ask this question explicitly then - is the modern industrial era the only period of time that includes the introduction of CO2 from a temperature independent source? If not, can you cite an example in the historical record?
No. It looks like the huge, rapid introduction of CO2 into the atmosphere without any change in the earth's orbit or solar output is without precedent, at least over the period of time for which we have good evidence.
False dichotomy - there are dozens of other factors that could be affecting temperature without resorting to the sun's output on specific wavelengths, or the earth's orbit.
Like what? Ultimately, thermodynamics tells us that the earth's temperature must be determined by the rate at which the earth absorbs energy from the sun and the rate at which it radiates energy to space. Nobody has found any changes in factors that could affect these, aside from atmospheric CO2.
You're mixing things up there a bit, so let's be clear - there may be models which predict increased warming as a result of human CO2 releases. None of these models predicts that this is a *problem* - that's a subjective and speculative judgement.
When you've got a lot of people living next to an ocean made of a substance (water) that expands when it is heated, you clearly have a problem, although perhaps you could debate how bad a problem it is.
Second of all, again, you're not fighting a competing model - you're fighting the null hypothesis that there is not a causal relationship between CO2 levels and temperature levels.
Once again, you don't understand what a null hypothesis is. "Null hypothesis" is not some sort of magic incantation you can intone to exempt your own favored hypothesis regarding what does or does not cause what from the normal requirements that a scientific theory be physically realistic and make testable predictions. You can't have a null model that says anything, positive or negative about causality, because the null hypothesis belongs exclusively to statistics, and statistics is inherently incapable of addressing questions of causality--it is entirely about correlation. So the only null models you can have are that temperature and/or CO2 are not changing with time. But the existing data is adequate to exclude the null model.
At this point the null model is dead. That's the only null hypothesis there is; you don't get another one. If you want to make a credible hypothesis that there is no causal relationship between temperature and CO2, you need to show that such a hypothesis makes sense: that is physically realistic, and that it is consistent with the observational and experimental data.
Apparently we now predict periods of cooling during warming "hiatus"
There is no "apparently" about it. The models, which incorporate the weather mechanisms of moving energy around, do indeed predict that there will be periods of limited duration when the warming trend is undetectable. This is not some sort of special exemption afforded to climate theory--it is a universal statistical property of measuring trends in the presence of noise (which is pretty much everything in the real world). Global warming "skeptics" are fond of looking at each little fluctuation and crying, "The warming trend is stopping!", much like the gambler who wins a hand or two and is convinced that his luck has turned. But just as the trend in temperature is inexorably up (even if weather fluctuations can obscure that for a few years), the casino may lose a game or two, or even have a losing day, but if you keep gambling, they will eventually get your money.
How does the CO2 know which one it is? You're asserting a tautology that is unfalsifiable.
That's kind of a silly objection. Obviously, the CO2 doesn't need to know anything. If I tell you that you can turn a wheel by pushing the top of the wheel forward or the bottom of the wheel backwards, do you ask, "How does the wheel know which one it is?" Equally obviously, it is not unfalsifiable, because it makes definite predictions. If warming leads CO2, then there should evidence of a change in some other factor that influences the energy balance of the earth, such as the earth's orbit or energy output by the sun. If CO2 leads warming, then there must be introduction of CO2 from a new, temperature-indpedent source. Both predictions are satisfied when it comes to ancient and modern climate change. For example, in the modern era, we know that temperature is not increasing due to changes in the sun's output or the earth's orbit, because the sun's output has been measured and shown not to change.
If you can come up with half a dozen models that reasonably hind cast, and share fairly similar forecasts, but have *wildly* differing base assumptions about climate sensitivity, you've already shown that it is possible to have wildly different models spit out the same tuned results:)
Yet nobody has been able to come up with such a model that does not predict a problem with future warming as a result of CO2 increase. What this suggests is that none of the models is absolutely perfect (but then again, no model is), but that to be able to do a good job in hind casting, the errors have to cancel out, and this may happen in a somewhat different way in different models. In other words, the necessity to be consistent with the temperature record imposes a powerful constraint on model structure, and models that do not predict future warming cannot satisfy this constraint. Again, it would be easy to disprove this: just show me a model that can hind cast and that does not predict future warming.
