Global warming--the Data, and serious debate

[grmorton]

Without more information your plot is impossible to evaluate. It appears that it is the difference in two monthly averaged global temperatures from two years (2004 and 2007). Is that correct?

Of course it is not hard to evaluate. Go to climate at a glance, make the spatial map and then down load the matrix of data. I just forced them to fix the downloadable data which didn't work until about a week ago even though I had been complaining to them for 4 months.

At climate at a glance when you make the plot, you can double click on any dot and it will bring up a linear regression of the temperature at each point.

Each point is several years worth of data converted to linear regressions. When you criticise, you really should do the work to actually go to the site and look at the data.

 

[grmorton]

I am not going to get embroiled in the argument about land based temperature measurements as it is somewhat irrelevant due to the large number of other measurements that show exactly the same trend.

However I do want to elaborate on one of the points you brought up in the quoted post, which I bolded for clarity below. You are exactly right when you point out that CO2 lags temperature for the little ice age and for all the glaciations before that as well, generally by about 800 years wich coincides well with the over turning time for the ocean. You also are completely correct about the mechanism. The implication of this is to refute the claim that the current warming is non-anthropogenic. As you pointed out previous warmings are forced by changes in Total Solar Irradiance (TSI) either due to the sun or variations in the earths orbit. These changes drive CO2 from the ocean (due to reduced solubility) into the atmosphere, where it feeds back to amplify the initial warming. Now for the important bit - In the current warming, CO2 leads temperature, it does not lag. So clearly the mechanism for the current shift in climate is not the same as in previous shifts. You inadvertantly refuted your own point.

This is my last tonight. I gotta go to bed or I will be in terrible shape tomorrow.

You say CO2 leads temperature. Why is the world now cooling? Why are the oceans cooling? Lets put the ocean temperature in bar graphs, I get this from that Climate at a glance site of NASA.

It seems to me that there are no airconditioners or urban heat island effects out in the ocean and so the oceans as a whole are a better indicator of what is happening than the tainted land data. And if that is true, then temperature once again is leading CO2. This is not at all to say that mankind isn't putting CO2 into the atmosphere in prodigious quantities. We are. But, what you guys won't answer is what is the climate sensitivity. is it 1.7 deg C for a doubling or 4.5 deg C? Even the IPCC doesn't know and at the lower end of this range there really isn't a problem with CO2.

 

[chaim]

Taking two points (1979 and 2007 in your case) and using the difference between those points IS taking a linear trend. The difference between any two points is a straight line. It is however a statistically invalid trend as it throws out all the data in between for no good reason. Just like you said trying to fit a linear trend to cyclical data is meaningless. But for this to be relevant you are making the assumption that the current trend is cyclical.

Of course there is cyclical noise on the temperature data, there is ENSO, solar cycles etc convolved with any background trend. However when you do a long term trend (longer than the solar cycle and ENSO) there is still a statistically significant upward trend. This trend cannot be explained via TSI as the long term trend for TSI has been downwards over the last 30 years. Secondly the rate of change of temperature rules out the current warming being caused by a millenial period cycle.

No I am not going to discuss individual surface station data. It is well known that some of the stations are bad, including to the folks at NCDC and GIS. They go to great pains to filter their data for such issues, and as a result the data agrees well with the multitude of other temperature records. Climate science does not rest on the veracity of surface temperature stations, they are merely one of the many pieces of evidence that point to a warming climate.

Sorry, but this all assumes that there are no long term trends or frequencies. If you take a 1000 year cycle and then take 50 years out of that time frame, you can get a linear regression that shows whatever you want. But you don't have a linear phenomenon. I repeat. Linear regressions are only great for noisy LINEAR phenomenon. If a phenomenon is cyclical with many different wavelengths, finding a linear trend is meaningless.

You can call this dishonest if you want. It is what I have come to expect from the GW advocates who would rather bully than actually discuss t he data.

Would you care to explain Watersville Washington? See above. You pick and chose what points you want to discuss if you don't want to discuss the raw data.

Another question. Do you think it is grand to put a thermometer next to an air conditioner vent??? Is that a sign of competence on the part of the weather burearu to approve those sites?

Please answer the above.

I will again upload the satellite data. From 1979 to 1997, there is no rise at all. Indeed, the zero line almost perfectly bifurcates the cyclical data. Then there is a bump with the very active solar cycles of the early 90s and early 2000s, then the temperature goes back to about where it was in 1979. I stand by this. This is NOT a linear phenomenon. The ups and down are NOT randomly distributed but cyclically distributed.

Please look at the data, not at your bias.

 

[grmorton]

Taking two points (1979 and 2007 in your case) and using the difference between those points IS taking a linear trend.

Sigh, agreed, but, this is a cyclical phenomenon. you know, UP and DOWN. Depending on where you stop the roller coaster, depends on the average rate of change--which is linear. Let's test your concept of linear phenomenon below.

Below is the temperature trend for central Greenland over the past few years. Note, that contrary to press reports and global warming hysteriacs, Greenland has been cooling since 2003. Do you believe that the linear trend of -3.31 deg/decade trend will continue on until absolute zero is reached?

