Toyota, BMW working on new battery technology

Jan 24, 2013 by Yuri Kageyama
In this photo released by Toyota Motor Corp., Toyota President Akio Toyoda, left, shakes hands with BMW AG chief executive Norbert Reithofer during a signing ceremony to jointly develop next-generation batteries for green vehicles in Nagoya, central Japan, Thursday, Jan. 24, 2013. Toyota and BMW are working together on next-generation batteries for green vehicles called "lithium-air" as their collaboration, first announced in late 2011, moves ahead in fuel cells, sports vehicles and other fields. (AP Photo/Toyota Motor Corp.)

Toyota Motor Corp. and BMW Group are working together on next-generation batteries for green vehicles called "lithium-air" as their collaboration, first announced in late 2011, moves ahead in fuel cells, sports vehicles and other fields.

But both sides said Thursday the partnership will not involve a capital alliance while spanning a wide range of technologies for green vehicles.

The Japanese and German automakers aim to complete a fuel-cell vehicle system by 2020, and a concept for a mid-size sports vehicle by the end of this year. They will also work together on developing lightweight technologies such as composites, which will help make cars greener.

Joint research will be started to develop a lithium-air battery, which will be more powerful than the current lithium-ion batteries used in electric vehicles, they said. The technology, which other automakers are also working on, will allow a major part of the battery's energy-making process to come from the oxygen in air.

BMW AG board member Herbert Diess told reporters the cooperation will help both companies boost competitiveness in new technologies.

"We really share the same vision," he said at a news conference in Nagoya, central Japan, live-streamed at Toyota's Tokyo office.

In this photo released by Toyota Motor Corp., Toyota President Akio Toyoda, third left, shakes hands with BMW AG chief executive Norbert Reithofer, third right, as their executives show signed documents during a signing ceremony to jointly develop next-generation batteries for green vehicles in Nagoya, central Japan, Thursday, Jan. 24, 2013. Toyota and BMW are working together on next-generation batteries for green vehicles called "lithium-air" as their collaboration, first announced in late 2011, moves ahead in fuel cells, sports vehicles and other fields. They are from left: Toyota's Director and Senior Managing Officer Yasumori Ihara, Toyota Executive Vice President Takeshi Uchiyamada, Toyoda, Reithofer, BMW AG board members, Herbert Diess and BMW Group Brand and Product Strategies Senior Vice President Klaus Frohlich. (AP Photo/Toyota Motor Corp.)

Toyota Vice Chairman Takeshi Uchiyamada said working with BMW will allow for a much faster development as they pool their resources.

He said the companies share a corporate culture and they have built trust over the last year. An agreement to work on technologies together was signed in June last year.

BMW, known for its strong design and sporty cars, could be a good match for Toyota, reputed for innovation and solid engineering but sometimes criticized as making dull cars.

Global automakers are forging such partnerships to become more competitive.

French carmaker PSA Peugeot Citroen and General Motors Co. of the U.S. have a deal to share in purchases of parts and services to cut costs. Toyota already has a joint venture with Peugeot Citroen to make small cars in Europe.

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Mike_Massen
1.7 / 5 (6) Jan 24, 2013
:hmmm: So other than the politics in this scientific article, where is the physics, where is there any detail, where is their any structural plan, packaging, influence on design, safety, utility, aims for capacity, integration with existing infrastructure, any necessary extensions upon same, or is this 'article' a mere filler - surely not - some deity forbid ?

Science = "The disciplined acquisition of knowledge"

Any chance one of the journo's who was involved in this article be able to expand on with something useful and which can be brought to discussion - of sorts ?

Thanks
triplehelix
1.4 / 5 (11) Jan 24, 2013
The entire green movement is political. It was never scientific.

antialias_physorg
4.5 / 5 (11) Jan 24, 2013
The entire green movement is political. It was never scientific.

Statements do not an argument make.

Green energy and products had been investigated by scientists long before politicians picked up on it (if it hadn't then politicians would have never known it was possible). So I'd argue that it did start with the science.

