how much warming from adding carbon dioxide to the atmosphere is what we

[itfitzme]

An additional, solid regression analysis, is based on this data

Which yields

"I used Microsoft Excel to run the regression. The data points covered the period from 1880 to 2007 inclusive, so there were N = 128 data points. The regression line I found was:

Anom = -1876.715416 * + 325.8718284 ln CO2

The numbers in parentheses are "t-statistics," and they measure how significant the numbers above them are. The coefficient of the CO2 term is significant at p < 2.4483 x 10-41. That means the chances against the relationship being coincidental are less than 1 in about 4 x 1040.

The correlation coefficient is about 0.874, which means 76.4% of the variance is accounted for. Every other factor that affected temperature during this time span, then, accounted for 23.6%."

Now here we have a nice ln fit of

"Anom = -1876.715416 * + 325.8718284 ln CO2" where CO2 is ranging from 290.7 to 383.6. *lnCO2 ranges from 5.6723 to 5.9495.

Temp is in hundreds of a degree and CO2 in ppm. "ln CO2 is the natural logarithm of the CO2 level. Radiation physics says the radiative forcing from accumulated carbon dioxide should be related to the log of the level rather than the level itself, so this is what we actually use in the computation."

The thing to do then, is to plot that regression result.

Here is the thing. *The ln function looks like this;

http://upload.wikimedia.org/wikipedia/commons/e/ea/Log.svg

Beyond x=2, the ln(x) is, for all practical purposes, linear. *And, it isn't asymptotic. *It does continue to increase without bound.

Over the range, as measured in the atmosphere, there is no significant difference between the linear and log response. Over that range,*from 290.7 to 383.6, the ln response is simply linear.

This is not uncommon. *In radio and television transmission, the power goes down at 1/r^2 in distance from the source. In the near field, near the transmitting antenna, the power is clearly not linear. *The far field is different because, at a distance from the source, 1/r^2 is linear, for all practical purposes. *The difference between 1/4 and 1/9 is noticable. *The difference between 1/10^2 and 1/11^2, not so much. *The difference between 1/100^2 and 1/101^2 is meaningless.

And over the range of CO2, from ln*290.7 to ln 383.6 is simply linear.

So that reconciles the linear vs log issue.

link -> Temp v CO2 Correlation

Yeabut, that doesn't give the answer that Rush promised.*

Yeabut, that implies a problem that requires action and it would be cheaper to not have the problem.*

Yeabut, that would make me wrong!

Yeabut, that would make Al Gore right!*

Yeabut, that would make you right!

Yeabut, that would imply that scientists know more science than laymen do.*

Yeabut, that would imply that liberals are smarter than conservatives. Democrats than Republicans. Left of center vs right of center.*

Yeabut, yeabut, yeabut.

IamC's point of the log function was the only one that came off as having some credibility. *So resolving that possibility against the obvious real measures was worth it. *It would have been way easier if I had Excel.

Unfortunately, I think the math and pretty graphs will go over most heads. *The shit's not easy. *It's not Dr. Seuss, a Harlequin romance, or your Sunday funnies. *It takes work to get use to, a couple of college semesters, at least. *If there was more demand at the CC level for it, it would be more common place, show up more often in the news, and we'd all be use to it.

A problem is that there is a huge gap between the basic highschool stuff and the Phd papers. *There is all this college level intro to whatever that just isn't on the web. Reading Wikipedia just doesn't do it.

 

[gslack]

LOL you two don't like the debate you get so you have a closed circle debate with each other? LOL you two are the worst AGW trolls I have ever seen.

 

[westwall]

On positive feedback possibilities.

Global warming may be amplified by feedback loops

Could, might, maybe....etc.

Don't you think the state of science is such that it could be determined whethere a feedback exists and whether it was positive or negative? Why promote could, might, and mabye rather than facts?

The language of charlatans the world over.

 

[PMZ]

An additional, solid regression analysis, is based on this data

Which yields

"I used Microsoft Excel to run the regression. The data points covered the period from 1880 to 2007 inclusive, so there were N = 128 data points. The regression line I found was:

Anom = -1876.715416 * + 325.8718284 ln CO2

The numbers in parentheses are "t-statistics," and they measure how significant the numbers above them are. The coefficient of the CO2 term is significant at p < 2.4483 x 10-41. That means the chances against the relationship being coincidental are less than 1 in about 4 x 1040.

The correlation coefficient is about 0.874, which means 76.4% of the variance is accounted for. Every other factor that affected temperature during this time span, then, accounted for 23.6%."

Now here we have a nice ln fit of

"Anom = -1876.715416 * + 325.8718284 ln CO2" where CO2 is ranging from 290.7 to 383.6. *lnCO2 ranges from 5.6723 to 5.9495.

Temp is in hundreds of a degree and CO2 in ppm. "ln CO2 is the natural logarithm of the CO2 level. Radiation physics says the radiative forcing from accumulated carbon dioxide should be related to the log of the level rather than the level itself, so this is what we actually use in the computation."