Again, the fatal flaw with these models is that they brook no falsifiability - every observation of future climate can simply be dispensed with by an ad hoc special pleading.
Some of the tests of the models can be found here. Again, if the models are so adjustable that they can predict whatever you choose, why has no critic been able to come up with a model that passes the hindcast test and does not predict troublesome warming?
A very key point - which makes reconciling the observed ice core record and CO2 lag of temperature difficult to refute. CO2 doesn't care where it came from, so to assume that it will drive temps now when it lagged temps before is a novel conclusion.
Not at all. Because of the two-way relationship between temperature and CO2, the models predict that CO2 will lead when warming is initiated by increased release of CO2, and that it will lag when warming is initiated by other factors such as changes in solar radiance or changes in earth's orbit. As this is exactly what is observed, this provides strong support of the theory.
...that after 150 years AGW theorists would actually be able to provide some *proof*....
Absolute proof exists only in mathematics, not science. Scientific proof is testing and confirming the predictions of a theory, and so far climate theory has done pretty well. See here for some of the tests of climate theory.
A hypothesis which predicts every possible observation doesn't predict anything very useful.
Agreed. But the claim that this is true of climate models has no substance. While it seems to be an article of faith among self-styled skeptics that the models can predict whatever you choose, none of them have ever been able to provide any evidence to support this claim. The climate models are published; anybody can formulate their own or use one of the existing models. So if you believe that the hypothesis predicts every possible observation, there is a simple way to substantiate that claim:
Take one of the models, tweak the the parameters in any physically plausible way that you please, and show that you can come up with a version of the model that is consistent with the known climate record, and which does not predict warming.
No, it means no relationship. The AGW/CAGW hypothesis asserts that there is a causal relationship between human emitted CO2 and global average temperature. The null hypothesis is that there is no such relationship, and that temperature can change independent of the CO2 (i.e., temperature fluctuates by natural mechanisms, and is not tied to human CO2).
Not quite. AGW is a prediction of models of overall climate, one that long predates the modern massive CO2 increase. These don't distinguish between "human emitted" and "natural" CO2, because that would be absurd. CO2 is CO2--the chemical properties of CO2 do not change dependent upon where it comes from. A role for CO2 is an integral part of climate models--nobody has been able to come up with any model consistent with temperatures at any point in the earth's history without including a role for CO2.
Statistics (which is the only realm in which the concept of a null hypothesis is meaningful) of course cannot answer questions of causality; the most it can do is ask whether or not there is a correlation. And again, there is no doubt about whether there is a correlation between average global temperature and CO2--the unequivocal answer is that there is a correlation and it is statistically significant, so the null hypothesis of no relationship is excluded.
Of course, correlation does not necessarily imply causality. To turn to the questions of causality, one has to turn to physics. And here, there are known mechanisms whereby temperature and CO2 can interact, although as is commonly the case, the interaction is two-way--i.e. changes in temperature alter CO2, and changes in CO2 alter temperature. It was this understanding of the physics that made it possible for scientists to predict AGW before it occurred.
So if you want to come up with a model in which adding more CO2 to the atmosphere does not affect temperature, you have a very different problem, because as I noted, nobody has ever managed to come up with a physically realistic model that comes anywhere close to being consistent with temperatures, either in the the past or today, that does not predict that our adding additional CO2 to the environment will lead to an increase in average temperatures.
You're not fighting a competing theory, you're fighting the null hypothesis of natural climate change.
It sounds like you don't understand what a "null hypothesis" is. Some people seem to think that by declaring their own hypothesis the "null hypothesis," they automatically get a pass on the normal requirement to substantiate your hypothesis with plausible mechanisms and testable predictions. In reality, "null hypothesis" is a term from statistics, and it has nothing to do with mechanism. The "null hypothesis" specifically refers to the hypothesis of no change . So to talk about a "null hypothesis of natural climate change" is an oxymoron. The actual null hypothesis that climate does not ever change is readily excluded by fairly simple statistics. Once you are hypothesizing a change, natural or otherwise, then you do not have a null hypothesis--and you need to support your hypothesis in the scientific way: formulate a physically realistic model, describe it mathematically, and test it for consistency with observations.
You want to falsify the climate models? Build a better model that proves your theory, and have it pass peer review. The ball, as they say, is in your court on that one.
