An Ocean of Overconfidence

How long will we have to take daily measurements before we know the temperature of the entire pool full of water to the nearest two thousandths of a degree C?
Until it has all evaporated, then the temperature of the liquid water in the entire pool will be Null with 100% accuracy, no data, no error.

paper here: http://www.leif.org/EOS/2012GL051106-pip.pdf

put another way- it looks to me that the gross energy content of the ocean is on the order of 10^27 J? so we are looking at changes somewhere around 0.01% to 0.001%? please

If the ocean heating is driven by increasing CO2 and increasing surface temperatures as the authors claim, why didn’t the oceans warm in the slightest from about 1978 to 1990, while CO2 was rising and the surface temperature was increasing?

This at least is possible and no contradiction. Ocean currents and therby connected heat transfer and overturn occurs on all timescales in the ocean. These variations may conceivably be due to heat moving in or out into/from deeper ocean layers.
Howver and regarding the ‘accurate measuring’ problem, a more viable method to determine (estimate) changes in in total ocean heat content would be through measuring sea level changes accurately. And this can be done at the surface, and with less probes (‘thermometers’) than in the swimming pool /the oceans, since gravity does not change over the time scales considered here.
Thermal heat expansion of ocean water is ~independent of water temperature, and thus changes in heat content and total volume match each other well. The contamination there is from melting land ice, and possibly a little from changing water content of cultivated land areas. Both these, however, should be easier to estimate/measure than 2000m ocean heat content using thermometers.

Deep sea thermal vents were not even discovered until 1977. Just sayin’.

Are they actually trying to claim that after about 1994, they have 100% of the ocean measured?

When Warmistas promulgate their cargo-cult ‘science’,
you’re supposed to genuflect and vote to outlaw carbon dioxide.
Error-finding critiques are only for ‘deniers’, not for Warmista Scripture.
When a Warmista claims accuracy of 1 part per trillion, then accept it!
Have faith in science and shut up! Don’t scrutinize, don’t doubt, don’t even look!

Thank you for your analysis – I’m going to show this to my teenage daughters as an example of how what some scientists present as “settled science” can be demolished in several paragraphs by other scientists; ie in minefields we cannot afford to passively “be informed” but must consider different views.

Leif provides a link to the paper (Thanks!), that includes this scarey bit”
“If this heat were instantly transferred to the lower 10 km of the global atmosphere it would result in a volume mean warming of this atmospheric layer by approximately 36°C (65° F).”
Then they admit this can’t and won’t happen. I wonder whose idea it was to make this calculation and why? Why not calculate how many vaporized climate scientists can dance on the head of a pin? Equally useful.

From a process engineering standpoint, it is impossible to get such high precision.
I work at a bakery, where we make about a million lbs of bread each week (seasonally averaged). We have a machine called a proof box. It is a room with about the same internal volume as an olympic sized swimming pool. The bread moves through this room on a continuous conveyor line. We have both wet and dry bulb thermometers placed throughout the interior, and we run a device called a mole through periodically to callibrate our climate controls. The climate controls inside our proof box are state of the art. There is a direct connection between our ability to control that environment precicely and our quality/profitability. Bread that doesn’t rise properly ends up going in the pig feed trailer. When money is at stake, you can bet your left leg that every effort is made to get it right. I can tell you that in a fluid such as air or water, convection can lead to very uneven temperature profiles. The temperature you read at any given location may be totally unrepresentitive of the temperature just a few feet away, and no given set of temperature/humidity readings can ever be assumed to be representative of the area as a whole. We have seen faulty trends of increase and/or decrease many times due to the quirky ways air can circulate inside the box and/or problems with the instruments.
As an added note: Taking two readings seperated by some space and assuming that the area between them has a value averaged between the two measurements is insane.