The thing to do then, is to plot that regression result.

Here is the thing. *The ln function looks like this;

http://upload.wikimedia.org/wikipedia/commons/e/ea/Log.svg

Beyond x=2, the ln(x) is, for all practical purposes, linear. *And, it isn't asymptotic. *It does continue to increase without bound.

Over the range, as measured in the atmosphere, there is no significant difference between the linear and log response. Over that range,*from 290.7 to 383.6, the ln response is simply linear.

This is not uncommon. *In radio and television transmission, the power goes down at 1/r^2 in distance from the source. In the near field, near the transmitting antenna, the power is clearly not linear. *The far field is different because, at a distance from the source, 1/r^2 is linear, for all practical purposes. *The difference between 1/4 and 1/9 is noticable. *The difference between 1/10^2 and 1/11^2, not so much. *The difference between 1/100^2 and 1/101^2 is meaningless.

And over the range of CO2, from ln*290.7 to ln 383.6 is simply linear.

So that reconciles the linear vs log issue.

link -> Temp v CO2 Correlation

Yeabut, that doesn't give the answer that Rush promised.*

Yeabut, that implies a problem that requires action and it would be cheaper to not have the problem.*

Yeabut, that would make me wrong!

Yeabut, that would make Al Gore right!*

Yeabut, that would make you right!

Yeabut, that would imply that scientists know more science than laymen do.*

Yeabut, that would imply that liberals are smarter than conservatives. Democrats than Republicans. Left of center vs right of center.*

Yeabut, yeabut, yeabut.

IamC's point of the log function was the only one that came off as having some credibility. *So resolving that possibility against the obvious real measures was worth it. *It would have been way easier if I had Excel.

Unfortunately, I think the math and pretty graphs will go over most heads. *The shit's not easy. *It's not Dr. Seuss, a Harlequin romance, or your Sunday funnies. *It takes work to get use to, a couple of college semesters, at least. *If there was more demand at the CC level for it, it would be more common place, show up more often in the news, and we'd all be use to it.

A problem is that there is a huge gap between the basic highschool stuff and the Phd papers. *There is all this college level intro to whatever that just isn't on the web. Reading Wikipedia just doesn't do it.

They want the answer that they want. You see the same behavior in little kids everywhere. It's called control freakishness.

Science is a tough love parent. If there was only a way to let it slap only them upside the head we'd be all set. But the consequences are random. So, the best that we can do is to ignore the noise and just pay attention to the signal.

 

[itfitzme]

Everyone is freaking out, even the Florida Keys.

Not exactly Chicken Little's "The sky is falling" *more like Chicken of The Sea, "The ocean is rising"

"A tidal gauge operating since before the Civil War has documented a sea level rise of 9 inches in the last century, and officials expect that to double over the next 50 years. So when building a new Stock Island fire station, county authorities went ahead added a foot and a half over federal flood planning directives that the ground floor be built up 9 feet. "

"It's really easy to see during our spring high tides that the sea level is coming up - for whatever reason - and we have to accommodate for that," said Johnnie Yongue, the on-site technician at the fire station for Monroe County's project management department. "

""We clearly have the most to lose. If sea-level rise is not curtailed by immediate reductions in greenhouse gases, the Florida Keys may eventually become unlivable," according to a March draft of the county's plans. "Planning decisions should take into consideration medium to extreme sea level rise predictions." "

50 years, a half century. No one is really freaking out. More like watching with morbid curiosity.



Climate change? Florida Keys prepare for sea level rise over the next 50 years

 

[itfitzme]

Now they are freaking out in Maine too!

"The surge in lobster numbers in the Gulf of Maine has led to oversupply, which last year caused the per-pound price at the pier to dip as low as $2.50 in some areas of the coast. Partly in response, the state launched a new marketing collaborative to expand promotion of Maine lobster to open untapped global markets."

Still, they are freaking out.

"The effects of climate change, including a continuing rise in water temperature and increased acidification in the Gulf of Maine, as well as disease and life cycle changes in lobsters and other shellfish, have raised alarm about the potential damage to the state’s most lucrative fishery, said environmental advocates from the Natural Resources Council of Maine and marine scientist Rick Wahle, a University of Maine zoologist in the School of Marine Sciences.

They joined with representatives of the Maine Lobster Council, Ready Seafood Co. and the Maine Restaurant Association to launch a public awareness campaign about the economic value of the state's lobster fishery and the challenges it faces.

“There is a problem. We are beginning to see the effects of climate change in the Gulf of Maine,” said Emmie Theberge, clean-energy outreach coordinator for the NRCM. “And the oceans are more sensitive to climate change.”

Give em an inch, and they are afraid of losing a tenth. Will they never be happy?! Warmer waters means pre-cooked. And who wouldn't
love softer shells? So much easier to eat.