Of course not, you expect the temperature to go back up at some point in the future. So, why do you expect the global warming temperature to rise forever? I posted a solar flux measurement over the past few years. The sun is outputting much less energy and the earth is now cooling. We are a year and a half late for the start of the next solar cycle's upswing in sunspots. One of the most optimistic predictions says the upswing will start early next year. There were no sunspots yesterday or the day before or the day before. Indeed, at this time in most solar cycles we are at 30-40 sunspots on average. So far this year we are in excess of 205 spotless days--if you add 2007's spotless days we are in one of the longer periods of time in which the sun has very few sunspots.

And that means the sun outputs less energy. CO2 isn't the big boogey man, the sun is.

The difference between any two points is a straight line. It is however a statistically invalid trend as it throws out all the data in between for no good reason. Just like you said trying to fit a linear trend to cyclical data is meaningless. But for this to be relevant you are making the assumption that the current trend is cyclical.

So, do you think that the global temperature will rise forever linearly?
Do you think Greenland's cooling will continue forever to absolute zero?


[quoteOf course there is cyclical noise on the temperature data, there is ENSO, solar cycles etc convolved with any background trend. However when you do a long term trend (longer than the solar cycle and ENSO) there is still a statistically significant upward trend. This trend cannot be explained via TSI as the long term trend for TSI has been downwards over the last 30 years. Secondly the rate of change of temperature rules out the current warming being caused by a millenial period cycle.[/quote]

But, the rate of current temperature trend can be explained by urbanization. Do you know when Asia's temperature began to rise dramatically? After Deng Xiao Ping set China off on modernization and they poured more cement. We will get into this more over the next few weeks, but for now, I want you to know the impact of the urban heat island on temperatures. Below is from the Orange County Register

Gary Robbins,"Urbanization raises the heat in O.C.August 7th, 2008, 2:00 pm][/u]
"The average annual temperature in Santa Ana has increased by 7.5 degrees in less than a century, a spike largely attributed to urbanization which has seen the city's population climb from less than 15,000 to more than 350,000. The temperature has gone from a low of 59.7 degrees in 1920 to 67.2 in 1997, with yearly temperatures near the all-time high as recently as 2006.

No I am not going to discuss individual surface station data. It is well known that some of the stations are bad, including to the folks at NCDC and GIS. They go to great pains to filter their data for such issues, and as a result the data agrees well with the multitude of other temperature records. Climate science does not rest on the veracity of surface temperature stations, they are merely one of the many pieces of evidence that point to a warming climate.

Yeah, it is inconvenient to discuss the abysmal state of the data upon which we base the conclusion that the earth has warmed. If that data is bad and so noisy, then how can we use it to conclude that the earth is warming? See, this is a double edged sword. If you claim that the earth is warmer in 2008 than it was in 1900, the ONLY data you have to demonstrate that is the temperature records of those individual stations you refuse to discuss. You can't have it both ways. Either the stations are good enough to know that global warming is happening, or they aren't. It appears from your refusal to discuss their abysmal state that you know they are useless.

You ought to look at this on the Los Angeles station (I know, like Cardinal Bellarmine, who refused to look in the telescope that Gallileo offered to him, you don't want to look at the data either. But this is interesting and I am sure other, more open minded people will look at the data.

wattsupwiththat.com/2008/03/24/how-not-to-measure-temperature-part-54-los-angeles-the-city/


Year after year, Los angeles was having record after record temperature. They had their thermometer on the hot roof of a parking garage. In 1999 or so, they moved it across the street to a small grassy area. The temperature dropped more than a degree and now they no longer have record temperature after record temperature. There are pictures of the site and the temperature graph. While you won't look through the telescope, others will.

If you can't get that report there, you can get it from google cache
http://74.125.45.104/search?q=cache...LA+temperature+Watts&hl=en&ct=clnk&cd=1&gl=us


Edited to add. One thing that really bothers me about your claim that they know how bad the individual stations are (and I agree, i have had meteorologists tell me that) but then claim that we shouldn't look at the data is that is an attitude of cherry picking the good and ignoring the bad in one's position. If all you look at is the output of the mathematical machinations, you are not doing much more than being a belliever waiting for the pope to drop an encyclical upon your head. My gosh, man, the data IS the game. IF it is bad, then all the conclusions tumble down. And you have just acknowledged how bad the data is but refuse to discuss it. Are you a scientist or a believer in AGW?

 

[plindboe]

Just wanted to say I find the debate fascinating, with lots of interesting points from all. Some of it goes over my head, but I'll study the thread more in the future to make sense of it all.

Sorry for mentioning some criticism, Glenn, but I notice you tend to add unneeded aggression, presumptions and generalizations about people into the debate. It's clear you've had bad past experiences concerning these debates, but subjecting others to these grievances might not be the best strategy for good communication. The thread can easily spiral downwards if/when your opponents start responding in kind, and I'd hate to see an interesting and enlightening debate ruined. I learn from reading your points, and the replies to them, and look forward to your future posts. You don't have to respond to this post (and perhaps shouldn't, so the debate doesn't get diverted), I just hope you might take my point into consideration.

I'm sorry to hear about your illness. I hope you'll still be in the game for a long time to come, as skeptical voices are what in the end makes science progress.

Peter

 

[thaumaturgy]

69% of the US stations are sited in ways that would cause more than a 2 deg F bias. The entire global warming is 1.1 over the last 100 years. Noise and bias are greater than signal.