It is an article of faith among many self-defined "skeptics" that climate models have so many free parameters that they can be tuned to show whatever you want. Yet even though several of these models are publicly available, no skeptic has ever managed to find a way to "tune" such a model such that it is consistent with the record of past climate, and yet does not predict substantial future warming.
To scientists, modeling is a discipline, a way of "sanity-checking" your ideas. It's easy to wave your hands and insist that something will or won't happen, but if the math doesn't work out, you are out of luck. So far, the skeptics have failed to pass the sanity check.
Whether you agree or disagree with their point of view, Skeptical Science is valuable because it is well documented, providing citations to the original literature where you can check to see whether the statements are accurate and whether the alleged strawmen are actually made of straw.
Except that in practice, with class action suits over consumer devices, it makes no difference whatsoever whether there is any actual merit to the suit. The company always settles anyway, because it's cheaper than going to court. So it's not a punishment or deterrent for anything--just legal extortion, and for the manufacturer, merely part of the cost of doing business. End the end, the cost is footed by the consumer in the form of higher prices. Nobody benefits from such suits but lawyers
Class action suits over consumer products are a lawyer scam. It doesn't much matter whether the alleged product flaw is real or not. The lawyer makes a lot of noise in the media and sues for a ridiculous amount of money, then offers to settle for less than it would cost the company to defend itself in court. The company settles--after all, defending itself in court would just generate more news reports and extend the bad publicity for months, and even if they won, would end up cost them more money than the settlement. All the "members of the class" get a piddly settlement, like a gift certificate for more of the company's products, that is barely even decent compensation for the time it took them to fill out the paperwork. But the lawyer gets a slice of all of those piddly settlements which add up to a nice chunk of change--all for no work other than giving a few press conferences and sending a few letters.
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Yes, we inevitably see these evidence-free claims of intentional shortages, but it almost never makes economic sense for the manufacturer. The release date is likely to be a balance between producing enough product to meet your most optimistic projections, and getting the product onto the market in a timely manner. Internet pre-sales are not even a particularly good way to build buzz. In fact, there were news reports last time around along the lines of "iPhone 4 released to short lines" because most of the sales were pre-orders, giving customers no reason to join long lines out of concern that stocks would run out. If Apple really wanted to generate buzz, they wouldn't have had pre-orders at all, but made everyone line up on release day where the world could see them. Apple did this with the iPad2, but the iPhone is an established market. Apple doubtless had a good idea that there was enough pent-up demand to sell as many units as they'd managed to build (even if the pundits hadn't managed to figure it out).
"Feedback" vs. "forcing" is not something that is written into the models, but rather a qualitative description of the way it behaves, based upon its fundamental physics (which is what the models are based upon). An explanation of what the terms mean may be found here.
This is nonsense. In physical systems, it is most commonly observed that coupling is two way. Like a see-saw. Which is cause and which is effect, the left side of the see-saw or the right side of the see-saw? Does the right side go up because you are pushing down on the left side, or does the left side go down because you are pushing up on the right side? It depends upon what the forcing is (which side you are pushing on). Has the fundamental behavior of a see-saw changed depending upon what side you pushed upon? Perhaps to a cargo cult scientist, it might seem so.
In climate models, the linkage between CO2 and temperature emerges naturally from the fundamental physics: either can lead, depending upon which side you are "pushing" on. If you push on the CO2 side, by adding CO2 to the atmosphere (from a temperature-independent source) then temperature subsequently follows by rising. If you push on the temperature side (by adding energy by a mechanism not dependent on CO2, such as an increase in solar radiation then temperature, then CO2 will follow by rising. This has been explained to you before. Which part of it do you not understand?
Note that this has nothing to do with "null hypotheses." Once you acknowledge that there is a correlation of any kind between CO2 and temperature, the null hypothesis has been rejected. A hypothesis about why there is a correlation cannot be can never be a null hypothesis. So if you want to propose that there is a "natural" mechanism that can account for these changes, you face the same challenges that climate scientists have met: develop a physically realistic model, show that it is consistent with historical data, test it by observation.