Maine lobster coalition calls for action to avert climate threats | The Portland Press Herald / Maine Sunday Telegram

 

[IanC]

An additional, solid regression analysis, is based on this data

Which yields

"I used Microsoft Excel to run the regression. The data points covered the period from 1880 to 2007 inclusive, so there were N = 128 data points. The regression line I found was:

Anom = -1876.715416 * + 325.8718284 ln CO2

The numbers in parentheses are "t-statistics," and they measure how significant the numbers above them are. The coefficient of the CO2 term is significant at p < 2.4483 x 10-41. That means the chances against the relationship being coincidental are less than 1 in about 4 x 1040.

The correlation coefficient is about 0.874, which means 76.4% of the variance is accounted for. Every other factor that affected temperature during this time span, then, accounted for 23.6%."

Now here we have a nice ln fit of

"Anom = -1876.715416 * + 325.8718284 ln CO2" where CO2 is ranging from 290.7 to 383.6. *lnCO2 ranges from 5.6723 to 5.9495.

Temp is in hundreds of a degree and CO2 in ppm. "ln CO2 is the natural logarithm of the CO2 level. Radiation physics says the radiative forcing from accumulated carbon dioxide should be related to the log of the level rather than the level itself, so this is what we actually use in the computation."

The thing to do then, is to plot that regression result.

Here is the thing. *The ln function looks like this;

http://upload.wikimedia.org/wikipedia/commons/e/ea/Log.svg

Beyond x=2, the ln(x) is, for all practical purposes, linear. *And, it isn't asymptotic. *It does continue to increase without bound.

Over the range, as measured in the atmosphere, there is no significant difference between the linear and log response. Over that range,*from 290.7 to 383.6, the ln response is simply linear.

This is not uncommon. *In radio and television transmission, the power goes down at 1/r^2 in distance from the source. In the near field, near the transmitting antenna, the power is clearly not linear. *The far field is different because, at a distance from the source, 1/r^2 is linear, for all practical purposes. *The difference between 1/4 and 1/9 is noticable. *The difference between 1/10^2 and 1/11^2, not so much. *The difference between 1/100^2 and 1/101^2 is meaningless.

And over the range of CO2, from ln*290.7 to ln 383.6 is simply linear.

So that reconciles the linear vs log issue.

link -> Temp v CO2 Correlation

Yeabut, that doesn't give the answer that Rush promised.*

Yeabut, that implies a problem that requires action and it would be cheaper to not have the problem.*

Yeabut, that would make me wrong!

Yeabut, that would make Al Gore right!*

Yeabut, that would make you right!

Yeabut, that would imply that scientists know more science than laymen do.*

Yeabut, that would imply that liberals are smarter than conservatives. Democrats than Republicans. Left of center vs right of center.*

Yeabut, yeabut, yeabut.

IamC's point of the log function was the only one that came off as having some credibility. *So resolving that possibility against the obvious real measures was worth it. *It would have been way easier if I had Excel.

Unfortunately, I think the math and pretty graphs will go over most heads. *The shit's not easy. *It's not Dr. Seuss, a Harlequin romance, or your Sunday funnies. *It takes work to get use to, a couple of college semesters, at least. *If there was more demand at the CC level for it, it would be more common place, show up more often in the news, and we'd all be use to it.

A problem is that there is a huge gap between the basic highschool stuff and the Phd papers. *There is all this college level intro to whatever that just isn't on the web. Reading Wikipedia just doesn't do it.

I didnt know which of your replies to respond to but this one will do.

radio/TV antennae couldnt be more off topic. that has to do with a reactive EM field transitioning into a radiative EM field, and is dependent on the wavelength of emission.

CO2 is logarithmic, at least in its atmospheric radiative properties. so in this case it is there is an asymptote, although I dont see any mechanism where you could swap out all the other gasses for CO2.

those are quibbles. what I really wanted to comment on is your understanding of correlations and p values.

correlation does imply causation, especially when there are known mechanisms involved. unfortunately there are at least several mechanisms known. while CO2 should theoretically cause heating at the surface, it is also known that warmer oceans release CO2. what is the standard amount of CO2 that should be in the atmosphere for this temperature? it is very difficult to say just from proxies, it is difficult to measure CO2 even with modern technology, so we have decided to use just one measurement in Hawaii.

what we are really interested in is how much of the extra CO2 is the result of mankind burning fossil fuels, and what impact that has had on surface temperatures. again, very difficult to know. temperature and proxy measured TSI have an r^2 of ~0.7 over the last few thousand years, supposedly meaning that 1/2 the variance is solar related. the 20th century was higher both in solar activity and temperature but do we know what the 'break-even' number is for TSI? I personally think that solar input is more meaningful per watt than atmospheric back radiation because there is entropy to be considered, as well as wavelength variation. but the climate models have it making a ~1% influence on the climate. if solar appeared to account for 1/2 the variance before, doesnt it seem striking that it has almost no influence now?

