So terrorists would either shield their payload perfectly or not at all--there's no chance that they'd only shield it down to the level that would be emitted by somebody who recently received an injection of a radioactive dye? That seems like pretty shaky reasoning to stake people's lives on.
And people who have recently received some kinds of radioactive tracers or radioactive implants for cancer treatment can be pretty hot. It is not uncommon for patients to be cautioned to keep their distance from kids and women who might be pregnant. Isotopes used for medical purposes mostly decay rapidly, but particularly early on, they can emit well above background. I knew a scientist who discovered after a test that he could not enter the room with his lab's radiation scintillation counter without screwing up the results.
"Probable cause" does not mean "proof beyond a shadow of doubt." You can legally be detained if a cop notices you driving with bags of white powder in the front seat, even though you may only be a baker transporting powdered sugar to your bakery. Stopping the occasional person who is emitting unusal levels of radioactivity for a benign reason hardly seems an overwhelming intrusion on civil liberty. An unusually high level of radioactivity could be an indication of crimes other than terrorism, by the way--unsafe transport of radioactive materials, for example
Something that most scientists know, but that is not widely appreciated by the public, is that "landmark" studies are particularly subject to positive bias. For a study to be acclaimed as a "landmark," it is the first report of a novel phenomenon, which by definition means that it has not yet been confirmed by other investigators, and moreover that it is in some sense unexpected--which means that there is not even much "indirect" evidence from other sources that it is correct. It is also likely to be submitted to one of the high-profile "newsy" journals, like Science or Nature, where submissions are not evaluated solely on the basis of whether the science is high quality, but are first screened (and usually by an editor, before it even gets specialist peer reviewers) on the basis of whether it is of "broad interest." Because these journals are widely read and cited , they have high impact factors, so even getting published in one of these journals is a feather in a researcher's cap. In contrast, a publication in a middle-rank journal does not give a major immediate boost to a scientist's career, but may have a long-term benefit--but only if it turns out to be correct. Being "scooped" (by having somebody else publish research leading to the same conclusion) will not prevent you from being published in a middle-rank journal, but it will knock you out of the newsy journals. So the alluring prospect of publication in a newsy journal may lead a scientist to be a bit less cautious than normal, and the risk of being "scooped" means that he/she may not take usual precautions (like seeing if somebody else in the lab can reproduce the result independently). High profile journals are stringently reviewed, but peer reviewers even in these highly-regarded journals necessarily take the authors at their word, unless there are blatant errors--nobody visits the authors' labs to look over the shoulders of the researchers or to verify that negative results have not been discarded. On the other hand, if you are planning to publish a result in a middle-rank journal, you are more likely to take the time to make sure that your conclusions will hold up over the long haul.
Working scientists know this, so they take these "landmark" studies with a grain of salt until they are independently confirmed. But the public can easily confuse "high profile" with "most reliable."
OK, the algae could use light and CO2 to synthesize reduced carbon compounds, which could then be oxidized in the dark to generate light. Basically, this is just a biological version of a solar lighting system. Sounds finicky to maintain, but maybe energy storage in algae could outperform conventional batteries. But the article implies that the lamp has a net consumption of CO2. That implies a net production of other organic compounds, because carbon atoms can't just vanish. So what happens to this carbon "waste." There article says this is just another kind of fuel. This is plausible, but how do you get the energy out of that fuel? The normal way to get energy out of reduced carbon compounds is to burn or otherwise oxidize them--in which case you end up with CO2 again (if you do it fully). So once again, it is hard to see how this process can lead to appreciable net carbon sequestration.
As reported in TFA, the die-shrunk version runs a bit cooler. Which if you know your thermodynamics, is pretty much inevitable if it has lower power consumption.
People sue for all kinds of stupid things. But a lawsuit based upon the fact that some units only do as well as advertised, while others do a bit better, would be unlikely to get far.
As reported in TFA, the iPad2 is extraordinarily power-efficient when watching video, using less power than merely idling on the home screen. Anandtech timed it at 13.3h continuous video play. And that is the original model; the die-shrunk version goes 15.7 hours.
So what you're saying is that if I use Safari on an Apple product and I go to Amazon or e-bay and buy something, then Apple gets a cut?
Nope. Buy something through a web site and Apple gets nothing.
But if a 3rd party developer's app sells you something, Apple gets a cut.
So anybody can go to Dropbox's web site on their iDevice and sign up for Dropbox and buy additional storage, but individual apps are not allowed to sell Dropbox directly without giving Apple a cut.
This is of course only a minor inconvenience to the user, who can set up Dropbox using Safari, and then access his Dropbox through any number of apps that support Dropbox access.
