One problem facing GCMs is how to accurately simulate the physics of earth’s radiative energy balance. Of this task, Harries (2000) says “progress is excellent, on-going research is fascinating, but we have still a great deal to understand about the physics of climate.”
Harries says “we must exercise great caution over the true depth of our understanding, and our ability to forecast future climate trends.” As an example, he states that our knowledge of high cirrus clouds is very poor, noting that “we could easily have uncertainties of many tens of Wm-2 in our description of the radiative effect of such clouds, and how these properties may change under climate forcing.” This state of affairs is disconcerting in light of the fact that the radiative effect of a doubling of the air’s CO2 content is in the lower single-digit range of Wm-2, and, to quote Harries, “uncertainties as large as, or larger than, the doubled CO2 forcing could easily exist in our modeling of future climate trends, due to uncertainties in the feedback processes.” Because of the vast complexity of the subject, Harries says “even if [our] understanding were perfect, our ability to describe the system sufficiently well in even the largest computer models is a problem.”
A related problem is illustrated by the work of Zender (1999), who characterized the spectral, vertical, regional and seasonal atmospheric heating caused by the oxygen collision pairs O2 . O2 and O2 . N2, which had earlier been discovered to absorb a small but significant fraction of the globally incident solar radiation. In addition, water vapor demers (a double molecule of H2O) shows strong absorption bands in the near-infrared of the solar spectrum. Zender revealed that these molecular collisions lead to the absorption of about 1 Wm-2 of solar radiation, globally and annually averaged. This discovery, in Zender’s words, “alters the long-standing view that H2O, O3, O2, CO2 and NO2 are the only significant gaseous solar absorbers in earth’s atmosphere,” and he suggests that the phenomenon “should therefore be included in … large-scale atmospheric models used to simulate climate and climate change.”
In another revealing study, Wild (1999) compared the observed amount of solar radiation absorbed in the atmosphere over equatorial Africa with what was predicted by three GCMs and found the model predictions were much too small. Indeed, regional and seasonal model underestimation biases were as high as 30 Wm-2, primarily because the models failed to properly account for spatial and temporal variations in atmospheric aerosol concentrations. In addition, Wild found the models likely underestimated the amount of solar radiation absorbed by water vapor and clouds.
Similar large model underestimations were discovered by Wild and Ohmura (1999), who analyzed a comprehensive observational dataset consisting of solar radiation fluxes measured at 720 sites across the earth’s surface and corresponding top-of-the-atmosphere locations to assess the true amount of solar radiation absorbed within the atmosphere. These results were compared with estimates of solar radiation absorption derived from four GCMs and, again, it was shown that “GCM atmospheres are generally too transparent for solar radiation,” as they produce a rather substantial mean error close to 20 percent below actual observations.
Another solar-related deficiency of GCMs is their failure to properly account for solar-driven variations in earth-atmosphere processes that operate over a range of timescales extending from the 11-year solar cycle to century- and millennial-scale cycles (see Section 4.11, Solar Influence on Climate). Although the absolute solar flux variations associated with these phenomena are rather small, there are a number of “multiplier effects” that may significantly amplify their impacts.
According to Chambers et al. (1999), most of the many nonlinear responses to solar activity variability are inadequately represented in the global climate models used by the IPCC to predict future greenhouse gas-induced global warming, while at the same time other amplifier effects are used to model past glacial/interglacial cycles and even the hypothesized CO2-induced warming of the future, where CO2 is not the major cause of the predicted temperature increase but rather an initial perturber of the climate system that according to the IPCC sets other more powerful forces in motion that produce the bulk of the ultimate warming. There appears to be a double standard within the climate modeling community that may best be described as an inherent reluctance to deal even-handedly with different aspects of climate change. When multiplier effects suit their purposes, they use them; but when they don’t suit their purposes, they don’t use them.
Ghan et al. (2001) warn that “present-day radiative forcing by anthropogenic greenhouse gases is estimated to be 2.1 to 2.8 Wm-2; the direct forcing by anthropogenic aerosols is estimated to be -0.3 to -1.5 Wm-2, while the indirect forcing by anthropogenic aerosols is estimated to be 0 to -1.5 Wm-2,” so that “estimates of the total global mean present-day anthropogenic forcing range from 3 Wm-2 to ‑1 Wm‑2,” which implies a climate change somewhere between a modest warming and a slight cooling. They conclude that “the great uncertainty in the radiative forcing must be reduced if the observed climate record is to be reconciled with model predictions and if estimates of future climate change are to be useful in formulating emission policies.”
Pursuit of this goal, Ghan et al. say, requires achieving “profound reductions in the uncertainties of direct and indirect forcing by anthropogenic aerosols,” which is what they set out to do in their analysis of the situation, which consisted of “a combination of process studies designed to improve understanding of the key processes involved in the forcing, closure experiments designed to evaluate that understanding, and integrated models that treat all of the necessary processes together and estimate the forcing.” At the conclusion of this laborious set of operations, Ghan et al. came up with some numbers that considerably reduce the range of uncertainty in the “total global mean present-day anthropogenic forcing,” but that still implied a set of climate changes stretching from a small cooling to a modest warming. They also provided a long list of other things that must be done in order to obtain a more definitive result, after which they acknowledged that even this list “is hardly complete.” In fact, they conclude, “one could easily add the usual list of uncertainties in the representation of clouds, etc.” Consequently, the bottom line, in their words, is that “much remains to be done before the estimates are reliable enough to base energy policy decisions upon.”
