And an offset of the mean from the true value will not impair your ability to accurately measure trends over time.
I'm not being clear, am I? Help me out here with the correct vocabulary -> you've got yourself a yardstick, and you want to tell if a screwdriver has increased in length by one nanometer. This isn't an offset problem, this is a problem.
For example, take the equation of a line, y=mx+b, where you can chose any numbers you want for m and b. From the equation, calculate a series of y values for various values of x (corresponding to different times), do a linear regression to obtain an estimate of the slope m
Not following you here -> you said I could choose m. Now that I've arbitrarily chosen it, why do I need to estimate it?
Calculate the mean and standard deviation for your estimates of the trend slope for each number of samples.
Again, not following. y=mx+b, where I get to choose m and b, is the equation of a straight line. No estimation is required at any point.
I'm a scientist. I do this sort of thing all the time. It absolutely works.
So what kind of science do you do that allows you to measure nanometers with a yardstick? You've definitely got a nobel prize coming if you've figured that out.
Take a number whose value you know, add normally distributed random noise of whatever magnitude you like.
Because all noise is normally distributed, right? Look, I've no doubt your computer model would work to demonstrate your point (I've done that kind of stuff many times in the past), but your model is not an accurate analogy to the real world. A temperature station does not take 10 million measurements at 12:00 on the first of July - it takes one. Once you've moved past that moment, you can't take another measurement of it to improve your accuracy, even if the error distribution was normal. Take a thousand temperature stations, and a hundred years, and you still don't increase your resolution, because you're not doing your measurements at the same frozen point in time (which, essentially, is what your simple computer model will do). At the root, you've got a problem with having to make too many assumptions to reduce the uncertainty of your results. a + b + c = 0, now tell me what a is, to the 6th decimal point.
But even that aside, you've got misplaced faith in statistics to show anything but correlation. We've all seen those studies that show that this, that or the other correlates to a rise in rectal cancer, but this is not causality. Now causality might even go against common sense (i.e., does exercise make you skinny or does being skinny make you exercise - and the answer is not what you think), but no amount of statistics can bring us any closer to knowing which direction.
Simply put, the assertion that somehow we can take a low-resolution temperature record, computer models with hard coded ex post facto assumptions and lots of missing variables, and come up with a prediction with any sort of greater accuracy than the weakest link, is silly on its face.
Well, I haven't seen the lost CRU data, but the temp record sheets do vary a lot -> some have the added fields as you note, but others are simply manual temp measurements logged by someone...or more often, not logged by someone, leaving some pretty long gaps here and there.
Here's a breakdown of the historical numbers on weather stations:
Seriously, though, if I was running a program that was supposed to collect data from hundreds, if not thousands of stations, and let's say worst case scenario these people were sending me paper forms, I'd still keep the originals around, either in those paper files or as data files (which would probably have been of reasonable size, even back then). At the very least, for the "value-added" data, I'd have recorded whatever adjustments were made, and saved that somewhere, so we could recreate the original data.
Now, if there had been some sort of flood of the computer room, or library, or some other natural disaster, I could be more forgiving.
Boy it would be nice if all errors were randomly distributed along a bell curve - we could use yardsticks to measure how many nanometers there are between NAND gates on an i7 chip.
Saying it again doesn't make it right. Let's apply your sad logic to your hair growth. I have a hypothesis that it grows an extra micrometer every time you say something stupid. The null hypothesis is that your hair never changes. Therefore, my hypothesis is correct, until you can build a better model.
I call horsepucky.
Rather, statistical evidence is accumulated which makes a hypothesis more or less likely.
Um, no. Take again the "all swans are white" hypothesis. Searching for, and accumulating more and more incidences of white swan observations does nothing to make the hypothesis more likely. Searching for just one black swan, and failing miserably, is what can expand our knowledge. And all it takes is one to falsify the hypothesis.
So it is always a matter of competing hypotheses.
No, it's not. That's the last refuge of a creationist claiming, "you can't explain this gap, therefore my competing hypothesis must be true"! A hypothesis can be validly refuted without resorting to "therefore god/man did it". Again, think about the whole idea of convicting someone for murder, because even though he has an airtight alibi, he hasn't produced the actual murderer for you.
The models predict that if the increase in temperature is initiated by something other than addition of CO2 to the atmosphere--an increase in solar output, for example--then CO2 increase will lag the temperature increase. On the other hand, if CO2 is added directly to the atmosphere, then the models predict that the temperature increase will lag the CO2 increase. To put it simply, there is a positive feedback arising from the basic physics of CO2: increased atmospheric CO2 increases temperature, which reduces CO2 solubility in the ocean, which increases atmospheric CO2, which increases temperature, etc. Which comes first depends upon which starts the cycle.
Think a little more carefully. You're asserting that all prior lags of CO2 to temperature increase in the historical record are because of solar variation, but that magically, after that solar variation, the added CO2 did not behave as "outside added" CO2, and cause further increase?
How, pray tell, do the CO2 molecules know when to stop heating in an ultimate feedback loop turning our planet into a raging fireball?
Between your magical CO2 particles and your sad devotion to the idea that any foolishly presented hypothesis is impervious to critique without a competing positive hypothesis, I don't know you you remember to breathe.
Now, semantic lesson aside, you've dreadfully abused the notion of standard deviation. You've just made the ridiculous case that if you took a 640x480 pixel pictures of someone a mile away, you could figure out the length of his nose, so long as you took that picture a million times.
Seriously, get yourself a balance scale that has a measurement resolution of 1g, and tell me how many micrograms one of your eyelashes is. Take as much time as you want.