An important factor in the current evolution of mankind is improved healthcare. Now that healthcare is improved, many more people survive their childhood, which actually mean that we as a species are becoming weaker and weaker.
I've often heard this said, but it makes little sense to me. Evolution is not a strength competition. It favors those genotypes that are fittest in the environment they actually live in. Why should we care whether we we would be more or less fit in a primitive society without good healthcare?
It seems that intelligence is a negative selection factor, because people with a high intelligence tend to have less children (or non at all) than people with an average intelligence.
And this likely has always been the case. There is little evidence that average human intelligence has changed much since our species emerged. High intelligence can benefit survival, but it can also lead one into activities, such as science or art, that distract from the real business of evolution--having as many children as possible and providing them with as much resources as possible. So we may well be at an evolutionary steady-state where on the average the positive and negative selection effects of intelligence cancel out.
There is no particular reason to suppose that evolution favors high intelligence. There is little evidence of any trend in human intelligence since the early evolution of the species. It is quite possible that human intelligence has long been at an effective steady-state. Up to a certain point, intelligence increases survival by reducing the likelihood of accidental death and increasing the ability to provide for oneself, but beyond a certain point, intelligence can lead people to devote their energies to distractions like science or art, rather than the critical evolutionary business of having as many children as possible and providing them with as much resources as possible.
It could be that modern technology, which offers more opportunities for people with high intelligence to make a good living, has increased selection for intelligence, but I wouldn't count on it.
I'd say that cockroaches are more evolved than humans. They have a shorter generation time, which means that they should evolve faster. So cockroaches are probably better adapted to do what they do than we are to do what we do. Of course, the microorganisms have us all beat. It's no surprise that we slow-evolving large beasts inherited most of our fundamental protein designs from our microorganism ancestors (or perhaps swiped them from viruses). The much faster evolution of microorganisms means that they are more creative when it comes inventing new protein families and functions. We are still running a slightly tweaked version of an ancient protein operating system, while modern microorganisms are running the up-to-date version.
No regulations? So if I decide that I can't pay my debts, I can just announce that I am defaulting, free of those pesky regulations that might enable my creditors to attach my assets or garnish my wages.
Indeed. Those hundreds of thousands of $0.99 e-books on Amazon can't possibly exist.
A while back I saw a study of the top 100 SF best-seller e-books on Amazon and if I remember correctly the most popular price was $2.99.
For the most part, the $.99 books on Amazon are from authors who are trying to build an audience. For the most part, they are not up to the quality of a full-price book in editing or proofreading, but readers understand the tradeoffs of a $0.99 book. This is a good thing, in my opinion, as it makes it easier for talented young authors to get a start, but for an author that I know and like, I'm perfectly willing to pay a few bucks more for a more polished work.
Another good thing about ebooks is that it makes it possible for authors to keep their backlist in print and offer discounts on these older works. Again, this helps to bring in new readers, some of whom will hopefully be enthusiastic enough to pay full price for the author's more recant works. The "first one is (almost) free" deal works for authors as it does for drug dealers.
In other words, these are loss leaders. But professional editing and proofreading, promotion, and translation into other languages, not to mention advances to authors so that they can afford to write as a full-time profession don't come cheap. So while there will be deals on older books and books by new authors, don't expect prices to drop drastically for new books by established authors.
I pretty much agree with this review. I enjoyed it, but thought that it came off a bit amateurish and I doubt if it will have much appeal to people who are not already fans of the strip.
You don't understand chaos at all do you. "A degree of accuracy in the starting conditions that is not achievable with real-world measurements" makes it sound like next year's model will solve it. As for monte-carlo analysis (just run the wrong prediction many times and average the mistakes, assuming weather is unidimensional and linear, aka. how we arrive at global warming prediction) it's just as worthless as a single run.
Nonsense. To begin with, a run of an accurate physical model of a chaotic process is not a "wrong" prediction, it is an accurate prediction given the starting conditions. Therefore, if the model is run with starting conditions that reflect the statistical distribution of those conditions in the real world (which can readily be measured), it is necessarily the case that the distribution of the output will reflect the distribution of the chaotic process in the real world. No assumptions whatsoever regarding "linearity" are involved. Indeed, as I've pointed out to you multiple times, statistics was developed as a way of modeling real world variability that most commonly arises out of chaotic physical mechanism. Indeed, the laws of thermodynamics arise out of statistical regularities of chaotic physics.
And of course, you were quite happy to accept statistical analysis when (in your mistaken understanding of significance testing) you thought that it rejected global warming. Now that you discover that it doesn't give you the answer that you would like, you've decided that statistics is invalid.