This is the same game as the precision and accuracy problem we all face when we try to treat a dynamic, heterogeneous, gross, and I mean Gross, amount, volume in this case, as if the work was being done in a laboratory. Nonsense is not a strong enough term. We can’t even achieve this in relatively static volumes such as large rock masses (hundreds of cubic meters not millions of cubic kilometers.) Who knows maybe they believe in the tooth fairy too. More seriously I have written a number of essays trying to address the precision/accuracy business from a practical and philosophical point of view. It is another one of those seemingly simple things that turns out to be highly complex.

It is good to see the paper. It is good to read the serious questions. Nothing surprises me more than all the ocean heat content claims. The oceans are not only huge, but have only an average temperature of about 4°C.

Even the draft paper at NOAA states a similar order of magnitude in temperature … which is silly as it is impossible in practice to achieve measurements of such precision across multiple sets of instruments operating over long periods in uncontrolled environments.

It is frequently possible to measure changes more accurately than absolute values.

The way these guys make up statistics is chilling, and even more chilling is the way most gullible people believe them. Common sense contradicts many of the ‘statistics’ climate activists come up with. Help get the truth out by visiting ClimateTruthIreland.

“Never believed that anyone can measure anything to any real sense to a thousanths of the degree C, rates of rise in temperature or actual rises in atmospheric or oceanic media.”
Professor Spencer’s UAH measure satellite temperatures to the same accuracy.

I don’t think how to use significant figures is required learning to become an astrologist. Er, I mean climatologist.

Just wanted to beat Robbie and Monty
Mr. Willis Eschenbach needs to publish this. /sarc off 🙂
Well…lllll…you KNOW they are gonna say it.

Its much easier to accurately measure volume than than temperature. Yet over the period considered by this study, estimates of ocean volume have been reduced by around 10 million cubic kilometres or 5 Gulfs of Mexico, or 1% of the total. Maybe the ‘missing heat’ was in that disappearing water? (http://www.tos.org/oceanography/archive/23-2_charette.pdf)

PPS—Bonus question. Suppose we have an Olympic-sized swimming pool, and one perfectly accurate thermometer mounted in one location in the pool. Suppose we take one measurement per day. How long will we have to take daily measurements before we know the temperature of the entire pool full of water to the nearest two thousandths of a degree C?
Answer
You will never know the temperature of the pool to within two thousandths of a degree C. All you will know is the temperature at that particular spot, to within the accuracy of your thermometer. The pools that I have been in have warm and cold spots.
And to make matters worse, in any pool of water exposed to the suns radiation you will always have temperature differentials in any given volume of water, where one area is slightly warmer or colder than another area. I own a pool service and spa repair business. When I add a colored chemical to the water, I love to watch he the chemical disperses. On a nice warm sunny day, you can see the chemical dye shifting this way and that as they disperse in the water, carried along by currents created by slight temperature differences in different areas of the pool of water.

Steamboat Jack, I was kindof thumbing my nose at them 🙂
Here’s a thought about the Consensus:- Climategate Email 3165.txt
Many in the solar terrestrial physics community seem totally convinced that solar output changes can explain most of the observed changes we are seeing … the solar terrestrial group are not going to go away

tallbloke wrote:
“James Annan found some gross maths errors in Levitus et al 2000. Once he pointed out the maths error, Levitus et al’s corresponding author stopped corresponding with him…”
Apparently, Levitus felt under pressure to not to produce lower trends since that would be even less consistent with AOGCM simulations. The errors really are gross – the trend line in the global heat content graph disagrees to the data in the table by approaching 25%, if I recall correctly.
Even worse, when James Annan reported the errors to the editor at Science, he refused to anything about the matter.
Given this history, I find it impossible to assign a high level of confidence to any study authored by Levitus.