I applaud you for trying to dig into the math of these complexities, everyone should at least try to understand some science. unfortunately you cannot pull out one simple relationship and prove it runs the whole system. this thread was started to tell konradv the same message.


edit- correlation does imply causation but it doesnt necessarily tell the direction of cause, and often correlation is simply seen between two symptoms of some other causative agent(s).

 

[itfitzme]

"radio/TV antennae couldnt be more off topic. that has to do with a reactive EM field transitioning into a radiative EM field, and is dependent on the wavelength of emission."

Then you completely get lost in the details of your own thoughts and miss the simple mathematical point.

**At large values of x, 1/x^2 and ln x both have curvatures that are tiny and the functions are nearly linear. *There is nothing wavelength dependent in the maximum intensity value of the far field relative to it's near field component. Total transmitted power is spread over a larger area as the emission moves further from the source, regardless of the wavelength. *For a spherical radiation, the intensity falls as 1/r^2. *Just so you don't go off all half cocked, I will add that a line source drops as 1/r, rather than 1/r^2, which does nothing in terms of the point, as 1/r becomes more linear for large values of r.

We can get all detailed about antenna coupling, antenna shape, etc, but that is off topic from the simple point that the function for power becomes effectively linear at large distances.

And like the 1/r and 1/r^2 functions, the ln(CO2) is nearly linear for large values of CO2. *That may not fully explain*

But it knocks off a large piece of it because*

a) that is the reality, in atmosphere, of temp v CO2 and it is a linear relationship. *Over the range of measured CO2, the curvature is flat, and any difference between a linear fit and a ln fit is buried in the residuals of the data. *

and b) any more complex function of anom=a*+ b*ln(CO2[factors]) + c*f[other factors], where CO2[factors] is a function where some secondary factors drive CO2 and f[other factors] is some other environmental influenced function, still has to match the real, in atmosphere, measurement of temp v CO2 as shown in the scatterplot.

Perhaps I should have used the term "inverse square law" instead of near-field and far-field.*

Inverse-square law - Wikipedia, the free encyclopedia

Then it would have been less confusing as you'd have looked there instead of

Near and far field - Wikipedia, the free encyclopedia

Please stop overestimating your own intelligence, it makes conversing with you difficult. I'm really not interested in writing a book every time I post. *You going to have to make some effort to get the point. *

 

[SSDD]

LOL you two don't like the debate you get so you have a closed circle debate with each other? LOL you two are the worst AGW trolls I have ever seen.

There is no they....there is one guy talking to himself. Mental masturbation at its best.

 

[SSDD]

Everyone is freaking out, even the Florida Keys.

Not exactly Chicken Little's "The sky is falling" *more like Chicken of The Sea, "The ocean is rising"

"A tidal gauge operating since before the Civil War has documented a sea level rise of 9 inches in the last century, and officials expect that to double over the next 50 years. So when building a new Stock Island fire station, county authorities went ahead added a foot and a half over federal flood planning directives that the ground floor be built up 9 feet. "

"It's really easy to see during our spring high tides that the sea level is coming up - for whatever reason - and we have to accommodate for that," said Johnnie Yongue, the on-site technician at the fire station for Monroe County's project management department. "

""We clearly have the most to lose. If sea-level rise is not curtailed by immediate reductions in greenhouse gases, the Florida Keys may eventually become unlivable," according to a March draft of the county's plans. "Planning decisions should take into consideration medium to extreme sea level rise predictions." "

50 years, a half century. No one is really freaking out. More like watching with morbid curiosity.



Climate change? Florida Keys prepare for sea level rise over the next 50 years

More coulds, mights, and maybes. Never mind that they don't mesh with actual observation or peer reviewed, published studies...

A recent paper reviewed by CO2 Science finds sea levels have risen over the past 9 years [2002-2011] at a rate of only 1.7 mm/yr, equivalent to 6.7 inches per century. The paper corroborates the NOAA 2012 Sea Level Budget which finds sea levels have risen at only 1.1-1.3 mm/yr over the past 7 years from 2005-2012 [less than 5 inches/century], and the paper of Chambers et al finding "sea level has been rising on average by 1.7 mm/year over the last 110 years." Contrary to alarmist claims, sea level rise decelerated over the 20th century, has also decelerated since 2005, and there is no evidence of any human influence on sea levels. Concomitantly, the air's CO2 concentration has risen by close to a third. And, still, it has not impacted the rate-of-rise of global sea level!

CO2 Science

 

[itfitzme]

those are quibbles. what I really wanted to comment on is your understanding of correlations and p values.

correlation does imply causation, especially when there are known mechanisms involved. unfortunately there are at least several mechanisms known. while CO2 should theoretically cause heating at the surface, it is also known that warmer oceans release CO2. what is the standard amount of CO2 that should be in the atmosphere for this temperature? it is very difficult to say just from proxies, it is difficult to measure CO2 even with modern technology, so we have decided to use just one measurement in Hawaii.