Ok, fair enough... until of course you look at that little word there... "ultimately"... the earth has been releasing stored energy for 5 billion years now and it still stores far more than the sum total of what it released.
Riiiight. And which specific physical processes do you imagine to have a billion year relaxation time? If the earth were storing appreciably more energy than it was receiving from the sun for a billion years, it would be molten, because the second law dictates that any physical process (including your hypothetical magical energy battery) is going to leak energy in the form of heat.
The temperature in the last 100.000 years has been close to constant.
The statistical null hypothesis of constant temperature is easily rejected. So this is just false.
It has barely risen with much more co2 than we have today, has warmed up with much more oxygen in the air than we have today, in short, it's historically shown itself supremely indifferent to this co2 gas... (or more accurately, the co2/o2 balance) except for the last 150 years.
On the contrary, nobody to date has come anywhere close to explaining temperature changes in the past arising from factors such as changes in the sun's output or the earth's orbit, temperatures on other planets, responses to "natural experiments" such as volcanoes, or even explaining why the earth is not much colder than it is, without a substantial role for CO2--a role that was predicted over 100 years ago based upon basic radiation physics. And the best you can do is appeal to imagined magical properties of chaotic mechanisms.
You started by citing a study by Hansen from 1981, saying it was somewhat accurate. I brought up a later study, which should be more accurate, which showed that more recent studies, with more computing power, can be less accurate than earlier studies.
Except that you didn't show that the 1988 model was "less accurate" by any valid statistical test. These models are designed to forecast long-term climate trends, not short-term ( 15 years or so) weather fluctuations.
Riiiiight. Please quote any paragraph in which I used the nonsensical expression "simulated variable."
Okay :
A proper statistical trend analysis will result in a best estimate of the trend (which may be warming or cooling) given the available data, as well as confidence limits on that trend--a measure of how much the estimated trend would be expected to vary if that observation could be repeated (i.e. if you had a population of earths with a similar climate trend but with different weather, each of which could be identically sampled over the same time period using the same methodology)
Let me guess, this is not really simulation ? Or it "just seems" ridiculous, perhaps ? Or are you perhaps trying to say that weather is random, but averages out "in the end" ? Or perhaps you just really suck in communication, and the idea behind it was in actuality kinda good ?
The nonsensical expression "simulated variable" does not occur anywhere int he passage that you quoted. So that's a FAIL.
Let me guess, your point is that you can calculate using the same formulas in chaotic systems but the predictions become worthless
Good, you are finally beginning to understand what I've explained to you a couple of times already. Chaotic systems can be simulated physically (there are some chaotic systems that have fairly trivial physics) to any desired degree of precision. But in practice, such simulations are only useful for exact prediction over the short term, because long-term prediction would require a degree of accuracy in the starting conditions that is not achievable with real-world measurements. But such models can still be useful over the long term for monte-carlo analysis (i.e. by doing a lot of runs with slightly different starting conditions) to determine the statistical properties of the system.
Note that the energy stored in ocean currents alone far exceeds the total energy that global warming has added to the earth in the last 2 centuries, and this amount of energy has been shown to vary wildly from year to year.
Sure, there is stored energy, but none of these energy reservoirs are infinite in capacity, and there are consequences to pumping more energy into them, and all of the energy ultimately has to end up as heat, due to the Second Law. The ones that equilibrate extremely slowly can only affect climate behavior over the very long term, and the ones that equilibrate rapidly come to steady state. So none of this is a major obstacle to physical modeling. Year to year variations due to chaotic behavior can be modeled statistically even if they can't be simulated exactly.
I somewhat suspect you would find a way to protect your preconceptions no matter what
Why would I have preconceptions? Debating how best top characterize the degree of accuracy of a 1988 paper is a bit like debating whether the 1998 Yankees were better than the 2011 team. It's the sort of thing one might discuss for a few moments of idle amusement, but not exactly a matter of great concern. Continually attacking an old paper seems very odd to me as a scientist. Scientists don't think this way. If you think there are weaknesses in a study, you demonstrate it by doing a better job. And certainly there have been a lot of research groups that have developed their own models since Hansen's early work. The only people I see doing this thing are cranks: creationists attack Darwin; germ theory denialists attack Pasteur; HIV/AIDS denialists attack Gallo. And global warming "skeptics" attack the early work of Hansen or Mann. Perhaps you can explain the motivation for me. Is it out of a misunderstanding of scientific thought, and a mistaken belief that the whole field will collapse if errors are found in this early work? Or is it just personal anger at these researchers for their contributions in getting the whole field started? Certainly, a lot of posts that I see on Climateaudit or WUWT seem to exhibit a level of personal animus that strikes me as frankly bizarre.
Would you estimate that in future, the temperature will more closely track the red line, the green line, or the blue line?