Also studying the aerosol-induced radiative forcing of climate were Vogelmann et al. (2003), who report that “mineral aerosols have complex, highly varied optical properties that, for equal loadings, can cause differences in the surface IR flux between 7 and 25 Wm-2 (Sokolik et al., 1998).” They say “only a few large-scale climate models currently consider aerosol IR effects (e.g., Tegen et al., 1996; Jacobson, 2001) despite their potentially large forcing.” Because of these facts, and in an attempt to persuade climate modelers to rectify the situation, Vogelmann et al. used high-resolution spectra to calculate the surface IR radiative forcing created by aerosols encountered in the outflow of air from northeastern Asia, based on measurements made by the Marine-Atmospheric Emitted Radiance Interferometer aboard the NOAA Ship Ronald H. Brown during the Aerosol Characterization Experiment-Asia. In doing so, they determined, in their words, that “daytime surface IR forcings are often a few Wm-2 and can reach almost 10 Wm-2 for large aerosol loadings,” which values they say “are comparable to or larger than the 1 to 2 Wm-2 change in the globally averaged surface IR forcing caused by greenhouse gas increases since pre-industrial times.” In a massive understatement of fact, the researchers concluded that their results “highlight the importance of aerosol IR forcing which should be included in climate model simulations.” If a forcing of this magnitude is not included in current state-of-the-art climate models, what other major forcings are they ignoring?
Two papers published one year earlier and appearing in the same issue of Science (Chen et al., 2002; Wielicki et al., 2002) revealed what Hartmann (2002) called a pair of “tropical surprises.” The first of the seminal discoveries was the common finding of both groups of researchers that the amount of thermal radiation emitted to space at the top of the tropical atmosphere increased by about 4 Wm-2 between the 1980s and the 1990s. The second was that the amount of reflected sunlight decreased by 1 to 2 Wm-2 over the same period, with the net result that more total radiant energy exited the tropics in the latter decade. In addition, the measured thermal radiative energy loss at the top of the tropical atmosphere was of the same magnitude as the thermal radiative energy gain that is generally predicted to result from an instantaneous doubling of the air’s CO2 content. Yet as Hartmann notes, “only very small changes in average tropical surface temperature were observed during this time.” How did this occur?
The change in solar radiation reception was driven by reductions in cloud cover, which allowed more solar radiation to reach the surface of the earth’s tropical region and warm it. These changes were produced by what Chen et al. determined to be “a decadal-time-scale strengthening of the tropical Hadley and Walker circulations.” Another helping-hand was likely provided by the past quarter-century’s slowdown in the meridional overturning circulation of the upper 100 to 400 meters of the tropical Pacific Ocean (McPhaden and Zhang, 2002), which circulation slowdown also promotes tropical sea surface warming by reducing the rate-of-supply of relatively colder water to the region of equatorial upwelling.
These observations provide several new phenomena for the models to replicate as a test of their ability to properly represent the real world. In the words of McPhaden and Zhang, the time-varying meridional overturning circulation of the upper Pacific Ocean provides “an important dynamical constraint for model studies that attempt to simulate recent observed decadal changes in the Pacific.”
In an eye-opening application of this principle, Wielicki et al. (2002) tested the ability of four state-of-the-art climate models and one weather assimilation model to reproduce the observed decadal changes in top-of-the-atmosphere thermal and solar radiative energy fluxes that occurred over the past two decades. No significant decadal variability was exhibited by any of the models; and they all failed to reproduce even the cyclical seasonal change in tropical albedo. The administrators of the test kindly concluded that “the missing variability in the models highlights the critical need to improve cloud modeling in the tropics so that prediction of tropical climate on interannual and decadal time scales can be improved.” Hartmann was considerably more candid in his scoring of the test, saying flatly that the results indicated “the models are deficient.” Expanding on this assessment, he noted that “if the energy budget can vary substantially in the absence of obvious forcing,” as it did over the past two decades, “then the climate of earth has modes of variability that are not yet fully understood and cannot yet be accurately represented in climate models.”
Also concentrating on the tropics, Bellon et al. (2003) note that “observed tropical sea-surface temperatures (SSTs) exhibit a maximum around 30°C,” and that “this maximum appears to be robust on various timescales, from intraseasonal to millennial.” Hence, they say, “identifying the stabilizing feedback(s) that help(s) maintain this threshold is essential in order to understand how the tropical climate reacts to an external perturbation,” which knowledge is needed for understanding how the global climate reacts to perturbations such as those produced by solar variability and the ongoing rise in the air’s CO2 content. This contention is further substantiated by the study of Pierrehumbert (1995), which “clearly demonstrates,” in the words of Bellon et al., “that the tropical climate is not determined locally, but globally.” Also, they note that Pierrehumbert’s work demonstrates that interactions between moist and dry regions are an essential part of tropical climate stability, which points to the “adaptive infrared iris” concept of Lindzen et al. (2001), which is reported in Section 1.2.