Which is why I say, if you want to quibble with the science done by hundreds, if not tens of thousands of professionals (if we include all the techs, assistants, and grad students), then break out excel, download the data, and run the analysis on at least

And study*

The Discovery of Global Warming - A History

including the citations. *Then see how far you get in designing the equations, either algebraically or procedurally, and modelling the climate to the level that is presented above.

Because, so far, all I've seen, are the climatology equivalence of arm chair atheletes, who, armed with some new phrase they have read, blurt out "correlation doesn't prove causality" because they mistake argument with intelligent analysis.

The first step in being even modesty intelligent is recognizing how ignorant you really are. *The difference between you and me, and folk that have a professional career as climatologists at NASA is the difference between a gammar school graduate and a college sophmore. That is, if we are at least smart as the college sophmore, in understanding how little we really know. So far as I've seen, the likes of gslack and westwall, are like a ten year old that just learned to read Cat in The Hat and feels they are now capable of critiquing Shakespere.

Perhaps an effort to figure out why they know that they can use Mauna Loa to measure the relative changes in atmospheric CO2, is the proper approach, *intead of starting with the perception that it can't possibly be adequate. *It's not like a thousand climatologists are just to stupid to have considered it's accuracy and precision.

And when we look into it, in depth, we will find that it is reasonably accurate and precise. It is just accurate and precise enough, to serve the purpose that it serves, given the funds and technology available.

And before you are to quick to respond, know why I use a paired term like "accuracy and precision" as well as "measure the relative changes".*

When you do, as with "correlation implies causality", 90% of your constenations will evaporate, like so many million tons of coal.

Then, examine the fundamentals of measurement, what exactly it is. *Figure out that there are no absolute measures of anything. All*measures are "proxies" of one sort or another. *From the calipers that has beem calibrated to a standard reference and the expanding mercury in a liquid thermometer, to the relative proportions of an oxygen isotope or tree rings, all measures are fundamentally proxies for the property being measured. It would be great, if some caveman had a thermometer, stuck it up the ass of a dozen dinosours, and scrawled the measurement of the wall of some cave, but they didn't. *So we are stuck with tree rings.

And when you've accomplished all that, the data analysys, the study of the full body of climatology, and the understanding that there are no absolute measures of anything, you won't feel the need to question my understanding of correlation, significance, or how to devise appropriate mathematical models that represent the signal beneath the noise.*

Cuz' so far, you just seem like gslack with more words. *And points like scaling on graphs are first year freshman issues. *Philosophcal constenations of correlation v causality is an evening among grad students, sharing a joint. *Proxies, accuracy, precision, reference points, relative measures, these are all just secondary freshman topics that get covered in one section of one chapter of introduction to measurements, which is a gimme course that they teach in community college.

"it is very difficult to say just from proxies, it is difficult to measure CO2 even with modern technology, so we have decided to use just one measurement in Hawaii", just doesn't say anything.

"What is the measurement error for CO2 at Mauna Loa?" starts to say something.

co2 hawaii mauna loa measurement error - Google Search starts to say something.

ESRL Global Monitoring Division - Carbon Cycle Group

and

http://scrippsco2.ucsd.edu/publications/the_mauna_loa_carbon_dioxide_record_2009_sundquist.pdf

begin to say something.

Global Change Master Directory (GCMD)

"Abstract: Daily atmospheric carbon dioxide (CO2) concentrations have been*
measured since March 1958 at Mauna Loa Observatory, Hawaii. These*
measurements constitute the longest, continuous record of atmospheric*
CO2 concentrations available in the world. The Mauna Loa Observatory*
site (19.5 N, 155.6 W, and elevation of 3400m) is one of the most*
favorable locations for vegetation or human activities on atmospheric*
CO2. This record provides scientific documentation for the degree of*
change in atmospheric CO2 concentrations over the past 30 years. The*
Mauna Loa data are extremely useful to modelers attempting to project*
future CO2 concentrations, climate scenarios, and vegetation responses*
to increased levels of CO2. The Mauna Loa record is considered to be*
a reliable indicator of the regional trend in the concentration of*
atmospheric CO2 in the middle layers of the troposphere. The steady*
rise in atmospheric CO2 concentration shown by this record has been*
widely interpreted as a global trend.*

Daily, monthly, and annual averages are computed for the Mauna Loa*
data after deletion of contaminated samples and readjustment of the*
data. These averages have shown a steady rise in annual average*
concentration from 316 parts per million by volume (ppmv) in 1959 to*
over 368 ppmv in 1999.*