Not sure if I buy the math there. I mean, you've definitely got more than one day per line of text at even just 80 columns, and we haven't even talked about compression.
Insofar as paper, certainly the CRU never copped to having multiple truckloads of paper, and though we have thousands of weather stations around the world, only a bare handful have continuous records going back over 100 years. I would imagine back in the 70s and 80s they'd use filing cabinets just like anyone else.
The real problem with the CRU, though, is that they claimed they had their "value-added" data, but had misplaced the originals. So they had one file cabinet, but not two. Or one truck, but not two. At the very least they were negligent, and at the very worst they were hiding something. And we'll never know for sure now.
First off, this isn't a prediction, but rather a question of historical fact.
Well, strictly speaking, you can make predictions on what you would find in the historical record (like the rabbit fossil in the Cambrian era that would falsify evolution). I would assert that any theory of AGW should have something interesting to predict about the history of climate.
It seems to me that CO2 concentration is unprecedented however.
Actually, it isn't. We're at around 350ppm, and we've got historical evidence showing it as high as 6000ppm (granted, hundreds of millions of years ago, but we've seen as high as 1000ppm during the last geological era.
Third, what does the lead/lag of CO2 vs temperature have to do with the magnitude of the warming trend?
Causality. You cannot have a lag of CO2 levels if it is a cause, just like you cannot assert that children create their mothers.
Finally, I would just mention that the rate of change is probably the important metric here, not the absolute temperature.
Agreed, and the rate of change is not unprecedented either.
Also I'm wondering why you're not mentioning some of the clearly obvious falsifiable predictions: Like the fact that earth-climate-models are generated using assumptions about how CO2 affects radiation in the atmosphere, and the implications of models can be compared with current climate data?
The fact that computer models are built with assumptions could possibly lead to falsifiability, if it was asserted that a failure of the model to predict let's say, next year's temperatures, falsified the theory. Unfortunately, the typical response is an ad hoc adjustment (a hard coded fudge factor), which severely reduces the utility of the model in the first place. I would submit that sufficient ad hoc adjustments have been made to the climate models to make their utility minimal at best, and completely misleading at worst.
So what's that "single bit of data" that just kills all hope of AGW? I'm intensely curious.
The killer for me? Well, I'd vote for the lag of CO2 levels, but a close second, which isn't exactly a "single" bit of data, but you could consider it a fatal flaw, is the surface temperature record - http://surfacestations.org/ for more details on that. I'd also lump in with the surface temp record the CO2 ppm metric being used -> Mauna Loa is our standard, which I think is probably a poor way to do the science, since CO2 concentrations, like other gases, are not even throughout the globe. I would expect any model which didn't take into account CO2 concentration variations wouldn't be able to make accurate predictions at all.
GIGO, so if you've got a temperature record that has a maximum resolution of 1 degree C, you certainly can't discern trends of.3 degrees C (just like you can't take any arbitrary digital camera footage and zoom into see that fuzzy guy in the background in full detail).
Now, I'll admit the second one is essentially a spamming of scattered nitpicks, but death by a thousand paper cuts is death nonetheless.
Of course, a lot of literature refuting the AGW hypothesis has been suppressed, either by implicit or explicit pressure, but I would suppose since ClimateGate we'll be seeing a more fertile field for skeptical publication.
That all being said, let's remember that "peer reviewed" does not mean "peer approved" or "peer consented to" or "peers think this is right" -> it just means that peers have decided it's worthy of publication.
You've also got the whole IPCC relying on non-peer reviewed literature (AmazonGate, GlacierGate, etc). If you want some serious answers on the link between the data they've destroyed or refused to release and claims made, I'd suggest trolling around at http://wattsupwiththat.com/ - they've got pretty savvy comments on a lot of the posts there.
So the "null hypothesis" of climate change is that climate is constant and unchanging throughout time.
Are you high? Seriously, did you just do a big whopping hit on something? The null hypothesis of climate change is that any changes in the system do not require any human activity to drive them. We have the fact of the historical record which has constantly changed, up and down, without humans. The null hypothesis is that what has happened before (constant change) shall continue to happen (constant change) without resorting to "man did it".
At this point, you enter the realm of competing hypotheses, and hypotheses must be compared on equal grounds--the "burden of proof" is the same for all.
Um, no. I don't need to have a competing hypothesis in order to falsify another hypothesis. We'll give you a simple case - I don't need to prove that some victim was murdered by someone else specifically if I can give an alibi that excludes me from being the murderer. You seem to think that anyone who wants to avoid a murder rap must present the actual murderer in court before being acquitted - and this clearly defies any sense of rational thought.
To show that the errors in a model invalidate the conclusions, you need to produce a corrected model without those errors and demonstrate that the conclusions are different.
No, all I need to do is prove that the model was in error. Adding ex post facto ad hoc corrections can only work for so long before you've started violating Occam's razor, and developed a theory of so many caveats that it really predicts nothing.
You know very little about the existing models if you don't know that those models do in fact predict that depending upon conditions, CO2 can either lead or lag temperature change
Are you kidding me? This is like "heads I win, tails you lose"! Please, explain under what conditions CO2 would lead a temp increase, and under what conditions CO2 would lag a temp increase. I assume that if we found a contradiction to those conditions, though, you'd finally admit your theory was wrong? Or would you add another fudge factor to your model for that single case?
Apologies to the grammar nazi for the improper use of "rate".
That being said, your fantasy that enough imprecise measurements can somehow yield a very precise measurement beyond the resolution originally sampled is like those times when Chloe Obrien just needs enough time to put that grainy, pixellated image through a filter in order to generate a crystal clear picture of the bad guy in the photo. You simply cannot generate improved resolution out of thin air, and you simply cannot generate a.01 C resolution if your measurement network can only distinguish to 10 C.
