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global warming: salvaging fact from heaps of BS


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So far, temperature rise, measured as global average, is only 0.8 Celsius. We can live with that, and quite a bit more. Sea level rise has been a fraction of a metre, and we can live with that, also, plus quite a bit more.

 

The time for drastic and reckless action is still way over the horizon. We need to address the cause, as swansont said. The real problem is that governments are still fooling around, when there are real things they can do now. As I have said before, the world needs about 1000 extra nuclear power plants, since electricity is going to supplant fossil fuels as a resource in lots of areas. The important thing is to get under way the things that we can do, and develop new alternatives where such are not yet available.

 

Bio-fuels are a case in point. Mostly biofuels consist of ethanol from corn, or biodiesel from such things as palm oil. Both have been utter disasters so far, and both should be curtailed. If the world is to use biofuels on a large scale, we need new technologies, such as whole plant conversion to ethanol - not just the edible part.

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What most of the models don't take into account, is the #1 greenhouse gas which is H2O. For example, in the fall if there is a frost warning, if clouds move in to prevent the radiational cooling, the surface stays warmer because the heat is reflected back to the ground to prevent frost. In the summer when getting a tan, a bunch of clouds can work the other way and reduce the amount of solar energy reaching the surface. I would also expect at least some of the solar energy will be reflected back upward into space because of clouds, especially the high attitude ones that contain lots of tiny shiny ice crystals.

 

On relative scale of 1-10, water is up there at 10 and the rest are closer to 1-2 which why we need the best and brightest to help quantify these. The water is obvious enough to ask uncle Joe to act as expert. The water, since it is not included as a dynamic variable in many models, may be treated as a constant. If CO2 works like it is suppose too, then the heating affect will put more water in the air. There will be make more cloud cover, higher cloud tops for reflection, etc. One may even expect more high altitude clouds as the percentage of water gets higher and higher. There is also more water falling from high altitude which cools earth, etc. The projected numbers may be biased high.

 

This is not intentional oversight, just the water is very complicated to model because it affect is as dynamic as the weather itself. Maybe at least a study of solar reflection as a function of atmospheric water, such as cloud cover, cloud type and cloud height. For example, if one cloud type is better than another and the earth is producing more or less, this could have an impact. Even if heat is bouncing between the upper level greenhouse gases and increasing cloud tops, each bounce back and forth means some extra heat is able to escape the greenhouse gases.

 

The simplified diagrams show heating coming off the surface with one bounce against the greenhouse giving 35% return yield. After two bounces that may drop to 30%, just to use a number. The more cloud cover means more average bounces. The more clouds also means a cooler surface since clouds give shade. What is also happening, is some of the surface heat doesn't reach the other greenhouse gases because it bounces back off the clouds. The result may be the projections biased high. Once the water is included we can trust the results more.

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What most of the models don't take into account, is the #1 greenhouse gas which is H2O. [/qUOTE]

I'm sorry, Pioneer, but pretty much all of the conclusions in your post are false since you began with such an inaccurate and invalid premise.

 

 

 

You are enormously mistaken to believe (and suggest) that "most models" don't take water vapor into account. That statement is laughable in the magnitude of it's error.

 

 

(emphasis mine):

 

http://en.wikipedia.org/wiki/Global_climate_model

Atmospheric GCMs (AGCMs) model the atmosphere (and typically contain a land-surface model as well) and impose sea surface temperatures (SSTs). A large amount of information including model documentation is available from AMIP [4]. They may include atmospheric chemistry.

 

  • AGCMs consist of a dynamical core which integrates the equations of fluid motion, typically for:
    • surface pressure
    • horizontal components of velocity in layers
    • temperature and water vapor in layers

    [*]There is generally a radiation code, split into solar/short wave and terrestrial/infra-red/long wave

    [*]Parametrizations are used to include the effects of various processes. All modern AGCMs include parameterizations for:

    • convection
    • land surface processes, albedo and hydrology
    • cloud cover

A GCM contains a number of prognostic equations that are stepped forward in time (typically winds, temperature, moisture, and surface pressure) together with a number of diagnostic equations that are evaluated from the simultaneous values of the variables. As an example, pressure at any height can be diagnosed by applying the hydrostatic equation to the predicted surface pressure and the predicted values of temperature between the surface and the height of interest. The pressure diagnosed in this way then is used to compute the pressure gradient force in the time-dependent equation for the winds.