This strikes me also as very strange. Those 3 lines reflect completely different scenarios in terms of CO2 control. Are you asking me to make a guess as to the politics of future CO2 control? And why make projections based on a decades-old paper when the field has advanced considerably since then? Not only have the models been refined, but computing power has increased, so that it is not more feasible to run models repeatedly with slightly different starting conditions to get a better idea of expected weather variability around the overall trend. So if I actually wanted to make a projection, I'd guess that it temperatures would tend to track somewhere within range estimated from the ensemble of model runs. But if you insist on using an out-of-date model, I'd say that over the long-run temperatures would probably track somewhere between Hansen's A and C scenarios, since these represent fairly extreme assumptions regarding CO2 mitigation that are unlikely to be realized in practice. These days, it is thought that Hansen's model had the climate sensitivity a bit high, but not so much that the temperatures are likely to track outside this range for long.
No, it does not. Really [abarim-publications.com].
More foolishness. The standard deviation is just a mathematical equation. It can be calculated for any series, although its meaning and practical usefulness depend upon the nature of the series.
The notion that statistics cannot be applied to chaotic systems is also foolish. In fact, most of the things to which we apply statistics are chaotic in a physical sense.
You are the one using the "simulated" terminology for variables.
Riiiiight. Please quote any paragraph in which I used the nonsensical expression "simulated variable."
So wait... I claim that accurate physical modeling of a dice roll is not possible. You claim it is. You're "right" despite the fact that you agree such models cannot actually predict dice rolls... Pray tell, what is the definition of a physical model again ? It wouldn't happen to involve accurate predictions now would it ?
Nope. A physical model is an accurate model of the physics. That does not necessarily make it useful. And it may be predictive in more than one way. A physical model of a chaotic system is predictive of the exact behavior of the system over only a short span of time, because of sensitive dependence upon initial conditions--i.e. the measurement precision required for long-term exact prediction is unattainable. However, such a model could still be used to predict the statistical properties of that system over longer time spans. Of course, with dice, that is more simply done with a purely statistical model than by monte-carlo modeling with a chaotic physical model, but for many natural systems the latter is the only approach available, because many natural systems lack the kind of simple symmetries that permit the construction of a purely statistical model of dice rolling from first principles.
The reason no-one is making tiny temperature sensors is that they're not stable... And that's caused by the nature of what you're measuring, not by the sensor. The small sensors really are more accurately telling you the brownian motion. The more accurate they are... the more extreme their ranges will be in the same circumstances. If smaller, more sensitive sensors are less stable than their bigger clunkier less accurate brothers... then what happens to this equation ?
Not a problem. A large sensor is physically averaging the Brownian impact energies rapidly, because it is large enough to experience a large number of impacts in a short period of time. A small sensor will experience fewer impacts per unit time, but you can achieve the same results (albeit with lower time resolution of rapid temperature changes) by mathematically averaging its response over a longer period of time. It's all just simple averaging, and analysis of the variance will tell you what period of time is required to yield an estimate of the temperature that is reproducible within desired statistical limits.
The problem here, of course is that pesky entropy... and that it only talks about the total value, not about it's spread within the system, and for a system not in equilibrium those will by definition differ by quite a bit. What is "work" ? Work is essentially any temperature difference anywhere on earth, and it's associated effects (such as wind, water movement, oceans, mountains, humans, animals, plants, cars, roads, oceans, rivers,...). How much is that ? Unknown, but it is not insignificant at all. So if, for some reason, internal temperature differences in a system decrease, temperature will increase. Let's see about a more difficult question. Suppose the temperature difference between the oceans and the athmosphere increases for some reason (ie, currents accelerate), what happens to temperature ? Think before
Considering that Hansen's model predicted global warming before it was evident in the temperature record (the strongest confirmation of a theory is when it predicts something that you don't already know), and that more than two decades of refinement has yielded models that are in qualitative agreement with its overall conclusions in terms of predicting a worrisome degree of warming, I'd say that qualifies as "quite good" by scientific standards. After all, we know that no model is perfect (that is, after all, why we call them models); the question is whether a model is good enough to tell you what you need to know. As RealClimate points out, Hansen's model "has out-performed any reasonable naive hypothesis that people put forward in 1988 (the most obvious being a forecast of no-change)."
One thing that scientists look at is the range of variation of different climate models, or multiple runs of a single model. This is discussed in the IPCC reports that I referred you to previously. See here, here, and here, for example. Additional explanation can be found here
The definition of standard deviation does not involve any simulated variables, believe it or not. The only definition of standard deviation in existence is the square root of the mean squared difference with the mean (for normal distributions... is temperature, which is the context here, normally distributed, however ? Of course not). Note the complete absence of anything remotely resembling generated data. No virtual earths in sight. No magic repeated experiments with the climate are involved, not even virtually.
