I'm glad you feel that way. I'm glad you like to make these definitive statements which are so easily disproved. All I need to do to disprove your statements is provide one year where the estimated anthropogenic rate of emissions could plausibly (within the rate of error) be less than the estimated rise in atmospheric CO2. In fact, I can find that information right in 2006, as you suggested:

2006 CR = 2.33ppmv, which you've agreed could be as high as 3.33ppmv (even higher if we include the adjustment to globalize it). That equates to 26Gt CO2 (3.33 * 7.8).

HC = 6.0Gt C, which equates to 22Gt CO2 (6.0 * 3.67)

Therefore:
NC = 26 - 22;
NC = 4Gt CO2;

The natural contribution of CO2 to the atmosphere is 4Gt. Therefore, the statements:
"The net effect is that nature removes more co2 from the atmosphere than it adds."

and...

"Without human co2 emissions the co2 levels in the atmosphere would start falling."

and...

"any time period you want to choose shows a higher anthropogenic co2 emission rate than atmospheric co2 rise"

are false. And I did it all without "human emissions [being] off by about 50%".

In fact, I could show this relationship for 5 of the past 10 years:

Deltas for Past 10 Years as Reported by MLO
1997 - 1.98
1998 - 2.95
1999 - 0.91
2000 - 1.75
2001 - 1.61
2002 - 2.55
2003 - 2.31
2004 - 1.54
2005 - 2.54
2006 - 2.33

Equally Possible Deltas for Past 10 Years When Adjusted For Errors
1997 - 1.98
1998 - 2.83
1999 - 0.53
2000 - 2.75
2001 - 0.61
2002 - 2.83
2003 - 2.83
2004 - 0.74
2005 - 2.83
2006 - 2.83

Note our equation will work out to a positive natural change with any CR>=2.83ppmv.

Now, I know you're going to think I'm trying to pull one over on you, so I'll show you the math.

If I had the raw data, I would use that. But the only source I've found for the actual annual mean CO2 concentrations as measured by the MLO don't match up with the reported variances on their web site! So, I must have the wrong data, but it sure looks like the right data. I wonder what's going on? Nevertheless, we don't need the actual data because we're only interested in:
a) what are the deltas
b) are the mean values from year to year reasonable given the error rate, i.e. do we have to change a measurement outside the range of error in order to arrive at the number we need to show the natural contribution to CO2 could be positive.

So, we can start at zero, use the deltas from the MLO site, then make sure we're not changing any one measurement outside its respective range.

Hypothetical CO2 Concentrations Given MLO's Deltas
Year .......... Reported Delta .......... CO2
1996 - ........... 0 ........................ 0
1997 - ........... 1.98 ................... 1.98
1998 - ........... 2.95 ................... 4.93
1999 - ........... .91 .................... 5.84
2000 - ........... 1.75 .................... 7.59
2001 - ........... 1.61 .................... 9.2
2002 - ........... 2.55 .................... 11.75
2003 - ........... 2.31 .................... 14.06
2004 - ........... 1.54 .................... 15.6
2005 - ........... 2.54 .................... 18.14
2006 - ........... 2.33 .................... 20.47

There's no magic here, I just took the MLO reported rise in CO2, year over year, and applied it to a base year of 0 in 1996.

Now that we have a baseline of what the possible values for each year could be, we can see what would happen to the variances if the measurements for those years were off by +/-.5ppmv.

Hypothetical CO2 Concentrations Given MLO's Deltas
Year ............. "Measured" CO2 ........... Possible CO2 ............. Variance
1997 - .................. 1.98 .................... 1.98 ......................... 0
1998 - .................. 4.93 .................... 4.81 ......................... -0.12
1999 - .................. 5.84 .................... 5.34 ......................... -0.5
2000 - .................. 7.59 .................... 8.09 ......................... 0.5
2001 - .................. 9.2 .................... 8.7 ........................... -0.5
2002 - .................. 11.75 ................. 11.53 ......................... -0.22
2003 - .................. 14.06 ................ 14.36 ......................... 0.3
2004 - .................. 15.6 ................. 15.1 .......................... -0.5
2005 - .................. 18.14 ............... 17.93 ........................ -0.21
2006 - .................. 20.47 ............... 20.76 ......................... 0.29

So, as you can see, part b) of our requirements is satisfied. No year varies more than +/-.5 from its "measured" amount. Using these new possible CO2 concentrations we get the new deltas posted above. Five of those years resolve to a delta of +2.83ppmv of CO2. This equates to an increase of 22.07Gt CO2 (2.83ppmv * 7.8). So, CR = 22.07.