If they really believe they can make measurements at that accuracy I submit that they should be willing to wager a months salary that in a blind test two teams of their choice, measuring the oceans temperature on the opposite side of the same boat at the same time and depth can get measurements that agree with in 2x their alleged accuracy.
They will use new temperature measuring devices of their specification supplied directly from the manufacture.
Each team can make any number of measurements within a one hour time period.
All measurements must be made at the same depth. They will report their measurements in real time to an independent 3rd party as they take them, for offical documentation of the readings.
Then apply their pre-documented processing to that officially certified data converge on what they assert is the true temperature of the ocean at that location at that time.
They teams will at no time be aware of or able to determine the temperatures being reported by their opposite team.
The final measurements of the two teams must agree to an accuracy of 4 thousandths of a degree C.
If they win they get to keep their previous months salary. If they lose, all the team members donate a months salary to the charity of Anthony’s choice.
Myth busters where are you?
Larry

John T says:
April 23, 2012 at 11:39 am
“So I don’t know where they got their error numbers…”
“Seems like it may be an accuracy vs. precision type of problem confounded by a lack of understanding of significant figures.
Kind of like thinking if one of my steps is ~1 yard, I can calculate the length of a field to the nearest 1/64th of an inch if I pace it off enough times.”
Excellent analogy. Probabilities and the tails of a normal distribution curve deal only with sample size and say nothing about sample selection, sample location, accuracy of measurement devices, etc., etc., ad infinitum ad nauseum.

Rich Lambert says:
April 23, 2012 at 7:44 am
Climate science needs something like the ISO 9000 quality control standards used by industry.
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NO THANK YOU!
I used to believe that too until the FDA’s HACCP Requirements. ISO (and HACCP) substitute paperwork for actual testing and depends on faith in others who have a vested interest in lying.
This is what Quality Engineers like me think. (Quality Magazine)

“…Scott Dalgleish, [is] vice president of manufacturing at Spectra Logic Corp., a Boulder, CO, maker of robotic computer tape backup systems. Dalgleish, an ASQ certified quality manager who has worked in the quality profession since the late 1980s, is not happy with the direction that the quality movement has taken in recent years. And he sees the ISO 9000 family of standards as the primary negative influence.
Among other things, Dalgleish contends that ISO 9000 misdirects resources to an overabundance of paperwork that does almost nothing to make products better, while fostering complacency among top management and quality professionals alike. The recent conversion to the 2000 version of the standard has only made things worse, he says. While ISO 9000:2000 has almost no effect on how good companies operate, it requires huge amounts of time for document revision that could better be spent on real quality improvement, he believes.
http://www.qualitymag.com/Articles/Letters_From_the_Editor/e4100ee7f4c38010VgnVCM100000f932a8c0____
Probing the Limits: ISO 9001 Proves Ineffective
http://www.qualitymag.com/Articles/Column/17062620c7c38010VgnVCM100000f932a8c0____

I’m wondering if there might be a silent majority of Quality readers out there on the topic of ISO 9000. The response to my July editorial, “Eliminate ISO 9000?,” was the heaviest that we have received in some time. I got lots of e-mails from readers about the piece, which reported the views of Scott Dalgleish, a quality professional who has been publicly critical of the impact of ISO 9000 on manufacturers, and has suggested that companies eliminate ISO 9000 altogether from their quality management systems.
Many of the responses were quite articulate, and some were humorous and entertaining. You can read a sampling in this month’s Quality Mailbag department on p. 12.
One thing that struck me about the letters I received is that almost all expressed some level of agreement with Dalgleish, particularly on issues related to excessive ISO 9000 documentation requirements. As you’ll see in the Mailbag department, one reader even said that his company has already dropped its ISO 9001 certification with no apparent negative effects.
What surprised me is that the July editorial elicited no ardent rebuttals in defense of ISO 9000.
http://www.qualitymag.com/Articles/Letters_From_the_Editor/65730ee7f4c38010VgnVCM100000f932a8c0____

No amount of paperwork can substitute for honesty. A good documentation system is always useful but it should not be the area of focus. Decent honest testing and data gathering is the backbone of all science including Quality Engineering.

agfosterjr says:
April 23, 2012 at 10:59 am
Give a million monkeys each a rectal thermometer and you’d be surprised what you can measure, as any primatologist will tell you.