 

Oceanic GCMs (OGCMs) model the ocean (with fluxes from the atmosphere imposed) and may or may not contain a sea ice model. For example, the standard resolution of HadOM3 is 1.25 degrees in latitude and longitude, with 20 vertical levels, leading to approximately 1,500,000 variables.

 

Coupled atmosphere-ocean GCMs (AOGCMs) (e.g. HadCM3, GFDL CM2.X) combine the two models. They thus have the advantage of removing the need to specify fluxes across the interface of the ocean surface. These models are the basis for sophisticated model predictions of future climate, such as are discussed by the IPCC.

 

AOGCMs represent the pinnacle of complexity in climate models and internalise as many processes as possible.

 

 

If you'd like to support your contention with anything more than personal opinion, I'd welcome that.

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Chris,

The error in Douglass et al is that their estimate of the uncertainty in the model projections is the uncertainty in the determination of the mean of the model projections rather than the spread.

Since the model spread is rarely mentioned, in fact probably all model projections I've read refer to using the mean of ensemble runs, I don't see the problem. Even the IPCC (SEction 8.3) says

The multi-model averaging serves to filter out biases

of individual models and only retains errors that are generally

pervasive. There is some evidence that the multi-model mean

field is often in better agreement with observations than any of the

fields simulated by the individual models

Why do you object to comparing the mean to observations when the IPCC obviously doesn't? Is it because you don't like the answer?

Using older data without justification

Yes he did justify it, an Addendum was sent explaining the choice on Jan 3, 2008. Douglass quotes the relevent section in response to Gavin in the Briggs thread you contributed to.

looking at time periods of high internal variability doesn't help either.

The ROABCORE data covers the satellite period 1979-2004. How do you suggest getting accurate tropospheric temperature readings without using satellites? Or are you suggesting that due to "internal variability" records from the satellites should not be used? AGW theory requires accelerated heating in the trop, the models predict accelerated heating in the trop, the observations show the model predictions to be wrong.

 

Now I don't have a scientific background, however in my time here I've found that those who do, espouse (and have to repeat it endlessly to posters in the pseudoscience subforum:D) a simple step process to check a theory.

1. Formulate theory. (Check.)

2. Make testable predictions. (Check.)

3. Compare to observations. (Che......Oops.):D

 

As a point of interest,

Gavin Schmidt said,

The error in Douglass et al is that their estimate of the uncertainty in the model projections is instead the uncertainty in the determination of the mean of the model projections rather than the spread. It is exactly equivalent to throwing a dice 100 times and calculating the the mean throw to be 3.5 +/- 0.1 and than claiming that a throw of a 2 is a mismatch.

Chris C said,

The error in Douglass et al is that their estimate of the uncertainty in the model projections is the uncertainty in the determination of the mean of the model projections rather than the spread. It's like saying the mean of rolling a dice 100 times is 3.5 +/- 0.1 and claiming that one throw of 2 is a mismatch.

And people on my side of the fence get accused of "Parroting"?:D

This seems to be a distraction though.

It is a bit. Since reading the original comment I've had these funny pictures running through my mind. (They always run, as it's not a safe place to be.:D) Like I said earlier, some sort of arcane ritual, a Climatologist having an epiphany on the road to Damascus, a large, forboding, leather bound book the "Climatomnicon" kept in secret places. Taking the comment at face value, you can have a ball imagining how this "unspoken" knowledge is passed on.:D

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My apologies on the quote w/o credit.

 

AGW theory does not "require" extra tropical heating; this is a principle of moist convection that is expected from any cause. In fact, the greenhouse effect requires a temperature decline with altitude, so if observations showed less atmospheric warming than models show, then that would mean climate sensitivity was *underestimated* because of less negative feedback from the lapse rate response. Not overly reassuring that the models could be wrong. The models are in fact not right with the sea ice decline either, but not on the conservative end (Rahmstorf 2007).

 

The weather noise over the interval looked at is very important, and because of that, the spread of the runs due to weather is important. An ensemble is a collection of simulations run by one model, for one experiment, and is good for a set of possible trajectories for some forcing x. It's fine if you use data, but make sure you understand that there is noise, and not just the forcing from some external perturbation. It's like "global warming stopped in 1998 while ghg's have increased." Silly.