No model is perfect. That's why we call them "models." The question is whether it is good enough to make useful predictions. For example, our soldiers calculate their trajectories using a physical model that has problems--it uses incorrect equations that do not properly deal with relativity. Yet it turns out that these problems are inconsequential with respect to targeting artillery shells. So nitpicking a model is easy to do, but has little scientific value--the challenge is to criticize a model in a meaningful way. That's why real scientists (unlike cargo cult scientists) always think in terms of competing models. To criticize a model in a scientifically meaningful way, you have to show that the "problem" that you have imagined that you have identified actually makes a difference in the conclusions. How do you do that? Fix the problem, and show your improved models is superior in terms of its ability to predict the results of real-world observations.
And indeed, that's one way we know that the coconut radio transmitters and bamboo landi
Feedback effects of are not "assumed," but are based upon established physical properties of CO2 and water, such as the effect of temperature on CO2 solubility and evaporation of water.
Yes it is: The "no relationship" hypothesis is that the derivative dy/dx = 0 (where x and y are two different measurements) . Nothing to do with causality--simply that a plot of y vs. x has a true slope of zero. Of course, if the slope is zero, then there is no evidence upon which to base a causal hypothesis relating x to y. But the converse is not true: a nonzero slope does not establish a causal relationship. In the case of CO2 and temperature, the null hypothesis of zero slope is readily excluded by simple statistics. There is a correlation between temperature and CO2; the question is why. For this question of causality, there is no null hypothesis, because the null hypothesis has already been excluded.
I've answered this question before. Did you miss it? Of course, there is no null hypothesis about "smoking causes cancer," because null hypotheses apply only to statistics, and statistics does not address questions of causality. But there are certainly null hypotheses that can be formulated regarding the relationship between smoking and cancer. Examples would be: "There is zero difference in the incidence of lung cancer in smokers and nonsmokers" or (for more quantitative data regarding smoking) "the derivative dy/dx (where y is the incidence of lung cancer and x is the number of cigarettes smoked)" is equal to zero."
Again, you are back to special pleading based upon your failure to understand that a question of causality cannot be a null hypothesis. The null hypothesis of no statistical relationship between temperature and CO2 is excluded. A causal model, whether "natural" or otherwise, must indeed be subject to strict scrutiny--which means you must do what climate scientists have done (and what the self-styled "skeptics" have so far failed to do): define a specific model of climate that makes definite predictions, and carry out observations to test those predictions.
There have been numerous papers published on the quality of hindcasts from the models (a good summary can be found in the IPCC report)--but you are hardly equipped to criticize the quality of those hindcasts unless you can offer a model that does a better job. Once again,
For about the fifth time, it is not assumed that CO2 drives global average temperature. That is a conclusion, not an assumption. The assumptions are with respect to things like thermodynamics or the fundamental physics of CO2. These are potentially falsifiable, but it's not even remotely likely--it's in the category of "If things start falling up, then gravity will be falsified." So what could be falsified are the details--how fine-grained the model needs, how it deals with things like ocean currents and clouds, etc. In a model of a complex system, there is always potentially room for improvement.
Yes, this simply rephrases what I told you: "Null" means "zero" and the null hypothesis is the hypothesis of zero difference between two measurements. Note the word "cause" does not appear. So burn it into your brain so you don't sound ridiculous when you talk to actual scientists: A hypothesis about causes cannot be a null hypothesis
Actually, the argument you are making is an expression of the precautionary principle: if you can think of a bad outcome, no matter how unlikely, then you cannot act. This has always been my objection to the precautionary principle: ultimately, it is a prescription for paralysis--because if you are imaginative enough, one can always imagine some sort of scenario whereby things can go wrong. But there are many circumstances in life in which doing nothing can carry oven greater hazard than the risk of doing the wrong thing. So if you are headed for what looks very much like a cliff, it makes sense to jump out of the wagon, rather than tell yourself "Well, maybe the cliff is not as sheer as it looks, and I could sprain my ankle if I jump." In other words, we always have imperfect information, and we are often obliged to act on the best current knowledge. There is no guarantee that it will always yield the best outcome, but that way gives you the best odds.
An effect without a cause isn't natural, it is magical. In nature, effects have causes. Modern climate science accounts for past warming episodes in terms of causes (and as you've been told repeatedly, but still apparently fail to comprehend, there are multiple potential causes of warming considered by climate theory), but none of those causes are applicable to the current warming. If it's natural, it must have a cause--so what is it? What is your model? What testable predictions does it make?