Plugging into our formula we get:

NC = 22.07 - 22.02;
NC = .05Gt Co2;

There's also one other year which is very close to our 2.83ppmv cut-off (2000). Given the MLO data doesn't accurately reflect the entire globe, it would also be possible to make this year fit if we could figure out how far off from the global data MLO is. However, I'm willing to ignore it.
Given they take the measurements simultaneously, from the same location, I would have to assume it's a measurement error.
First, how do you know there's no such thing as "anthropogenic sinks"? Perhaps we're absorbing extra carbon in our cells? Secondly, and more importantly, that's not the point. I'm not arguing there are "anthropogenic sinks". I'm arguing that, according to your source, it is possible that well over the amount of anthropogenic carbon is absorbed by nature. It's curious you argue we only need to know net natural fluxes (which you haven't been able to prove is negative), but when presented your own source's argument that the net contribution of Man's emissions could be negative you balk.
That's not true either. The table shows quite clearly that the authors have the same confidence that ALL AND MORE of the carbon from fossil fuel burning and cement production could possibly be absorbed by the ocean, forests and other terrestrial sinks:

Anthropogenic CO2 from fossil fuel burning and cement production: 5.0GtC

Oceanic uptake: 2.8
Forest uptake: 1.0
Additional terrestrial sinks: 2.8
Total NON-Atmospheric storage: 6.6GtC

Meaning all of the anthropogenic carbon from fossil fuel burning and cement production, plus an extra 1.6Gt, could be absorbed somewhere other than the atmosphere.

I am utterly amazed at how well you explained this. Even a lay-person as myself can grasp this.

I have a question that perhaps you could answer. How much co2 is in the entire earth's atmosphere? Is is a number that cannot be written in tonnes because it would be too huge?

__________________
United We Stand.

Thank you. But keep in mind this is only a possibility. It shouldn't be construed as being definitive in any way. Most climatologists believe most of the rise in atmospheric CO2 since the industrial revolution is due to Man. And it's probably a fairly safe bet - I mean, we're pumping out tons of it. However, there are natural processes that could cause it. We just don't have the enough understanding, or the proper tools, to make any definitive statements yet.
That's a good question. It depends on when you take your measurements, where you take those measurements, and what you're using to take those measurements with. Most estimates peg the carbon content of the atmosphere between 600 and 700 gigatons (billion tons). That would equate to between 2202 and 2569 gigatons of CO2 (it's heavier). These are big numbers, to be sure, but it's a big atmosphere. These values are going to change throughout the year because plants grow in the spring and summer (absorbing CO2), and die off in the fall and winter (releasing CO2). Where you take measurements will change the reading because you need to be in a carbon neutral place, which is kind of hard to find in an open system like ours. Different measuring tools will also give you different results. And when you're dealing with such a minute gas (relative to the entire atmosphere), small measurement variances make for huge variances in the estimates you arrive at.

[/quote]

Take any year and the figures show anthropogenic emissions higher than the rate of co2 rise in the atmosphere. That is without the error rates. I pointed out that taking a single year, or the long 250 year period has problems with accuracy (ie due to the error rate) which is why I proposed using a 10 year period.

2006 saw over 28 billion tons of co2 emissions, while co2 rose about 18 billion tons. As you pointed out it is possible these figures are inaccurate enough to mean the rise is actually more than emissions. All that requires is that the total inaccuracy brings them more than 10 billion tons closer together. So in your example you have emissions being overvalued by 20%, and co2 rise undervalued by 40%. However while I don't think this is very likely at all, I do accept it is possible. Which is why I suggested using a 10 year period in which the error range cannot "meet" co2 emissions with co2 rise. So onto that..

I accept due to inaccuracy that for a particular year it could be possible for these not to be true, but I find it very unlikely that both figures would be off by near max error and in the right direction too.


Yea that's fine

Ok

Okay

Okay. But have you taken the 20.76ppm rise figure you've got and applied that to 10 * 22 (10 years of 22gTC)?

20.76 * 7.8 = 162 gTC rise in atmospheric co2
10 * 22 = 220 gTC rise in human emissions

So over that 10 year period NC = 162 - 220
NC = -58

So even though nature could be a net emitter in particular years assuming a overvalue for emissions and an undervalue for co2 rise, over 10 years these errors melt away and it becomes much clearer that nature is a net sink. The yearly errors could be seen as noise on an overall trend.

Well there is natural background noise, for example co2 cycles up and down during a single year like a sine wave due to plants,seasons and temperatures. This wave is noise over the top of the rising trend, so the differences being natural variation rather than measurement error are very likely.

The table isn't presenting what you think it is. Notice the second part is called Partitioning among reservoirs. What are you partitioning? The human emissions. Therefore if you say there are only 6gTC anthropogenic emissions then you get to distribute 6 across those natural storages in the 2nd part of the table (meeting the contraint range of each one).

The items and their uncertainty ranges are not independent. "Partitioning among reservoirs" adds up to 7.1 for a reason - it's exactly what anthropogenic emissions are given as. It's not a coincidence - the basis of the table is to divide yearly anthropogenic emissions into the places it ends up going, with uncertainty ranges for individual components.

You can't, for example, set all the "Partitioning among reservoirs" items to the max of their ranges because that would give you 10.1, which is more than the max for anthropogenic emissions (8.2). That would be saying that out of 8.2 human emissions 10.1 of those emissions end up in those various places. That doesn't make sense.