 

Because there is an incorrect treatment of the model uncertainty, and no discussion on the data choices (the original paper would have been nice, rather than being lost in blog comments), it seems that the other analysis which show no difference between models and observations are worth looking at, no?

 

...................................

Now I don't have a scientific background, however in my time here I've found that those who do, espouse (and have to repeat it endlessly to posters in the pseudoscience subforum) a simple step process to check a theory.

1. Formulate theory. (Check.)

 

-- Based on a centuries+ work of radiative physics, fluid dynamics, etc

 

2. Make testable predictions. (Check.)

 

--Like the temperature rise over the last century, strat cooling, increased ocean heat content, sea level rise, polar amplification, increased NH response, trop warming a bit more than surface, ice declines, species response, etc

 

3. Compare to observations. (Che......Oops.)

 

--Like the temperature rise over the last century, strat cooling, increased ocean heat content, sea level rise, polar amplification, increased NH response, trop warming a bit more than surface, ice declines, species response, etc. Now models aren't perfect, but when comparing them to observations, maybe a correct analysis would be good. Right now, the main and "broad" predictions are being borne out.

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My apologies on the quote w/o credit.

No sweat, my comment was meant in a friendly fashion, hence the :D. You gave me a great straight line and I wasn't big enough to pass it up. Just because we are on opposing sides doesn't mean we can't have levity or respect for each other.

Like the temperature rise over the last century

Applies to natural warming cycles also, is not indicative of AGW theory.

increased ocean heat content

Applies to natural warming cycles also, is not indicative of AGW theory.

sea level rise

Applies to natural warming cycles also, is not indicative of AGW theory.

polar amplification

Applies to natural warming cycles also, is not indicative of AGW theory.

increased NH response

Applies to natural warming cycles also, is not indicative of AGW theory.

ice declines

Applies to natural warming cycles also, is not indicative of AGW theory.

species response

Applies to natural warming cycles also, is not indicative of AGW theory.

 

All of the above points apply to a warming cycle of the climate in general. Are you trying to show that AGW theory is robust because it tells us

1. When the climate heats up, the temperature is warmer.

2. When the climate heats up, the oceans get warmer.

3. When the global temp goes up, sea levels will rise.

4. When global temp goes up it is more apparent in higher latitudes.

5. When global temp goes up, the increase will be greater in the NH.

6. When the temp goes up, the ice will melt.

7. When climate changes, species will migrate.

 

With the exception of 4 and 5 above, most primary school students would respond "Well, Duh!"

 

WRT strat cooling, I do have to read more on this to comment properly.

 

WRT accelerated trop warming, it should be a fair bit more than surface, which is what the models predict and the obs don't show. I have been thinking about this today and to be fair I think it would be better to say that the Douglass paper shows that using the mean of the ensembles does not have good predictive value. This would be a conclusion I can wholeheartedly agree with. Rather than using the mean of 22 models, find which ones most closely resemble the obs and throw the other ones away as the rejects are the ones moving the mean away from the obs.

it seems that the other analysis which show no difference between models and observations are worth looking at, no?

Certainly, do you have a link?

It's like "global warming stopped in 1998 while ghg's have increased."

Just to be clear, I've never said that. IMO the best that can be said concerning the last 10 years or so is that "The warming trend appears to have paused (or plateaued)". The Hadley 5 year running mean indicates that and nothing more. To say the trend has "stopped" is extrapolating future values from insufficient data. Although it should make one ask, just what is the negative forcing that appears to be masking the CO2 forcing?

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It may seem "well duh" which isn't the point, but rather that the models successfully capture these responses.

 

Concerning AGW vs. "natural cycles," there are very few examples of "fingerprints" associated with ghg warming that you don't get with solar warming, stratospheric cooling being one. Night/winter temperatures going up faster than day/summer temperatures is another, and that's observed. You might expect increased downward infrared radiation, which seems to be consistent (though this isn't exactly why the planet warms with more ghg's) with observations. The changes in tropopause height also seem to be consistent with externally forced ghg's. The ability to simulate anthropogenic + natural, but not natural variations with models helps, and the simple underlying physics and paleoclimatic evidence (what ought to happen in theory) all helps. A good read on detection and attribution (which also goes over the surface/atmosphere warming and models observations) is at https://e-reports-ext.llnl.gov/pdf/315840.pdf

 

See

http://www.agu.org/pubs/crossref/2007/2007GL029875.shtml

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This debate (between JohnB and Chris C) seems to show that there isn't as much consensus among the scientific community as I'm lead by that community to believe. Are we or are we not certain that AGW is real? Do the AGW deniers have a reasonable case?