The temperature record has a standard deviation. It is a simple mathematical calculation, as you've described. It seems that you are throwing around terms that you do not actually understand. A variable is a mathematical construct. How can it be "simulated"?
Deterministic... another mathematical term ! Again massively misused. Why don't you deterministically model a roll of the proverbial dice ?
I suspect that this is another term that you do not actually understand. Physical modeling of the roll of the dice can readily be done, with no randomness involved. It's pretty straightforward physics. But it ends up having such a sensitive dependence on boundary conditions that such a model is pretty much useless for practical purposes--a statistical description turns out to be more useful in practice, for dice as for many phenomena in the real world (e.g. short term weather variations).
I can't help notice that you were perfectly happy to talk about statistical significance until I explained to you that you had the definition wrong, and that it did not support your argument. Then you started arguing that statistical analysis is invalid when it comes to climate. This is a dead giveaway that you are thinking in an emotional, biased way, rather than rationally. Scientists learn early in their training to be alert to this kind of cognitive error, which even intelligent people sometimes make. Indeed, much of the discipline of science--statistical analysis, mathematical modeling, peer review--is designed to protect us from fooling ourselves in this way.
Statistical model of a physical process ?
We do it routinely. For example, when you estimate that there is a one in 36 chance of throwing snake eyes with two dice, you are engaging in statistical modeling of a physical process.
If you look at updated data in that first diagram [climateaudit.org], you can see that the land-sea temperatures are below scenario C, ie below what he estimated if we stopped emitted CO2 completely. The satellite temperature reading is off from between A and B by nearly half a degree. If I were trying to be misleading, I could say he was off by 100%.
Above vs. below is an incorrect, and usually misleading, way to look at it. Statistically speaking, the actual temperatures are more likely to be above or below the expected trend than exactly on it, because climate models do not perfectly simulate factors (e.g. volcanic eruptions) that influence temperature on a short time span of a decade ago. You have to do an appropriate statistical test taking into account the uncertainties of both the predicted trend and the measured temperatures. From this point of view, the agreement is well within the expected range of variation.
Slashdot Mirror
It's not all that common. Medical isotopes mostly decay rapidly, so people receiving such treatments are only hot for a few days
So terrorists would either shield their payload perfectly or not at all--there's no chance that they'd only shield it down to the level that would be emitted by somebody who recently received an injection of a radioactive dye? That seems like pretty shaky reasoning to stake people's lives on.
And people who have recently received some kinds of radioactive tracers or radioactive implants for cancer treatment can be pretty hot. It is not uncommon for patients to be cautioned to keep their distance from kids and women who might be pregnant. Isotopes used for medical purposes mostly decay rapidly, but particularly early on, they can emit well above background. I knew a scientist who discovered after a test that he could not enter the room with his lab's radiation scintillation counter without screwing up the results.
"Probable cause" does not mean "proof beyond a shadow of doubt." You can legally be detained if a cop notices you driving with bags of white powder in the front seat, even though you may only be a baker transporting powdered sugar to your bakery. Stopping the occasional person who is emitting unusal levels of radioactivity for a benign reason hardly seems an overwhelming intrusion on civil liberty. An unusually high level of radioactivity could be an indication of crimes other than terrorism, by the way--unsafe transport of radioactive materials, for example
Something that most scientists know, but that is not widely appreciated by the public, is that "landmark" studies are particularly subject to positive bias. For a study to be acclaimed as a "landmark," it is the first report of a novel phenomenon, which by definition means that it has not yet been confirmed by other investigators, and moreover that it is in some sense unexpected--which means that there is not even much "indirect" evidence from other sources that it is correct. It is also likely to be submitted to one of the high-profile "newsy" journals, like Science or Nature, where submissions are not evaluated solely on the basis of whether the science is high quality, but are first screened (and usually by an editor, before it even gets specialist peer reviewers) on the basis of whether it is of "broad interest." Because these journals are widely read and cited , they have high impact factors, so even getting published in one of these journals is a feather in a researcher's cap. In contrast, a publication in a middle-rank journal does not give a major immediate boost to a scientist's career, but may have a long-term benefit--but only if it turns out to be correct. Being "scooped" (by having somebody else publish research leading to the same conclusion) will not prevent you from being published in a middle-rank journal, but it will knock you out of the newsy journals. So the alluring prospect of publication in a newsy journal may lead a scientist to be a bit less cautious than normal, and the risk of being "scooped" means that he/she may not take usual precautions (like seeing if somebody else in the lab can reproduce the result independently). High profile journals are stringently reviewed, but peer reviewers even in these highly-regarded journals necessarily take the authors at their word, unless there are blatant errors--nobody visits the authors' labs to look over the shoulders of the researchers or to verify that negative results have not been discarded. On the other hand, if you are planning to publish a result in a middle-rank journal, you are more likely to take the time to make sure that your conclusions will hold up over the long haul.