As an analogy the table is like this one:

Total money given to someone: $10 (9-11)

What they did with it (ie partitioning the amount given to them):
Spent it on candy: $3 (2.5-3.5)
Gave it away: $5 (3-7)
Lost it: $2 (1-3)

Clearly you cannot take all the maximums from the last list and the minimum from the first, and say they spent $15.5 of the $9 given to them. That does not make sense.

Equally it makes no sense to say that the anthropogenic sinks took 6.6gTC of the 6gTC humans put into the atmosphere (and that would also violate the constraint that at least 3.1GtC has to be placed with the atmosphere)

They say
So if you are going to use the lower figure, its 6.0, not 5.0. But that means you have to distribute 6.0 in the "Partitioning among reservoirs" table, you cannot distribute more than the value you choose for anthropogenic emissions.

You left out the Atmospheric storage:
Storage in the atmosphere 3.3 (3.1-3.5)

It has to take 3.1 of human emissions as a minimum.

Note that if you are saying humans are emitting 6.6GtC + 3.3 into the atmosphere. That's what these tables correspond to. The tables are linked, not independant. You cannot take the low end of the first and the high end of the second. The individual items are not independent. If you set ocean uptake to the high end and forest uptake to the high end then you have to "sacrifice additional terrestrial sinks" for example, you cannot set them all to max.

Although conclusions of a rise over many years is a very accurate assessment:
Global Monitoring Division

LOL! Of course, onon, do whatever it takes to make the number fit the conclusion you want to arrive at. It makes no difference to me.
Man, even when slapped in the face with them you still choose to use these absolute statements. Let me rephrase for you:

2006 saw possible emissions of 28 billion tons of CO2, while CO2 possibly rose about 18 billion tons.
No, I don't have them "overvalued" or "undervalued". The possibility of getting the numbers you choose to prove your preconceived conclusion is equal to the possibility of getting the numbers I chose to prove my preconceived conclusion. The difference is that I understand my conclusion was preconceived, you seem to believe your preconceived conclusion is absolute fact.
Precisely my point all along. You want to pick and choose the numbers which will prove your conclusion - post hoc, ergo propter hoc.
Well, good. I guess our debate is over. However, I find it necessary to point out there is no "right direction" in science - there is only observed direction. Those who have a conclusion to prove believe in "right" directions.
Of course not. Not only would that be poor math, it would be even worse science. You're arguing we can take one measurement, of a highly complex and wildly variable system, and extrapolate that over a ten year period. That's just irresponsible. It reminds me of the Hockey Stick.
Sure, and if that didn't give you the right numbers you could go out to 11 years, then 12, then 20, then 30 - whatever it takes to prove the conclusion, eh? But that wouldn't be science, would it? That wouldn't be honest and impartial analysis, would it? That wouldn't actually reflect reality, would it? But, hell, what does any of that matter?

Actually, since we're allowed to use whatever math we need to prove our conclusions, you should recognize the amount of human contribution wouldn't be 220Gt CO2 over 10 years. If you're only going to apply the error rate of CR to the front and back ends, why not just apply the error rate of HC to only the front and back ends? That way you can get 68.8Gt C ((7.1*8) + (2*6)), or 253Gt CO2 over 10 years. Yea, that's the ticket!

Honest and impartial analysis would require an error range of statistical relevance plotted against the derived estimated averages. Honest and impartial analysis would determine the true yearly anthropogenic emissions, with a statistically relevant error range. I replicated that as closely as possible by using the numbers reported by your sources. But shit, you can't get grants by confusing people, or telling them it's statistically possible things might not be as dire as you want them to believe. You can't make definitive, absolute statements with honest and impartial analysis.
Natural background noise is eliminated with the dual measurements. Both measurements include the noise, so it can't be the reason the measurements differ from one another.
The table is presenting exactly what I think it is, and I never implied nor wrote it said anything different from what you just wrote. If 6GtC are anthropogenic, then that could be entirely absorbed ("partitioned", if you prefer) by non-atmospheric sources. The total of non-atmospheric sources exceeds 6GtC.
Post hoc, ergo propter hoc, onon. You're making an assumption about one, if not both, of these sides of the equation. You're implying these researchers did not research how much human emissions were absorbed where. You're implying they simply plugged in whatever numbers they felt would prove their point. I guess you're right about one thing - it's not a coincidence.
Yes, it does. Mathematically, statistically, logically, and intuitively. And if your example has the same 90% confidence level these researchers claimed to have, then you would have to wonder what happened. Did someone give you some more money? Are your estimates off? Did you have more money than you thought? Did you spend less than you thought? Did you get the wrong change back? You would have to go back and re-investigate your data.

Or, you could simply plug in whatever numbers prove your conclusion.
Nope, again. The lower figure is 5.0 because we're talking about human emissions, not human changes to tropical land use. Changes to tropical land use aren't emissions, they're a perturbation of the natural ability to absorb emissions.
And I didn't. I merely pointed out that atmospheric absorption wasn't needed in order to deal with all human emissions. There's no requirement that any particular partition receive any particular amount, merely that the confidence level is high within those ranges.

