Disproving The Anthropogenic Global Warming (AGW) Problem

Reposted from The Air Vent

Disproving The Anthropogenic Global Warming (AGW) Problem

Leonard Weinstein, ScD

April 25, 2009

A theory has been proposed that human activity over about the last 150 years has caused a significant rise in Earth’s average temperature. The mechanism claimed is based on an increased greenhouse effect caused by anthropogenic increases in CO2 from burning of fossil fuels, deforestation, cement manufacture, and also from increases in CH4 from farm animals and other causes. The present versions of the theory also include a positive feedback effect due to the increased temperature causing an increase in water vapor, which amplifies the effect. The combined result are used to claim that unless the anthropogenic increases of CO2 are slowed down or even made to decrease, there will be a continuing rapid increase in global temperature, massive melting of ice caps, flooding, pestilence, etc.

In order to support a theory, specific predictions need to be made that are based on the claims of the theory, and the predictions then need to happen. While the occurrence of the predicted events is not proof positive of a theory, they increase the believability of the claims. However, if the predictions are not observed, this tends to indicate the theory is flawed or even wrong. Some predictions are absolute in nature. Einstein’s prediction of the bending of light by the Sun is such a case. It either would or would not bend, and this was considered a critical test of the validity of his theory of general relativity. It did bend the predicted amount, and supported his theory.

Many predictions however are less easily supported. For example weather forecasting often does a good job in the very short term but over increasing time does a poor job. This is due to the complexity of the numerous nonlinear components. This complexity has been described in chaos theory by what is called the butterfly effect. Any effect that depends on numerous factors, some of which are nonlinear in effect, is nearly impossible to use to make long-range predictions. However, for some reason, the present predictions of “Climate Change” are considered by the AGW supporters to be more reliable than even short-term weather forecasting. While some overall trends can be reasonably made based on looking at past historical trends, and some computational models can suggest some suggested trends due to specific forcing factors, nevertheless, the long term predicted result has not been shown to be valid. Like any respectable theory, specific predictions need to be made, and then shown to happen, before the AGW models can have any claim to reasonable validity.

The AGW computational models do make several specific predictions. Since the time scale for checking the result of the predictions is small, and since local weather can vary enough on the short time scale to confuse the longer time scale prediction, allowances for these shorter lasting events have to be made when examining predictions. Nevertheless, if the actual data results do not significantly support the theory, it must be reconsidered or even rejected as it stands.

The main predictions from the AGW models are:

  1. The average Earth’s temperature will increase at a rate of 0.20C to 0.60C per decade at least to 2100, and will continue to climb after that if the CO2 continues to be produced by human activity at current predicted rates.

  2. The increasing temperature will cause increased water evaporation, which is the cause for the positive feedback needed to reach the high temperatures.

  3. The temperature at lower latitudes (especially tropical regions) will increase more in the lower Troposphere at moderate altitudes than near the surface.

  4. The greatest near surface temperature increases will occur at the higher latitudes.

  5. The increasing temperature at higher latitudes will cause significant Antarctic and Greenland ice melt. These combined with ocean expansion due to warming will cause significant ocean rise and flooding.

  6. A temperature drop in the lower Stratosphere will accompany the temperature increase near the surface. The shape of the trend down in the Stratosphere should be close to a mirror reflection of the near surface trend up.

The present CO2 level is high and increasing (http://www.esrl.noaa.gov/gmd/ccgg/trends/). It should be fairly easy to show the consequences of AGW predictions if they are valid.