That societies adopt it - that is certainly political. But politics is (or should be) about what is needed or the public wants. Not about what a select few politicians want.
Mike_Massen
4.3 / 5 (6) Jan 24, 2013
triplehelix clearly doesn't understand efficiency or economics or combinatorial risk assessment with this immensely puerile obtuse assertion
The entire green movement is political. It was never scientific.
Since the so called 'green' movement relies on the knowledge of environmental effects, their historical consequences and offers methods to ameliorate same, then it must be fundamentally scientific with a strong engineering and economic objective, such as our species survival for the long term - anything else whilst population continues to increase would have to be plain stupid as an artefact of an immature mind that cannot deal with entrenched destructive habits .. !
weezilla
5 / 5 (1) Jan 24, 2013
The entire green movement is political. It was never scientific.


It seems like you're implying global warming is created by politics. Companies are moving towards green, and there should be pressure from all around causing it. Any reason is good.
triplehelix
1 / 5 (6) Jan 24, 2013
The entire green movement is political. It was never scientific.

Statements do not an argument make.

Green energy and products had been investigated by scientists long before politicians picked up on it (if it hadn't then politicians would have never known it was possible). So I'd argue that it did start with the science.

That societies adopt it - that is certainly political. But politics is (or should be) about what is needed or the public wants. Not about what a select few politicians want.


My apologies, what I meant to say was

The green movement is entirely political. It was never TRULY scientific.

Envrionmental science basically makes statements based on 1 sample set, and uses the same sample over and over. No controls. It's not real science
triplehelix
1.1 / 5 (9) Jan 24, 2013
Let me paint you a very clear picture of the logic environmentalists use.

Lets get 1 petri dish, just one. Now lets populate it with just 1 thousand bacteria, and for the sakes of this hypothetical situation, none out-compete each other. I now want to see what antibiotics work against these bacteria. So I put in 250 antibiotics at once. Some bacteria die, but not all. I then make a claim that only 1 of the 250 was at work. I then repeat similar studies like this, but instead of using a new petri dish, I use the same one, for 4.6 billion years.

You cant gain ANY statistically significant data from 1 sample, and as we only have 1 Earth, you cannot prove anything, because you have NOT accounted for EVERY variable. Like how frogs were dying out and they blamed global warming for decades...Oops, a real scientist came along, made some controls and used proper sampling techniques and found it was a virus. That case isnt a one off, its quite common....

1 sample fits all...LOL
canuckit
3 / 5 (2) Jan 24, 2013
"He said the companies share a corporate culture"
An alliance between a reliable car maker and a unreliable car maker does not seem like a win-win situation.
yep
3.4 / 5 (8) Jan 24, 2013
Last time the Germans and Japanese got together they almost took over the world!
antialias_physorg
3.7 / 5 (3) Jan 25, 2013
Envrionmental science basically makes statements based on 1 sample set, and uses the same sample over and over.

Unless you have some evidence to back up this statment I call "brainfart" on that one. You have no clue what you're talking about - especially when it comes to science.

Last time the Germans and Japanese got together they almost took over the world!

This time we'll just buy it.
(Nah. Who'd buy all our shiny products? Japan and Germany are heavily dependent on exports - which is a model that has served them well. But it's not a model that you can have all over the world. As long as there are net exporters there have to be net importers)

triplehelix
1 / 5 (4) Jan 25, 2013
"Unless you have some evidence to back up this statment I call "brainfart" on that one. You have no clue what you're talking about - especially when it comes to science.

"

We have 1 planet...Environmental science is about our planet. Ergo we have 1 sample. Sampling in India, and sampling in Brazil for example doesn't count as 2 samples. It is a pseudo replicate technique, using the same 1 sample, just different times and sections. This technique in science is allowed, however most admit it has severe statistical limitations. Every other science has controls, where all variables are removed, we can't do that with one planet. Every other science repeats, and replicates, using multiple INDIVIDUAL samples, not multiple readings of the SAME sample.

How can one deduce an affector variable when so many exist and none can be experimentally eliminated (a control). You can't.

I have a big clue about science, im in the real scientific industry, and no grumbles about my science so far
triplehelix
1 / 5 (4) Jan 25, 2013
For hypothetical example antialias, let's say one wants to see the effects of sulphur by product concentrations and foliage of trees. One measures an increase in sulphur, and one measures a loss of quality in foliage (keeping simple for clarifications sakes). How do you know it isn't co2? CFC's? Virus of the tree? Natural cycle of the trees? (some trees rely on forest fires to re-grow and bloom, if no fires occur they begin to die out.)