Perhaps this will help you:
Total money given to someone: $10 (9-11)

What they did with it (ie partitioning the amount given to them):
Spent it on candy: $3 (2.5-3.5)
Gave it away: $5 (3-7)
Lost it: $2 (1-3)

Now, I'm 90% sure any of these ranges of numbers represent reality. I have less confidence in any numbers outside that range, but they are possible.

So, I have 90% confidence I gave someone $9. I have 90% confidence they spent $3.50 on candy, and 90% confidence they gave $5.50 of it away. Even if I'm only 1% confident they lost some of it, given the numbers I am 90% confident of it would appear they did not lose any of it.

Mathematically, statistically, logically, and intuitively all of the anthropogenic emissions have a 90% confidence level of being partitioned among non-atmospheric sinks. To make this false, you would have to argue (as you are trying to do) that atmospheric partitioning has a 100% confidence level between 3.1 and 3.5. But that's not what your source claims.

Well, sure, but that's only if one approaches things from a scientific standpoint!

Al Gore, by way of contrast, has no trouble whatsoever traipsing around the country, showing his "documentary" to whomever is willing to actually watch it, and Al Gore (credentialed scientist that he is) has no problem whatseover making all sorts of wild-eyed definitive statements.

Al Gore is a huxter, shamelessly promoting his "global warming" hoax to the gullible. And many of them are fooled by him, and they end up making remarks like "You can't argue with the pictures Al Gore shows us!"

40 years of our government-run schools being dominated by Liberals and members of the Teacher's Union has taken its toll. Our children "graduate" from high school lacking the ability to do basic math, to write English correctly, to understand the difference between hard scientific data and mere theory. In short, they have ended up gullible, pliable, easily-manipulated by the likes of hucksters such as Al Gore.

EXCELLENT point, Cato.

But one which, sadly, obviously escapes onon. He has bought the hoax being perpetrated by Al Gore The Scientist, hook, line, and sinker. Algore shows him pictures, and he gasps.

Yes you do. The only way you can bridge the gap between emissions and co2 rise in 2006 is if the estimates for emissions are overvalued and the estimates of co2 rise are undervalued. You require both to be true. I have said that you can do this for individual years using very liberal error rates for both co2 emissions and co2 level measurements, but when you extend this analysis over X years you don't get to multiply the error rate by X too. The error rate is not linear with the number of years, so what emerges is that over such periods of time is not possible for human co2 emissions to be less than the atmospheric co2 rise.

My point is that it is not, you require a specific case where the co2 emissions and rise are both off by a signficant amount in a certain direction. You talk about possibility, but not probability. I can see that the 2006 figures being off by so much and off in the direction you need has low probability - there is a far better chance that 2006 did see emissions more than co2 rise.

But furthermore for a period of 10 years or more the probability of human emissions being less than the co2 rise falls even further.

Why would it be poor maths? I am simply taking the 20ppm rise seen in the last 10 years (hell lets make it 22ppm), and taking a total of co2 emissions in that time (in fact the total I use is actually lower than the estimated figures as it assumes 22gTC every year even though recent year figures are around 28 and even 1997 was about 25)

Then we use the formula Natural contribution = co2 rise - human contribution

Even if we
18 * 7.8 = 171 gTC rise in atmospheric co2
10 * 22 = 220 gTC rise in human emissions

So over that 10 year period NC = 171 - 220
NC = -59

And that's using the error ranges for co2 emissions and co2 concentration that you used for a single year. This is what I mean about the uncertainty in a single year making it possible (although unlikely) that co2 rise > anthropogenic emissions, but as you take a range of more years, the uncertainty does not rise linearly with the number of extra years, and what you get is that you require higher and higher error ranges in order to make co2 concentration rise meet anthropogenic emissions.

I don't need to do that because even the last 10 year period makes it clear humans have emitted more. Like I said an individual year could be subject to more inaccuracy, but over a long time period the actual situation emerges.

Actually the figures are over 260Gt co2 emissions over the last 10 years before you start applying errors, so I was using a 15% lower figure and still co2 emissions were 50GtC higher than the co2 rise in that 10 year period.

Are you implying that isn't justified? Seeing as we agreed that co2 measurements are accurate to 1ppm, 2006 measurements are about 380ppm +-1ppm and 1996 measured about 360ppm +-1ppm. Which makes a total of 20ppm rise with only 2ppm error - ie 20ppm +-2ppm. I could even point out that the further you deviate from the 20ppm mean, the less confidence you have. A 22ppm rise and a 18ppm rise is less likely than a 20ppm rise for example. 22 and 18 are possible, but not likely.

Because we don't calculate the emissions over 10 years as emissions in 2006 minus emissions in 1997

As I pointed out, you get more than that figure just by using the actual figures. Over 260GtC in 10 years.

Natural background noise is not eliminated. You only have to look at the measurements taken over a single year to see it.

But as the table says, a minimum of 3.1GtC of that 6GtC must be put in "Storage in the atmosphere" within 90% confidence interval. Setting it at 0GtC is going to fall well outside that 90% confidence interval.

No Im not. The second part of the table is titled "Partitioning among reservoirs", ie you have to partition the amount of human emissions amount the reservoirs. You don't get to partition a higher number than human emissions among the reservoirs.