So, instead of "rate", I should've used the word "accuracy". If you've got a temperature measurement network that only has accuracy to the 10s of degrees C, you'll never be able to spot a trend of.01 degrees C, no matter how many measurements you carry out.
by taking a sufficient number of measurements you can get your errors down as low as you want.
Wrong. Go back to statistics 101, please. If I've got a thermometer that has an error rate of +/- 10 degrees, I can take a million measurements and not be able to assert an accuracy of.01 degrees. Your assumption that +/- 10 degrees has some sort of bell curve that you can drive to the top of is unsupportable.
There are always results reported that do not appear to fit with theory--any theory that you might choose.
Show me one for evolution.
It is easy--and basically meaningless--to nitpick somebody else's theory if you don't have to offer an alternative.
It may be easy, but it's not meaningless. I think your confusion here is your misunderstanding of "an alternative". The null hypothesis of climate change is that all variation is natural. This is a reasonable null hypothesis to hold, and requires no particular proof. The null hypothesis AGW supporters seem to claim is, "all climate change that is not clearly identified as natural must be man made". This is not reasonable, and mimics the "intelligent design" position ("all missing links between fossils must've been done by god").
Genuine criticism here does not need to offer an alternative.
Show me an alternative mathematical theory that is equally compatible with the data.
Again, you misunderstand. Your assertion that any area of ignorance automatically means that "man did it" is the same thing as creationists insisting that any gaps in the fossil record mean "god did it". Put another way, you seem to want to build a theory that is strengthened by ignorance, in the same way creationists do. Your theory (as with creationism) becomes less and less useful as we learn more and more about other natural drivers. This isn't good science, if it's science at all.
show me that you can produce a mathematical model of climate, based on established and testable physical principles, that does not predict global warming in response to increased CO2, and is still consistent with the existing data on historical climate change, as well as "natural experiments" such as climate perturbations in response to volcanic eruptions.
All I have to show is that your mathematical model, implicating man-made CO2, has errors in it that would invalidate the conclusions. That's trivially easy, but the typical response is, "well, we'll just make a tiny arbitrary adjustment to the model, and claim its still right". In the end you have so many hard coded fudge factors that your theory really doesn't explain anything.
Chew on this though -> the proxy record shows CO2 concentrations lagging temp changes by 800 years, and CO2 concentrations many times higher without runaway warming. Explain how the models can be run backwards, fail to accurately depict the history we know of, yet should be trusted going forward.
Look throught the literature on any field, and you can find data that is inconsistent with theory--whatever theory you happen to choose.
Show me a fossil rabbit in the Cambrian.
Who doesn't have a falsifiable theory? The AGW critics.
AGW critics don't need to have a falsifiable theory -> they're not making the assertion. The burden of proof here clearly belongs to the proponents of AGW.
There are measurment errors, statistical anomalies, unrecognized procedural errors.
I think what you're missing here, though, is that this applies to the work done by AGW supporters. For measurement errors in particular, see http://surfacestations.org/ The problem that AGW folks have is that the nitpicks and flaws pointed out to them represent some very important impacts on their conclusions. If you have error bars of measurement that are greater than 5 degrees C, how can you predict a change of.05 degrees C? If you cannot sustain your theory without erasing the MWP, how can we trust you haven't just found another statistical anomaly and interpreted too much into it?
Look, on the one hand you want me to be skeptical of data that refutes AGW, but you won't apply the same scrutiny to data that supports AGW. The simple fact of the matter is that the scientific view should always be skeptical, and its a shame the AGW supporters have turned that into an insult.
I haven't heard of a single fossil placement that so grossly violates any possible theory of evolution as a rabbit in the Cambrian, but if you come up with a single example, I'd be very interested. I would imagine any lack of explanations on the part of biologists are of the minor sort rather than the major sort.
Regarding your physics problems, and the search for a grand unified theory, I think your analogy to AGW doesn't quite hold though -> let's take the standard model and general relativity. The problem here is that AGW doesn't caveat it's model in quantitative ways the way we caveat between the atomic scale and the galactic scale, nor does it provide any sort of falsification test for where we would draw that caveat. For example, what falsifiable hypothesis would we put forward that AGW works at the hemisphere level, but not the global level? Or that AGW works in 100 year increments but not 20 year increments?
I guess the second thing is that nobody has suggested a worldwide experiment in economics based on whether or not dark matter exists - which helps keep dark matter skeptics and dark matter supporters from becoming torn into "good" and "bad" camps by the media. When you've got a theory upon which you premise a dramatic change in the lives of every human on the planet, suddenly the stakes get higher and falsifiability becomes much more important.
I would argue AGW fails the Lakatos test too -> it certainly hasn't produced many novel predictions at this point (frankly the error bars are just too big).
What do you mean, "you just have to ask whether something is true or not"? It sounds as if you're propounding a point a view that says that "what is science" is a relative question determined by perspective without any formal limits...could intelligent design be called science by some stretch of the imagination, and why?
Then help me out here - let's pretend for a moment that "Popperism" in the absolute sense (naive falsifiability) is our common standard that everyone can agree on, but that there are alternatives that you could describe that would violate the "Popper Principle" that we might all agree are good science? I'm challenged to think of a single example of science that would be universally considered "good science" without being falsifiable.
I suppose in my Popperist way, I'm asking you for the one refutation to my theory, rather than bothering to come up with a list of "good science" that does fit Popperism (evolution for one - find a rabbit in the pre-Cambrian to falsify).