Actually, your model needs to account for two things: it must explain why CO2 is not producing the warming predicted from basic physics, and it must come up with some other mechanism that is coincidentally producing warming similar to that predicted based upon knowledge of the physics of CO2
Global Climate Models are based upon known physics, so no, if in the future the models diverge from prediction, as they have not done so far, scientists will not say, "Well, I guess we were wrong about the First and Second Laws of Thermodynamics, so we'll throw those out and start over." Rather, if discrepancies are found, the models will be improved to model the underlying physics with greater accuracy and detail.
Don't try to teach your grandmother how to suck eggs. You are engaging in what Richard Feynman referred to as "cargo cult science", trying to sound "sciencey" and gain credibility by using scientific jargon the you don't understand. But these scientific terms have actual meanings. "Null hypothesis" has a very specific and unambiguous meaning in science--it is the hypothesis of "no change" or "zero difference." That's what the word "null" in "null hypothesis" means: zero. So the null hypothesis with respect to smoking and cancer is: "there is zero difference in the incidence of cancer between smokers and nonsmokers." Note that there is no mention of "cause." The concept of "null hypothesis" belongs exclusively to statistics, which does not address causality. Thus, any statement with the word "cause" in it cannot be a null hypothesis.
As Feynman writes, "The first principle is that you must not fool yourself--and you are the easiest person to fool." Scientific disciplines such as mathematical modeling and statistics were developed to help scientists protect themselves against the natural human vulnerability to wishful thinking and self-deception.
You are also mistaken in imagining that "GCM models which start with the assumption that CO2 drives global average temperature." In fact, GCMs start out by simulating the basic underlying physics. The conclusion that increasing CO2 would result in an increase in temperature was a prediction of these models, not a starting assumption. And in fact, the models indicate that many things can drive changes in global average temperature: changes in the earth's orbit, changes in other greenhouse gasses, changes in the sun's energy output. At this point, scientists have had to step away from the models and look at the real world to see what is actually changing: the earth's orbit hasn't changed; other greenhouse gasses have not increased enough to account for the warming; the sun's output hasn't changed; ENSO/PD has been around for a long time--there is no evidence that it has changed (even if there were some plausible mechanism whereby it could produce long-term warming, which there isn't).
The models predicted the modern warming before it happened. But of course, one can always say, "That's not good enough, what if it stops warming tomorrow, and the temperatures 100 years from now are the same as today?" Similarly, one could be a gravity skeptic, and say "What if objects stopped falling tomorrow? Wouldn't that disprove gravity?" And I suppose it would-
No, obviously not, because there might be some other mechanism whereby CO2 could be released by natural sources--some sort of extraordinary period of intense volcanism, perhaps. But if there were a massive release of CO2 without warming, that would certainly falsify the hypothesis. However, given the massive amount of evidence already available to support the impact of CO2 on climate, that's a pretty thin straw to cling to, a bit like asking, "If I found a kind of rock that always falls up, would that falsify the theory of gravity?"
Ocean currents move heat around, so it is possible to get warming in one area at the expense of another. That's why the theory's prediction is about the globally averaged temperature, which reflects the overall energy balance.
Energy can take many forms, but from basic thermodynamics, we know that it all ultimately must end up as heat. So the model allows (and indeed predicts) short term fluctuations in temperature. The prediction of global warming is on a multi-decade time scale. So, obviously, observing short term fluctuations such as El Nino, which are in fact seen in global climate models, is not a challenge to the theory.
Yes, this is a common crank objection to genuine science, one that has been applied to fields as diverse as climate science and quantum mechanics: "If your model can't predict what I want it to predict, then it must be wrong." But testing of scientific models does not require that a model be able to predict everything, merely that it makes testable predictions. This is something that climate science has done with flying colors. Meanwhile the vague hand-waving notions of "natural variation" cited by the self-styled critics have been unable to predict anything, and when challenged, they fall back upon special pleading: "It's not a theory, it's just a 'null hypothesis' (never mind that that makes no sense) so I don't have to subject it to the standard scientificdiscipline of creating a mathematical model that makes actual testable predictions."
I don't. No actual scientist would make such a claim. As I've explained to you several times, a physical model such as AGW cannot be a null hypothesis. The term "null hypothesis" is only meaningful in the context of statistics and statistical models, and has a well-defined meaning, so nobody gets to choose what is the null hypothesis. The null hypothesis is the hypothesis of no change--and nobody seems to be crazy enough to claim that climate is unchanging.