Figure 1. Global average temperature from 1850 through 2008. Annual series smoothed with a 21-point binomial filter by the Met Office. (http://hadobs.metoffice.com/hadcrut3/diagnostics/global/nh+sh/)

It should be noted that the largest part of the last 150 year increase in CO2, which is blamed on human activity, did not occur until after 1940, so the largest temperature rise effects should have occurred in that time. The proponents of AGW have generally used the time period from 1970 to 2000 as the base line for an indicator of the rapid warming. In that base line period, the average temperature rose about 0.50C, which averages to 0.160C per decade. The claim was then made that this would accelerate due to continuing increases in CO2 level. However if we look at the temperature change from 1940 through 2008, the net increase is only 0.30C. This is due to a drop from 1940 to 1970 and a slight drop from 2000 through 2008. Now the average rise for that period is only 0.040C per decade. If the time period from 1850 through 2008 is used as a base, the net increase is just under 0.70C and the average rise is also 0.040C per decade! It is clear that choosing a short selected period of rising temperature gives a misleading result. It is also true that the present trend is down and expected to continue downward for several more years before reversing again. This certainly makes claim 1 questionable.

The drop in temperature from 1940 to 1970 was claimed to have been caused by “global dimming” caused by aerosols made by human activity. This was stated as dominating the AGW effects at that time. This was supposed to have been overcome by activity initiated by the clean air act. In fact, the “global dimming” continued into the mid 1990’s and then only reduced slightly before increasing more (probably due to China and other countries increased activity). If the global dimming was not significantly reduced, why did the temperature increase from 1970 to just past 2000?

A consequence of global dimming is reduced pan-evaporation level. This also implies that ocean evaporation is decreased, since the main cause of ocean evaporation is Solar insolation, not air temperature. The decreased evaporation contradicts claim 2.

Claim 3 has been contradicted by a combination of satellite and air born sensor measurements. While the average lower Troposphere average temperature has risen along with near ground air temperature, and in some cases is slightly warmer, nevertheless the models predicted that the lower Troposphere would be significantly warmer than near ground at the lower latitudes, especially in the tropics. This has not occurred! The following is a statement from:

Synthesis and Assessment Product 1.1

Report by the U.S. Climate Change Science Program

and the Subcommittee on Global Change Research

April 2006

While these data are consistent with the results from climate models at the global scale, discrepancies in the tropics remain to be resolved”.

Claim 4 implies that the higher latitudes should heat up more than lower latitudes. This is supposed to be especially important for melting of glaciers and permafrost. In fact, the higher latitudes have warmed, but at a rate close to the rest of the world. In fact, Antarctica has overall cooled in the last 50 years except for the small tail that sticks out. See:

http://ff.org/centers/csspp/library/co2weekly/20061013/20061013_02.html

Greenland and the arctic region are presently no warmer than they were in the late 1930’s, and are presently cooling! See:

http://www.worldclimatereport.com/index.php/2006/11/17/cooling-the-debate-a-longer-record-of-greenland-air-temperature/

The overall effect of Antarctic and Greenland are now resulting in net gain (or at least near zero change) of ice, not loss. While some small areas have recently lost and are some are still losing some ice, this is mostly sea ice and thus do not contribute to sea level rise. Glaciers in other locations such as Alaska have lost a significant amount of ice in the last 150 years, but much of the loss is from glaciers that formed or increased during the little ice age, or from local variations, not global. Most of this little ice age ice is gone and some glaciers are actually starting to increase as the temperature is presently dropping. For more discussions on the sea level issue look at the following two sites:

http://docs.google.com/Doc?docid=dnc49xz_19cm8×67fj&hl=en

http://www.telegraph.co.uk/comment/columnists/christopherbooker/5067351/Rise-of-sea-levels-is-the-greatest-lie-ever-told.html

This indicates that claim 5 is clearly wrong. While sea level will rise a small amount, and has so since the start of the Holocene period, the rise is now only 10 to 15 cm per century, and is not significantly related to the recent recovery from the little ice age, including the present period of warming.