So you are claiming that mathematically, statistically, logically and intuitively you can spend $15.5 of $9 given to you....

The important thing is that the table is including them as anthropogenic emissions. The 2nd part of the table would have lower values if they had left land use changes out.

Given that it's a 90% condifence interval you don't have much room to go outside them. You certainly have no scope for going 16 times outside the confidence interval by saying the atmosphere took zero (which falls way outside the 3.1-3.5 90% confidence range). It's not the case that any value outside that range has 10% chance. A value less than 3.1 has 5% chance (the other 5% is for above 3.5). And the further you go down from 3.1 the lower the probability goes.

$0 for "Lost it" falls outside of the 90% range of $1-$3, so there is less than 5% chance that they lost none (5% for anything lower than $1). Probably less than that depending on where the 99% condifidence interval lies, you are twice the 90% confidence range out so it's going to be lower than 5%

You are saying that 0 of the carbon is partitioned into the atmosphere, wheras the 90% confidence interval given is 3.1-3.5. That means:

--------5%--------|-90%-|---------5%-------

there is less than 5% chance of no < 3.1 GtC going into the atmosphere. But it's going to be much less than 5% given that you are so far from the 90% range. It will look like this:

------2.5------|A-2.5%-|----90%----|-2.5%-B|-------2.5--------

Where A and B represent the 95% confidence interval, and it can be subdivided further into 99% and beyond. zero co2 is going to fall outside of a very large confidence interval given that it is 16 times outside the 90% interval.

What will be the case is that the further a figure gets from the mean of 3.3, the less confidence there is. There is less than 10% confidence of it being more than 0.2 from 3.3GtC. Yet a zero figure is 3.3 off, not just 0.2. That is going to be outside even the 99.9% confidence interval.

You're missing the concept of an error rate. An error rate implies that any value within the range of error has equal likelihood of occurence. I could just as well argue your numbers are overvalued or undervalued.
Oh, so now they're "liberal" error rates? Before, you agreed you could "easily accept a given year's value may be off by .5ppm." But now that you've been shown how those equally likely values would prove you wrong 50% of the time, they're suddenly "liberal". You're funny.
Of course, like I said, go out a million years if you need to prove your point. See, I'm not married to any one conclusion, so you don't have to convince me. I will require you use at least some semblence of scientific method though.
As do you. You require the numbers to be a certain amount in a certain direction. Again, you miss the concept of error ranges.
That's true. Do you have any standard deviations for these numbers? Do you have any confidence levels? Do you have any distribution data? I mean, if you claim to be "99.99% sure", then you must have some statistical data that brings you to that conclusion. Unless, of course, you're simply taking the word of press releases you read on the internet. Naw, that couldn't be the case.
*sigh* The numbers are not "off". Those with an open mind will grasp this. I only continue writing for them.
And if we go out a billion years the probability of the CO2 rise being greater than human emissions grows. But, you just feel free to extend it or cut it off wherever you like to alleviate any internal dissonance facts may cause with your desired conclusion.
I explained why:
"You're arguing we can take one measurement, of a highly complex and wildly variable system, and extrapolate that over a ten year period."
Of course, because 10 years gave you the answer you needed, so you stopped there. Good science.
Yes, it isn't justified. Onon, are measurements taken every 10 years, or every hour?
Ahhh, but we calculate the change in CO2 concentrations over 10 years?
What actual figures? Have you provided a source to actual anthropogenic emissions over the past 10 years that I missed?
Uhhh, the measurements are taken every hour, simultaneously with two different flasks. Those two measurements do not match. If they are off by more than .5ppmv then both measurements are discarded (or one is kept depending upon the subjective judgement of the researcher). Both measurements are recording the same air, ergo the difference can only be explained as a measurement error. You should read your sources.
First of all, the table doesn't say any amount must be put anywhere. Just because something is outside the 90% confidence level doesn't mean it is an impossible occurence.
*sigh* I'm not arguing we are partitioning a higher number than human emissions among the reservoirs. I'm arguing that all of it could be partitioned without using the atmosphere.
Given the probabilities and possibilities of the problem you presented, yes.
How so? You can't have two variables dependent upon each other in the same equation. Are you arguing the researchers first determined the emissions values, then simply plugged some numbers into the partitions in order to make their equation work?
Yet still possible, making your absolute and definitive statements false.

No it doesn't imply that. Many error ranges follow a normal distribution of probability where the liklihood decreases the further from the midpoint.

Even if the probabilies were equally distributed across the error range (and I don't believe they would be - as if all of a sudden one value is possible and 0.1 below it is totally impossible) you used for co2 rise in 2006 they would be:

1.33-1.73 20%
1.73-2.13 20%
2.13-2.53 20%
2.53-2.93 20%
2.93-3.33 20%

You used the very highest figure of 3.33 which is in the < 20%. That's what I mean by using a liberal error rate - you have taken the most extreme amount of error possible for the example. I understand you were showing it was possible for co2 rise in a certain year to be more than human co2 emissions, but it certainly isn't anyway near as probable as the co2 rise being less than the co2 emissions.