AGW has more credibility with the scientific community not because it has some sort of nonsensical privileged "null model" status, but rather because it has been subjected to the standard scientific disciplines of "sanity checking" that any credible theory must conform to: it has been implemented in mathematical form consistent with known physics to derive definitive mathematical predictions, and those predictions have been tested against observation, yielding dramatic confirmation (of which the prediction of the modern warming trend before it occurred is just one). Here, once again, are some of the successful predictions of climate theory:
http://bartonpaullevenson.com/ModelsReliable.html
I'm skeptical, particularly since there is no single projection, but rather a series of scenarios depending upon how successful we are at controlling CO2. Over a single year, the difference between them is negligible, but over 100 years, it can make quite a bit. Please explain what specific model or models and scenarios you used for your projection (with appropriate citations), and describe (or provide a citation to) how the variance of annual temperature was calculated.
And considering that a loss of $10 per unit could add up to substantial cost to Amazon when multiplied by millions of sales, while cutting the price by $10 will not sell appreciably more units relative to selling them at cost, it would be crazy for Amazon to sell them just $10 below cost.
oops...meant "tablets" not "phone"
Yes, this is clearly within error of break-even. Amazon is not going to sell appreciably more phone by taking a $10 loss per phone, so why do it? And since the main goal is not to make money on the hardware, but rather to sell Amazon's other products and contents, selling the tablet essentially at cost makes the most sense.
I think that he's an extremely good author. "Dying of the Light" was a very impressive novel. "Fever Dream" is also very strong. And the Wild Cards series was a lot of fun. I generally don't get into medievalist fantasy, but I've been impressed with the GoT series: it is intricately plotted and not predictable, with convincing characters who have some emotional depth. Considering how slowly the larger plot arc advances, I'm wondering if he plans for it so support him for the rest of his life (not that I begrudge him that; I'm just worried that he'll die and leave it unfinished). His prose isn't flashy or particularly poetic, but it conveys vivid images and is not repetitive. His dialog is good (as evinced by the fact that it works on the screen as well as on the page; a lot of written dialog sounds foolish when spoken by a live person).
As far as being a "sell out," if that's what he's done, it's on the best terms I've ever seen. The TV series was the most careful and faithful adaptation of a fantasy novel that I've encountered to date. It is virtually a scene by scene adaptation. The sets and costumes are pretty much exact. I've only seen one issue of the comic book, but it looks like the same will hold there. Either he has found adapters who genuinely respect his work, or else he has gotten a great deal of creative control. Writing can be a chancy living, and most writers, particularly of genre fiction do not make a great deal of money. Martin has been at it a long time, it seems terribly petty to begrudge him taking advantage of an opportunity to profit from his work.
Obviously, there are some people who already live very close to the water line, for whom any increase in ocean level whatsoever will be a problem, even somebody else happens benefit (perhaps Al Gore's house in the hills of Montecito will increase in value by virtue of becoming oceanfront property).
Sorry, but that's scientific gibberish. Read up on statistics. The null hypothesis has nothing to do with causal relationships. "Null" means one thing, and one thing only: it is the hypothesis that there is no difference in the true value of two measurements that are subject to error. Any hypothesis other than that cannot be considered a null hypothesis. The term has no meaning whatsoever in any other area of science.
No, as a scientist, I do not base my judgements on faith, but on how well a hypothesis is able to make testable predictions and how well those predictions are borne out. So I am impressed by a theory that successfully predicted the modern warming before it happened, as well as a whole host of details about how that warming has manifested.
I am not impressed by self-styled skeptics who have subjected their ideas to the discipline of mathematical modeling. I am not impressed by those who dismiss the careful modeling of others, and yet have consistently failed to create a model of their own that is consistent with observational data and does not predict warming. And I am even less by those who try to excuse their failing by the statistically illiterate insistence that their ideas are a "null hypothesis" and therefore exempt from the type of scrutiny to which real scientists subject their scientific hypotheses.
If I had a casino, I'd love to have you for a customer. If a mathematician told you, "You know, the roulette wheel is statistically weighted in favor of the house, and you will lose your money if you keep playing," you would doubtless insist, "Well if you think you know so much, make a testable prediction on the outcome of the next spin," and keep playing.