The claims in 6 are particularly interesting. Figure 2 below shows the Global Brightness Temperature Anomaly (0C) in the lower Troposphere and lower Stratosphere made from space.

a) Channel TLT is the lower Troposphere from ground to about 5 km

b) Channel TLS is the lower Stratosphere from about 12 to 25 km

Figure 2. Global satellite data from RSS/MSU and AMSU data. Monthly time series of brightness temperature anomaly for channels TLT, and TLS. Data from: http://www.ssmi.com/msu/msu_data_description.html

The anomaly time series is dominated by ENSO events and slow troposphere warming for Channel TLT (Lower Troposphere). The three primary El Niños during the past 20 years are clearly evident as peaks in the time series occurring during 1982-83, 1987-88, and 1997-98, with the 1997-98 being the largest. It also appears there is an aditional one at 2007. Channel TLS (Lower Stratosphere) is dominated by stratospheric cooling, punctuated by dramatic warming events caused by the eruptions of El Chichon (1982) and Mt Pinatubo (1991). In these, and other volcanic eruption cases, the increased absorption and reflectivity of the dust and aerosols at high altitudes lowered the surface Solar insolation, but since they absorbed more energy, they increased the high altitude temperature. After the large spikes dropped back down, the new levels were lower and nearly flat between large volcanic eruptions. It is also likely that the reflection or absorption due to particulates also dropped, so the surface Solar insolation went back up. It appears that a secondary effect of the volcanic eruptions is present that is unknown in nature (but not CO2)! One possible explanation is a modest but long-term drop in Ozone. It is also clear that the linear fit to the data shown is meaningless. In fact the level drop events seem additive if they overlap soon enough for at least the two cases shown. That is, after El Chicon dropped the level, then Pinatubo occurred and dropped the level even more. Two months after Pinatubo, another strong volcano, Cerro Hudson, also erupted, possibly amplifying the effect. It appears that the recovery time from whatever causes the very slow changing level shift has a recovery time constant of at least several decades.

The computational models that show that the increasing CO2 and CH4 cause most of the present global warming all require that the temperature of the Stratosphere drops while the lower atmosphere and ground heat up. It appears from the above figures that the volcanic activity clearly caused the temperature to spike up in the Stratosphere, and that these spikes were immediately followed by a drop to a new nearly constant level in the temperature. It is clear from the Mauna Loa CO2 data (http://www.esrl.noaa.gov/gmd/ccgg/trends/) that the input of CO2 (or CH4) from the volcanoes, did not significantly increase the background level of this gas, and thus, this cannot be the cause of the drop in the Stratosphere temperature. The ramp up of atmospheric CO2 also cannot explain the step down then level changes in high altitude temperature. Since the surface temperature rise is supposed to be related to the Stratosphere temperature drop, and since a significant surface rise above the 1940 temperature level did not occur until the early 1980’s, it may be that the combination of the two (or more) volcanoes, along with Solar variability and variations in ocean currents (i.e., PDO) may explain the major causes of recent surface temperature rises to about 2002. In fact, the average Earth temperature stopped rising after 2002, and has been dropping for the last few years!

The final question that arises is what prediction has the AGW made that has been demonstrated, and that strongly supports the theory. It appears that there is NO real supporting evidence and much disagreeing evidence for the AGW theory as proposed. That is not to say there is no effect from Human activity. Clearly human pollution (not greenhouse gases) is a problem. There is also almost surely some contribution to the present temperature from the increase in CO2 and CH4, but it seems to be small and not a driver of future climate. Any reasonable scientific analysis must conclude the basic theory wrong!!


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Dave Middleton
June 4, 2009 8:47 am

Achaean should be Archaean…Never trust spell checkers!

oms
June 4, 2009 10:01 am

Dave Middleton (08:19:24) :

If you think you can meaningfully fit a 12th-order polynomial to any physical phenomenon, I’m afraid you’re horribly mistaken.
Then don’t ever become a seismic data processor or a sequence stratigrapher…because the name of both of those games is cyclical resolution of physical phenomena….Polynomial trend-line functions are analogous to seismic wavelets. The higher the polynomial – the higher the frequency – the higher the resolution. A densely sampled data set, like the UAH monthly temperature anomaly series can return meaningful cyclical information with polynomial trend-line functions.

In seismology, wavelet transforms have a clear physical analogy to wave packets. Does high order polynomial fitting have a similar interpretation?
Isn’t the point of polynomial fitting for these temp series actually interpolation and data reduction (opposite to the point about Nyquist)? If so, it makes more sense to present “trends” produced from a low-order polynomial fit.