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This debate (between JohnB and Chris C) seems to show that there isn't as much consensus among the scientific community as I'm lead by that community to believe.

 

How can you use two posters on a forum, one who is formally trained in climate science and another who is not, as enough data to make such an absolute statement about the "scientific community?"

 

 

That was rhetorical, you can't. Seems you have already decided what answer you want to see and now you are searching for and cherry-picking examples which help you to reinforce this biased preconception.

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This debate (between JohnB and Chris C) seems to show that there isn't as much consensus among the scientific community as I'm lead by that community to believe. Are we or are we not certain that AGW is real? Do the AGW deniers have a reasonable case?

 

I don't know if either of us are trained professionally in climate science (I certainly am not, I'm a student here though) but you can find "debate" in a lot of topics over the internet, from evolution to climate change to the shape of the Earth. The discussion in this forum is not indicative of the scientific "consensus" or lack of. There is a lot of "real" debate amongst credible scientists on many specifics such as how hurricanes might respond, how ecosystems will respond to a warmer climate, how much warming it will take to melt Greenland (and how fast), how soon we might cross various "tipping points," why strengthening convection enhances ocean heat uptake in one region while weakening convection enhances it in another, etc. But the broad brush details like "more CO2 will cause warming" or "massive releases of greenhouse gases and deforestation are influencing climate" are not seriously questioned, and these details are in fact "settled."

 

The real consensus on this can be found in the academic literature, but also every major scientific organization has accepted these conclusions. See for example

http://nationalacademies.org/onpi/06072005.pdf

http://royalsociety.org/displaypagedoc.asp?id=13619

http://gristmill.grist.org/story/2006/11/13/221250/49

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gib65, I'm not trained in Climate Science either. This is a debate between (as inow says) two posters on an internet forum.

 

Chris, sorry for the delay in replying, but RL is very busy ATM. (We do 60% of our annual business in the May-July period) I have to find the time to fully read and respond to your links.

 

Thanks for your patience.:D

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I'm more worried about the intellectual contamination of political science intruding on empirical science while pushing an agenda. Global warming is too often a social movement and not a scientific fact.

 

When climate change is understood as well as a set of simple chemical reactions, I'll believe the results. However, nobody but nobody understands all of the complex interactions that amount to climate and many, many significant variables are merely presumptions and belief so anyone who pretends have faith in the current generation of climate models has a God complex that they didn't earn.

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The fact that it's enormously complex and involves a great number of dynamic variables IN NO WAY means that it is not understood.

 

 

You can sew the word "faith" into your posts all you want, but I still don't understand how this argument from ignorance does anything to validate your mindset that "because it's difficult and complex" you refuse to accept the science. Also, how does one earn a god complex? Is there some sort of certification program involved? I think I'd like one of those. :rolleyes:

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The fact that it's enormously complex and involves a great number of dynamic variables IN NO WAY means that it is not understood.

 

 

You can sew the word "faith" into your posts all you want, but I still don't understand how this argument from ignorance does anything to validate your mindset that "because it's difficult and complex" you refuse to accept the science. Also, how does one earn a god complex? Is there some sort of certification program involved? I think I'd like one of those. :rolleyes:

 

There are many significant dynamics and variables that are simply not known, barely understood, filled in with presumption and theory and then spewed out as simple fact. Scientists are only human and are certainly not of like mind on a thousand thousand points within the picture these computer models try to project.

 

It is time to get beyond the Fossil Fuel Age in any event, and that belief is based on something far more compelling than global warming computer models.

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So, if they are so unknown and filled with presumptions, how is it that the models are so successful modelling past climates? Seems to me they are pretty damned close to accurate, and that all of them agree where we are heading if major changes aren't made immediately to the societal status quo.

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There are many significant dynamics and variables that are simply not known, barely understood, filled in with presumption and theory and then spewed out as simple fact. Scientists are only human and are certainly not of like mind on a thousand thousand points within the picture these computer models try to project.

 

Sounds like a pretty canonical argument from ignorance to me, or at the very best an argument from personal incredulity. Claiming the models are inaccurate because the inputs are based on scientific theory is hardly a credible argument.