I'll talk to you in 20 years. Or can we just wait another 5 since we've had 15 years of cooling?
The problem with the precautionary principle is that even if your prediction is right, you've got no reason to believe that your suggested remedies will a) do anything to help, b) not do anything to harm. The precautionary principle was notoriously applied in regards to dietary fat (Ancel Keys, may he burn in hell), and we've been suffering the results of this nationwide nutritional experiment for the past 30 years of low-fat/low-calorie/exercise dogma. The result, an increase in obesity, diabetes, heart disease, cancer, alzheimers, and other chronic diseases. The real culprit? Carbohydrates.
So the problem with your belief is that even if your hypothesis is right, we have no reason to believe your proposed action would work and not harm us all greatly. Given the gravity of the situation, it seems reasonable to wait 20 years before deciding upon a course of action that may destroy humanity.
1 - Predicting an increase is easy -> what were the error bars around the prediction. Would Hansen have been falsified if the increase was slightly less or slightly more than his error bars? And please, be honest with yourself.
2 - Not sure if this one really counts -> if the arctic and antarctic warmed slower, and the tropics warmed faster, but we still had the increase of temperatures, would this have falsified the idea that man-made CO2 was causing a temp increase? And again, error bars, please. Would any of the models have been falsified if the arctic and antarctic were just barely below or barely above the error bars of the prediction?
3 - Same thing, error bars.
4 - Do you have one that would prove that the increase was due to man made activity rather than natural factors? Or is this just a base assumption?
5 - Same thing, error bars.
So please, be more specific in your falsifiable predictions, and let me know if you'd be willing to mark off which models are bad because the real world data was outside the error bars of their predictions.
Evidence, please. Let's get some idea of how many boxes of paper you're talking about, or how many 5 1/4" floppies -> I think you're talking out of your hat, and that any sufficiently large closet would've done the trick. Back in the 70s and 80s, they didn't have nearly the data collection network we have today either.
Now, I'll agree, they might not have been able to mail all the data to anyone who requested it, but not keeping track of it? That's just plain inexcusable.
Here's my straw man of AGW, in terms of falsifiability:
1) The warming trend in the late 20th century is unprecedented. This can be falsified by any historical record which shows CO2 rises lagging temperature rises;
2) The warming trend in the late 20th century is caused by man-made CO2 emissions, which create a tipping point with a positive feedback loop. The critical point is 350ppm. Any higher, and we will have constantly increasing temperatures. This can be falsified by either a plateau in the increase of temp or a decrease in temp while we increase CO2 levels, or by showing that any time we had > 350ppm in the fossil record, the temperature ran away into a positive feedback loop and left the earth a burning husk.
Let me state once again, finding more data that supports your theory does not protect it against even a single bit of data that refutes it. Science != consensus. Scientists in the Renaissance could have insisted that gravity accelerated heavier masses more than lighter ones, and gotten loads of evidence to support them. A bowling ball and a feather. Paper and a stone. A bigger paper and a bigger stone. Ad infinitum. None of that data would refute the large bowling ball and small bowling ball falling at the same rate off of some tower.
Science is the highly rigorous application of skepticism. If you can't be skeptical of your own ideas, you really aren't cut out to do science, or even think scientifically.
1) Show me the unit tests and the code coverage statistics;
2) Run the analysis on HARRY_READ_ME.TXT.
Defect density is a notoriously poor metric, and I'd bet that LOC here includes a bunch of fluff data hard coded in which artificially lowers any defects/LOC.
And as before, adding to your enormous pile doesn't scientifically deal with even a single refutation. It's an unfair game when skeptics have it so easy, but that's the game of science.
So the assertion that climate modeling is "not science", because, given the unsupported assertion that climate modelers don't look for counter-evidence, it doesn't fit some abstract idea of what science should be, is worth pretty much nothing.
Yes, it does. Asserting that Popper's falsifiability criterion is not as simple as just being naively falsifiable is one thing. Asserting that additional complexity in the understanding of falsifiability, or demarcation, means that AGW gets a free pass is something else. You come close to admitting that yourself ("someone can always come up with some sort of explanation which preserves the original theory"), but then fail to illustrate why AGW is still a useful theory which makes useful predictions that could be scientifically refuted.
Your citation of "peer-review" seems to fall victim to the "talking-out-of-ass" syndrome as well -> the standard for peer review is not that all the peers that reviewed it believe that it is correct, or even probably correct, but simply that it is worthy of publishing. You could reasonably assert that peer review may help us with the demarcation problem, but arguing that peer review makes something patently true is absurd.
On the specific question of AGW, make a real prediction -> how many years, how much CO2, how much temperature. More importantly, can they make any predictions about prior climate? We've got a lot more past at our fingertips than future, and AFAIK, none of the models work when you run them backwards.
More importantly, let's get real measurements. "average global temperature" and "CO2 concentration" in the atmosphere is bandied about as if someone sticks a super thermometer out their window, and gets the same answer as someone on the other side of the planet. If we don't have a useful standard for the prediction (you use one method of calculating "average global temperature", with fudge factors written into your code to decrease temps in the 1930s, and to increase them from the 1970s on, someone else uses the satellite record, etc), then you can always assert that the data being used is the problem, not your theory.
Climate models are wild suppositions at best. RealClimate's worship of Hansen aside (take a closer look at the error bars in your reference my friend), I haven't heard an AGW support yet say either, "This is the right model, and the other 500 climate models are wrong as you can plainly see" (yes, virginia, there are lots of climate models out there, and they don't all make the same predictions), or "if this model is wrong in 20 years, I'll admit my theory was wrong". At best, the response is, "let me adjust the model to fit, my theory is still correct".