Could you remind me where that statistic comes from? It is obviously very important.

In the effort of full disclosure, I am dying of a cancer

VERY sad to hear that!

which could have been caught early, but wasn't because I lived in the UK during those years and lived under national health care. The government decided that the PSA test was too expensive so they didn't do it. If I had lived here in the US, it would have been caught early and maybe I wouldn't now be dying because of socialized medicine. If you haven't lived under it, you don't have a clue how bad it really is.

Obviously a debate for another time. I would stress the subtle differences between "Single Payer" (like California SB840) and full-on socialized medicine.

But again, a debate for another time.

(I do have a statistically robust reason for my backing a "single payer" system, not merely my "Lib'rul Gut Feeling", that is important to me; to have a statistically valid point to my reasoning, but again, a different debate for a different time and different forum. I also realize that if you and I were in reversed roles those statistics would be of no "value" to me. "Statistics is what happens to other people". I recognize that in myself. You have my deepest sympathies).

 

[thaumaturgy]

The problem with linear regressions is what is wrong with most investment decisions. People think linearly, not cyclically.

There is a "Lack of Fit" test that can be run to determine if any model lacks higher order polynomial terms.

A linear regression is grand if the phenomenon is linear.

Thankfully statisticians and modellers are more than aware of the limitations of a non-linear response!

if it is cyclical, it isn't so grand and goes up and down depending upon when one does the regression.

There are models that fit sine waves, and on shorter terms one can fit a 2nd, 3rd, or 4th order polynomial. These are all within the bounds of reason.

Look at the number of ups and downs over the past 30 years and you use a linear regression. tsk

Please, then fit the data to a sine/cosine function or some higher order polynomial bounded by the last 30 years. I would be ammenable to looking at that data.

I just ran the data with both a 2nd order Quadratic and 3rd order Cubic. The Lack of Fit tests for all (linear, quadratic and cubic) are all indicating that the spread is too large to rule out higher orders or the existence of a better fit).

Linear R^2 = 27%, p-value = 0.0001
Quadratic R^2 = 28%, p-value = 0.0001
Cubic R^2 = 32%, p-value = 0.0001

All have Lack of Fit analyses of p<0.0001, so none of these higher orders fit perfectly. I suspect the data is simply to noisy. The R^2 improves but imperceptibly.

I am as yet unsure how to transform the data to get a good fit to a sine wave.

HOWEVER, that being said, there is precious little reason to a priori throw out the linear fit considering that it has a statistically significant f-test against being "dead flat".

In point of fact here's the equations for both higher order polynomial fits:

Global = -25.53854 + 0.0128303*Year + 0.0003636*(Year-1993.34)^2

Global = -48.96657 + 0.0245834*Year + 0.0003667*(Year-1993.34)^2 - 0.0000879*(Year-1993.34)^3

If you take 1980 and 2000 values for both you'll see the "Global" increases.

Now I will not claim greater insight into this, I am not that familiar with this application, but this seems that there is still a general trend upwards, even at higher orders.

I will agree to a very very slight warming but it is not comparable to the quantity of CO2 rise in the atmosphere over that time frame.

That is an interesting point. I think the key, again, is that we know CO2 is a greenhouse gas, which we are pumping into the atmosphere at an alarming rate compared to the recent past. Since we are dealing with a known system guaranteed to increase temperatures why would we assume we are not merely looking at the limited buffering capacity of the planet and that we, in the words of Roger Revelle when discussing the ocean's buffering capacity to CO2 in the atmosphere: "Human beings are now carrying out a large scale geophysical experiment of a kind that could not have happened in the past nor be reproduced in the future."

And Revelle wasn't even a global warming maven...this was in the 1950's before anyone even thought of anthropogenic global climate change!

I don't deny that the regression shows a rise. What I am pointing out is that the starting and ending point are almost the same. this is a cyclical phenomenon, not a linear phenomenon.

You are still focusing on individual data sets and points. You have yet to mathematically provide me with a compelling reason to reject, out of hand, a linear least-squares fit. You must address the Analysis of Variance. Not just look at the first and last set and decree "cyclicity".

By all means, fit it to a wave function and let me know the R^2, f-test and Lack-of-Fit p-value.

I too have to run. Got a carbonate grind going which is begging for dispersant as we speak.

 

[chaim]

It seems to me that your argument relies on the claim that climate science is based on surface temperature data. If, as you claim, surface temperature data is unreliable, we can ignore that data. If the data is bad it doesn't present an argument for or against climate change. For the sake of this discussion, let us agree that surface temperature station data is bad, thus we will not use it in our arguments. Lets focus on the other temperature measurements, satellite tropospheric temperatures, sea surface temperature, mid-water temperatures, bore hole, temperatures, alpine glacier isotope ratios and the indirect proxies, glacial mass balance, dendrochronolgy, sea ice extent. All of these data sets indicate a warmng over the past 30 years (satellite), ~60 years (sea surface temperature), 500 years (bore hole) and 2k years (alpine galciers). How does your model explain these results?

Sigh, agreed, but, this is a cyclical phenomenon. you know, UP and DOWN. Depending on where you stop the roller coaster, depends on the average rate of change--which is linear. Let's test your concept of linear phenomenon below.