Now you’ve put me in mind of the old joke:
“How can one tell the difference between an oral and a rectal thermometer?”
“The taste.”

Gary Pearse says:
April 23, 2012 at 11:22 am
They need a disciplinary body created by a legislative act as is the case for professional engineers. They have this for engineers because when they are wrong, bridges can fall down, mines collapse, dams breach, buildings fall over…. We have reached a point where incompetence and advocacy in science is heading for doing real damage to civilization and risk of death for billions by taking away abundant, affordable energy and wasting scarce resources and wealth on unworkable alternatives. A few of the main scientist advocates, well known to all, would already have been barred from practicing their “professions” by now.
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That I can certainly agree with. I took the ASQ Quality Engineering tests to be come certified although that is not the same as a PE. Giving engineers/scientists LEGAL immunity when the company is cheating is also a big plus that comes with being a PE.
You actually need both, minimum competency and legal immunity.

@ Gail Combs says:
April 23, 2012 at 12:04 pm
Rich Lambert says:
April 23, 2012 at 7:44 am
Climate science needs something like the ISO 9000 quality control standards used by industry.
_________________________
NO THANK YOU!
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Small world! 🙂 I knew Scott thru ASQ. He’s not the only one who had problems with the ISO concept, and related auditing industry. It was a godsend for consultant larvae. What isn’t often mentioned is that the ISO auditors or their parent organization are not contractually liable for anything. That remains with the audited company. So there is really no incentive for a company to contract with an auditing organization, such as ASME or any of the many others, especially since the costs of doing so are significant. Then there was that loophole – self-certification. And of course various regulatory agencies get very nervous about it. FAA in my case.
We had this discussion at Boeing in the ’90’s. If you go back in the history of the 9000 series you’ll find that it’s primary raison d’etra was to ease trade restrictions and such within the budding European Union, by imposing standards of various sorts on the participating countries. It was sold to US companies as a way to ease entry into Euro markets.
I’m a little surprised that it’s still around, actually. Anything a company needs to know for QA/process control is available in many books on the subject from Juran, Deming, etc. as well as professional’s like Scott.

Rich Lambert says:
April 23, 2012 at 7:44 am
Climate science needs something like the ISO 9000 quality control standards used by industry.
REPLY: Yep, I argued for this back in 2008:
I’ve said the same thing here before too. I never believed that peer review was adequate quality assurance and neither do many regulators (e.g. the USFDA, USNRC). Actually better would be something less custormer focused, more along the lines of ISO 13485 or 21CRF820, Good Manufacturing Practices, which require you to fire the customer if they cut corners, are known to be engaging in fraud or dangerous practices.
“Sorry NSF, I’m returning your cheque because the Administration is misusing and misrepresenting my research to the National detriment”