Climate models do not purport to accurately predict the temperature next year--or to put in in statistical terms, the projected increase in average temperature next year is much smaller than the variance of annual average temperature.
No. It looks like the huge, rapid introduction of CO2 into the atmosphere without any change in the earth's orbit or solar output is without precedent, at least over the period of time for which we have good evidence.
Like what? Ultimately, thermodynamics tells us that the earth's temperature must be determined by the rate at which the earth absorbs energy from the sun and the rate at which it radiates energy to space. Nobody has found any changes in factors that could affect these, aside from atmospheric CO2.
When you've got a lot of people living next to an ocean made of a substance (water) that expands when it is heated, you clearly have a problem, although perhaps you could debate how bad a problem it is.
Once again, you don't understand what a null hypothesis is. "Null hypothesis" is not some sort of magic incantation you can intone to exempt your own favored hypothesis regarding what does or does not cause what from the normal requirements that a scientific theory be physically realistic and make testable predictions. You can't have a null model that says anything, positive or negative about causality, because the null hypothesis belongs exclusively to statistics, and statistics is inherently incapable of addressing questions of causality--it is entirely about correlation. So the only null models you can have are that temperature and/or CO2 are not changing with time. But the existing data is adequate to exclude the null model.
At this point the null model is dead. That's the only null hypothesis there is; you don't get another one. If you want to make a credible hypothesis that there is no causal relationship between temperature and CO2, you need to show that such a hypothesis makes sense: that is physically realistic, and that it is consistent with the observational and experimental data.
There is no "apparently" about it. The models, which incorporate the weather mechanisms of moving energy around, do indeed predict that there will be periods of limited duration when the warming trend is undetectable. This is not some sort of special exemption afforded to climate theory--it is a universal statistical property of measuring trends in the presence of noise (which is pretty much everything in the real world). Global warming "skeptics" are fond of looking at each little fluctuation and crying, "The warming trend is stopping!", much like the gambler who wins a hand or two and is convinced that his luck has turned. But just as the trend in temperature is inexorably up (even if weather fluctuations can obscure that for a few years), the casino may lose a game or two, or even have a losing day, but if you keep gambling, they will eventually get your money.
That's kind of a silly objection. Obviously, the CO2 doesn't need to know anything. If I tell you that you can turn a wheel by pushing the top of the wheel forward or the bottom of the wheel backwards, do you ask, "How does the wheel know which one it is?" Equally obviously, it is not unfalsifiable, because it makes definite predictions. If warming leads CO2, then there should evidence of a change in some other factor that influences the energy balance of the earth, such as the earth's orbit or energy output by the sun. If CO2 leads warming, then there must be introduction of CO2 from a new, temperature-indpedent source. Both predictions are satisfied when it comes to ancient and modern climate change. For example, in the modern era, we know that temperature is not increasing due to changes in the sun's output or the earth's orbit, because the sun's output has been measured and shown not to change.
Yet nobody has been able to come up with such a model that does not predict a problem with future warming as a result of CO2 increase. What this suggests is that none of the models is absolutely perfect (but then again, no model is), but that to be able to do a good job in hind casting, the errors have to cancel out, and this may happen in a somewhat different way in different models. In other words, the necessity to be consistent with the temperature record imposes a powerful constraint on model structure, and models that do not predict future warming cannot satisfy this constraint. Again, it would be easy to disprove this: just show me a model that can hind cast and that does not predict future warming.
Some of the tests of the models can be found here. Again, if the models are so adjustable that they can predict whatever you choose, why has no critic been able to come up with a model that passes the hindcast test and does not predict troublesome warming?
Not at all. Because of the two-way relationship between temperature and CO2, the models predict that CO2 will lead when warming is initiated by increased release of CO2, and that it will lag when warming is initiated by other factors such as changes in solar radiance or changes in earth's orbit. As this is exactly what is observed, this provides strong support of the theory.
Absolute proof exists only in mathematics, not science. Scientific proof is testing and confirming the predictions of a theory, and so far climate theory has done pretty well. See here for some of the tests of climate theory.