Working scientists know this, so they take these "landmark" studies with a grain of salt until they are independently confirmed. But the public can easily confuse "high profile" with "most reliable."
OK, the algae could use light and CO2 to synthesize reduced carbon compounds, which could then be oxidized in the dark to generate light. Basically, this is just a biological version of a solar lighting system. Sounds finicky to maintain, but maybe energy storage in algae could outperform conventional batteries. But the article implies that the lamp has a net consumption of CO2. That implies a net production of other organic compounds, because carbon atoms can't just vanish. So what happens to this carbon "waste." There article says this is just another kind of fuel. This is plausible, but how do you get the energy out of that fuel? The normal way to get energy out of reduced carbon compounds is to burn or otherwise oxidize them--in which case you end up with CO2 again (if you do it fully). So once again, it is hard to see how this process can lead to appreciable net carbon sequestration.
As reported in TFA, the die-shrunk version runs a bit cooler. Which if you know your thermodynamics, is pretty much inevitable if it has lower power consumption.
People sue for all kinds of stupid things. But a lawsuit based upon the fact that some units only do as well as advertised, while others do a bit better, would be unlikely to get far.
As reported in TFA, the iPad2 is extraordinarily power-efficient when watching video, using less power than merely idling on the home screen. Anandtech timed it at 13.3h continuous video play. And that is the original model; the die-shrunk version goes 15.7 hours.
Nope. Buy something through a web site and Apple gets nothing.
But if a 3rd party developer's app sells you something, Apple gets a cut.
So anybody can go to Dropbox's web site on their iDevice and sign up for Dropbox and buy additional storage, but individual apps are not allowed to sell Dropbox directly without giving Apple a cut.
This is of course only a minor inconvenience to the user, who can set up Dropbox using Safari, and then access his Dropbox through any number of apps that support Dropbox access.
I've often heard this said, but it makes little sense to me. Evolution is not a strength competition. It favors those genotypes that are fittest in the environment they actually live in. Why should we care whether we we would be more or less fit in a primitive society without good healthcare?
And this likely has always been the case. There is little evidence that average human intelligence has changed much since our species emerged. High intelligence can benefit survival, but it can also lead one into activities, such as science or art, that distract from the real business of evolution--having as many children as possible and providing them with as much resources as possible. So we may well be at an evolutionary steady-state where on the average the positive and negative selection effects of intelligence cancel out.
Have they? Is their resistance to disease unchanged? Is their behavior unchanged? Is the efficiency of their enzymes the same? How do you know?
There is no particular reason to suppose that evolution favors high intelligence. There is little evidence of any trend in human intelligence since the early evolution of the species. It is quite possible that human intelligence has long been at an effective steady-state. Up to a certain point, intelligence increases survival by reducing the likelihood of accidental death and increasing the ability to provide for oneself, but beyond a certain point, intelligence can lead people to devote their energies to distractions like science or art, rather than the critical evolutionary business of having as many children as possible and providing them with as much resources as possible.
It could be that modern technology, which offers more opportunities for people with high intelligence to make a good living, has increased selection for intelligence, but I wouldn't count on it.
If natural selection were to stop, we'd accumulate harmful mutations, because new mutations are happening all the time.
I'd say that cockroaches are more evolved than humans. They have a shorter generation time, which means that they should evolve faster. So cockroaches are probably better adapted to do what they do than we are to do what we do. Of course, the microorganisms have us all beat. It's no surprise that we slow-evolving large beasts inherited most of our fundamental protein designs from our microorganism ancestors (or perhaps swiped them from viruses). The much faster evolution of microorganisms means that they are more creative when it comes inventing new protein families and functions. We are still running a slightly tweaked version of an ancient protein operating system, while modern microorganisms are running the up-to-date version.
No regulations? So if I decide that I can't pay my debts, I can just announce that I am defaulting, free of those pesky regulations that might enable my creditors to attach my assets or garnish my wages.
For the most part, the $.99 books on Amazon are from authors who are trying to build an audience. For the most part, they are not up to the quality of a full-price book in editing or proofreading, but readers understand the tradeoffs of a $0.99 book. This is a good thing, in my opinion, as it makes it easier for talented young authors to get a start, but for an author that I know and like, I'm perfectly willing to pay a few bucks more for a more polished work.