At the risk of not preserving anonymity, I know the company that makes the sensors on the ARGO floats – competitors of ours….
It is perfectly reasonable that they claim an accuracy of better than ±0.002°C for any individual measurement. In fact this particular company has an excellent reputation and can achieve even better than that. In order to achieve this claimed accuracy, they do pretty much what we do – basically you calibrate your sensors in a highly controlled environment, against highly accurate standards. Amongst other things, this means regular checking of your reference sensors against Triple Point of Water cells, Melting Point of Gallium cells, etc. It also means your calibration laboratory is temperature controlled (much like Gary Swift’s proving oven, above), and uses well stirred, insulated and very stable liquid baths. All of which is as you might expect.
Being in possession of several such insulated and stable liquid baths, I can tell you that the pinnacle of stability that we can achieve in a highly controlled calibration environment is to be able to hold ~1m³ water to ±0.001°C for about a minute or so* (what I mean by that is that taking point measurements at say 1Hz intervals in an agressively stirred bath, the peak to peak noise over a minute will be less than ±0.001°C). Over a day it may fluctuate by up to ±0.05° , or perhaps more if we are not careful. We can hold smaller volumes (1 or 2 litres) to perhaps ±0.0005°C for 2 or 3 minutes on a good day*. Not having been given a guided tour of our competitor’s facility I am straying into guesswork, but I would imagine that this is similar to their own experience.
My eventual point is that I agree with you, Willis. We can and do try our hardest to measure to this level of accuracy for a single measurement, but to suggest that an entire dataset can be reduced to a single value with this same level of accuracy just doesn’t add up. It fails the smell test. We go to a hell of a lot of effort to be able to measure temperature to this precision and accuracy in a controlled environment. The sea is not a controlled environment – I see data all the time where people take a temperature profile at a site, and then take another a few minutes later, and the results have changed by fractions of a degree (if they are lucky – sometimes it’s completely different). Even within a single profile, at “stable” conditions, the temperature data will vary within a metre or two by more than a couple of millidegrees.
I put my hands up – I am not a professional statistician, but am obviously familiar with most simple principles such as averaging to reduce white noise, statistical significance, distributions, SD , etc, etc; I am however a scientist of a certain stripe by (first degree) training, and now a bit-part engineer, production engineer, finance guy, salesman and HR “expert”, as most entrepreneurs end up being, with an added dose of expertise in one’s chosen field, which in my case happens to be oceanography. The oceans are a highly dynamic environment, not a controlled one. I could be persuaded that minute by minute readings of a single location over a year could yield an average for that exact location to this order of millidegree accuracy. Would that average mean much? Not in isolation, no. I just don’t find it conceivable that the sporadic nature of ARGO measurements (and highly sporadic methods beforehand) can yield that level of accuracy for the whole globe. A finger in the air (or dipped in the sea)? I would suggest that considering their paucity of data, combined with the variability of the environment they are operating in, it would not be unreasonable to think that the globalised average number (over the top bit of the ocean only) was correct to within ±2°C , whatever that single distilled number is actually worth. But what do I know? Two things:
1) When the guys who make your test equipment** doubt your conclusions, there is something seriously wrong.
2) There should be many many more sensors in the sea 😉
(*) As measured against many 10’s of thousands of dollars worth of measurement bridges and PRTs.
(**) Just to reiterate – my company doesn’t make ARGO sensors, just instruments with similar sensors.

Just a comment on standardization in general: There are 3 basic types of standardization. In Europe and some other countries, Standards carry the weight of law and are enforceable as such. In the US we have a voluntary Standards system, which is usually contractually enforced between companies and their customers, but only carries civil liability in most cases. In Asia, Standards are usually company based – or in the case of Japan within the Kiretsu (sp?) – a large company will have their own internal standards that are imposed on suppliers. Very little government involvement.
These different systems often result in trade problems with import/export, as we see from time to time, with regard to products and commodities.
A bit of trivia – the ancient Chinese dynasties were among the first to implement quality and process control standards. A bow and arrow from one manufacturer would be indentical to that from another, or somebody would lose their head. Same goes for many other ancient cultures. The Pyramids in Egypt could not have been built without formal standards (of measurement, process, etc.) that were rigidly enforced.

Forget the ocean data. I don’t buy that we have 1/10th of enough thermometers to measure the air temperature. When the temperature varies by as much as 10F on my way to work(15 miles) outside Denver and the closest NOAA station is in CO Springs, there is not enough data to plot global temperature. And don’t get me started on all the corrections they make.

Don´t know about the rest of you guys, but to me that’s an example of a climbing curve.

Bob Tisdale says:
April 23, 2012 at 7:41 am
>>
Willis: A free draft of the Levitus et al (2012) paper is available through the NODC website:
http://data.nodc.noaa.gov/woa/PUBLICATIONS/grlheat12.pdf
>>
Good find Bob, that copy includes the all important supplementary information section that covers the uncertainty calculations.