Agreed. But the claim that this is true of climate models has no substance. While it seems to be an article of faith among self-styled skeptics that the models can predict whatever you choose, none of them have ever been able to provide any evidence to support this claim. The climate models are published; anybody can formulate their own or use one of the existing models. So if you believe that the hypothesis predicts every possible observation, there is a simple way to substantiate that claim:
Take one of the models, tweak the the parameters in any physically plausible way that you please, and show that you can come up with a version of the model that is consistent with the known climate record, and which does not predict warming.
Not quite. AGW is a prediction of models of overall climate, one that long predates the modern massive CO2 increase. These don't distinguish between "human emitted" and "natural" CO2, because that would be absurd. CO2 is CO2--the chemical properties of CO2 do not change dependent upon where it comes from. A role for CO2 is an integral part of climate models--nobody has been able to come up with any model consistent with temperatures at any point in the earth's history without including a role for CO2.
Statistics (which is the only realm in which the concept of a null hypothesis is meaningful) of course cannot answer questions of causality; the most it can do is ask whether or not there is a correlation. And again, there is no doubt about whether there is a correlation between average global temperature and CO2--the unequivocal answer is that there is a correlation and it is statistically significant, so the null hypothesis of no relationship is excluded.
Of course, correlation does not necessarily imply causality. To turn to the questions of causality, one has to turn to physics. And here, there are known mechanisms whereby temperature and CO2 can interact, although as is commonly the case, the interaction is two-way--i.e. changes in temperature alter CO2, and changes in CO2 alter temperature. It was this understanding of the physics that made it possible for scientists to predict AGW before it occurred.
So if you want to come up with a model in which adding more CO2 to the atmosphere does not affect temperature, you have a very different problem, because as I noted, nobody has ever managed to come up with a physically realistic model that comes anywhere close to being consistent with temperatures, either in the the past or today, that does not predict that our adding additional CO2 to the environment will lead to an increase in average temperatures.
It sounds like you don't understand what a "null hypothesis" is. Some people seem to think that by declaring their own hypothesis the "null hypothesis," they automatically get a pass on the normal requirement to substantiate your hypothesis with plausible mechanisms and testable predictions. In reality, "null hypothesis" is a term from statistics, and it has nothing to do with mechanism. The "null hypothesis" specifically refers to the hypothesis of no change . So to talk about a "null hypothesis of natural climate change" is an oxymoron. The actual null hypothesis that climate does not ever change is readily excluded by fairly simple statistics. Once you are hypothesizing a change, natural or otherwise, then you do not have a null hypothesis--and you need to support your hypothesis in the scientific way: formulate a physically realistic model, describe it mathematically, and test it for consistency with observations.
It is an article of faith among many self-defined "skeptics" that climate models have so many free parameters that they can be tuned to show whatever you want. Yet even though several of these models are publicly available, no skeptic has ever managed to find a way to "tune" such a model such that it is consistent with the record of past climate, and yet does not predict substantial future warming.
To scientists, modeling is a discipline, a way of "sanity-checking" your ideas. It's easy to wave your hands and insist that something will or won't happen, but if the math doesn't work out, you are out of luck. So far, the skeptics have failed to pass the sanity check.
Whether you agree or disagree with their point of view, Skeptical Science is valuable because it is well documented, providing citations to the original literature where you can check to see whether the statements are accurate and whether the alleged strawmen are actually made of straw.
Except that in practice, with class action suits over consumer devices, it makes no difference whatsoever whether there is any actual merit to the suit. The company always settles anyway, because it's cheaper than going to court. So it's not a punishment or deterrent for anything--just legal extortion, and for the manufacturer, merely part of the cost of doing business. End the end, the cost is footed by the consumer in the form of higher prices. Nobody benefits from such suits but lawyers
Class action suits over consumer products are a lawyer scam. It doesn't much matter whether the alleged product flaw is real or not. The lawyer makes a lot of noise in the media and sues for a ridiculous amount of money, then offers to settle for less than it would cost the company to defend itself in court. The company settles--after all, defending itself in court would just generate more news reports and extend the bad publicity for months, and even if they won, would end up cost them more money than the settlement. All the "members of the class" get a piddly settlement, like a gift certificate for more of the company's products, that is barely even decent compensation for the time it took them to fill out the paperwork. But the lawyer gets a slice of all of those piddly settlements which add up to a nice chunk of change--all for no work other than giving a few press conferences and sending a few letters.