Global Warming Science -


CO2 and IPCC Climate Modeling


[last update: 2010/04/03]



The IPCC conclusion that the warming trend in the late 20th century is significant and caused mainly by anthropogenic CO2, is a result of theoretical climate models (General Circulation Models - GCMs) in which the human-defined models are only able to reproduce current global temperature trends since 1970 by increasing the CO2 levels.


The availability of the CRU emails since November 2009 has shed further light on some of the modeling issues. For example: Tom Wigley (senior scientist at NCAR) to Michael Mann (creator of the hockey stick graph) [Oct 14, 2009]: “The Figure you sent is very deceptive. As an example, historical runs with PCM look as though they match observations -- but the match is a fluke. PCM has no indirect aerosol forcing and a low climate sensitivity -- compensating errors. In my (perhaps too harsh) view, there have been a number of dishonest presentations of model results by individual authors and by IPCC.” []


This document contains sections on:





IPCC Models – Climate Forcing


The following figure shows the estimated radiative forcing components as defined by the IPCC in the latest scientific basis report (May 2007). The report states: Energy consumption by human activities, such as heating buildings, powering electrical appliances and fuel combustion by vehicles, can directly release heat into the environment. Anthropogenic heat release is not an RF, in that it does not directly perturb the radiation budget; the mechanisms are not well identified and so it is here referred to as a non-initial radiative effect.”  Note also in the following figure the large uncertainty bar for aerosols and cloud effects, which are poorly understood and thus not well modeled.


A serious flaw is obvious in the IPCC chart shown below: the only “Natural process” affecting climate is a very slight influence of solar irradiance!


Estimated Radiative Forcing Components (Figure FAQ 2.1 – 2 in the IPCC AR4)





CO2 – IPCC Modeling Problems


The IPCC conclusion that the warming trend in the late 20th century is significant and caused mainly by anthropogenic

The IPCC AR4 Scientific Basis report (Part 6) states: “Climate models are used to simulate episodes of past climate... Models allow the linkage of cause and effect in past climate change to be investigated. Models also help to fill the gap between the local and global scale in palaeoclimate, as palaeoclimatic information is often sparse, patchy and seasonal. For example, long ice core records show a strong correlation between local temperature in Antarctica and the globally mixed gases CO2 and methane, but the causal connections between these variables are best explored with the help of models.” So, models in which the causal connections are programmed in, are then used to explore the causal connections – a circular proof.


One major problem is that Antarctica does not match the models and is now ignored by the IPCC.


The following figure is from the IPCC AR4 report (2007). It does not show modeling of Antarctica, because Antarctica does not fit the models.


From IPCC AR 4 Figure 9.6



The following figure (left) shows modeled temperature change from the IPCC TAR report (2001). The models show warming in Antarctica with cooling around the Antarctic Peninsula and in the adjacent Weddell Sea – exactly the opposite of the observed trend. The following figure (right) shows the observed temperature trend in the “cooling” area.



Left: From IPCC TAR Figure 9.2 – Modeled temperature differences from 1975 to 1995 to the first decade in the 21st century. Right: From NASA / GISS database.



Unlike the northern hemisphere, temperature measurements in Antarctica only started in the 1950’s, and there are very few stations covering a 40-year period to the present. The following figure shows two of the available non-peninsula temperature stations’ measurements are shown in the following figures (plots from stations in the NASA / GISS database). [ ]



Typical Antarctica Temperature Station Trends



For a more detailed regional study of Antarctica, see:


The NOAA Earth System Research Laboratory – Global Monitoring Division maintains a network of CO2 monitoring stations around the world. []. The following figures compare the recent CO2 trends at Palmer Station (on the Antarctic Peninsula) and the South Pole. There is virtually no difference between the two locations, although there is a substantial temperature difference as seen in the previous temperature trend graphs. The next figure compares CO2 and temperature trend at the South Pole showing the lack of correlation between the two.