As I have said before a particular year is subject to more uncertainty than a range of multiple years. So there is a small probability that cannot be written off that co2 emissions do not meet the co2 rise in a particular year. It's only when using multiple years that you reduce the uncertainty and see human co2 emissions are greater than overall co2 rise.

At least 95% of the possible configurations are compatible with co2 rise in 2006 being less than human emissions in 2006. Only 5% are compatible with co2 rise being more than human emissions.

Gt co2 rise error range for 2006 10.4 - 26
Gt co2 emissions error range for 2006 22 - 32

You require the co2 rise to be more than 22 in order for co2 rise to be more than co2 emissions. That's just 25% of this error range you can accept (ie only 22-26 out of 10.4-26)

You require the co2 emissions to be no more than 26, otherwise co2 emissions will be more than the co2 rise. That's just 40% of the error range you can accept (ie only 22-26 out of 22 - 32)

Altogether you require both of these to be true. 25% x 40% = 10%

But also half of those 10% of configurations will still result in co2 emissions being more than co2 rise (eg a 23gt co2 rise and 25gt co2 emissions), so in fact you can only accept 5% of possible configurations.

Not to mention that this assumes an flat distribution of probability across the error ranges, when the actual case is probably a normal distribution which would lower your proportion even more.

So the probability that the human emissions in 2006 were higher than the co2 rise in 2006 is more than 95%

I said above that
"a particular year is subject to more uncertainty than a range of multiple years. So there is a small probability that cannot be written off that co2 emissions do not meet the co2 rise in a particular year."
And here you can see that this small probability less than 5% for 2006

That figure gives an indication of how certain I think the recent co2 rise (100ppm) being attributable to humans is. Equally I could say I am also 99.99% sure that common descent of species is true, but no statistical data there either. The 99.99% is to emphasise that I see it as more certain than 80% or 90%.

You do require them to be off. Using the estimated figures will show that the co2 rise is much lower than co2 emissions for 2006. You require the estimates to be off, ie for the co2 emission estimate to be overestimated and the co2 rise estimate to be underestimated. You require both estimates to be off, not just one of them, and they must be off in a certain direction and by quite a lot too.

Using a longer period than a single year minimizes the proportion of the error range for the co2 rise. For example using the 2006 figure you gave of 2.33ppm+-1ppm, that error range means it could be as much as 43% off.

But for a ten year period the error range is just 20ppm +- 2ppm, meaning the actual figure can only be as much as 10% off the estimate of 20ppm. So clearly it is better to use data with less error range no?

And when using data with less possible error what emerges is that co2 emissions are clearly over the co2 rise.

Nope, we don't need to extrapolate - we have the data for the last 10 years so why are you so reluctant to use that? What's wrong with taking the rise over the past 10 years, and emissions over the past 10 years?

Well lets take 20 years then, a co2 rise of about 33ppm +-2ppm (notice the proportion of the error range has decreased again, so now it is only going to be about 6% off, that is the key to why using longer periods causes the fact to emerge that humans are putting more co2 into the atmosphere than co2 concentrations are rising)

co2 rise error range: 241Gt - 272.6Gt

co2 emissions for last 20 years: 485Gt (from http://cdiac.ornl.gov/ftp/ndp030/global.1751_2003.ems 2004,2005 and 2006 taken as the same as 2003)

So the co2 emission estimate is 212Gt more than the upper end of the co2 rise error range. You need co2 emissions to be 44% overestimated in order to stand any chance of co2 rise being more than co2 emissions in that time period.

So no I didn't have to stop at 10 years.

Yes, both. By definition if you take co2 measurements every hour you are going to be taking them every 10 years too...

Look it's simple. We took measurements in 2006 with +-1ppm error, and took measurements in 1997 with +-1ppm error. So the co2 rise in 10 years is calculated as the measured level in 2006 minus the level in 1997, with the error rate being +-2ppm (the combination of both end year errors)

Yes it's simply a matter of taking the measured co2 concentration in 1997 and taking this from the measured co2 concentration in 2006. That will be the rise over the 10 years.
Global Monitoring Division
http://www.cmdl.noaa.gov/projects/we...co2_mm_mlo.dat

http://cdiac.ornl.gov/ftp/ndp030/global.1751_2003.ems gives you the years 1997-2003, then I took 2003 value as the 2004-2006 figure. That actually works in your favor given that co2 emission rates have risen in that time period (Growth rate of carbon dioxide emissions doubles since 1990s "From 2000 to 2005, the growth rate of carbon dioxide emissions was more than 2.5 per cent per year, whereas in the 1990s it was less than one per cent per year"), but I do not have the actual figures for every one of those years.

If you look at the monthly data you can see the natural background noise, that does cause uncertainty in estimating the co2 level for a given year:
http://www.cmdl.noaa.gov/projects/we...co2_mm_mlo.dat

When the 90% confidence interval is between 3.1 and 3.5, how much confidence do you actually believe there is for a value below 0.1? It's very likely you are outside even the 99.9% confidence interval there.

Well you are implicitly doing this by ignoring the land use change emissions. I am also arguing that it cannot be partitioned without using the atmosphere.