The real problem here is that the pro-AGW group is going about science all wrong -> they're trying to prove their point with more data that buttresses their theory. They look around, find scads of data that fits their model, and with enough data, declare the "debate is over".
Except that's not science. It's not even bad science, it's just simply not science. You don't prove your point by finding more data that agrees with you, you prove your point by looking hard for data that does *not* agree with you, and not finding it. It's a subtle point, but one that is profoundly misunderstood by the masses. You can always find more data to support your theory, if you're willing to ignore data that does not support it.
So the anti-AGW folk have it easy -> they just need to "cherry pick" data that refutes the AGW theory. Their search for data has a much, much lower bar because they don't need to have 10,000 refutations, or a million refutations, they just need one refutation. Just one bit of data that breaks the model, and the model must be changed, or abandoned.
The bigger problem of all this is that when it comes right down to it, the pro-AGW folks haven't really stated a falsifiable theory. They have in fact scrupulously avoided a falsifiable theory (warm winter? Global warming! cold winter? Global warming!), and have instead created a political movement rather than a scientific discussion.
For those pro-AGWers who want to mod down, fine. But do me a favor and come up with a falsifiable hypothesis while you're at it.
Slashdot Mirror
I'm not being clear, am I? Help me out here with the correct vocabulary -> you've got yourself a yardstick, and you want to tell if a screwdriver has increased in length by one nanometer. This isn't an offset problem, this is a problem.
Not following you here -> you said I could choose m. Now that I've arbitrarily chosen it, why do I need to estimate it?
Again, not following. y=mx+b, where I get to choose m and b, is the equation of a straight line. No estimation is required at any point.
So what kind of science do you do that allows you to measure nanometers with a yardstick? You've definitely got a nobel prize coming if you've figured that out.
Because all noise is normally distributed, right? Look, I've no doubt your computer model would work to demonstrate your point (I've done that kind of stuff many times in the past), but your model is not an accurate analogy to the real world. A temperature station does not take 10 million measurements at 12:00 on the first of July - it takes one. Once you've moved past that moment, you can't take another measurement of it to improve your accuracy, even if the error distribution was normal. Take a thousand temperature stations, and a hundred years, and you still don't increase your resolution, because you're not doing your measurements at the same frozen point in time (which, essentially, is what your simple computer model will do). At the root, you've got a problem with having to make too many assumptions to reduce the uncertainty of your results. a + b + c = 0, now tell me what a is, to the 6th decimal point.
But even that aside, you've got misplaced faith in statistics to show anything but correlation. We've all seen those studies that show that this, that or the other correlates to a rise in rectal cancer, but this is not causality. Now causality might even go against common sense (i.e., does exercise make you skinny or does being skinny make you exercise - and the answer is not what you think), but no amount of statistics can bring us any closer to knowing which direction.
Simply put, the assertion that somehow we can take a low-resolution temperature record, computer models with hard coded ex post facto assumptions and lots of missing variables, and come up with a prediction with any sort of greater accuracy than the weakest link, is silly on its face.
Well, I haven't seen the lost CRU data, but the temp record sheets do vary a lot -> some have the added fields as you note, but others are simply manual temp measurements logged by someone...or more often, not logged by someone, leaving some pretty long gaps here and there.
Here's a breakdown of the historical numbers on weather stations:
http://climateaudit.org/2008/02/10/historical-station-distribution/
Seriously, though, if I was running a program that was supposed to collect data from hundreds, if not thousands of stations, and let's say worst case scenario these people were sending me paper forms, I'd still keep the originals around, either in those paper files or as data files (which would probably have been of reasonable size, even back then). At the very least, for the "value-added" data, I'd have recorded whatever adjustments were made, and saved that somewhere, so we could recreate the original data.
Now, if there had been some sort of flood of the computer room, or library, or some other natural disaster, I could be more forgiving.
But shouldn't 2009 have been increasingly hotter, since CO2 (as measured upon the peak of Mauna Loa) has been increasing all this time?
Look, we'll all be around in 20 years, and if slashdot is still running, we'll all have a good laugh over this.
Boy it would be nice if all errors were randomly distributed along a bell curve - we could use yardsticks to measure how many nanometers there are between NAND gates on an i7 chip.
Saying it again doesn't make it right. Let's apply your sad logic to your hair growth. I have a hypothesis that it grows an extra micrometer every time you say something stupid. The null hypothesis is that your hair never changes. Therefore, my hypothesis is correct, until you can build a better model.
I call horsepucky.
Um, no. Take again the "all swans are white" hypothesis. Searching for, and accumulating more and more incidences of white swan observations does nothing to make the hypothesis more likely. Searching for just one black swan, and failing miserably, is what can expand our knowledge. And all it takes is one to falsify the hypothesis.
No, it's not. That's the last refuge of a creationist claiming, "you can't explain this gap, therefore my competing hypothesis must be true"! A hypothesis can be validly refuted without resorting to "therefore god/man did it". Again, think about the whole idea of convicting someone for murder, because even though he has an airtight alibi, he hasn't produced the actual murderer for you.
Think a little more carefully. You're asserting that all prior lags of CO2 to temperature increase in the historical record are because of solar variation, but that magically, after that solar variation, the added CO2 did not behave as "outside added" CO2, and cause further increase?
How, pray tell, do the CO2 molecules know when to stop heating in an ultimate feedback loop turning our planet into a raging fireball?
Between your magical CO2 particles and your sad devotion to the idea that any foolishly presented hypothesis is impervious to critique without a competing positive hypothesis, I don't know you you remember to breathe.