CO2 Trends at Palmer Station and at the South Pole – Same CO2 Trends, Very Different Temperature Trends


Combining CO2 and South Pole Temperature Trends – No Correlation



The greenhouse hypothesis suggests the warming would be greatest in the atmosphere (troposphere) and that the warming would be significant both day and night. It would also be greatest in the polar regions because gases like CO2 are most effective at trapping the heat in very cold temperatures. The reason that the warming should be greatest at the polar regions is due to the following: CO2 in the atmosphere absorbs and re-emits infra-red radiation in distinctive wavebands, particularly around 12 - 18 microns. Radiation at other wavelengths simply passes through the atmosphere without being intercepted by CO2. The wavelength of infrared radiation from the earth's surface depends on the temperature of the surface. All bodies emit infrared over a wide band of wavelengths, but peak at a `dominant wavelength' determined by the temperature of the emitting surface. For example, an object with a temperature of 32°C will radiate most intensely at 9.5 microns. At 15°C (the mean surface temperature of the earth), the dominant wavelength will be 10 microns. At -25°C, it becomes 11.7 microns, and at -50°C becomes 13 microns. The problem is that the observations do not match the CO2 hypothesis.


The IPCC 2007 Report Chapter 9 – Understanding and Attributing Climate Change [] provides a climate model based simulation of the expected CO2 “spatial signature” of all forcings including anthropogenic CO2 (left-hand figure below shows degrees change per decade).  However, a study of actual data from radiosonde data shows a non-CO2 based signature []. The models do not match reality. In reference to this, Richard Lindzen (MIT Atmospheric Sciences Professor) stated: “surface warming should be accompanied by warming in the tropics around an altitude of about 9km that is about 2.5 times greater than at the surface. Measurements show that warming at these levels is only about 3/4 of what is seen at the surface, implying that only about a third of the surface warming is associated with the greenhouse effect, and, quite possibly, not all of even this really small warming is due to man (Lindzen, 2007, Douglass et al, 2007). This further implies that all models predicting significant warming are greatly overestimating warming. This should not be surprising (though inevitably in climate science, when data conflicts with models, a small coterie of scientists can be counted upon to modify the data. Thus, Santer, et al (2008), argue that stretching uncertainties in observations and models might marginally eliminate the inconsistency. That the data should always need correcting to agree with models is totally implausible and indicative of a certain corruption within the climate science community).” []



Trends in degrees per decade – left: IPCC CO2-based trend; right: actual data



A study comparing the models to observations from satellites and balloons (1979-2004) also shows a problem with the models. The following figure is from the study. “A comparison of tropical temperature trends with model predictions”, by Douglass, D.H., J.R. Christy, B.D. Pearson, and S.F. Singer, 2007 - International Journal of Climatology. []. The models exhibit the CO2 theory of most warming occurring in the troposphere. However, the satellite and balloon based observations show warming only at the surface of the earth. The report stated: Model results and observed temperature trends are in disagreement in most of the tropical troposphere, being separated by more than twice the uncertainty of the model mean. In layers near 5 km, the modelled trend is 100 to 300% higher than observed, and, above 8 km, modelled and observed trends have opposite signs. … On the whole, the evidence indicates that model trends in the troposphere are very likely inconsistent with observations that indicate that, since 1979, there is no significant long-term amplification factor relative to the surface. If these results continue to be supported, then future projections of temperature change, as depicted in the present suite of climate models, are likely too high.”




A 2009 paper states: “There appears to be something fundamentally wrong with the way temperature and carbon are linked in climate models” []


In a 2008 paper published by Engel et al in Nature Geoscience [] found that “Most atmospheric models predict that the rate of transport of air from the troposphere to the above lying stratosphere should be increasing due to climate change. … an international group of researchers has now found that this does not seem to be happening. On the contrary, it seems that the air masses are moving more slowly than predicted. … Due to the results presented now, the predictions of atmospheric models must be re-evaluated.


In an assessment of the IPCC modeling, a paper by: Bellamy, D. and Barrett, J. (2007). “Climate stability: an inconvenient proof”, (Proceedings of the Institution of Civil Engineers – Civil Engineering, 160, 66-72) states: “The climate system is a highly complex system and, to date, no computer models are sufficiently accurate for their predictions of future climate to be relied upon.”


In another review of IPCC modeling (Carter, R.M. (2007). “The myth of dangerous human-caused climate change” The Aus/MM New Leaders Conference, Brisbane May 3, 2007) Carter examined evidence on the predictive validity of the general circulation models (GCMs) used by the IPCC scientists. He found that “while the models included some basic principles of physics, scientists had to make “educated guesses” about the values of many parameters because knowledge about the physical processes of the earth’s climate is incomplete. In practice, the GCMs failed to predict recent global average temperatures as accurately as simple curve-fitting approaches. They also forecast greater warming at higher altitudes in the tropics when the opposite has been the case.