The scientific way to do this would be to run either a univariate parallell study design, or a multivariate design where more than one variable is used, but one isn't used. You either prove by affirmation, or by singling one out. You can't do that on 1 planet. The CFC's are there, you cant get rid of them, so their is no way to experimentally prove whether it is the sulphur, or the CFC's, or both, or neither. One must separate the variables to prove a variable is the cause and not a false correlation, or a non causative correlation, aka CO2 and AGW.
antialias_physorg
1 / 5 (1) Jan 25, 2013
We have 1 planet...Environmental science is about our planet. Ergo we have 1 sample. Sampling in India, and sampling in Brazil for example doesn't count as 2 samples.

Wow. I think you need to take a basic course in what science is before we continue this conversation. The amount of confusion in your posts on that subject is just mind boggling.

Every other science has controls

No. You cannot have controls in astrophysics for example. Nor in psychology, nor social sciences, nor medicine, or ...
But good statistical analyses - even though weaker without controls - are FAR from impossible in these sciences. You just need adequate amounts of data.

How can one deduce an affector variable when so many exist

As I said. Read an introductory book on statistical analysis. The terms 'multivariate analysis', 'linear discriminant analysis', 'principle component analysis', et al should give you a pointer
triplehelix
1 / 5 (4) Jan 25, 2013
"Wow. I think you need to take a basic course in what science is before we continue this conversation. The amount of confusion in your posts on that subject is just mind boggling."

Okay, so you think two differing geographical locations is 2 individual samples?

Great, let's populate a petri dish with two bacteria, on either side, they're different geographically. You'll get unusable data, aka, contamination, and any real scientist would laugh at someone saying they tried multisampling using the same dish.

"No. You cannot have controls in astrophysics for example. Nor in psychology, nor social sciences, nor medicine, or ..."

Yes you can, astrophysics, lets say, solar system formation. We can witness potentially millions at many stages, all with differing variables, this would be considered a multivariate technique.
Psychology has parallel blind studies, aka, a control.
Sociology isn't a science.
Medicine, seriously? Double blind placebo study clinical trials?!?!?!
triplehelix
1 / 5 (4) Jan 25, 2013
"As I said. Read an introductory book on statistical analysis. The terms 'multivariate analysis', 'linear discriminant analysis', 'principle component analysis', et al should give you a pointer"

I know what all those are, the issue arises that you still need to remove variables.

Univariable is slow but easy, you just very painstakingly remove all variables but one, and repeat ad nauseum with each variable.

Multivariate is a technique where say 10 variables exist, you run a sequentially patterned multible variable sets, which is quicker, but requires more number crunching to detect the variable(s) as the causative.

You cannot remove ANY variable in environmental sciences, the planet does what it wants, you are a slave to its occurrences, and can simply observe what happens with thousands, maybe tens of thousands of variables all playing a factor.

The fact you thought Medicine has no control just proves your ignorance. Double blind parallel placebo control studies = contro
triplehelix
1 / 5 (4) Jan 25, 2013
"But good statistical analyses - even though weaker without controls - are FAR from impossible in these sciences. You just need adequate amounts of data."

Again, astrophysics, we can monitor millions of INDIVIDUAL samples.

Climate science, we have one sample, OUR planet.

The difference between every other science is it has a larger "population" size than 1.

If you perform a mixture of variables and tests on the same sample to achieve a dataset this is terms pseudo-replication.

1 planet = 1 sample = no control.

If you gave just 1 patient a placebo for a month and then the active for a month, this wouldn't prove anything. You need MULTIPLE, INDIVIDUAL, CONTROLLED populations to achieve any decent dataset.
triplehelix
1 / 5 (4) Jan 25, 2013
Also, experimental design is supposed to allow us to gain predictive power, and the ability to force a reaction we want.

We can repeat, and replicate (yes they are different) with certainty, the effect of penicillin on non penicillin resistant bacteria. We cant force or replicate planetary symptoms, despite the fact the science laughably says we are forcing it.

The past 18 years the IPCC has had to admit no increase in global temperatures, and has in fact, on some dataset analyses suggested a slight decline.

co2 = warmer temps is the dogma. This has been shown to not be true. It has shown co2 either isnt a cause, or is only a bit player. Physorg published only a week ago how jurassic had lush vegetation and strong fauna due to "low co2 levels", jurassics were 5x higher than todays. Inconsistencies and contradicting data everywhere. 1.Because its a load of rubbish anyway and 2.It has no controls so has lacking predictive power.
antialias_physorg
3 / 5 (2) Jan 25, 2013
Okay, so you think two differing geographical locations is 2 individual samples?