Below is the temperature trend for central Greenland over the past few years. Note, that contrary to press reports and global warming hysteriacs, Greenland has been cooling since 2003. Do you believe that the linear trend of -3.31 deg/decade trend will continue on until absolute zero is reached?

Of course not, you expect the temperature to go back up at some point in the future. So, why do you expect the global warming temperature to rise forever? I posted a solar flux measurement over the past few years. The sun is outputting much less energy and the earth is now cooling. We are a year and a half late for the start of the next solar cycle's upswing in sunspots. One of the most optimistic predictions says the upswing will start early next year. There were no sunspots yesterday or the day before or the day before. Indeed, at this time in most solar cycles we are at 30-40 sunspots on average. So far this year we are in excess of 205 spotless days--if you add 2007's spotless days we are in one of the longer periods of time in which the sun has very few sunspots.

And that means the sun outputs less energy. CO2 isn't the big boogey man, the sun is.





So, do you think that the global temperature will rise forever linearly?
Do you think Greenland's cooling will continue forever to absolute zero?


[quoteOf course there is cyclical noise on the temperature data, there is ENSO, solar cycles etc convolved with any background trend. However when you do a long term trend (longer than the solar cycle and ENSO) there is still a statistically significant upward trend. This trend cannot be explained via TSI as the long term trend for TSI has been downwards over the last 30 years. Secondly the rate of change of temperature rules out the current warming being caused by a millenial period cycle.

But, the rate of current temperature trend can be explained by urbanization. Do you know when Asia's temperature began to rise dramatically? After Deng Xiao Ping set China off on modernization and they poured more cement. We will get into this more over the next few weeks, but for now, I want you to know the impact of the urban heat island on temperatures. Below is from the Orange County Register





Yeah, it is inconvenient to discuss the abysmal state of the data upon which we base the conclusion that the earth has warmed. If that data is bad and so noisy, then how can we use it to conclude that the earth is warming? See, this is a double edged sword. If you claim that the earth is warmer in 2008 than it was in 1900, the ONLY data you have to demonstrate that is the temperature records of those individual stations you refuse to discuss. You can't have it both ways. Either the stations are good enough to know that global warming is happening, or they aren't. It appears from your refusal to discuss their abysmal state that you know they are useless.

You ought to look at this on the Los Angeles station (I know, like Cardinal Bellarmine, who refused to look in the telescope that Gallileo offered to him, you don't want to look at the data either. But this is interesting and I am sure other, more open minded people will look at the data.

wattsupwiththat.com/2008/03/24/how-not-to-measure-temperature-part-54-los-angeles-the-city/


Year after year, Los angeles was having record after record temperature. They had their thermometer on the hot roof of a parking garage. In 1999 or so, they moved it across the street to a small grassy area. The temperature dropped more than a degree and now they no longer have record temperature after record temperature. There are pictures of the site and the temperature graph. While you won't look through the telescope, others will.

If you can't get that report there, you can get it from google cache
http://74.125.45.104/search?q=cache...LA+temperature+Watts&hl=en&ct=clnk&cd=1&gl=us


Edited to add. One thing that really bothers me about your claim that they know how bad the individual stations are (and I agree, i have had meteorologists tell me that) but then claim that we shouldn't look at the data is that is an attitude of cherry picking the good and ignoring the bad in one's position. If all you look at is the output of the mathematical machinations, you are not doing much more than being a belliever waiting for the pope to drop an encyclical upon your head. My gosh, man, the data IS the game. IF it is bad, then all the conclusions tumble down. And you have just acknowledged how bad the data is but refuse to discuss it. Are you a scientist or a believer in AGW?[/quote]

 

[Split Rock]

Glenn:

I am following the debate here, but will let thaumaturgy and chaim carry the pro-side of the debate, since they know more about this stuff than I do (I'm a biologist). A couple of points, however,

You have agreed that carbon-based fuels are becoming more scarce and we will run out soon. You have also claimed there is no good alternative fuel source(s) for someone like yourself. Why are you then against reducing our dependence on carbon-fuels and conserving energy? This is what most professionals are asking the government to support (please do not bother quoting any individual scientist who has more dramatic requests).

Your range may not be in a good location for economical use of either solar or wind power, but other locations are. The government should help subsidize alternative energy production, in those areas in which it is feasible to do so. This may, or may not help you in your situation, but will help others reduce their dependence on carbon fuels.

In addition, we can also conserve energy, by being more efficient in our energy use. The government should also support and encourage the use of building/home insulation, compact fluorescent bulbs, high mpg vehicles, recycling of plastics, etc. Also, the government should fund more research into making alternative energy systems (like solar) more efficient and less costly for consumers such as yourself.

 

[thaumaturgy]

I think the tone of the debate must be moderated from emotional accusations of systemic bias backed up only with "anecdotal data" and "shocking pictures" of badly placed gauges.

Let's see what IPCC says about how they treat their land data. THIS REPORT is a gold mine for how the data is treated. It is from the IPCC itself, specifically Working Group I which is responsible for the scientific basis.