A 2007 study by Douglass and Christy published in the Royal Meteorological Society’s International Journal of Climatology [] found that the climate models do not match the data for the tropical troposphere. ““When we look at actual climate data, however, we do not see accelerated warming in the tropical troposphere. Instead, the lower and middle atmosphere are warming the same or less than the surface. For those layers of the atmosphere, the warming trend we see in the tropics is typically less than half of what the models forecast.””. A previous study cited in the same article blamed the data instead of the models!


A 2008 study “On the Credibility of Climate Predictions” (D. Koutsoyiannis, A. Efstradiadis, N. Mamassis & A. Christofides, Department of Water Resources, Faculty of Civil Engineering, National Technical University of Athens, Greece) states: “Geographically distributed predictions of future climate, obtained through climate models, are widely used in hydrology and many other disciplines, typically without assessing their reliability. Here we compare the output of various models to temperature and precipitation observations from eight stations with long (over 100 years) records from around the globe. The results show that models perform poorly, even at a climatic (30-year) scale. Thus local model projections cannot be credible, whereas a common argument that models can perform better at larger spatial scales is unsupported.”  []


Increasing atmospheric CO2 does not by itself result in significant warming. The climate models assume a significant positive feedback of increased water vapor in order to amplify the CO2 effect and achieve the future warming reported by the IPCC. According to the models, as the Earth warms more water evaporates from the ocean, and the amount of water vapor in the atmosphere increases. Since water vapor is the main greenhouse gas, this leads to a further increase in the atmospheric temperature. The models assume that changes in temperature and water vapor will result in a constant relative humidity (i.e. as temperatures increase, the specific humidity increases, keeping the relative humidity constant. This is one of the most controversial aspects of the models. Some studies say that the positive feedback is correct, others say not. Models that include water vapor feedback with constant relative humidity predict the Earth's surface will warm more than twice as much over the next 100 years as models that contain no water vapor feedback.


According to the IPCC [] “Water vapour is also the most important gaseous source of infrared opacity in the atmosphere, accounting for about 60% of the natural greenhouse effect for clear skies, and provides the largest positive feedback in model projections of climate change.


A 2004 NASA study using satellite humidity data found that “The increases in water vapor with warmer temperatures are not large enough to maintain a constant relative humidity” resulting in overestimation of temperature increase. []


MIT’s Richard Lindzen (the Alfred P. Sloan Professor of Meteorology at MIT) argues that the IPCC models have not only overestimated warming due to positive water vapor feedback, they also have the sign wrong: “Our own research suggests the presence of a major negative feedback involving clouds and water vapor, where models have completely failed to simulate observations (to the point of getting the sign wrong for crucial dependences). If we are right, then models are greatly exaggerating sensitivity to increasing CO2.” [] He also stated: “the way current models handle factors such as clouds and water vapor is disturbingly arbitrary. In many instances the underlying physics is simply not known. In other instances there are identifiable errors. … current models depend heavily on undemonstrated positive feedback factors to predict high levels of warming.” []


Roy Spencer (Team Leader, Advanced Microwave Scanning Radiometer – Earth Observing System (AMSR-E), NASA) has a presentation providing evidence that there is net negative feedback due to water vapor:


A study of model feedbacks “Validating and Understanding Feedbacks in Climate Models” (D-Z. Sun, T. Zhang, and Y. Yu, NOAA-CIRES/Climate Diagnostics Center) states: “The models tend to overestimate the positive feedback from water vapor in El Nino warming. … [and] tend to underestimate the negative feedback from cloud albedo in El Nino warming.” Another paper by the same authors concludes: “The extended calculation using coupled runs confirms the earlier inference from the AMIP runs that underestimating the negative feedback from cloud albedo and overestimating the positive feedback from the greenhouse effect of water vapor over the tropical Pacific during ENSO is a prevalent problem of climate models“ []


See for more details on the problem of water vapor not cooperating with the CO2 based theory.


The National Research Council (National Academy of Sciences) produced a study called “Climate Change Science: An Analysis of Some Key Questions” []. Here are a couple of statements from that report:


  • Because of the large and still uncertain level of natural variability inherent in the climate record and the uncertainties in the time histories of the various forcing agents (and particularly aerosols), a causal linkage between the buildup of greenhouse gases in the atmosphere and the observed climate changes during the 20th century cannot be unequivocally established. The fact that the magnitude of the observed warming is large in comparison to natural variability as simulated in climate models is suggestive of such a linkage, but it does not constitute proof of one because the model simulations could be deficient in natural variability on the decadal to century time scale.”