Apologies to the vocabulary nazi.
Now, semantic lesson aside, you've dreadfully abused the notion of standard deviation. You've just made the ridiculous case that if you took a 640x480 pixel pictures of someone a mile away, you could figure out the length of his nose, so long as you took that picture a million times.
Seriously, get yourself a balance scale that has a measurement resolution of 1g, and tell me how many micrograms one of your eyelashes is. Take as much time as you want.
Not sure if I buy the math there. I mean, you've definitely got more than one day per line of text at even just 80 columns, and we haven't even talked about compression.
Insofar as paper, certainly the CRU never copped to having multiple truckloads of paper, and though we have thousands of weather stations around the world, only a bare handful have continuous records going back over 100 years. I would imagine back in the 70s and 80s they'd use filing cabinets just like anyone else.
The real problem with the CRU, though, is that they claimed they had their "value-added" data, but had misplaced the originals. So they had one file cabinet, but not two. Or one truck, but not two. At the very least they were negligent, and at the very worst they were hiding something. And we'll never know for sure now.
Well, strictly speaking, you can make predictions on what you would find in the historical record (like the rabbit fossil in the Cambrian era that would falsify evolution). I would assert that any theory of AGW should have something interesting to predict about the history of climate.
Actually, it isn't. We're at around 350ppm, and we've got historical evidence showing it as high as 6000ppm (granted, hundreds of millions of years ago, but we've seen as high as 1000ppm during the last geological era.
Causality. You cannot have a lag of CO2 levels if it is a cause, just like you cannot assert that children create their mothers.
Agreed, and the rate of change is not unprecedented either.
The fact that computer models are built with assumptions could possibly lead to falsifiability, if it was asserted that a failure of the model to predict let's say, next year's temperatures, falsified the theory. Unfortunately, the typical response is an ad hoc adjustment (a hard coded fudge factor), which severely reduces the utility of the model in the first place. I would submit that sufficient ad hoc adjustments have been made to the climate models to make their utility minimal at best, and completely misleading at worst.
The killer for me? Well, I'd vote for the lag of CO2 levels, but a close second, which isn't exactly a "single" bit of data, but you could consider it a fatal flaw, is the surface temperature record - http://surfacestations.org/ for more details on that. I'd also lump in with the surface temp record the CO2 ppm metric being used -> Mauna Loa is our standard, which I think is probably a poor way to do the science, since CO2 concentrations, like other gases, are not even throughout the globe. I would expect any model which didn't take into account CO2 concentration variations wouldn't be able to make accurate predictions at all.
GIGO, so if you've got a temperature record that has a maximum resolution of 1 degree C, you certainly can't discern trends of .3 degrees C (just like you can't take any arbitrary digital camera footage and zoom into see that fuzzy guy in the background in full detail).
Now, I'll admit the second one is essentially a spamming of scattered nitpicks, but death by a thousand paper cuts is death nonetheless.
Well, here's a start:
http://www.uoguelph.ca/~rmckitri/research/trc.html
Of course, a lot of literature refuting the AGW hypothesis has been suppressed, either by implicit or explicit pressure, but I would suppose since ClimateGate we'll be seeing a more fertile field for skeptical publication.
That all being said, let's remember that "peer reviewed" does not mean "peer approved" or "peer consented to" or "peers think this is right" -> it just means that peers have decided it's worthy of publication.
You've also got the whole IPCC relying on non-peer reviewed literature (AmazonGate, GlacierGate, etc). If you want some serious answers on the link between the data they've destroyed or refused to release and claims made, I'd suggest trolling around at http://wattsupwiththat.com/ - they've got pretty savvy comments on a lot of the posts there.
Are you high? Seriously, did you just do a big whopping hit on something? The null hypothesis of climate change is that any changes in the system do not require any human activity to drive them. We have the fact of the historical record which has constantly changed, up and down, without humans. The null hypothesis is that what has happened before (constant change) shall continue to happen (constant change) without resorting to "man did it".
Um, no. I don't need to have a competing hypothesis in order to falsify another hypothesis. We'll give you a simple case - I don't need to prove that some victim was murdered by someone else specifically if I can give an alibi that excludes me from being the murderer. You seem to think that anyone who wants to avoid a murder rap must present the actual murderer in court before being acquitted - and this clearly defies any sense of rational thought.
No, all I need to do is prove that the model was in error. Adding ex post facto ad hoc corrections can only work for so long before you've started violating Occam's razor, and developed a theory of so many caveats that it really predicts nothing.
Are you kidding me? This is like "heads I win, tails you lose"! Please, explain under what conditions CO2 would lead a temp increase, and under what conditions CO2 would lag a temp increase. I assume that if we found a contradiction to those conditions, though, you'd finally admit your theory was wrong? Or would you add another fudge factor to your model for that single case?
Apologies to the grammar nazi for the improper use of "rate".
That being said, your fantasy that enough imprecise measurements can somehow yield a very precise measurement beyond the resolution originally sampled is like those times when Chloe Obrien just needs enough time to put that grainy, pixellated image through a filter in order to generate a crystal clear picture of the bad guy in the photo. You simply cannot generate improved resolution out of thin air, and you simply cannot generate a .01 C resolution if your measurement network can only distinguish to 10 C.
So, instead of "rate", I should've used the word "accuracy". If you've got a temperature measurement network that only has accuracy to the 10s of degrees C, you'll never be able to spot a trend of .01 degrees C, no matter how many measurements you carry out.