Long-term temperature data from individual climate stations almost always suffer from inhomogeneities, owing to non-climatic factors. These include sudden changes in station location, instruments, thermometer housing, observing time, or algorithms to calculate daily means; and gradual changes arising from instrumental drifts or from changes in the environment due to urban development or land use. Most abrupt changes tend to produce random effects (source)

Urbanisation usually produces warming, although examples exist of cooling in arid areas where irrigation effects dominate.(ibid)

In addition to errors from changing coverage and from random measurement and sampling errors, errors arise from biases (Section 3.B.2). Major efforts have been made to adjust for known systematic biases, but some adjustments nonetheless are quite uncertain. Nevertheless, recent studies have estimated all the known errors and biases to develop error bars (Brohan et al., 2006). (ibid)

Key among these might be:

The impact of random discontinuities on area-averaged values typically becomes smaller as the area or region becomes larger, and is negligible on hemispheric scales (Easterling et al., 1996). (ibid)

(emphasis added).

As Chaim has pointed out in an earlier post, there are still the issues around data that does not suffer from the shocking "bad placement" photos Glenn has presented so far. SST, satellite, etc.

I would very much like to know where the 69% figure comes from, I might have missed it earlier in a post.

 

[grmorton]

Just wanted to say I find the debate fascinating, with lots of interesting points from all. Some of it goes over my head, but I'll study the thread more in the future to make sense of it all.

Sorry for mentioning some criticism, Glenn, but I notice you tend to add unneeded aggression, presumptions and generalizations about people into the debate. It's clear you've had bad past experiences concerning these debates, but subjecting others to these grievances might not be the best strategy for good communication. The thread can easily spiral downwards if/when your opponents start responding in kind, and I'd hate to see an interesting and enlightening debate ruined. I learn from reading your points, and the replies to them, and look forward to your future posts. You don't have to respond to this post (and perhaps shouldn't, so the debate doesn't get diverted), I just hope you might take my point into consideration.

Fair enough. I am an agressive person and it has nothing to do with past debates on the topic. I am in a business where if you screw up the data, you cost someone $100 million or more. We don't have patience with data mis-handling or ignoring the data. Thus, my demand that people pay attention to the data and the consequences therein are due to a lifetime of working in a very unforgiving industry. I worked for one company that in 10 years laid of 99% of the people who were there the day I started. I survived it all by paying attention to the data and not sugar coating bad news.

That being said, I apologize to anyone whom I might have offended, but, I will constantly demand answers to the data problems I post. Ignoring data is the worst crime a scientist (or an investor) can do. I expect people to hold me to the very same standard, so if I don't answer something people want to hear me answer, point it out, I answer ALL questions, not just those that are easy for my point of view. I expect scientists will all do the same.

I'm sorry to hear about your illness. I hope you'll still be in the game for a long time to come, as skeptical voices are what in the end makes science progress.

Peter

Thank you. The average survival for this kind of cancer in the UK, under the National Health Service from diagnosis to death is 5 years. As it looks, I will get about 10. I am at 5 right now. I had surgery, they thought it was cured, but it came back. I had radiation, they thought it was cured and it came back. There is now no cure because it has metastasized. Thank God for the US medical system, it will give me 5 extra years

But, I want no one feeling sorry for me. I have lived an incredible life, published 100+ articles, traveled the world, lived on 3 continents, learned Mandarin, been in 26 countries, and have made an impact on the world with my web pages. But the most important accomplishment I have is a great relationship with my three sons. My father and mother couldn't say that.

I expect debate opponents to be as hard as they can with my position. Afterwards, after the debate, we can all go laugh over beer and pretzels and tell war stories.

 

[grmorton]

Could you remind me where that statistic comes from? It is obviously very important.

Yes, it is very important. It is at http://www.surfacestations.org. about halfway down the page.

look through the pictures of the stations. It was seeing this information that convinced me as a scientist that the temperature data was crap. It is very easy to find bad stations there.

VERY sad to hear that!




Obviously a debate for another time. I would stress the subtle differences between "Single Payer" (like California SB840) and full-on socialized medicine.

Thank you but as I said, I have had a wonderful life and we all are terminal. I simply have some idea of when, you don't. I don't know if you know who Wil Provine is. He is a professor who eats Christians for breakfast. I am a christian, but he admires my clarity of thought. I admire his honesty with the data. We are friends. When he came down with brain cancer, I told him that I wasn't going to treat him any differently. He said he would be mad at me if I did. I am as hard on him and he on me, as we ever have been. If I have a screwy argument, I want it pointed out so I can drop it. But, I expect the same of others. Unfortunately, most others don't play by that rule. I have been trained to by the very cruel nature of my job--succeed and find oil, or get fired.

(I do have a statistically robust reason for my backing a "single payer" system, not merely my "Lib'rul Gut Feeling", that is important to me; to have a statistically valid point to my reasoning, but again, a different debate for a different time and different forum. I also realize that if you and I were in reversed roles those statistics would be of no "value" to me. "Statistics is what happens to other people". I recognize that in myself. You have my deepest sympathies).

As I said, thanks for the thoughts. I would advise not to confuse theory with data. That goes in all areas, not just the area of health care. I believe we are running out of oil Theory would say that oil prices would rise. But, the data said that people were not using it as much because the demand was dropping. I paid attention to the data, sold all my oil in early July and then watched everything fall. The only mistake I made was to buy back in too early and I watched it fall with my money after that. . One shouldn't believe one's own story too much.

 

[AV1611VET]

I don't know if you know who Wil Provine is. He is a professor who eats Christians for breakfast.