Another good thing about ebooks is that it makes it possible for authors to keep their backlist in print and offer discounts on these older works. Again, this helps to bring in new readers, some of whom will hopefully be enthusiastic enough to pay full price for the author's more recant works. The "first one is (almost) free" deal works for authors as it does for drug dealers.
In other words, these are loss leaders. But professional editing and proofreading, promotion, and translation into other languages, not to mention advances to authors so that they can afford to write as a full-time profession don't come cheap. So while there will be deals on older books and books by new authors, don't expect prices to drop drastically for new books by established authors.
I pretty much agree with this review. I enjoyed it, but thought that it came off a bit amateurish and I doubt if it will have much appeal to people who are not already fans of the strip.
Nonsense. To begin with, a run of an accurate physical model of a chaotic process is not a "wrong" prediction, it is an accurate prediction given the starting conditions. Therefore, if the model is run with starting conditions that reflect the statistical distribution of those conditions in the real world (which can readily be measured), it is necessarily the case that the distribution of the output will reflect the distribution of the chaotic process in the real world. No assumptions whatsoever regarding "linearity" are involved. Indeed, as I've pointed out to you multiple times, statistics was developed as a way of modeling real world variability that most commonly arises out of chaotic physical mechanism. Indeed, the laws of thermodynamics arise out of statistical regularities of chaotic physics.
And of course, you were quite happy to accept statistical analysis when (in your mistaken understanding of significance testing) you thought that it rejected global warming. Now that you discover that it doesn't give you the answer that you would like, you've decided that statistics is invalid.
Riiiight. And which specific physical processes do you imagine to have a billion year relaxation time? If the earth were storing appreciably more energy than it was receiving from the sun for a billion years, it would be molten, because the second law dictates that any physical process (including your hypothetical magical energy battery) is going to leak energy in the form of heat.
The statistical null hypothesis of constant temperature is easily rejected. So this is just false.
On the contrary, nobody to date has come anywhere close to explaining temperature changes in the past arising from factors such as changes in the sun's output or the earth's orbit, temperatures on other planets, responses to "natural experiments" such as volcanoes, or even explaining why the earth is not much colder than it is, without a substantial role for CO2--a role that was predicted over 100 years ago based upon basic radiation physics. And the best you can do is appeal to imagined magical properties of chaotic mechanisms.
Except that you didn't show that the 1988 model was "less accurate" by any valid statistical test. These models are designed to forecast long-term climate trends, not short-term ( 15 years or so) weather fluctuations.
The nonsensical expression "simulated variable" does not occur anywhere int he passage that you quoted. So that's a FAIL.
Good, you are finally beginning to understand what I've explained to you a couple of times already. Chaotic systems can be simulated physically (there are some chaotic systems that have fairly trivial physics) to any desired degree of precision. But in practice, such simulations are only useful for exact prediction over the short term, because long-term prediction would require a degree of accuracy in the starting conditions that is not achievable with real-world measurements. But such models can still be useful over the long term for monte-carlo analysis (i.e. by doing a lot of runs with slightly different starting conditions) to determine the statistical properties of the system.
Sure, there is stored energy, but none of these energy reservoirs are infinite in capacity, and there are consequences to pumping more energy into them, and all of the energy ultimately has to end up as heat, due to the Second Law. The ones that equilibrate extremely slowly can only affect climate behavior over the very long term, and the ones that equilibrate rapidly come to steady state. So none of this is a major obstacle to physical modeling. Year to year variations due to chaotic behavior can be modeled statistically even if they can't be simulated exactly.
Why would I have preconceptions? Debating how best top characterize the degree of accuracy of a 1988 paper is a bit like debating whether the 1998 Yankees were better than the 2011 team. It's the sort of thing one might discuss for a few moments of idle amusement, but not exactly a matter of great concern. Continually attacking an old paper seems very odd to me as a scientist. Scientists don't think this way. If you think there are weaknesses in a study, you demonstrate it by doing a better job. And certainly there have been a lot of research groups that have developed their own models since Hansen's early work. The only people I see doing this thing are cranks: creationists attack Darwin; germ theory denialists attack Pasteur; HIV/AIDS denialists attack Gallo. And global warming "skeptics" attack the early work of Hansen or Mann. Perhaps you can explain the motivation for me. Is it out of a misunderstanding of scientific thought, and a mistaken belief that the whole field will collapse if errors are found in this early work? Or is it just personal anger at these researchers for their contributions in getting the whole field started? Certainly, a lot of posts that I see on Climateaudit or WUWT seem to exhibit a level of personal animus that strikes me as frankly bizarre.