Noting that previous box models of tropical climate have shown it to be rather sensitive to the relative areas of moist and dry regions of the tropics, Bellon et al. analyzed various feedbacks associated with this sensitivity in a four-box model of the tropical climate “to show how they modulate the response of the tropical temperature to a radiative perturbation.” In addition, they investigated the influence of the model’s surface-wind parameterization in an attempt to shed further light on the nature of the underlying feedbacks that help define the global climate system that is responsible for the tropical climate observations of constrained maximum sea surface temperatures (SSTs).
Bellon et al.’s work, as they describe it, “suggests the presence of an important and as-yet-unexplored feedback in earth’s tropical climate, that could contribute to maintain the ‘lid’ on tropical SSTs.” They say the demonstrated “dependence of the surface wind on the large-scale circulation has an important effect on the sensitivity of the tropical system,” specifically stating that “this dependence reduces significantly the SST sensitivity to radiative perturbations by enhancing the evaporation feedback,” which injects more heat into the atmosphere and allows the atmospheric circulation to export more energy to the subtropical free troposphere, where it can be radiated to space by water vapor.
This literature review makes clear that the case is not closed on either the source or the significance of the maximum “allowable” SSTs of tropical regions. Neither, consequently, is the case closed on the degree to which the planet may warm in response to continued increases in the atmospheric concentrations of carbon dioxide and other greenhouse gases, in stark contrast to what is suggested by the climate models promoted by the IPCC.
In conclusion, there are a number of major inadequacies in the ways the earth’s radiative energy balance is treated in contemporary general circulation models of the atmosphere, as well as numerous other telling inadequacies stemming from the non-treatment of pertinent phenomena that are nowhere to be found in the models. IPCC-inspired predictions of catastrophic climatic changes due to continued anthropogenic CO2 emissions are beyond what can be soundly supported by the current state of the climate modeling enterprise.
Eisenman et al. (2007) used two standard thermodynamic models of sea ice to calculate equilibrium Arctic ice thickness based on simulated Arctic cloud cover derived from 16 different general circulation models (GCMs) that were evaluated for the IPCC’s Fourth Assessment Report. Their results indicated there was a 40 Wm-2 spread among the 16 models in terms of their calculated downward long-wave radiation, for which both sea ice models calculated an equilibrium ice thickness ranging from 1.0 to more than 10.0 meters. However, they note that the mean 1980–1999 Arctic sea ice thickness simulated by the 16 GCMs ranged from only 1.0 to 3.9 meters, a far smaller inter-model spread. Hence, they say they were “forced to ask how the GCM simulations produce such similar present-day ice conditions in spite of the differences in simulated downward longwave radiative fluxes.”
Answering their own question, the three researchers observe that “a frequently used approach” to resolving this problem “is to tune the parameters associated with the ice surface albedo” to get a more realistic answer. “In other words,” they continue, “errors in parameter values are being introduced to the GCM sea ice components to compensate simulation errors in the atmospheric components.”
In consequence of the above findings, the three researchers conclude, “the thinning of Arctic sea ice over the past half-century can be explained by minuscule changes of the radiative forcing that cannot be detected by current observing systems and require only exceedingly small adjustments of the model-generated radiation fields” and, therefore, “the results of current GCMs cannot be relied upon at face value for credible predictions of future Arctic sea ice.”
In another pertinent study, Andronova et al. (2009) “used satellite-based broadband radiation observations to construct a continuous 1985–2005 record of the radiative budget components at the top of the atmosphere (TOA) for the tropical region (20°S–20°N)” and then (1) “derived the most conservative estimate of their trends” and (2) “compared the interannual variability of the net radiative fluxes at the top of the tropical atmosphere with model simulations from the Intergovernmental Panel on Climate Change fourth assessment report (AR4) archive available up to 2000.”
The three researchers found “the tropical system became both less reflective and more absorbing at the TOA” and, “combined with a reduction in total cloudiness (Norris, 2007), this would mean the tropical atmosphere had recently become more transparent to incoming solar radiation, which would allow more shortwave energy to reach earth’s surface.” Second, they found “none of the models simulates the overall ‘net radiative heating’ signature of the earth’s radiative budget over the time period from 1985–2000.”
With respect to the first of their findings and the associated finding of Norris (2007), Andronova et al. state these observations “are consistent with the observed near-surface temperature increase in recent years,” which provides an independent validation of the TOA radiation measurements. With respect to their second finding, however, the failure of all of the AR4 climate models to adequately simulate the TOA radiation measurements discredits the models. The combination of these two conclusions suggests the historical rise in the air’s CO2 content has likely played a next-to-negligible role in the post-Little Ice Age warming of the world.
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