@ Dr Burns says:
April 23, 2012 at 2:47 pm
Is there any evidence of 1955 marine thermometer temperature measurement having a measurement accuracy better than +/- 0.5 degrees ?
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For things metrological, I’d suggest you contact NIST – http://www.nist.gov/index.html . They are very helpful folks if you email the right person.

I have just scanned the version the Bob linked above that has the error calculations. This details the error propagation involved in their gridding method based on the variance of the readings. Unless I have misread it, it makes NO reference to the measurement uncertainty, ie it assumes (implicitly) that the measurement uncertainty is zero.
JK: However, to get an idea of the power of averaging suppose that there are 3000 argo floats, each reporting once every 10 days for 5 years. This will give 547,500 measurements. Each of those measurements will have an error associated with it. But to the extent that the error is random these will cancel out. From basic statistics we can expect that the error on the mean will be down by a factor of about square root of 547,500 which is about 740. That means that if there is a random error in each individual float of about 1.5 degrees the error on the 5 year global mean will be about 0.002 degrees.
Willis:
>>
Thanks, JK. You are correct in general. There are, as always, two questions. One is whether their assumption of random errors is correct. The other is whether they have done all parts of the statistics correctly. I am engaged in some fascinating research on that question right now, more to follow.
>>
No.This is the fundamental fallacy behind the ridiculously low ARGO uncertainty. You do not have 547,500 measurements of the same thing , that would allow the ‘divide by square root’ thing. You have 547,500 separate measurements of separate temperatures each with the full uncertainty. An uncertainty that is far larger than the simple platinum sensor precision.
Some part of that uncertainty , the instrument calibration uncertainty, will be reduced in this way over the thousands of individual floats. In any case it will probably be negligible compared to other errors.
However, that idea can not be applied to averaging of the temperatures which introduces a whole realm of other uncertainties. Principally, how representative is one reading at one point and a depth of the average temperature of the HUGE volume of water that it is being taken to represent. The uncertainty here is not millikelvin , it’s probably several degrees. That is several orders of magnitude bigger than some silly claims based on the total number of individual measurements as JK suggested above.
This representative accuracy of the one temperature then has to be added to the variance of the individual readings used to calculate the propagation errors in the paper.
Just how that will affect the overall uncertainty needs digging into but it will make a significant difference.
The problem here is that this has been totally ignored without the slightest discussion or recognition in the paper. Once again, climate scientists seem quite incapable (or unwilling) to correctly asses the uncertainty in their work.

While we are at it, I would love to see all the unit tests, for all the functions, for all the climate models that the US government has paid for. Surely they do that, right?

i have not read all the above but speaking as a layperson nothing manmade continues to work the same after a period of time — particularily if it is around salt water. Do they take some of these out of the water and check to see if they are still accurately recording data? They must have some spot check program in place — but wait — this is government funded — maybe not. If such exists it would be nice if it were given a quick mention to allay needless doubts in an old boatboy’s mind..

thermometer mounted in one location in the pool. Suppose we take one measurement per day. How long will we have to take daily measurements before we know the temperature of the entire pool full of water to the nearest two thousandths of a degree C?
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Interesting question.
Let’s change it slightly. Let’s measure temperature every 1 second with a precision of 0.1C.
Number of readings per day is 60x60x24.
That’s 86,400.
So 0.0003C is the precision for the average measurement assuming the pool is in equilibrium and isolated.
What we don’t know is how much variation there is in the pool due to changes in heating and cooling. Air currents and other stuff like clouds can affect this. Then you need to look at the measurements and their distribution and the frequency properties of the noise.

Had another think and read. The variation in heat capacity is moderate and not enough to affect an estimate of the average temperature in the context of Willis’ argument.