Since 1958, CO2 concentrations at Mauna Loa Observatory have been*
obtained using a nondispersive, dual detector, infrared gas*
analyzer. Air samples are obtained from air intakes at the top of four*
7m towers and one 27m tower. Four samples are collected every hour*
from air intakes on the taller tower and from one of the 7m towers.*
Air is sampled from one tower intake for 10 minutes, followed by a*
second tower intake for 10 minutes, and then from a reference gas for*
10 minutes. Air flow through the intakes registers a voltage on the*
infrared gas analyzer which then records the concentrations on a strip*
chart recorder. (The air intakes are operating continuously but the*
air is shunted when not being analyzed by the infrared gas analyzer.)*
Two intakes are used in the sampling to help detect possible*
contamination that would be shown by significant differences in CO2*
concentrations between the two intakes.*

Those involved in the monitoring project have attempted to improve*
sampling techniques, reduce possible contamination sources, and adjust*
data to represent uncontaminated, true conditions throughout the*
twenty-eight year sampling period. The gas analyzer is calibrated by*
standardized CO2-in-nitrogen reference gases twice daily. Flask*
samples are taken twice a month for comparison to the data recorded*
using the infrared gas analyzer. Data are scrutinized daily for*
possible contamination and archived on magnetic tape for further*
scrutiny and adjustment.*

Possible ambient error sources at Mauna Loa include volcanic,*
vegetative, and man-made effects (e.g., vehicular traffic,and*
industry). Daily peaks in measured concentrations occur because of*
complex wind currents. Downslope winds often transport CO2 from*
distant volcanic vents causing elevations in measured CO2*
concentrations. Upslope winds during afternoon hours are often low in*
CO2 because of photosynthetic depletion occurring in sugarcane fields*
and forests. Vehicular traffic problems (since corrected) caused*
exaggerated elevations in 1971. Despite these sources of error and*
contamination, considerable effort has been made to alleviate and*
detect these sources.*

The imprecision in measuring references gases approaches 0.1 ppmv and*
is rarely greater than 0.2 ppvm. However, agreement differences less*
than 0.5 ppmv between flask and analyzers or between different
analyzers on a short-term basis are difficult to obtain. Monthly*
averages from May 1964 to January 1969 may be in error by as much as*
1.0 ppmv; but since 1970, systematic error probably does not exceed*
0.2 ppmv. The precision of monthly averages is approximately 0.5*
ppmv. In summary, monthly and annual averages of the Mauna Loa data*
are statistically robust and serve as a precise, long-term record of*
atmospheric CO2 concentrations.

The Mauna Loa CO2 data set has been updated with data through December*
2002 in August 2003. This data set is continuously updated as new data*
becomes available.*

All CDIAC numerical data packages include copies of pertinent*
literature discussing the data, summaries discussing the background,*
source and scope of the data, as well as applications limitations and*
restrictions of the data.*

The NDP-001 data set is located in CDIAC's anonymous FTP in*

ftp://cdiac.esd.ornl.gov/pub/maunaloa-co2/*

and on the WWW:*
http://cdiac.esd.ornl.gov/ndps/ndp001.html*
and*
http://cdiac.esd.ornl.gov/ftp/ndp001/*
"

That says something!!!

 

[SSDD]

Well it says that when you fall for a hoax, you really fall hard.

 

[itfitzme]

I applaud you for trying to dig into the math of these complexities, everyone should at least try to understand some science. unfortunately you cannot pull out one simple relationship and prove it runs the whole system. this thread was started to tell konradv the same message.

I hardly need your applause or accolades.

And your statement "unfortunately you cannot pull out one simple relationship and prove it runs the whole system." simply demonstrates a lack of understanding of how measurment, modeling and prediction functions.

All you do is present yourself as an armchair athelete, great at watching and critisizing, lacking the ability to get out on the field and hit a ball.

The reality is*

A the linear regression is anom=-3.03+0.00922*CO2

And given the 95% confidence interval, a series of bets on that will yield 95% wins. *So, yes, lacking any other information, I can pull out one relationship and bet on the other being related. *And I don't need to know why. *It is sufficient to demonstrate the utility of moving forward and looking into why they are related.

And whatever that relation should be, it has to fit with

anom=-3.08+0.00922*CO2,*

within the level of error estaished by the least squares analysis.

Because all I've done is restate the reality in a quantifiable manner, in accordance with established scientific procedures.

The difference being, I can say something and all you are saying is that you can't.

So, as it has been pointed out, the world moves forward, while you stand still, yelling at the crowd, "YOU CAN'T GO THAT WAY!!", as it dissappears into the distance.

The science knows, the management listens to them, and you're just standing on the curb, whining that it's the wrong bus.

I'm just standing on the step, pointing at the map. But the bus driver is closing the door.

 

[itfitzme]

....

those are quibbles. what I really wanted to comment on is your understanding of correlations and p values.

correlation does imply causation,

...

edit- correlation does imply causation but it doesnt necessarily tell the direction of cause, and often correlation is simply seen between two symptoms of some other causative agent(s).

Yeah, you're not quite clear on how this measurement and statistics thing works.