Yes. The second part of the table is giving the ratios for the anthropogenic co2 emissions go into. The second part is dependent on the first. The first is not dependent on the second.

Just because it is possible for something not to be true doesn't mean it cannot be scientific fact.

Something might be possible, yet too improbable to entertain. Effectively a low enough probability event is treated as effectively impossible in science. Otherwise nothing could be a fact and be given in absolute and definitive statements.

Yes, it does imply that. You still haven't read your source. I'll repeat it for you:

Two measurements are taken at exactly the same time in the same place. These two measurements are compared. As long as the measurements do not differ by more than .5ppmv they are included in the data set. Therefore, two measurements exist in the data set for one data point. It is possible these two measurements differ from each other by .5ppmv. Which measurement is the "true" measurement? They don't know, they only know the "true" measurement is somewhere within the range. It has nothing to do with probability, and everything to do with the inaccuracy of the data collection method.
Do you have a distribution for the data set? Mode? Median? Range? Standard deviation? If not, then you're just making shit up.
And as I have repeatedly tried to point out to you, we're not taking measurements every 10 years. We're taking measurements every hour. Ergo, every measurement has the very real possibility of being within .5ppmv of the reported value. That's why I went to great pains to show you multiple years. The fact remains that in 5 of those 10 years, 50% of the time, the rise in CO2 could be greater than the anthropogenic emisions.
All values within the error ranges have equal probability of occuring. It is no more accurate to say that 7.1GtC is the correct figure for anthropogenic emissions than it is to say that 6.0GtC is the correct figure for anthropogenic emissions. Both have a 90% probability of occuring, according to your source. It is no more accurate to say that 2.33ppmv is the correct increase in CO2 concentrations than it is to say that 2.83ppmv is the correct increase in CO2 concentrations. Both have 100% probability of occuring, according to your source. All irregardless of how badly you want them to be something definite.
Then we should just start taking measurements every 100 years, that way we can be certain.
You know what they call belief in the absence of evidence don't you, onon?
Oh, no doubt. As I wrote, let's take measurements every 100 years, then the estimate will only be off by 2%. Hell, we could approach fact by never taking measurements at all.
Don't be dishonest, onon. I've used the data you provided. I've used it as nearly in accordance with how the data is collected and how it was meant to be used. The data was meant to show hourly variation in CO2 concentrations. Without the hourly data, and their concomitant error ranges, we can't make as accurate an analysis as the data would provide. We should go to the next best thing, which would be the monthly averages, which are provided. But I didn't need to go to all that trouble to prove your statements false. I only needed to use the third best option - the yearly averages - which is still a damn sight closer to the intent of the data set than 10 years of averages. You're implying an average of the average of the average of the average is a better indication of reality than an average of an average. The more you manipulate the data, the farther from reality you get.
And yet 5 of the past ten years could have had an increase in CO2 concentrations greater than the estimated amount of anthropogenic emissions.
Doesn't matter. The two flasks are collected at the same time, in the same place. If there is background noise, it is not possible that one flask would contain it and the other would not.
Doesn't matter. It's still possible the entire anthropogenic emissions could be absorbed by non-atmospheric sinks.
Land use changes aren't emissions, ergo they are not part of the amount that needs to be absorbed. That claim fits the data. Your claim does not fit the data because the researchers did not argue atmospheric absorption is a 100% certainty.
Ahhh, that's good science. Let's just plug in numbers that make our conclusion true.
I never argued anything definitive, so I don't have to prove anything is fact. Still, one fact remains: 50% of the time, your statements are false.

I'm done, onon. You're just repeating yourself and not providing any substantive new arguements. I've proven to you your statements are not necessarily true and that was the intent of engaging you. You can either accept the proof and add it to your knowledge of this subject, or continue dismising everything that contradicts what you want to be true. Either way it makes no difference to me. I don't debate deists and I won't debate AGW proponents. I've got nothing to gain, and nothing to lose either way.

Climate Change 2001: The Scientific Basis

Looks like the actual figure for anthropogenic emissions in a given year can only be off by about 6.5% off from the estimates.

That just about settles this. You were only able to show co2 rise could outweigh co2 emissions in a given year by assuming anthropogenic emissions could be off by about 30%.




That is true for one measurement, but not the average of many measurements which is where the co2 figure for a given year comes from. The error range for that figure will follow a normal disribution. co2 measurements are taken thousands of times during a year, so the error range due to measurement error is far lower for the average than for a single measurement.

I used your assumptions:
1. that the max co2 rise is 3.33 for 2006
2. that the error range of 1.33-3.33 for 2006 co2 rise has equal probability distribution.

Those are nice assumptions for me to use because they are the best case senario for you. If the error range is normally distributed (as I believe it is) in which case co2 rise above 3ppm in 2006 is unlikely, then the results will show the co2 rise is close to the actual average figure given of 2.33, and that makes it very difficult for co2 rise to be more than co2 emissions.