 

It is time to get beyond the Fossil Fuel Age in any event, and that belief is based on something far more compelling than global warming computer models.

 

Can you point out something specific you think is wrong with the models, beyond completely baseless claims regarding their accuracy?

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Speaking of salvaging information from a heap of BS...

 

Another win for ClimateAudit.org.

 

Over three years ago, Steve McIntyre and his crew reported on a troubling bias they found in the "bucket" method used to measure ocean temperatures pretty much from the turn of the century until 1970. The "bucket" method, and many other methods were eventually phased out over the 30+ years following 1970. Here is a graph of the distributions of methods since 1970:

 

sstbucketor3.gif

 

This is important in that the "bucket" method introduced a 0.3 C downward bias in temperatures that was never accounted for. So the phase out of the bucket method over the last 30 years introduced an erroneous 0.3 C observed rise in ocean temperatures over that period. This is huge considering the total surface temperature rise that has the world so concerned is a total of 0.63 C... and that number used the ocean surface temps in their average.

 

I call this a win for ClimateAudit.org because after reporting on this serveral years ago (as well and refining their observation over serveral subsequent articles... and revisited once more here), the journal Nature has accepted a peer reviewed study that came to the same conclusion.

 

It should be noted, however, that the Journal Nature article was somewhat sugar coated when compared to ClimateAudit.org. Steve McIntyre has covered the Nature Article twice (here and here), and argues that the adjustments are not final as far as he is concerned.

 

At this point, who should we listen to?

 

On another front, Theodor Landscheidt gets more kudos as a solar scientist for predicting over two decades ago the sudden drop in temperature at the beginning of this year. He has long been a proponent of global climate being driven by solar variance, and was roundly discredited in his theories because the last 30 years of surface temps have not matched his predictions even as the solar activity has matched well with prediction (from the first part of this post, I guess we may see why).

 

Considering that Theodor Landscheidt was right 20 years in the future, but climatology is still adjusting temperatures in early 1900s, who should we listen to? Theodor Landscheidt can apparently tell us what the temperature will be in 2028, whereas climatology can't tell us what the temperature in 1914 will be next month.

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There are a lot of logical fallacies in your post, and it is much more "rhetoric" than proof. However, I agree with you that it's important to closely analyze the data and correct any errors once they are found.

 

That said, one error does not negate the mountains of other work which has been conducted without said errors. Further, one "correct" prediction does not negate the decades of incorrect predictions (such as those made by Landscheidt and McIntyre). Even a broken analog watch can be right twice a day. :rolleyes:

 

 

Oh yeah, speaking of logical fallacies and false premises:

 

Theodor Landscheidt can apparently tell us what the temperature will be in 2028, whereas climatology can't tell us what the temperature in 1914 will be next month.

 

Hmmm... "Next month" almost a century "ago?" Your statement is temporally confusing. Either way, I'll try to interpret what I think you mean.

 

 

June 1914 is shown here:

http://data.giss.nasa.gov/gistemp/tabledata/GLB.Ts.txt

http://data.giss.nasa.gov/gistemp/tabledata/GLB.Ts+dSST.txt

http://data.giss.nasa.gov/gistemp/tabledata/ZonAnn.Ts+dSST.txt

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There are a lot of logical fallacies in your post, and it is much more "rhetoric" than proof. However, I agree with you that it's important to closely analyze the data and correct any errors once they are found.

 

That said, one error does not negate the mountains of other work which has been conducted without said errors. Further, one "correct" prediction does not negate the decades of incorrect predictions (such as those made by Landscheidt and McIntyre). Even a broken analog watch can be right twice a day. :rolleyes:

 

 

Your statement is complete and utter bunk, as this particular data set was the one used to build that mountain of research that you speak of. Every model, every proxy study, every one referred back to the Hadley SST dataset in one fashion or another. It is and was the SST of record. And it was off by HALF of the observed rise.

 

So, as the 0.3 cold bias was weeded out of the measurement, we saw a bogus 0.3 C rise in the SST over that period of time.

 

Again, that is half of the 0.63 C we have seen..... you can't see the trouble in using dataset that has a calibration error of 50%???

 

Oh yeah, speaking of logical fallacies and false premises:

 

 

 

Hmmm... "Next month" almost a century "ago?" Your statement is temporally confusing. Either way, I'll try to interpret what I think you mean.