  • Knowledge of the climate system and projections about the future climate are derived from fundamental physics and chemistry through models and observations of the atmosphere and the climate system… A major limitation of these model forecasts for use around the world is the paucity of data available to evaluate the ability of coupled models to simulate important aspects of past climate. In addition, the observing system available today is a composite of observations that neither provide the information nor the continuity in the data needed to support measurements of climate variables.”


  • Solar irradiance, the amount of solar energy striking Earth, has been monitored accurately only since the late 1970s. However, indirect measures of solar activity suggest that there has been a positive trend of solar irradiance over the industrial era… It is not implausible that solar irradiance has been a significant driver of climate during part of the industrial era, as suggested by several modeling studies. However, solar forcing has been measured to be very small since 1980, and greenhouse gas forcing has certainly been much larger in the past two decades


The sun provides the energy that warms the earth. And yet according to the NOAA National Climatic Data Center [ ] “Our understanding of the indirect effects of changes in solar output and feedbacks in the climate system is minimal”. The importance of fluctuations and trends in solar inputs in affecting the climate is inadequately modeled. Although the sun exhibits varies types of energy related events (sunspots, solar flares, coronal mass ejections), sunspots have been observed and counted for the longest amount of time.


A 2010 paper by Ohashi and Tanaka (“Data Analysis of Recent Warming Pattern in the Arctic”, SOLA 2010) [] reports: “It is concluded that the arctic warming before 1989 especially in winter was explained by the positive trend of the AOI. Moreover the intensified Beaufort High and the drastic decrease of the sea ice concentrations in September after 1989 were associated with the recent negative trend of the AOI. Since the decadal variation of the AO is recognized as the natural variability of the global atmosphere, it is shown that both of decadal variabilities before and after 1989 in the Arctic can be mostly explained by the natural variability of the AO not by the external response due to the human activity.


A 2007 paper by Syun-Ichi Akasofu at the International Arctic Research Center (University of Alaska Fairbanks) provides an analysis of warming trends in the Arctic. [ ] They analyzed the capability of climate models (GCMs) to reproduce the past temperature trends of the Arctic (shown in the following figure): we asked the IPCC arctic group (consisting of 14 sub-groups headed by V. Kattsov) to “hindcast” geographic distribution of the temperature change during the last half of the last century. To “hindcast” means to ask whether a model can produce results that match the known observations of the past; if a model can do this, we can be much more confident that the model is reliable for predicting future conditions … Ideally, the pattern of change modeled by the GCMs should be identical or very similar to the pattern seen in the measured data. We assumed that the present GCMs would reproduce the observed pattern with at least reasonable fidelity. However, we found that there was no resemblance at all.


Model vs Observed temperature Changes [from Akasofu, above]



The authors’ conclusions: only a fraction of the present warming trend may be attributed to the greenhouse effect resulting from human activities. This conclusion is contrary to the IPCC (2007) Report, which states that “most” of the present warming is due to the greenhouse effect. One possible cause of the linear increase may be that the Earth is still recovering from the Little Ice Age. It is urgent that natural changes be correctly identified and removed accurately from the presently on-going changes in order to find the contribution of the greenhouse effect… The fact that an almost linear change has been progressing, without a distinct change of slope, from as early as 1800 or even earlier (about 1660, even before the Industrial Revolution), suggests that the linear change is natural change


The University of Alabama at Huntsville provides monthly plots of worldwide temperature anomalies for the troposphere since 2000 []. The following figure is from UAH and shows the temperature trend (degrees per decade) for 1978 to 2006. According to the CO2 theory, warming should be occurring over both poles – but this is not happening.





A recent paper studying the effect of “brown clouds” (caused by biomass burning) on warming in Asia (Ramanathan, V., M.V. Ramana, G. Roberts, D. Kim, C. Corrigan, C. Chung, and D. Winker, 2007. “Warming trends in Asia amplified by brown cloud solar absorption”. Nature, 448, 575-578) concludes “atmospheric brown clouds contribute as much as the recent increase in anthropogenic greenhouse gases to regional lower atmospheric warming trends”.