Hmmm --- sounds familiar --- put him on and let him try this Christian on for size.

 

[thaumaturgy]

Yes, it is very important. It is at http://www.surfacestations.org. about halfway down the page.

Very interesting link. I will definitely have to spend more time on that.

Ah, so only about 43.5% of the entire network has been assessed of land-based temperature stations in the U.S., right? And of that figure (which amounts to 534 stations altogether) there are >50% that have a positive bias of >5degC on the microscale (ie on a gauge by gauge scale).

299 stations total have a CRN rating of 5 (bad) out of what, 1221 stations in the U.S.?

That is troubling, indeed. But not fatal, yet. Surely if the only thing we were going on was land-based systems we'd be much more concerned. AND if, added onto this, the IPCC and related groups were not taking large scale grid averages, indeed the noise would be nearly overwhelming.

Again, I say "nearly overwhelming" in regards to the noise. I will definitely need to see how their "bias estimations" run because it looks like their CRN4 and 5 ratings are only a positive bias. Clearly seems a bit "one-tailed" in the error assessment, since negative bias is presumably also possible (as pointed out early from IPCC report).

As I said, thanks for the thoughts. I would advise not to confuse theory with data. That goes in all areas, not just the area of health care.

I am an empirical scientist. I normally like theory as a "pasttime" but realize it isn't real for me until I see the data. Statistics gives me the proper "magical glasses" with which to make sense of the data cloud.

 

[grmorton]

There is a "Lack of Fit" test that can be run to determine if any model lacks higher order polynomial terms.

With cyclical phenomenon a Fourier analysis is far more appropriate.

Thankfully statisticians and modellers are more than aware of the limitations of a non-linear response!

I was just pointing out that you were applying a linear analysis to an obviously cyclical data set. Cycles come back to close to their starting points. Noisy linear systems don't. They trend one way or the other. Thus, while statisticians are aware of it, and you might be aware of it, you didn't apply it in my opinion.

There are models that fit sine waves, and on shorter terms one can fit a 2nd, 3rd, or 4th order polynomial. These are all within the bounds of reason.

As I said, a Fourier spectral analysis is far more appropriate. One can't claim that this is rising linearly when it is clearly a cyclical signal.

Please, then fit the data to a sine/cosine function or some higher order polynomial bounded by the last 30 years. I would be ammenable to looking at that data.

The sum would not be informative. it would be in the form of {sum(i) i=1,100} A[sub]i[/sub] Sin (w[sub]i[/sub] x t) + Phi[sub]i[/sub].

If I showed you the Fourier spectrum, it wouldn't mean much to you. There would be a strong peak with a periodicity of between 4-6 years.

You are claiming that this shows a rise in temperature. In fact, the fact that the present tropospheric temperature is about the same as what it was in 1979 means that the linear increase in CO2 shown in the Keeling curve, isn't having much effect on the starting and ending points.

I just ran the data with both a 2nd order Quadratic and 3rd order Cubic. The Lack of Fit tests for all (linear, quadratic and cubic) are all indicating that the spread is too large to rule out higher orders or the existence of a better fit).

Linear R^2 = 27%, p-value = 0.0001
Quadratic R^2 = 28%, p-value = 0.0001
Cubic R^2 = 32%, p-value = 0.0001

All have Lack of Fit analyses of p<0.0001, so none of these higher orders fit perfectly. I suspect the data is simply to noisy. The R^2 improves but imperceptibly.

I am as yet unsure how to transform the data to get a good fit to a sine wave.

None of this is applicable to cyclical phenomenon. I have spent my life dealing with sound waves. I interpret sound reflections off of the subsurface. We do all sorts of things to the seismic traces we record. But doing a quadratic or cubic analyses are not among them. Hilbert transforms, Quadrature traces, Fourier analysis etc are the tools of a signal analyist. Remember just because you can use a hammer on that tree, it doesn't mean that the hammer will chop it down as well as a saw would.

HOWEVER, that being said, there is precious little reason to a priori throw out the linear fit considering that it has a statistically significant f-test against being "dead flat".

I am not the one who has claimed that it is dead flat. I said it was slightly rising given the starting and ending point. But, with cyclical signals, the average change is constantly changing, but not going up linearly.

Of the fact that the slight temperature rise is not equal to the CO2 rise (0r even its logarithmic increase) you wrote:

That is an interesting point. I think the key, again, is that we know CO2 is a greenhouse gas, which we are pumping into the atmosphere at an alarming rate compared to the recent past. Since we are dealing with a known system guaranteed to increase temperatures why would we assume we are not merely looking at the limited buffering capacity of the planet and that we, in the words of Roger Revelle when discussing the ocean's buffering capacity to CO2 in the atmosphere: "Human beings are now carrying out a large scale geophysical experiment of a kind that could not have happened in the past nor be reproduced in the future."

But, the problem is that we don't know if a doubling of CO2 will raise the earth's temperature by 1.7 degrees or 4.2 degrees. Yes, CO2 is a greenhouse gas. Its effect on temperature is unkown. That is according to the IPCC reports.