If they are merely correlatd but not FULLY CAUSALLY linked then: Yes. The correlation merely weakens the statistical analysis you can do (that is why you need a greater sample size for PCA et al).

As in medicine (where even a randomized double blind study does not change the fact that the test subjects do not have identical physiology but share some). Or in astrophysics where even though we can observe many intermediate stages there are always things that affect the process which aren't identical/but merely similar accross all observed instances but affect it (local gravity, radiation environment, etc.)

An instance where your argument WOULD hold is if someone e.g. would argue:
"Life in the universe must be common because we see so many living things down here". But they all originated from one ancestor and are therfore fully causally linked. So in THAT case we'd have only one datapoint.
triplehelix
1 / 5 (4) Jan 25, 2013
"As in medicine (where even a randomized double blind study does not change the fact that the test subjects do not have identical physiology but share some)."

This is why some clinical trials require 3-5 thousand patients, and you usually need to run dozens of clinical trials, all with different variables. This way, while different physiologies exist, you have a large enough sample set to gain a much stronger statistical analysis. This is considered a control. Is it a 100% control as removing a variable entirely, no, but is certainly very close to it...

antialias_physorg
3 / 5 (2) Jan 25, 2013
Univariable is slow but easy, you just very painstakingly remove all variables but one, and repeat ad nauseum with each variable.

Yes. But that isn't possible except in the most basic physics experiments (and even there it's hard to remove stuff like gravitational variations between test locations or even test-times(e.g. different positions of the Moon affect your local gravity value))

You're falling here into the dichotomy of causally linked and unrelated datapoints. If that were the truth of the universe we wouldn't need statistics at all.

But there are also correlated datapoints (to various degrees) - and if you want to be precise then ALL datapoints in any subject are correlated to some degree.
triplehelix
1 / 5 (4) Jan 25, 2013
"If they are merely correlatd but not FULLY CAUSALLY linked then: Yes. The correlation merely weakens the statistical analysis you can do (that is why you need a greater sample size for PCA et al)."

Circular argument. I asked you if 2 differing geographical locations are 2 samples, or 1. You say if they're not linked then yes. How do you prove they're not linked without first removing every variable and testing this? You then answer this by stating that you increase your sample size, which I agree with but!... The issue is you have yet to prove analysing differing geographical locations equates to a different sample, and round and round you go.

Gathering data from many plots on Earth doesn't equate to many samples. I can sample hundreds of bacterial colonies on one petri dish. This is considered 1 sample.

If two geographical locations are separate enough for statistical analysis, why are we bothered about Chinas pollution? If you're right, only China will suffer, not us.
antialias_physorg
3 / 5 (2) Jan 25, 2013
This is why some clinical trials require 3-5 thousand patients, and you usually need to run dozens of clinical trials, all with different variables

As it so happens I did my PhD on a software used for clinical trials of a drug (and I did the analysis of the effects of the drug). You run it with all variables (ages, gender, severity of the disease before treatment, after treatment, lifestyle, ... ) at once and then look for the principle components via multivariate analysis.
There is no way to do this by 'removing variables'. If you'd remove variables to the point where you test for just one variable then you'd have a sample size of one (which gives you no statistical power whatsoever) - because humans ARE variable. You'l never find two of the EXACT same age, or with the EXACT same severity of the disease. Or with the EXACT same metabolism. Or with the EXACT same lifestlye.
triplehelix
1 / 5 (4) Jan 25, 2013
"You're falling here into the dichotomy of causally linked and unrelated datapoints. If that were the truth of the universe we wouldn't need statistics at all."

Apologies, I fail to understand this statement?

I'm not suggesting there are 0% factors and 100% factors. What I am suggesting is, if your experiment is limited to having to work around variables one cannot modify, your statistical analysis will become less strong.

Having two contra-indicating variables is fairly trivial and easy to get past. Having potentially thousands which the planet undoubtebly has causes a much larger issue, it is such a convoluted system the signal to noise ratio is going to be disproportionately high. I'm not suggesting we all go around in hummers, but the apocalyptic tales of some enviro babble is just laughable, and completely unscientific.
triplehelix
1 / 5 (4) Jan 25, 2013
Clinical trials misunderstanding. I never meant the technique was univariate.