Data regarding volcanic aerosols is very sparse. A recent NASA study found that the levels of cooling volcanic aerosols has been declining in recent decades, as shown in the following figure. (Global 'Sunscreen' Has Likely Thinned, Report NASA Scientists  3/15/07) [] The National Research Council (National Academy of Sciences) in their study “Climate Change Science: An Analysis of Some Key Questions, said “The monitoring of aerosol properties has not been adequate to yield accurate knowledge of the aerosol climate influence”. (Notice in the above IPCC radiative forcing components figure, volcanic aerosols do not appear in the Natural Processes section of the figure.)



Atmospheric Volcanic Aerosols 1981 – 2006 Showing General Declining Trend



Recent studies are showing that black carbon (soot) plays a larger role than CO2 in causing Arctic warming.

A 2008 Cornell University report “Global Warming Predictions are Overestimated, Suggests Study on Black Carbon” []. The report states: “As a result of global warming, soils are expected to release more carbon dioxide, the major greenhouse gas, into the atmosphere, which, in turn, creates more warming. Climate models try to incorporate these increases of carbon dioxide from soils as the planet warms, but results vary greatly when realistic estimates of black carbon in soils are included in the predictions, the study found. … black carbon can take 1,000-2,000 years, on average, to convert to carbon dioxide. … the researchers found that carbon dioxide emissions from soils were reduced by about 20 percent over 100 years, as compared with simulations that did not take black carbon's long shelf life into account. The findings are significant because soils are by far the world's largest source of carbon dioxide, producing 10 times more carbon dioxide each year than all the carbon dioxide emissions from human activities combined. Small changes in how carbon emissions from soils are estimated, therefore, can have a large impact.”


The following figure shows the temperature response around the world due to black carbon from research at the University of California, Irvine []. The global pattern matches the global temperature changes shown above more closely than does the modeled results of CO2 influence.




See also for details on the effects of biomass burning and black carbon.


The atmospheric CO2 generally has a low correlation with temperature. The following figure shows the global temperatures and CO2 from 1998 to 2008 (comparing the satellite-measured lower troposphere temperature and the Hadley Climatic research Unit data (used by IPCC). []. While CO2 has steadily increased over the last decade, temperatures have not.




A 2008 study of the satellite-era temperature data (Christy & Douglass: “Limits on CO2 Climate Forcing from Recent Temperature Data of Earth”) []. “The recent atmospheric global temperature anomalies of the Earth have been shown to consist of independent effects in different latitude bands. The tropical latitude band variations are strongly correlated with ENSO effects. …The effects in the northern extratropics are not consistent with CO2 forcing alone  … These conclusions are contrary to the IPCC [2007] statement: “[M]ost of the observed increase in global average temperatures since the mid-20th century is very likely due to the observed increase in anthropogenic greenhouse gas concentrations.”” They found that the underlying trend that may be due to CO2 was 0.07 degrees per decade.


The following two figures are from the above Christy & Douglass study. The first (left) shows the satellite-based temperature anomalies for the Tropics (red), globe (black), northern extratropics (blue) and southern extratropics (green). The second figure (right) shows the correlation between the tropical temperatures and the ENSO3.4 (El Nino SSTs for area 3.4)




A 2010 study [] states: “A new estimate of the feedback between temperature and atmospheric carbon dioxide (CO2) concentration has been derived from a comprehensive comparison of temperature and CO2 records spanning the past millennium. The result, which is based on more than 200,000 individual comparisons, implies that the amplification of current global warming by carbon-cycle feedback will be significantly less than recent work has suggested.




CO2 Atmospheric Residence Time


There are many scientific studies on the atmospheric residence of CO2, with many disagreements (i.e. the science is not settled). Many studies show a residence of 5 to 15 years (although the IPCC claims that it’s 100-200 years).


An example:“Atmospheric CO2 residence time and the carbon cycle : Global warming” []: “An atmospheric CO2 residence time is determined from a carbon cycle which assumes that anthropogenic emissions only marginally disturb the preindustrial equilibrium dynamics of source/atmosphere/sink fluxes. This study explores the plausibility of this concept, which results in much shorter atmospheric residence times, 4-5 years, than the magnitude larger outcomes of the usual global carbon cycle models which are adjusted to fit the assumption that anthropogenic emissions are primarily the cause of the observed rise in atmospheric CO2. The continuum concept is consistent with the record of the seasonal photosynthesis swing of atmospheric CO2 which supports a residence time of about 5 years, as also does the bomb C14 decay history.”


This link: provides a list of published studies showing CO2 residence times as listed below. See that reference for details on this.




The following figure compares maximum atmospheric CO2 residence time from various studies []