Wrong. Go back to statistics 101, please. If I've got a thermometer that has an error rate of +/- 10 degrees, I can take a million measurements and not be able to assert an accuracy of .01 degrees. Your assumption that +/- 10 degrees has some sort of bell curve that you can drive to the top of is unsupportable.
Show me one for evolution.
It may be easy, but it's not meaningless. I think your confusion here is your misunderstanding of "an alternative". The null hypothesis of climate change is that all variation is natural. This is a reasonable null hypothesis to hold, and requires no particular proof. The null hypothesis AGW supporters seem to claim is, "all climate change that is not clearly identified as natural must be man made". This is not reasonable, and mimics the "intelligent design" position ("all missing links between fossils must've been done by god").
Genuine criticism here does not need to offer an alternative.
Again, you misunderstand. Your assertion that any area of ignorance automatically means that "man did it" is the same thing as creationists insisting that any gaps in the fossil record mean "god did it". Put another way, you seem to want to build a theory that is strengthened by ignorance, in the same way creationists do. Your theory (as with creationism) becomes less and less useful as we learn more and more about other natural drivers. This isn't good science, if it's science at all.
All I have to show is that your mathematical model, implicating man-made CO2, has errors in it that would invalidate the conclusions. That's trivially easy, but the typical response is, "well, we'll just make a tiny arbitrary adjustment to the model, and claim its still right". In the end you have so many hard coded fudge factors that your theory really doesn't explain anything.
Chew on this though -> the proxy record shows CO2 concentrations lagging temp changes by 800 years, and CO2 concentrations many times higher without runaway warming. Explain how the models can be run backwards, fail to accurately depict the history we know of, yet should be trusted going forward.
Show me a fossil rabbit in the Cambrian.
AGW critics don't need to have a falsifiable theory -> they're not making the assertion. The burden of proof here clearly belongs to the proponents of AGW.
I think what you're missing here, though, is that this applies to the work done by AGW supporters. For measurement errors in particular, see http://surfacestations.org/ The problem that AGW folks have is that the nitpicks and flaws pointed out to them represent some very important impacts on their conclusions. If you have error bars of measurement that are greater than 5 degrees C, how can you predict a change of .05 degrees C? If you cannot sustain your theory without erasing the MWP, how can we trust you haven't just found another statistical anomaly and interpreted too much into it?
Look, on the one hand you want me to be skeptical of data that refutes AGW, but you won't apply the same scrutiny to data that supports AGW. The simple fact of the matter is that the scientific view should always be skeptical, and its a shame the AGW supporters have turned that into an insult.
I haven't heard of a single fossil placement that so grossly violates any possible theory of evolution as a rabbit in the Cambrian, but if you come up with a single example, I'd be very interested. I would imagine any lack of explanations on the part of biologists are of the minor sort rather than the major sort.
Regarding your physics problems, and the search for a grand unified theory, I think your analogy to AGW doesn't quite hold though -> let's take the standard model and general relativity. The problem here is that AGW doesn't caveat it's model in quantitative ways the way we caveat between the atomic scale and the galactic scale, nor does it provide any sort of falsification test for where we would draw that caveat. For example, what falsifiable hypothesis would we put forward that AGW works at the hemisphere level, but not the global level? Or that AGW works in 100 year increments but not 20 year increments?
I guess the second thing is that nobody has suggested a worldwide experiment in economics based on whether or not dark matter exists - which helps keep dark matter skeptics and dark matter supporters from becoming torn into "good" and "bad" camps by the media. When you've got a theory upon which you premise a dramatic change in the lives of every human on the planet, suddenly the stakes get higher and falsifiability becomes much more important.
I would argue AGW fails the Lakatos test too -> it certainly hasn't produced many novel predictions at this point (frankly the error bars are just too big).
What do you mean, "you just have to ask whether something is true or not"? It sounds as if you're propounding a point a view that says that "what is science" is a relative question determined by perspective without any formal limits...could intelligent design be called science by some stretch of the imagination, and why?
Then help me out here - let's pretend for a moment that "Popperism" in the absolute sense (naive falsifiability) is our common standard that everyone can agree on, but that there are alternatives that you could describe that would violate the "Popper Principle" that we might all agree are good science? I'm challenged to think of a single example of science that would be universally considered "good science" without being falsifiable.
I suppose in my Popperist way, I'm asking you for the one refutation to my theory, rather than bothering to come up with a list of "good science" that does fit Popperism (evolution for one - find a rabbit in the pre-Cambrian to falsify).
Do you have an example?
I'll talk to you in 20 years. Or can we just wait another 5 since we've had 15 years of cooling?
The problem with the precautionary principle is that even if your prediction is right, you've got no reason to believe that your suggested remedies will a) do anything to help, b) not do anything to harm. The precautionary principle was notoriously applied in regards to dietary fat (Ancel Keys, may he burn in hell), and we've been suffering the results of this nationwide nutritional experiment for the past 30 years of low-fat/low-calorie/exercise dogma. The result, an increase in obesity, diabetes, heart disease, cancer, alzheimers, and other chronic diseases. The real culprit? Carbohydrates.
See http://webcast.berkeley.edu/event_details.php?webcastid=21216
So the problem with your belief is that even if your hypothesis is right, we have no reason to believe your proposed action would work and not harm us all greatly. Given the gravity of the situation, it seems reasonable to wait 20 years before deciding upon a course of action that may destroy humanity.
Wait a tick, just wait a tick:
1 - Predicting an increase is easy -> what were the error bars around the prediction. Would Hansen have been falsified if the increase was slightly less or slightly more than his error bars? And please, be honest with yourself.