I absolutely laugh at the claim that this is a geophysical experiment that couldn't be carried out in the past. It HAS been carried out. The Eocene period had 1000 parts per million CO2 in the atmosphere. What part of this do you not understand (sorry for the agreesion here)? Today the earth has 380 ppm, 1/3 of what the earth's atmosphere contained just 55 million years ago. Why is a rise from 280 to 380 considered an unprecedented geophysical experiment in light of that? Go look above, I posted a picture of the historical CO2 levels for the past 600 million years.

And Revelle wasn't even a global warming maven...this was in the 1950's before anyone even thought of anthropogenic global climate change!

Regardless of what he is, he doesn't know much about earth history.

Here are some previous atmospheric CO2 levels from paleosol studies

Early in late Miocene.&#65533;The first evidence of C4 biomass being a significant part of local ecosystems in the Old World is about 7 to 8 my. Carbonates from preserved paleosols in Africa, Asia, and Europe older than 8 my have del 13 C values from about &#65533;10 to &#65533;12 permil. Figure 7 and table 2 show that there are compatible with a maximum P(CO2) level of about 700 ppmV.&#65533; Thure E. Cerling, &#65533;Carbon Dioxide in the Atmosphere: Evidence from Cenozoic and Mesozoic Paleosols,&#65533; American Journal of Science, 291(1991):377-400, p. 394
P(CO2) ppm
Miocene Pakistan <700
Miocene E. Africa <400
Eocene Wyoming <600
L. Cretaceous Texas 2500-3300
Spain 1600-2600
U. Triassic/
l. Jurassic New Haven 2000-3000
New Haven 2500-4200
Fundy Rift 3000-6000

Your source is utterly wrong about this being an unprecedented experiment.

You are still focusing on individual data sets and points. You have yet to mathematically provide me with a compelling reason to reject, out of hand, a linear least-squares fit. You must address the Analysis of Variance. Not just look at the first and last set and decree "cyclicity".

And you haven't proven that the cyclicity seen is just random noise. Standoff.

You have admitted that the individual station data is bad. If it is bad, how can you say that you know that the temperature has risen by 1.1 F over the past century? Please explain that?

 

[grmorton]

It seems to me that your argument relies on the claim that climate science is based on surface temperature data. If, as you claim, surface temperature data is unreliable, we can ignore that data. If the data is bad it doesn't present an argument for or against climate change. For the sake of this discussion, let us agree that surface temperature station data is bad, thus we will not use it in our arguments. Lets focus on the other temperature measurements, satellite tropospheric temperatures, sea surface temperature, mid-water temperatures, bore hole, temperatures, alpine glacier isotope ratios and the indirect proxies, glacial mass balance, dendrochronolgy, sea ice extent. All of these data sets indicate a warmng over the past 30 years (satellite), ~60 years (sea surface temperature), 500 years (bore hole) and 2k years (alpine galciers). How does your model explain these results?

Well, the satellite data I showed does NOT show warming, or not that much. If it did, the ending temperature would be much higher than the starting temperature. That is one of those points. I have posted sea surface temperature data showing that the seas are cooling over the past 5 years. Now, you will say it is short term, I can't disprove that, but it still isn't INCREASING, as your CO2 theory would require. The average temperature of the earth's oceans is currently cooling. So, that is the second point.

I have posted an Antarctican Sea Ice extent showing that the antarctican sea ice extent has actually grown over the past 30 years.

Below is a picture of Arctic Ice coverage between 2007 and 2008. Arctic Ice is now growing. And for your information, Arctic ice and Antarctican ice are out of phase. This is well known and ignored by Global warming people. I posted yesterday that central Greenland has cooled at -3.31 deg per decade over the past 5 years. Maybe you missed that chart

“Age synchronization
between Greenland and Antarctic ice cores
through atmospheric CH4 variations reveals that
Antarctic and Greenlandic temperature are linked,
but not in phase (4, 5) (Fig. 1, A, B, and D).
Antarctic warming started before warming in
Greenland for most of the large millennial
events in the records, and Antarctic temperatures
began to decline when Greenland rapidly
warmed.”

The fact that the arctic is melting while the antarctic is cooling is something seen over and over.

By bore hole temperatures what are you referring to? The earth heats up as one goes deeper, but it has nothing to do with CO2.

 

[grmorton]

Hmmm --- sounds familiar --- put him on and let him try this Christian on for size.

Don't be too eager. He is tougher. Maybe sometime when I am through with this GW debate, you and I can debate science and Christianity. I left YEC because they told me absolutely nothing true about geology.

 

[thaumaturgy]

Fair enough. I am an agressive person and it has nothing to do with past debates on the topic.

Personally I'm more than willing to get worked up. I've had debates where I let my lesser nature come to the fore. You aren't going to offend me in any way. I would be the world's largest hypocrite if I were to complain about "snarkiness".

I am in a business where if you screw up the data, you cost someone $100 million or more. We don't have patience with data mis-handling or ignoring the data. Thus, my demand that people pay attention to the data and the consequences therein are due to a lifetime of working in a very unforgiving industry.

Also be mindful of the statistics not just the "raw data". Noise and variance components both have an impact. Statistics allows us to cut through the natural variation in data.

I too work in industry and when something goes horridly awry it costs money and jobs. As I said earlier, I was called in on a project in which a huge tanker full of our stuff had solidified in someone's storage tank. Lots of money lost and we were threatened with losing their business and they were a big customer. We in R&D worked hard to figure out what went wrong and the best we could tell was that something had drifted either "out of spec" or the spec ranges were set too high.