You have a double blind procedure, to which you have groups on placebo and active, and this is run parallel with others, where the variables can possibly change, in terms maybe of strength of drug etc.

Multivariate design is just as strong as univariate, it's just more maths heavy.

You can have effectively one variable with humans. If you sample enough humans, your signal to noise ratio declines with respect to your sample size. Yes we are variable, but if your sample size is big enough, this lowers the compounding issue of differing physiology. Every increase in population will lower the signal to noise ratio, so you have more signal than noise.

Multivariate is identical to univariate almost, it is still the process of variable vs variables, multivariate is simply quicker because you test for eg, 3 variables per analysis rather than 1, and sequentially change them for the affectors vs effectors
antialias_physorg
3 / 5 (2) Jan 25, 2013
How do you prove they're not linked without first removing every variable and testing this?

You show (e.g. via ANOVA) that the common variable between them is not the determining factor. This works in medicine (and climate research) the same.

It's a very complicated subject. You do tests. You do tests FOR the tests to find out that the test is even applicable with the distribution envisiond.
You even do tests FOR the tests FOR the tests to make sure you're evaluating your tests correctly.

That's why I'm saying: You need to pick up a book on statistcs before it makes any real sense to continue discussing this. 'Everyday intuition' just doesn't work here.

It's a very hard subject (and a susbtantive amount of reseach papers use wrong statistical measures. That doesn't necessarily invalidate their findings. using a different test doesn't give you a TOTALLY different result in most cases)
triplehelix
1 / 5 (3) Jan 25, 2013
If you perform the same clinical trial on 20 people, then 200, then 2000, then 20,000 you will almost definitely get different p values.

The less people you have, the more "chance" you have of missing particular physiologies, causing noise, or false correlation.

The more people you have, the more "chance" you have of getting many physiologies and genetic "families", lowering the noise, and increasing our confidence the correlation is true.

No science is 100%, sample size increases simply give us stronger confidence.

Also, medicine is able to treat millions every week correctly, it has an almost 100% track record.

Climate science doesn't. It still continues to fail to accurately or even precisely predict things, yet still publishes itself with an austere attitude as if their is no other possibly scenario. I have a 1980's paper which says where im typing right now will be underwater by 2015. 2 years left, and no water in sight.
triplehelix
1 / 5 (3) Jan 25, 2013
"It's a very complicated subject. You do tests. You do tests FOR the tests to find out that the test is even applicable with the distribution envisiond.
You even do tests FOR the tests FOR the tests to make sure you're evaluating your tests correctly."

So your stats results are based on an assumption, based on an assumption, based on an assumption. If your initial readings have accuracy issues, then the 2nd round of testing is simply going to compound this inaccuracy.

ANOVA testing requires removal of variables, so you can chart out the "response" of the population based on the variables you placed on it. If the responses change with 1 or more variables, they are the causative. AGAIN, circular argument. You cannot remove variables in climate science, so how can your ANOVA show anything but massive signal to noise messy baselines, which are then compounded further-more with more testing based on the assumptions placed beforehand. GIGO.
antialias_physorg
3 / 5 (2) Jan 25, 2013
The less people you have, the more "chance" you have of missing particular physiologies, causing noise, or false correlation.

The less people you have the lower your statistical power. Because one exceptional result can drastically influnce the statistic. And since you're sampling you never know which results are exceptions and which ones are not.
If you did then you could exclude the outliers beforehand - some people do that by excluding what they THINK are outliers. It's what's called "introducing a bias" (or simply "fudging a statistic")

No science is 100%, sample size increases simply give us stronger confidence

That's why it's called a statistic. Only math is 100% (and that one is arguably not a science, as it's not falsifiable)

Also, medicine is able to treat millions every week correctly, it has an almost 100% track record.

No it does not have a 100% track record - far from it. It's simply better than doing nothing.
antialias_physorg
1 / 5 (2) Jan 25, 2013
It still continues to fail to accurately or even precisely predict things

The have been getting pretty good. ertainly MUCH better than the model that says "it aint't so".
Science isn't about having the correct model (you never know whether you have that because the NEXT measurement can always prove you wrong - and philosophically you can even show that it's never possible to have THE 100% correct model, because you can show that such a model doesn't exists)

So your stats results are based on an assumption, based on an assumption, based on an assumption. If your initial readings have accuracy issues, then the 2nd round of testing is simply going to compound this inaccuracy.