2 - Not sure if this one really counts -> if the arctic and antarctic warmed slower, and the tropics warmed faster, but we still had the increase of temperatures, would this have falsified the idea that man-made CO2 was causing a temp increase? And again, error bars, please. Would any of the models have been falsified if the arctic and antarctic were just barely below or barely above the error bars of the prediction?
3 - Same thing, error bars.
4 - Do you have one that would prove that the increase was due to man made activity rather than natural factors? Or is this just a base assumption?
5 - Same thing, error bars.
So please, be more specific in your falsifiable predictions, and let me know if you'd be willing to mark off which models are bad because the real world data was outside the error bars of their predictions.
Evidence, please. Let's get some idea of how many boxes of paper you're talking about, or how many 5 1/4" floppies -> I think you're talking out of your hat, and that any sufficiently large closet would've done the trick. Back in the 70s and 80s, they didn't have nearly the data collection network we have today either.
Now, I'll agree, they might not have been able to mail all the data to anyone who requested it, but not keeping track of it? That's just plain inexcusable.
Here's my straw man of AGW, in terms of falsifiability:
1) The warming trend in the late 20th century is unprecedented. This can be falsified by any historical record which shows CO2 rises lagging temperature rises;
2) The warming trend in the late 20th century is caused by man-made CO2 emissions, which create a tipping point with a positive feedback loop. The critical point is 350ppm. Any higher, and we will have constantly increasing temperatures. This can be falsified by either a plateau in the increase of temp or a decrease in temp while we increase CO2 levels, or by showing that any time we had > 350ppm in the fossil record, the temperature ran away into a positive feedback loop and left the earth a burning husk.
Let me state once again, finding more data that supports your theory does not protect it against even a single bit of data that refutes it. Science != consensus. Scientists in the Renaissance could have insisted that gravity accelerated heavier masses more than lighter ones, and gotten loads of evidence to support them. A bowling ball and a feather. Paper and a stone. A bigger paper and a bigger stone. Ad infinitum. None of that data would refute the large bowling ball and small bowling ball falling at the same rate off of some tower.
Science is the highly rigorous application of skepticism. If you can't be skeptical of your own ideas, you really aren't cut out to do science, or even think scientifically.
1) Show me the unit tests and the code coverage statistics;
2) Run the analysis on HARRY_READ_ME.TXT.
Defect density is a notoriously poor metric, and I'd bet that LOC here includes a bunch of fluff data hard coded in which artificially lowers any defects/LOC.
And as before, adding to your enormous pile doesn't scientifically deal with even a single refutation. It's an unfair game when skeptics have it so easy, but that's the game of science.
Yes, it does. Asserting that Popper's falsifiability criterion is not as simple as just being naively falsifiable is one thing. Asserting that additional complexity in the understanding of falsifiability, or demarcation, means that AGW gets a free pass is something else. You come close to admitting that yourself ("someone can always come up with some sort of explanation which preserves the original theory"), but then fail to illustrate why AGW is still a useful theory which makes useful predictions that could be scientifically refuted.
Your citation of "peer-review" seems to fall victim to the "talking-out-of-ass" syndrome as well -> the standard for peer review is not that all the peers that reviewed it believe that it is correct, or even probably correct, but simply that it is worthy of publishing. You could reasonably assert that peer review may help us with the demarcation problem, but arguing that peer review makes something patently true is absurd.
On the specific question of AGW, make a real prediction -> how many years, how much CO2, how much temperature. More importantly, can they make any predictions about prior climate? We've got a lot more past at our fingertips than future, and AFAIK, none of the models work when you run them backwards.
More importantly, let's get real measurements. "average global temperature" and "CO2 concentration" in the atmosphere is bandied about as if someone sticks a super thermometer out their window, and gets the same answer as someone on the other side of the planet. If we don't have a useful standard for the prediction (you use one method of calculating "average global temperature", with fudge factors written into your code to decrease temps in the 1930s, and to increase them from the 1970s on, someone else uses the satellite record, etc), then you can always assert that the data being used is the problem, not your theory.
Climate models are wild suppositions at best. RealClimate's worship of Hansen aside (take a closer look at the error bars in your reference my friend), I haven't heard an AGW support yet say either, "This is the right model, and the other 500 climate models are wrong as you can plainly see" (yes, virginia, there are lots of climate models out there, and they don't all make the same predictions), or "if this model is wrong in 20 years, I'll admit my theory was wrong". At best, the response is, "let me adjust the model to fit, my theory is still correct".
The real problem here is that the pro-AGW group is going about science all wrong -> they're trying to prove their point with more data that buttresses their theory. They look around, find scads of data that fits their model, and with enough data, declare the "debate is over".
Except that's not science. It's not even bad science, it's just simply not science. You don't prove your point by finding more data that agrees with you, you prove your point by looking hard for data that does *not* agree with you, and not finding it. It's a subtle point, but one that is profoundly misunderstood by the masses. You can always find more data to support your theory, if you're willing to ignore data that does not support it.
So the anti-AGW folk have it easy -> they just need to "cherry pick" data that refutes the AGW theory. Their search for data has a much, much lower bar because they don't need to have 10,000 refutations, or a million refutations, they just need one refutation. Just one bit of data that breaks the model, and the model must be changed, or abandoned.
The bigger problem of all this is that when it comes right down to it, the pro-AGW folks haven't really stated a falsifiable theory. They have in fact scrupulously avoided a falsifiable theory (warm winter? Global warming! cold winter? Global warming!), and have instead created a political movement rather than a scientific discussion.
For those pro-AGWers who want to mod down, fine. But do me a favor and come up with a falsifiable hypothesis while you're at it.