JK says:
>>
In this simple model the errors on the floats are uncorrelated: whether one float finds itself at a higher or lower temperature than the average for its region is independent of whether it’s neighbours are higher or lower than the average for their regions. Note, in this model it is the errors that are uncorrelated not the average. If a float in a high average region then it’s neighbour is more likely to be in a high average region. That’s a different question.
In that case then averaging, adding up these uncorrelated error terms, will indeed reduce their expected sum by a square root factor.
If you disagree with that, please explain where the disagreement is. Otherwise we can move on to clarify what changes in more realistic situations.
>>
Within the assumption that these errors are normally distributed and uncorrelated that seems correct. The question is what is the error of any reading , maybe this could be assumed to be less than 10K for example but I’m not sure how it could be evaluated.
Then there is : square root of what. the paper states that many cells have only one reading.
http://data.nodc.noaa.gov/woa/PUBLICATIONS/grlheat12.pdf
This version has the supplementary information on how they calculate the uncertainty due to propagation of errors in the averaging technique. You have to read it a few times but the crux is that they start with a complicated formula from another paper but do not have enough data to apply it , so they start doing some very inappropriate simplifications.
>>
… may be from one observation in data sparse regions up to several hundred or more.
Ideally, we would like to have a time series of measurements in each ODSQ [one degree sqr] with which we can produce statistics but this is simply not possible with the available data. Hence to evaluate standard deviations we will use the spatial variance of ODSQs containing data.
>>
For heavily populated squares they have a mean and a std error around that mean. Which, with lots of data, should be relatively small.
The problem is, for the cells with few data, they use the std error of the well populated cells and assume this reflects the error of single reading from the true mean.
Now if you stop to think, that means that they are incorrectly assuming the error of a one-off reading is the same as the error of a well balanced sample with hundreds of readings.
So their uncertainty calculations seem to be based on attributing the uncertainty for “several hundred” readings to cells of just ONE reading.
That dirty little secret gets tucked away in the S.I. which is not even available in the published version of the paper.
Now, until they can be bothered to do a correct analysis and a valid error estimation, using “hundreds” instead of one suggests that their error estimates are at least AN ORDER OF MAGNITUDE too small.
That is probably at least some way to Willis’ puzzle in the other thread:
http://wattsupwiththat.com/2012/01/26/decimals-of-precision-trenberths-missing-heat/

Let’s argue this from another angle. The oceans have warmed. Knowing the theorized mathematical equation for the ability of long wave radiation to warm the ocean skin, and thus by mixing, the layers below the mixing, it would be possible to determine what amount of that warming could be due to re-radiated LW infrared. It would also be possible to determine the part of THAT warming that is due to the anthropogenic increase in CO2.
My hypothesis would be that the LW warming would fall within the standard error of their data. This is a paper that would then appear to point towards a natural phenomenon.

Well queried Willis.
My question about the Argo floats has to do with the build up of bio material on the surface of the diving units. I suspect that there is something in place to control the film buildup, but from just using a squeege in my shower, I know that over time buildup still occurs. The film will affect the conductivity, and definitely with a change in conductivity, the measurement will drift. This would be true even if there weren’t currents etc. Moreover, the drift would be positive, as the electronics emit heat, small as that amount might be, it still would cause an upward bias. SInce the accuracy with which they are perporting to measure the temperature is so good, it would seem to be necessary to take into account small error contributions to the temperature measurement.
The above quibble is void if there is something like a plasma cleaner built into the devices.