Dave Middleton
June 4, 2009 11:14 am

oms (10:01:45) :
Dave Middleton (08:19:24) :
[…]
Then don’t ever become a seismic data processor or a sequence stratigrapher…because the name of both of those games is cyclical resolution of physical phenomena….Polynomial trend-line functions are analogous to seismic wavelets. The higher the polynomial – the higher the frequency – the higher the resolution. A densely sampled data set, like the UAH monthly temperature anomaly series can return meaningful cyclical information with polynomial trend-line functions.
In seismology, wavelet transforms have a clear physical analogy to wave packets. Does high order polynomial fitting have a similar interpretation?

Sort of…
In seismic reflection profiling, the thinnest bed that can be resolved is determined by frequency and seismic velocity. “Over-fitting” the frequency content in wavelet processing is desirable so long as the frequency is below Nyquist and the signal-to-noise ratio can be managed.
If I simply had the raw data that went into this Relative Changes of Sea Level chart, a third or sixth order polynomial might give me the First Order curve; whereas a higher polynomial might give me the Second Order curve. A linear trend-line wouldn’t reveal anything about the cyclical nature of past sea level changes…In the same manner that linear trend-lines through the obviously non-linear temperature data do not reveal anything about modern cyclical changes.

Isn’t the point of polynomial fitting for these temp series actually interpolation and data reduction (opposite to the point about Nyquist)? If so, it makes more sense to present “trends” produced from a low-order polynomial fit.

Yes. You are correct. In this graph of UAH Lower Trop. Temp’s The 12-month moving average captures the high frequency cycles and the 6th order polynomial captures the low frequency cycle…In a similar fashion as the second and first order sea level changes mentioned above.
I’m essentially using the sixth order polynomial as a low frequency filter to image the low frequency cycle. Ideally, I should take the data into the frequency domain and apply various filters. But, that would be turning a hobby into a job.

RW
June 10, 2009 2:34 pm

Dave Middleton: you have a woefully inadequate understanding of some very basic maths and physics. It’s clear that you simply do not understand what ‘logarithmic’ means. A logarithmic relationship never ‘disappears’ or ‘diminishes’. If y=log(x), then any doubling of x leads to exactly the same increase in y. See that? Any doubling leads to exactly the same increase in y. With some very, very simple maths, you can work out that the difference between 4,000ppm and 185ppm is in fact not minor but a factor of 4.5. Your failure to understand logarithms renders much of what you say otiose.
You also appear not to understand that many factors affect climate. You appear to think that unless there is a 100% correlation between CO2 and temperatures, then CO2 does not affect climate. I guess I’ll have to spell the reductio ad absurdum out to you – in your beloved phanerozoic graph, there is only a weak correlation between temperature and any variable you care to consider. Your premise would lead to the conclusion that nothing affects the climate. The conclusion is absurd; that’s because the premise is absurd.
You keep on using the word ‘secular’ in ways that don’t make sense. Secular in this context simply means non-cyclic.
You don’t seem to understand that the Sun has been increasing in luminosity throughout its main sequence evolution, and thus its output changed significantly over the period covered by your favourite graph.
You don’t seem to understand just how approximate the temperature line is on that graph of yours. You clearly haven’t read the literature widely enough to know that much more realistic reconstructions exist.
Please do explain what physical basis there is in a 12th order polynomial fit. I look forward to that very much.
I don’t think you’re incapable of understanding these things, because most 16-year olds could grasp them quite easily. Your lack of knowledge is, I think, self-inflicted. You clearly want to believe that CO2 is not a greenhouse gas. Unfortunately, to maintain that belief, you have to pretend not to understand simple physics and maths. Well, it’s your choice, I suppose.

Dave Middleton
June 10, 2009 2:49 pm

RW (14:34:08) :
[Snark snipped]
Well, it’s your choice, I suppose.

And my choice is to stop feeding the local troll.

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