 

 

June 1914 is shown here:

http://data.giss.nasa.gov/gistemp/tabledata/GLB.Ts.txt

http://data.giss.nasa.gov/gistemp/tabledata/GLB.Ts+dSST.txt

http://data.giss.nasa.gov/gistemp/tabledata/ZonAnn.Ts+dSST.txt

 

Well, you are simply wrong. Go to:

 

http://web.archive.org/web/*/http://data.giss.nasa.gov/gistemp/tabledata/GLB.Ts.txt

 

Now look at all the previous versions of the data posted by GISS.... notice that previous years are not static things, but change constantly. This is because of the strange smooting technique used at GISS... temperature fluctuations ripple through the GISS database constantly. A cold snap in March 2008 changed the temperature record for 1903 and 1946.

 

So as temporally confusing as my statement may seem, it is the truth. They are not capable of predicting the temperature in June, and are therefor not able to predict the smoothing of prior years due to the temperature in June... so they indeed can not predict what the GISS temperature for 1914 will be in June 2008.

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Claiming the models are inaccurate because the inputs are based on scientific theory is hardly a credible argument.

 

I said there are a lot of unknowns, presumptions and unknowables within the realm of contemporary knowledge. You seem to think that all the presumptions are based on sound and proven scientific theory. Climate modeling as it exists today is at best a an art form pretending to be a science.

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Chris, I've finally had time (and ability) to read your links. The first especially is interesting although I do have trouble with some of their conclusions.

The simultaneous warming in all basins could not be explained

by solar variability or geothermal forcing.

Geothermal I can understand but to say that synchronous warming of all ocean basins could not be caused by the sun seems a bit far fetched.

 

I found the Wentz/Christy comparison (Figure 8) interesting. It would appear that the two plots "pivot" on the year 1988, with Christy higher prior to that date and lower aferwards.

 

I must also admit I find their logic somwhat nebulous at times. A sort of "We compared this estimate with that estimate and found they agree so we can conclude......." While I conceed that this can have a place in investigations, they seem to do an awful lot of it.

 

As an aside, I note that the paper is in favour of using the mean of ensemble model runs for projections. So Gavin's (and your) argument is that it is all right to use the ensemble mean for projections, but not verification. Is that right? IOW, "We can make any statement we like about model projections, but if you try to actually compare them to obs, we'll cry foul."

 

Your second link to the Thorne paper abstract may now be moot. I don't think anyone here is going to claim that Peter Thorne doesn't know his stuff, and in light of his comment at CA a couple of days ago I think all comments on surface/trop warming need to be scaled back.

The upshot is that the raw data is a mess and the choices that a dataset creator makes imparts non-negligible and unintentional bias into the resulting database. So, how do you address this? You get many people to look at the data independently. Yes, some may make dumb choices, but only through getting this multi-effort approach can you begin to understand what you can and cannot say about the data.

 

The fact of the matter is that we cannot definitively say whether the troposphere is warming less quickly, as quickly, or more quickly than the surface, either from sondes or satellites, although no-one doubts it is warming. Ambiguity is large (and nobody has a dataset without issues) and kills us every time especially when you are asking a much harder second-order question about relative rates of change at which point you need that uncertainty range to be much smaller. I’m amazed that our structural uncertainty in tropospheric trends is as small as it seems (order 0.3K/decade from both sondes and satellites) to be given the state of the raw data.

Such comments would appear to render papers from both sides of this debate somewhat moot until there is better interpretation of the data, (Although please don't bing in the Allen/Serwood paper. We can't trust the thermometers on the sondes so we'll use wind speed as a temp proxy? People get paid for this?)

Can you point out something specific you think is wrong with the models, beyond completely baseless claims regarding their accuracy?

I provided two links on page 2, will that do for a start? (Although given Peter Thorne's comment above, I think further discussion of Douglass et al should perhaps be put in abeyance.) I can find others if you wish. At the same time, perhaps you can find some proof for the matters I raised in that post?

 

inow, jryan is essentially correct. The GISS dataset is probably the most "adjusted" in history. As a layman I assumed that the temp measured in the past was just that, the temp measured. As such it becomes part of the historical record and remains unchanged but with GISSTEMP this is not the case, the past is being constantly adjusted and without explanation.