I can use gslack as a negatively correlated proxy for climate science. *I don't need to know how it works, just that abnormal psychology and the data demonstrates a 100% correlation that he's worse than random chance at having knowledge. As a control group, I can use a chimpanzee pointing at flashcards.

I could then publish in the Journal of Abnormal Statistics and the Journal of Climate Science Eduction simultaniously. *I'd title it "Evidence From Online Forums of Signals Of Learning To Be*A Moron :A Case Study"

 

[westwall]

Now they are freaking out in Maine too!

"The surge in lobster numbers in the Gulf of Maine has led to oversupply, which last year caused the per-pound price at the pier to dip as low as $2.50 in some areas of the coast. Partly in response, the state launched a new marketing collaborative to expand promotion of Maine lobster to open untapped global markets."

Still, they are freaking out.

"The effects of climate change, including a continuing rise in water temperature and increased acidification in the Gulf of Maine, as well as disease and life cycle changes in lobsters and other shellfish, have raised alarm about the potential damage to the state’s most lucrative fishery, said environmental advocates from the Natural Resources Council of Maine and marine scientist Rick Wahle, a University of Maine zoologist in the School of Marine Sciences.

They joined with representatives of the Maine Lobster Council, Ready Seafood Co. and the Maine Restaurant Association to launch a public awareness campaign about the economic value of the state's lobster fishery and the challenges it faces.

“There is a problem. We are beginning to see the effects of climate change in the Gulf of Maine,” said Emmie Theberge, clean-energy outreach coordinator for the NRCM. “And the oceans are more sensitive to climate change.”

Give em an inch, and they are afraid of losing a tenth. Will they never be happy?! Warmer waters means pre-cooked. And who wouldn't
love softer shells? So much easier to eat.


Maine lobster coalition calls for action to avert climate threats | The Portland Press Herald / Maine Sunday Telegram

It couldn't possibly be related to overharvesting now could it....nope...

 

[gslack]

....

those are quibbles. what I really wanted to comment on is your understanding of correlations and p values.

correlation does imply causation,

...

edit- correlation does imply causation but it doesnt necessarily tell the direction of cause, and often correlation is simply seen between two symptoms of some other causative agent(s).

Yeah, you're not quite clear on how this measurement and statistics thing works.

I can use gslack as a negatively correlated proxy for climate science. *I don't need to know how it works, just that abnormal psychology and the data demonstrates a 100% correlation that he's worse than random chance at having knowledge. As a control group, I can use a chimpanzee pointing at flashcards.

I could then publish in the Journal of Abnormal Statistics and the Journal of Climate Science Eduction simultaniously. *I'd title it "Evidence From Online Forums of Signals Of Learning To Be*A Moron :A Case Study"

Aww now there you go talking about me to others again... LOL, you sockos never learn do ya..When you idiots do that, it doesn't matter what you type, what you're actually saying is "gslack kicked my ass and now I want to cry"..

ROFL

 

[itfitzme]

Nothing to sneeze at: Climate change is making your allergies worse

"&#8220;The link between rising carbon dioxide and pollen is pretty clear,&#8221; says Lewis Ziska, a weed ecologist at the U.S. Department of Agriculture and a top researcher in the field.

His lab tests show that pollen production rises along with carbon dioxide. It doubled from 5 grams to 10 grams per plant when CO2 in the atmosphere rose from 280 parts per million (ppm) in 1900 to 370 ppm in 2000. He expects it could double again, to 20 grams, by 2075 if carbon emissions continue to climb. The world&#8217;s CO2 concentration is about 400 ppm."

Nothing to sneeze at: Climate change is making your allergies worse | Grist

 

[gslack]

Nothing to sneeze at: Climate change is making your allergies worse

"“The link between rising carbon dioxide and pollen is pretty clear,” says Lewis Ziska, a weed ecologist at the U.S. Department of Agriculture and a top researcher in the field.

His lab tests show that pollen production rises along with carbon dioxide. It doubled from 5 grams to 10 grams per plant when CO2 in the atmosphere rose from 280 parts per million (ppm) in 1900 to 370 ppm in 2000. He expects it could double again, to 20 grams, by 2075 if carbon emissions continue to climb. The world’s CO2 concentration is about 400 ppm."

Nothing to sneeze at: Climate change is making your allergies worse | Grist

Let's see plants grow faster with CO2, and therefore pollinating plants will occur faster as well... Wow, you guys are real geniuses for that one... Bet they spent billions on research for that... ROFL

 

[IanC]

"radio/TV antennae couldnt be more off topic. that has to do with a reactive EM field transitioning into a radiative EM field, and is dependent on the wavelength of emission."

Then you completely get lost in the details of your own thoughts and miss the simple mathematical point.