This strikes me also as very strange. Those 3 lines reflect completely different scenarios in terms of CO2 control. Are you asking me to make a guess as to the politics of future CO2 control? And why make projections based on a decades-old paper when the field has advanced considerably since then? Not only have the models been refined, but computing power has increased, so that it is not more feasible to run models repeatedly with slightly different starting conditions to get a better idea of expected weather variability around the overall trend. So if I actually wanted to make a projection, I'd guess that it temperatures would tend to track somewhere within range estimated from the ensemble of model runs. But if you insist on using an out-of-date model, I'd say that over the long-run temperatures would probably track somewhere between Hansen's A and C scenarios, since these represent fairly extreme assumptions regarding CO2 mitigation that are unlikely to be realized in practice. These days, it is thought that Hansen's model had the climate sensitivity a bit high, but not so much that the temperatures are likely to track outside this range for long.
More foolishness. The standard deviation is just a mathematical equation. It can be calculated for any series, although its meaning and practical usefulness depend upon the nature of the series.
The notion that statistics cannot be applied to chaotic systems is also foolish. In fact, most of the things to which we apply statistics are chaotic in a physical sense.
Riiiiight. Please quote any paragraph in which I used the nonsensical expression "simulated variable."
Nope. A physical model is an accurate model of the physics. That does not necessarily make it useful. And it may be predictive in more than one way. A physical model of a chaotic system is predictive of the exact behavior of the system over only a short span of time, because of sensitive dependence upon initial conditions--i.e. the measurement precision required for long-term exact prediction is unattainable. However, such a model could still be used to predict the statistical properties of that system over longer time spans. Of course, with dice, that is more simply done with a purely statistical model than by monte-carlo modeling with a chaotic physical model, but for many natural systems the latter is the only approach available, because many natural systems lack the kind of simple symmetries that permit the construction of a purely statistical model of dice rolling from first principles.
Not a problem. A large sensor is physically averaging the Brownian impact energies rapidly, because it is large enough to experience a large number of impacts in a short period of time. A small sensor will experience fewer impacts per unit time, but you can achieve the same results (albeit with lower time resolution of rapid temperature changes) by mathematically averaging its response over a longer period of time. It's all just simple averaging, and analysis of the variance will tell you what period of time is required to yield an estimate of the temperature that is reproducible within desired statistical limits.
Considering that Hansen's model predicted global warming before it was evident in the temperature record (the strongest confirmation of a theory is when it predicts something that you don't already know), and that more than two decades of refinement has yielded models that are in qualitative agreement with its overall conclusions in terms of predicting a worrisome degree of warming, I'd say that qualifies as "quite good" by scientific standards. After all, we know that no model is perfect (that is, after all, why we call them models); the question is whether a model is good enough to tell you what you need to know. As RealClimate points out, Hansen's model "has out-performed any reasonable naive hypothesis that people put forward in 1988 (the most obvious being a forecast of no-change)."
One thing that scientists look at is the range of variation of different climate models, or multiple runs of a single model.
This is discussed in the IPCC reports that I referred you to previously. See here, here, and here, for example. Additional explanation can be found here
The temperature record has a standard deviation. It is a simple mathematical calculation, as you've described.
It seems that you are throwing around terms that you do not actually understand. A variable is a mathematical construct. How can it be "simulated"?
I suspect that this is another term that you do not actually understand. Physical modeling of the roll of the dice can readily be done, with no randomness involved. It's pretty straightforward physics. But it ends up having such a sensitive dependence on boundary conditions that such a model is pretty much useless for practical purposes--a statistical description turns out to be more useful in practice, for dice as for many phenomena in the real world (e.g. short term weather variations).
I can't help notice that you were perfectly happy to talk about statistical significance until I explained to you that you had the definition wrong, and that it did not support your argument. Then you started arguing that statistical analysis is invalid when it comes to climate. This is a dead giveaway that you are thinking in an emotional, biased way, rather than rationally. Scientists learn early in their training to be alert to this kind of cognitive error, which even intelligent people sometimes make. Indeed, much of the discipline of science--statistical analysis, mathematical modeling, peer review--is designed to protect us from fooling ourselves in this way.
We do it routinely. For example, when you estimate that there is a one in 36 chance of throwing snake eyes with two dice, you are engaging in statistical modeling of a physical process.
Above vs. below is an incorrect, and usually misleading, way to look at it. Statistically speaking, the actual temperatures are more likely to be above or below the expected trend than exactly on it, because climate models do not perfectly simulate factors (e.g. volcanic eruptions) that influence temperature on a short time span of a decade ago. You have to do an appropriate statistical test taking into account the uncertainties of both the predicted trend and the measured temperatures. From this point of view, the agreement is well within the expected range of variation.