You misunderstand (as I knew you would). The subject is awesomely complicated. Much too complicated for 1000 letters. The second test is a test to see IF the first TEST TYPE is the right test type. The third test is to see if the second test TYPE you used to test the first test type is correct.
antialias_physorg
3 / 5 (2) Jan 25, 2013
ANOVA testing requires removal of variables, so you can chart out the "response" of the population based on the variables you placed on it. If the responses change with 1 or more variables, they are the causative.

Stuff like these tests show you which of your factors have the highest probability of influencing the outcome. I.e. which factors are most correlated and which ones are weakly correlated.

Example: In my study we got CTs of knee arthritis from several sites around Europe (patients with and without the disease) to see if a certain image analysis method could distinguish severity of the disease. Multivariate analysis showed that for the russian site age was a much greater predictor of the disease than for othr sites (they had gotten sloppy. Because they hadn't found any people without some knee arthritis their sample population for that batch was from much younger people). For other sites the image extracted values were most correlated.

Then you show significance.
triplehelix
1 / 5 (3) Jan 26, 2013
"The second test is a test to see IF the first TEST TYPE is the right test type. The third test is to see if the second test TYPE you used to test the first test type is correct"

And how do you test to test the 1st test was correct? Your 2nd test still makes assumptions from the 1st test. If it doesn't how is it different from the 1st test?

There are many forms of ANOVA, also, the explanation of the knee diagnoses is an example of INTRA smple variation, not INTER sample variation. With Multiple ANOVA you have differences WITHIN groups and BETWEEN groups, again, from MULTIPLE, INDIVIDUAL populations. Climate science does neither. It doesn't have a multiple or individual population. Again, we have one planet, ergo 1 sample. Until you prove differing geographical locations are equal to differing samples you're just running round in circles and talking nonsense.
triplehelix
1 / 5 (3) Jan 26, 2013
Also, again, science is not based on 100% or 0%. No science is fact. Gravity has only been observed on a few celestial instances and only since we began observing it. It is inerential confidences from experiment and stat analysis to suggest it is a constant throughout the universe.

AGW, as I have said before, CANNOT accurately predict ANYTHING. A scientist can inject someone with smallpox and make a 99.99999% prediction you will get smallpox. A scientist making a cup of tea can predict almost 100% it will get colder with time, for 2nd law of thermodynamics. I have a 1980's paper saying I should be underwater by now. You can say "we didnt know as much then" but this is a logical fallacy. I am almost certain that in 2050, your kind will be saying "we didnt know as much in 2010" and continue to make more bullshit up.

Scientific theories (real ones) can PREDICT with frightening accuracy! (atomic theory, gravity, evolution). The theory of AGW has pathetic predictive power.
triplehelix
1 / 5 (3) Jan 26, 2013
Take Evolution. It at the very get go said we evolved from apes. Guess what? After 150 years, that is still true, it is still part of its foundations, and better yet, is supported more and more everyday. Germ theory, every day goes by proves germs exist.

Global warming theory? There has been no statistically significant increase in Global temperature since 1994 from some analyses, and 1998 from every analyses despite CO2 ppm going up a good 25%. Linear or not, if co2 was a big player, it would go up. Lo and behold, 1994 onwards has seen extremely low sun activity....

The point is, AGW can't predict anywhere NEAR the level of evolution, germ theory, atomic theory, gravity etc. Scientific truth is best shown via predictive capability. If you truly know the subject and how something works-you can predict its next move. AGW can't predict shit. It is NOT scientific. At best technology cant predict it properly, in which case, why are laws and money being FORCEFULLY involved?
sciencemister
5 / 5 (2) Jan 26, 2013
Thank you Grand Master of Science Triplehelix! Just because the temperature in the mountains were I live have gone up by 30 degrees in 20 years is no proof of anything except maybe I need a new thermometer. Science can not prove that it is hotter, so therefore it must not be hotter. I like your logic. Please email Beijing and tell them to stop bitching about their smog. Since it can not be proven to be smog, as there is no other earth to compare, they must instead realize they are under a plague of sorcery. Chinese black magic, just like we were foretold in Big Trouble in Little China, is the only logical possibility left.
triplehelix
1 / 5 (4) Jan 26, 2013
sciencemister.