mtobis (@mtobis) says:
April 23, 2012 at 8:56 am
It is frequently possible to measure changes more accurately than absolute values.
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markx says: @ April 23, 2012 at 9:26 am
….What you need to get increasing accuracy with repeated measures is, strangely enough, repeatable conditions.
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mtobis, that is the fallacy that is being discussed. I am going to expand on what markx said.
IF you are taking 10 or 25 or 100 readings with the same instrument within a short time period of a UNIFORM material in a lab, then you can use the average to give you a very good estimate of the “True Value” with tight error bars (+/- 2 sigma.) Once you are talking about a non-uniform material (the ocean) measured by different instruments at different times at different depths at different locations then you are talking about huge error bars because you adding up all the errors inherent in each measurement and not increasing the accuracy by repeating the measurement under the same conditions.
Think of that swimming pool again vs a mix room tank filled with water and with specially engineered blender blades. I dump the same percentage of a chemical into the water of both the swimming pool and the mix tank (blenders on) a half hour later I take 100 samples from the mix tank and from the pool at different depths and at different locations. With the mix tank I use the same equipment and technician to analyse the 100 samples. With the swimming pool I use different people to take each sample at different depths and at different locations. I use different people at different labs with different equipment to analyse for the chemical.
Do you really think I am going to come up with the same statistical distribution for the two sets of data points and similar standard deviation and therefore similar error bars? Or do you think the swimming pool is going to have a much wider spread (range) in the data and therefore a much larger error?
Which mean of the two sets of data do you think is going to come closer to the “True Value,” that is the known percentage of the chemical placed in the water?
The swimming pool data is analogous to the ocean data and Levitus et al. are trying to convince us they are dealing with a mix tank with the blender on when they apply the statistics to estimate the error.

Smokey says:
April 24, 2012 at 7:06 am
America is a “can-do” country that can out compete anyone. But we are being sold out by anti-American traitors. There is no better term for what is being done.
Actually, there are several — but there are ladies present…

Chuck Wiese says:
April 23, 2012 at 2:22 pm
…. There is no way to separate the contributing wavelengths that vary anywhere from solar ultra violet to the far end of the infrared spectrum, so in this regard, the claim of a rising heat content as being a proof that greenhouse gases were the cause is patently ridiculous.
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Actually there is given this graph of the solar radiation intensity for different wavelengths at various ocean depths. The climate scientists are shooting themselves in the foot and proving it is the SUN not CO2 that is the culprit for ocean heating. This is because as the graph states there is no absorption of energy at depth from the wavelengths given off by GHGs. Those wavelengths are around 10 micrometers and well beyond where the chart approaches zero around a wavelength of 2.5 micrometer. ( depth of 0.01m) Essentially the GHG energy can not penetrate beyond the surface “skin”

Underwater Sound Propagation: Temperature and sound velocity profiles
….The ocean depths, where little or no sunlight penetrates is of uniform temperature… In these isothermal regions, the sound speed, C, increases with increasing pressure as a function of depth….
In colder waters with less solar radiation results in small or no isothermal surface layer. The temperature continuously declines with depth from the surface…. Knowledge of the temperature profile and hence the sound speed profile, enables the prediction of sound transmission paths. Such information serves as input to the tactical environment in which submarine and surface navies operate…

Engineers have to get the science right. They can not play the games ivory tower scientists do or they fail.

theofloinn says:
April 23, 2012 at 8:18 pm
ISO 9000 is like any other tool, capable of being used in foolish ways.
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As W. Edwards Deming said: “Quality starts in the boardroom.” It does not matter what system is used if $$$ is all that concerns the members of the board.
My other big gripe was Just in Time. One nasty ice storm and you are up the creek without a paddle, and have nothing to go into the furnaces. (Fought and lost that battle too until nature whapped the CEO upside the head)

Gail Combes sez “Once you are talking about a non-uniform material (the ocean) measured by different instruments at different times at different depths at different locations then you are talking about huge error bars because you adding up all the errors inherent in each measurement and not increasing the accuracy by repeating the measurement under the same conditions.”
Indeed. At the ‘precision’ of .001°, there is no such thing as a right answer, as the hypothetical point which is being ‘measured’ is changing too fast.
BTW, Gail, though you are a possibly hairy primate, I suspect it was guerrilla war you were waging.

I would bet they are doing things like averaging measurements and assuming they are uncorrelated, so that they can scale the uncertainties by the inverse square root of the number of measurements. And, that assumption is, of course, bollocks. Inappropriate statistical manipulations have driven the CO2 bandwagon from the very start.