**At large values of x, 1/x^2 and ln x both have curvatures that are tiny and the functions are nearly linear. *There is nothing wavelength dependent in the maximum intensity value of the far field relative to it's near field component. Total transmitted power is spread over a larger area as the emission moves further from the source, regardless of the wavelength. *For a spherical radiation, the intensity falls as 1/r^2. *Just so you don't go off all half cocked, I will add that a line source drops as 1/r, rather than 1/r^2, which does nothing in terms of the point, as 1/r becomes more linear for large values of r.

We can get all detailed about antenna coupling, antenna shape, etc, but that is off topic from the simple point that the function for power becomes effectively linear at large distances.

And like the 1/r and 1/r^2 functions, the ln(CO2) is nearly linear for large values of CO2. *That may not fully explain*

But it knocks off a large piece of it because*

a) that is the reality, in atmosphere, of temp v CO2 and it is a linear relationship. *Over the range of measured CO2, the curvature is flat, and any difference between a linear fit and a ln fit is buried in the residuals of the data. *

and b) any more complex function of anom=a*+ b*ln(CO2[factors]) + c*f[other factors], where CO2[factors] is a function where some secondary factors drive CO2 and f[other factors] is some other environmental influenced function, still has to match the real, in atmosphere, measurement of temp v CO2 as shown in the scatterplot.

Perhaps I should have used the term "inverse square law" instead of near-field and far-field.*

Inverse-square law - Wikipedia, the free encyclopedia

Then it would have been less confusing as you'd have looked there instead of

Near and far field - Wikipedia, the free encyclopedia

Please stop overestimating your own intelligence, it makes conversing with you difficult. I'm really not interested in writing a book every time I post. *You going to have to make some effort to get the point. *

A simple "you're right IanC, TV antennae was a poor choice for an example" would have sufficed.

While I did admit that a linear approximation is OK for a restricted range of the curve, especially now that it has passed into a relatively flat region, the problem is that you are claiming that the relationship actually is linear.

Climate is driven by a myriad of factors, each responsible for a certain portion of the variability. If, for example, solar input was reponsiblefor 25 percent and CO2 only 1 per cent then ignoring solar and focusing only on CO2 will give a wildly exaggerated importance to CO2 at the expence of wildly underestimated solar. Even if solar is not changing that does not mean it is unimportant. Even if CO2 is changing that does not necessarily increase its importance to climate.

 

[itfitzme]

"radio/TV antennae couldnt be more off topic. that has to do with a reactive EM field transitioning into a radiative EM field, and is dependent on the wavelength of emission."

Then you completely get lost in the details of your own thoughts and miss the simple mathematical point.

**At large values of x, 1/x^2 and ln x both have curvatures that are tiny and the functions are nearly linear. *There is nothing wavelength dependent in the maximum intensity value of the far field relative to it's near field component. Total transmitted power is spread over a larger area as the emission moves further from the source, regardless of the wavelength. *For a spherical radiation, the intensity falls as 1/r^2. *Just so you don't go off all half cocked, I will add that a line source drops as 1/r, rather than 1/r^2, which does nothing in terms of the point, as 1/r becomes more linear for large values of r.

We can get all detailed about antenna coupling, antenna shape, etc, but that is off topic from the simple point that the function for power becomes effectively linear at large distances.

And like the 1/r and 1/r^2 functions, the ln(CO2) is nearly linear for large values of CO2. *That may not fully explain*

But it knocks off a large piece of it because*

a) that is the reality, in atmosphere, of temp v CO2 and it is a linear relationship. *Over the range of measured CO2, the curvature is flat, and any difference between a linear fit and a ln fit is buried in the residuals of the data. *

and b) any more complex function of anom=a*+ b*ln(CO2[factors]) + c*f[other factors], where CO2[factors] is a function where some secondary factors drive CO2 and f[other factors] is some other environmental influenced function, still has to match the real, in atmosphere, measurement of temp v CO2 as shown in the scatterplot.

Perhaps I should have used the term "inverse square law" instead of near-field and far-field.*

Inverse-square law - Wikipedia, the free encyclopedia

Then it would have been less confusing as you'd have looked there instead of

Near and far field - Wikipedia, the free encyclopedia

Please stop overestimating your own intelligence, it makes conversing with you difficult. I'm really not interested in writing a book every time I post. *You going to have to make some effort to get the point. *

A simple "you're right IanC, TV antennae was a poor choice for an example" would have sufficed.*

While I did admit that a linear approximation is OK for a restricted range of the curve, especially now that it has passed into a relatively flat region, the problem is that you are claiming that the relationship actually is linear.*

Climate is driven by a myriad of factors, each responsible for a certain portion of the variability. If, for example, solar input was reponsiblefor 25 percent and CO2 only 1 per cent then ignoring solar and focusing only on CO2 will give a wildly exaggerated importance to CO2 at the expence of wildly underestimated solar. Even if solar is not changing that does not mean it is unimportant. Even if CO2 is changing that does not necessarily increase its importance to climate.

Why? *Your ignorance doesn't make it a bad example. It just means I have to make things simpler for you.