30 degrees? 20 years and your entire geographical region has gone up by 30°C? I call massive bullshit there for one. Warming means humans are at fault? You have completely missed the point entirely it seems, and simply gone on a 1/5 tirade. Science can easily prove it is hotter, the issue is, the planet has tens of thousands of affector variables, and without being able to experimentally remove any of them, you can't gain any decent accuracy as to the "weighting" of each INDIVIDUAL variable at play.

Your smog analogy is pointless and is comparing apples to oranges.
One can forecefully rise smog levels and see an affect. One cannot forcefully rise co2 and see an affect. In fact, despite the fact CO2 has increased 25% due to humans, we havent seen a single increase in temperature for nearly 2 decades. We only saw an increase for 1 decade prior to this and everyone went mental about AGW.
triplehelix
1 / 5 (4) Jan 26, 2013
http://egret.psyc...NOVA.pdf

Page 5 excerpt

"We'll presume your experiment was sensibly designed and free of confounds. No
amount of analysis will fix a bad design."

A confound?

Hidden or exraneous variables. Of which Climate Science has a huge amount. Hell we probably don't know, let alone understand mathematically, half the affector variables of climate.

You have to experimentally remove variables in most sciences to even see another variable. This is basic real science in genetics, where you have to knock genes out to see underlying causes, which can't be seen when a gene is in the way hiding it (as one example)

No, once again, Climate science is "infallible" and if anyone even begins to dissent from it, a bunch of ecowarriors will outright flat out refuse even the basic concept of a SCIENTIFIC CONTROL, which is the ENTIRE underpinnings of the SCIENTIFIC METHOD!

Screw controls, were Climate Scientists!
triplehelix
1 / 5 (4) Jan 26, 2013
Too dry-GW
Too wet-GW
Too snowy-GW
Too windy-GW
Not windy enough-GW
Too many hurricanes-GW
Not enough hurricanes-GW

Every single thing "proves" Global Warming. This is a religion. It's like explaining the evolution of the eye to a religious person and they reply "aha, this just proves God even more"

Same principle

"GW should make things hotter and drier"

**Rain ensues**

"Well actually, this is expected as well, and just reinforces GW"

Eh? The entire thing is a massive circular argument with no IN or OUT, this is not scientific. All scientific theories must be disprovable, or are circular arguments. Evolution? Find a modern rabbit in jurassic strata. Germ theory? Innoculate a plate and see no growth. Even if these things will never happen, they're still "thought experiment" or hypothetically disprovable. AGW isn't, it's an ever reinforcing circle of political bullshit.

triplehelix
1 / 5 (4) Jan 26, 2013
http://www.biocab...ical.jpg

1.There isn't even correlation most of the time, and
2.The planet has once had many times our level of CO2, famously, the proterozoic, which had mass glaciation

The carboniferous period had 4x our current CO2...Mean Global temperature according to data? 14°C. Todays mean global temp? 14°C.

I'm not your mother, you can very easily google the statements above, as I did, and gather this very simple data. Despite the fact the carboniferous had 4x industrial level of CO2, its mean temperature had NO change. IPCC says at worst we'll only triple our current ppm, so considering the Earth didn't do anything with quadrouple, why is everyone hissy fitting and making green taxes everywhere? Climate changes, regardless of what we do. Deserts USED to be seas! How else do you think sand formed there?! We werent driving SUV's then though and it still happened.
antialias_physorg
3.7 / 5 (3) Jan 26, 2013
It's really pointless to argue. There is just too much understanding of statistics missing, here.
Strap
5 / 5 (1) Jan 28, 2013
The planet is finite. The air, the water, the minerals its made of are all finite. So far as science can tell, the only thing we have found in an infinite abundance on earth is human ignorance. Statistical mind games seem to be a symptom of this abundant resource. Until the humans realize their potential to shape the finite for their long term successes, they will be finite as well.
Guy_Underbridge
1 / 5 (1) Jan 28, 2013
You cant gain ANY statistically significant data from 1 sample, and as we only have 1 Earth, you cannot prove anything

All you science guys can just go home, now.
You're no longer required.
Thadieus
not rated yet Jan 28, 2013
triplehelix!
Dinosaurs are real!!!

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