 

Again I post the GISTEMP record for Wellington NZ.

attachment.php?attachmentid=1767&d=1206844975

What was the temp in 1920? 11.2 or 12.5 degrees? What will the temp be after the next adjustment? Your guess is as good as mine. In that same thread I showed that the unadjusted temps for all of New Zealand showed no temp increase over the instrumental period, but after adjustment, warming.

 

This BTW is an area where I have problems with the climate models. How on earth can they be said to be accurately calibrated against past temps if the thing they are compared to (the instrumental record) keeps bloody changing?

 

jryan's point about the bucket adjustments is just another thing making the water ;) murkier. Climate models that fit the current instrumental record won't fit the new one after the bucket adjustments are adjusted. Make no mistake, this is a major adjustment accounting for some 40% of observed SST rise in the last 100 years. I'll also add that the Thompson paper is not "news", people have been aware of the problem for years.

 

(jryan, Judith Curry knew about it years before SteveM bloged on it.)

 

With regard to GHCN and USHCN I had high hopes for the new USCRN to bring some sort of sense to temp records. NOAA says this will be state of the art, properly sited and calibrated stations. However this remains to be seen.

 

Atmoz (who can't be called a "skeptic" by any means) d/loaded the data to have a look.

 

He posts this graph

uscrn_image1.png

and asks "Where am I?"

 

So my American friends, where in the US has regular daytime temps of 600+ Celcius in Summer and -10 to -150 in Winter? Personally I would think Death Valley or somewhere like that, but Wiki puts the highest temp ever recorded in the US at 56.70C and that was in Death Valley. This is a good 80C lower than the CRN reading shown on the graph.

 

And people wonder why I think there is some trouble with the LST records?:D

Edited by swansont
multiple post merged; adjust quote tag
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So, basically all I need to do is find one single study which does not use that same data set and your argument would be proven false.

 

Actually, no. BUt for the sake of argument, how about you do just that.

 

While you do that, I'll move on to some other interesting observations at climateaudit.org.

 

Here is a chart where they show a strange correlation between the SST in the 1900s and the number number of SST obervations that came from U.S. sources:

 

thomps1hj8.gif

 

Generally one would think that that is a clear indicator that the U.S. method of collecting temperatures was introducing a bias into the data.

 

And here is the adjusted SST...

 

sstadj1gx3.gif

 

The new data blunted the 1970 to 2000 heat spike considerably, while shifting a good deal of the warming shown in the SST to pre-WWII. This no longer jibes with the CO2 charts.

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Generally one would think that that is a clear indicator that the U.S. method of collecting temperatures was introducing a bias into the data.

Actually, my first inclination was that the US was measuring US temperatures and the UK was measuring UK temperatures, however, since you did not cite a source (and your image came from imageshack), I could not find out more.

 

What is the source of the data presented in your graphs? I'd like to see for myself what was being measured, what methods were used, and what those pictures you posted truly represent (that is, of course, if they represent anything useful at all, or if they are perhaps some random persons scribblings).

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inow, it's SST records.

 

The situation is interesting. SSTs were measured by literally dropping a canvas (uninsulated) bucket over the side of the ship, hauling it up and sticking a thermometer in it. This was the prevalent method for the British at the time. It also introduced a slight negative bias as bucket cooled by about 1/2 degree due to evaporation.

 

As you can see, there is a sharp drop in 1941. In December 1941 the US entered the war and their readings were taken into account. US temp measurements however were done by thermometers in the engine intake. This introduced a positive bias of an estimated 30. Folland et al in 1993 tried to rationalise and adjust for these biases.

 

His assumption was that in 1941, measurements went from predominantly buckets (needing a .50 positive adjustment) to predominantly engine intakes (needing a 30negative adjustment). This situation was deemed to somewhat reverse itself with wars end. It was further assumed that there was eventually a complete changeover to engine intakes by the mid 70s. He also took the (unjustifiable IMO) step of taking all readings from "unknown" methods and lumped them in with buckets.

 

We can now add to the mix tar covered (insulated) buckets, satellites, bouys and hull sensors. Each of these methods measures the SST at a different depth and requires a different adjustment.

 

With the oceans making up 70% of the surface area, any "oops" factor will have a large effect on GMST. Have a look at the CA posts jryan links to, it is an interesting subject.

 

I'm still following up so can't really comment except to say that our SST records don't appear to be as good as they should.

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