Gauges get ignored or, if not ignored, then badly set. The robustness of the overall trends is something that can be determined. In the present case of global temperature we are demonstrably not limited to solely unit-by-unit land-based temperature gauges. The fact that two unrelated guages show similar trends is usually an indication that neither gauge is horridly off.

In addition, significant amounts of effort are, as shown earlier in the IPCC report, taken to assess bias, correct for bias and, on a broader scale, compensate for individual guage biases.

It is a great thing for the one group to go around and rate the temperature systems on an individual basis. Indeed it will surely help generate better data in the future. But that is like look at one set of gauges while ignoring how others "overlap it".

That being said, I apologize to anyone whom I might have offended, but, I will constantly demand answers to the data problems I post. Ignoring data is the worst crime a scientist (or an investor) can do.

Actually ignoring statistics is probably a worse crime. Since data contains noise, statistics helps quantify noise in an effort to get at the best answer.

I've seen perfectly smart scientists make decisions on graphs without statistical analyses behind the data points. I count that as worse than useless because there is no idea where on the map you are with just a single or small handful of data points.

There's two problems to face: Type I errors (erroneously rejecting a true null hypothesis: "false positive") and Type II errors (erroneously accepting a false null). We can never ever remove both. In order to eliminate one you have to accept you increase the chance for the other.

In the case of global warming the null is reasonably stated as "There is no (anthropogenic) global warming trend in the data". I am merely testing the data to see if I can reasonably avoid making an error in rejecting that null (which is, effectively, the "Climate Skeptic Stance".)

Further, one can make the assumption that in the general pay-offs of the responses it is probably better to avoid Type II errors than Type I.

Type I errors mean you were wrong in assuming there was Anthropogenic Global Warming so you end up forcing everyone to live more within their limits and you wean yourself from a known "limited" resource (carbon fuels) and you incur some costs.

A Type II error in this case, failing to reject the null and embrace the alternate, that indeed there is anthropogenic global warming which we can and should deal with, means runaway greenhouse effect the certain destruction of human civilization or at least the destruction of modern human civilization.

It is, after all, kind of a "Pascal's Wager" on global climate. We are ultimately going to run out fossil fuels some day, must we really take our civilization down with it in such a way that it cannot recover, ever?

That being said, I still couch the discussions of the data on Type I analyses. When I post the f-test data and the attendent p-values for the temperature trend graphs, I am showing at least some estimate of how sure we are that we are not making a Type I error in rejecting the null of "no trend", as quantified by the p-value (relative to some arbitary alpha). I am testing the data against the status quo of the Climate Skeptic. Am I being reasonable in assuming my stance of belief in anthropogenic global climate change is correct and the Climate Skeptic stance of no anthropogenic change is to be rejected? Will I make an error by rejecting their stand?

The p-values have become very important for me when assessing the data and possible correlations. It keeps me from merely relying on my "view" of the data plots.

(Again, I am still relatively new to the world of statistics, so I hope I have not misstated a point here, hopefully a statistically savvy poster will correct me if I'm mistaken).

 

[AV1611VET]

Maybe sometime when I am through with this GW debate, you and I can debate science and Christianity. I left YEC because they told me absolutely nothing true about geology.

Thanks anyway, Dr Morton, but to be honest, I'll respectfully pass. My style is a little ... well ... unorthodox. Thanks, anyway ---

Just one question though --- and you don't have to answer --- are you Dr Glen Morton?

 

[grmorton]

Very interesting link. I will definitely have to spend more time on that.

Ah, so only about 43.5% of the entire network has been assessed of land-based temperature stations in the U.S., right? And of that figure (which amounts to 534 stations altogether) there are >50% that have a positive bias of >5degC on the microscale (ie on a gauge by gauge scale).

299 stations total have a CRN rating of 5 (bad) out of what, 1221 stations in the U.S.?

Yeah, that site is an eye-opener. 1200 is about right. I don't know the exact number. The thing is that a political poll will only sample a few hundred out of millions. This site has sampled 43% of the stations and 13% are class 5, 53% are class 4. The bias errors on these is such that about half of the supposed global warming is due to this. Then when you add the fact that the Peterson article you cited specifically says that they make the 'bad' station trend match the 'good'stations,, you can see that there is zero chance for one to find a smaller trend than those stations judged, good. This is because the bad stations are tilted to match the trend of the 'good' stations. If we are trying to know the trend in global temperature, this is precisely the wrong technique.

That is troubling, indeed. But not fatal, yet. Surely if the only thing we were going on was land-based systems we'd be much more concerned. AND if, added onto this, the IPCC and related groups were not taking large scale grid averages, indeed the noise would be nearly overwhelming.

It is indeed troubling, especially in light of the fact that THE OCEANS ARE COOLING and measurments out there can't be due to air conditioners or cement. If you look at the land vs. oceans over the past few years, it is the rise in the land temperatures which cause the average global climate to rise. The oceans have not participated in this rise to the extent that the land has. Does CO2 only affect the land stations? Cement and air conditioning do

I appreciate the fact that you are willing to actually look at the data. Too few are. Most want to avoid contradictory data. My hat is off to you.