Right, so from what you are saying then at most the average of the 1997 measurements could be 1ppm off, and the average of the 2006 measurements could be 1ppm. That means subtracting the average 2006 level from the average 1997 level gives you the 10 year rise with a max of 2ppm off. That is what I am doing, and none of your arguments address that at all. I don't know what you mean by "we're not taking measurements every 10 years". Yes we are.

But most probably is not. You'd be lucky to find one year in 10 that did that.

That is not necessarily true I believe it follows a normal distribution where the further you get from the average the less liklihood there is.

But I did show you what happens by even assuming equal probability:

1.33-1.73 20%
1.73-2.13 20%
2.13-2.53 20%
2.53-2.93 20%
2.93-3.33 20%

That represents an equal probability across the error range for co2 in 2006. Any value has as equal chance of being the actual value as any other. But ranges of course have differeing probabilities. The probability of the actual value falling above 2.93 is just 20% for example.

No the source does not say that. It says that the actual value has 90% chance of falling somwhere between 6.0-8.2 has 90% chance, not that all those values inbetween have equal probability. You might find that the 50% confidence interval is just 6.8-7.4 for example (and it looks like from the above links that the error range is even less that this)

But the probability of the actual value being more than 2.93 is 20%, with 80% probability of it being less than 2.93.

1.33|-----20%-----|1.73|-----20%-----|2.13|-----20%-----|2.53|-----20%-----|2.93|-----20%-----|3.33

Ie

1.33|--------------------------------------------80%--------------------------------------|2.93|-----20%-----|3.33|

Only 20% probability of the actual value being higher than 2.93

We can be certain with just 10, more certain with 20. More than 50 and we have to start using ice core measurements for the pre 1950's period. But it would still work out as higher co2 emissions than co2 rise.

Why not use a period in which the error rate gives us good enough certainty of the result? 20 years does it for sure.

It's meant to be used exactly how they have used it. Observe:
co2graph

Notice they are perfectly happy to use the data to show long term trends. They even show the rise for the last 60 years. Yet you seem to be complaining that we shouldn't calculate the rise over the last 10...

And monthly, annually, and on decadal time scales. All of them, not just hourly. That's like claiming that because market levels are measured every few seconds, therefore they intend to see variation over only a few seconds and that they don't intend to perform analysis on weeks, months, or even 10 years of stock market trends.

You say "the next best thing" as if the monthly averages are somehow inferior to the hourly averages. You are aware that by measuring every hour they implicitly measure every month too? I don't see you argument at all.

If you only want to use measurements on the 1st hour of the 15th day of every month then that option is available. However it won't be as accurate as taking the average measurements over each month.

The intent of the dataset is not to take hourly readings, it's to compile hourly, daily, monthly, yearly and decadal trends. All of them, not just hourly.

Seeing as I am performing the same calculation you did, but for two year - 2006 and 1997, I don't see your point. I am not averaging an average of an average, I am taking the difference of two averages of averages.

With a very low probability. On the otherhand the probability that co2 emissions over the past 10 years are more than the co2 rise is very high to be beyond reasonable doubt.

The background noise affects the yearly figure, not a single measurement. Measurement error has very little impact on the yearly average, as by taking many measurements you reduce the overall measurement error. For example imagine co2 levels were static at 380ppm for an entire year, and you took 8760 hourly measurements over the course of that year.

A single measurement has an error range of 379.5ppm - 380.5ppm, and assuming equal probability across this error range any one measurement could fall anywhere between with equal probability. But the average of 8760 such measurements does not have the same equally distrbuted error range between 379.5ppm - 380.5ppm.

I did 1000 runs of averaging 8760 hourly measurements of random value between 379.5 and 380.5 and got these results:



The lowest average I got was 379.912, the highest was 380.083

That's an error range for an average of about +-0.085. rather than an error range of +-0.5 for a single measurement.

Also you can see it the probability of an average falls the further away it is from the actual value, ie a normal distribution.

It's overwhelmingly certain that this isn't the case.

Land use changes are technically not emissions, but because they result in loss of absorption they therefore result in extra co2 in the atmosphere, and that's why scientists do include them as anthropogenic emissions. Anthropogenic sources might be a better phrase, but that's just an argument over words.

When the 90% confidence interval is between 3.1 and 3.5, 0 is not going to be likely at all. Beyond reasonable doubt.

Your the one trying to use the table wrongly, not me. That table simply shows the partitioning of co2 emissions into natural reservoirs. It's probably based on ratios, ie they know the oceans absorb a certain proportion more co2 than forests, so they plug in the first set of numbers to get the second.

That is not true, it is based on false assumptions on your part that a figure of 0 into the atmosphere is just as likely as a figure of 2.9 going into the atmosphere. Just becuase both are outside the 90% confidence interval doesn't mean both are just as likely.

I understand that the Global Warming UN Socialist Seminar mentioned that humans actually are causing 25% less co2 than they originally estimated. Also, I heard that there isn't anything that could be done to change the climate as well.

Meantime, there is too much snow for skiing.

__________________
United We Stand.

The real deal?

Meanwhile, the Algore types are too busy gasping at the pictures Algore shows them in his "documentary" to bother spending any time doing actual scientific research like Dr. Shariv does.