DQF, FCT, and CIQA, Universidade do Algarve, Campus de Gambelas, 8005-139
The Intergovernmental Panel on Climate Change (IPCC) in its Fourth Assessment Report uses various suitably parameterized finite-difference computer models, concluding that currently occurring climate change is caused by anthropogenic carbon dioxide (CO2), and therefore advocating measures to drastically reduce anthropogenic emissions of CO2, for fear that these will cause a climatic catastrophe 1. We demonstrate that essential physics is missing in the aforesaid models, which therefore lack any credibility as regards climate predictions. We also show that the climate system is entirely deterministic, and thus may be comprehensively understood and predicted using models that include complete physics. These findings prove that the Anthropogenic Global Warming hypothesis is not a valid theory, its models deficient in physics essential for long-term weather and climate predictions. This in turn renders unnecessary any measures aimed at reducing anthropogenic emissions of CO2, for complete lack of scientific evidence that such emissions may be causing significant climate change, and allows humanity to avoid economic and social costs of such measures. Moreover, such measures are counter productive in light of the beginning global cooling, much more dangerous than warming, due to inevitable losses in agricultural productivity, and which we should rather try to slow down than accelerate 2,3.
The evidence of the fatally incomplete physics of the IPCC climate models is provided by the 25 years of pioneering research and development experience of Prof. P. Corbyn and co-workers, who are consistently producing accurate long-range forecasts of the extreme weather events, mostly for UK and Ireland, based on their Solar Lunar Amplification Magnetic (SLAM) theory 2. This approach correlates external factors (EFs), such as solar activity and solar magnetic field conditions and exact location of the Moon, with past extreme weather events, and then looks for the same set of EFs to reproduce in the near future, and thus predicts future extreme weather events up to 12 months in advance, indicating date, location and type of event, with ca. 90% success rates. Probability of such accurate predictions occurring by chance is zero, as demonstrated by the well known inability of the traditional climate models used by meteorologists to predict weather for more than 10 days in advance – one can confirm this by searching internet for weather forecasts – and by their generally recognized inability to produce long-range forecasts, traditionally attributed to stochastic nature of the climate system. Indeed, as we will shortly see, popular wisdom should be better in long-range forecasts than traditional meteorology: popular wisdom correctly assumes the deterministic approach and states that certain weather events are bound to produce other well-defined weather events. The unquestionably outstanding long-range predictive success of the SLAM theory, vs consistent failure of traditional meteorology, thus provides us with three important pieces of information:
- the terrestrial climate system is completely deterministic, its current state determined by the acting EFs and its previous state;
- physical phenomena essential for weather and climate prediction are missing from both traditional meteorological models and IPCC climate models;
- the missing physics is essential for weather and climate, as traditional weather models drift away from the real terrestrial climate system already on the time scale of 1-2 weeks.
Let us consider how the EFs, acting by physical mechanisms unknown to both traditional meteorologists and IPCC climate modelers, affect their respective models. Traditionally, the inability of the models to predict weather for more than about 2 weeks in advance is attributed to the stochastic nature of the climate system, whereby any small deviations from the imperfectly known initial state of the climate system develop exponentially in time in the models, obliterating any causality and predictive capacity of these models within a relatively short time span. However, being aware of the physics lacking in these models, and of the deterministic nature of the climate system, we conclude that the stochastic nature of the traditional climate models necessarily results from the EFs being variable in time – indeed, the loss of predictability within a couple of weeks implies that the EFs in the Sun-Earth-Moon system do change significantly within such a time period – the most evident reason for such rapid change being the Moon orbiting the Earth, with the period of ca. 4 weeks. Turning now to the IPCC climate models, we note that these use incomplete (and therefore incorrect) physics, similar to that of weather models, with added greenhouse effects, solar constant variations with solar activity changes, etc. Although these models were tuned to reproduce the temperature history of the 20th century, by way of adjusting several parameters that are poorly defined by the available experimental data, and succeed in attributing most of the observed warming to growth in atmospheric CO2 concentrations, they consistently fail to reproduce any of the other measurable properties of the climate system. With the missing physics in mind, we should not be surprised, for example, by the intuitively absurd and experimentally unconfirmed results of the IPCC models as regards changes in the outgoing flux of infrared radiation upon global warming: indeed, the models consistently predict that the Earth will emit less infrared radiation if warmed, whereas the experimental results confirm that it does emit more 4, exactly as intuitively expected taking into account the Stefan-Boltzmann law 5. Indeed, it is this very property of the IPCC climate models that results in predictions of a climate catastrophe, due to positive "climate feedbacks" introduced into models in an attempt to explain warming by growing atmospheric CO2, other possible causes either unknown or ignored. We see that the failure to include complete physics has produced models that have nothing in common with the real climate system of our home planet – they do explain the past warming by largely attributing it to atmospheric CO2, but they fail to reproduce other properties of the climate system, and therefore have no predictive capacity. They in effect model some imaginary non-existent climate system, with properties essentially different from those of our real climate system, and thus probably even disobeying fundamental principles of physics that every natural system does obey. Obviously, it may be possible to approximately reproduce the natural evolution of any one parameter in such deficient models, by suitable parameterization of effects difficult or impossible to properly include in the simulations, such as cloud formation phenomena, as in fact happens in the IPCC climate models. On the other hand, it is impossible to comprehensively reproduce the behavior of the climate system in its entirety without knowing complete physics acting in it, as shown by utter failure of the traditional models in long-range predictions – which necessarily leads to a still bigger failure in the very-long-range predictions, that is, predictions of the climate change, at the very least influenced by (same as the weather is – see the discussion above) and/or caused by changes in EFs. On the other hand, the SLAM theory attributes almost the entire warming of the 20th century to the EFs, leaving very little margin for any affect of the changes of concentrations of atmospheric CO2 and/or other greenhouse gases 2.
We therefore conclude that failure to include complete physics may and does produce arbitrarily large deviations in the results of the IPCC climate models that describe the future of the climate, as compared to the real climate system. We describe as arbitrarily large, for example, the predicted exponential growth of temperature in the climate scenarios that presume no reduction in CO2 emissions. We shall illustrate this statement by a simple example from daily experience. Imagine we are observing a car on a motorway and want to predict its location in function of time. Knowing some "physics" (cars can't reverse on a motorway etc), we will obtain a fairly accurate and highly probable prediction, up to the moment when the car arrives to the nearest junction, the point where the behavior of our system becomes "stochastic" – at the junction the driver may either get off the motorway, or stay on it (missing/unknown "physics" in our model). However, if we had the complete "physics" (knowing, for example, that the car belongs to Mr. A, who is going to visit his girlfriend, Ms. B, as he usually does each Friday), we would produce a much better forecast of the car location in time, with the stochastic contribution disappearing completely, and would also produce a much better long-range forecast, easily and correctly predicting that Mr. A's car will stay on Ms. B's driveway till Sunday evening, as it usually does. Naturally our predictions would be completely wrong (arbitrarily large difference) if we were erroneously informed that Mr. A goes to meet his friends for a beer each Friday (wrong/incomplete "physics" in our model). Similarly, EFs unknown to the modelers may, as logically demonstrated, and will, as demonstrated on the specific example of the "climate feedbacks", produce arbitrarily large deviations in the models as compared to the real climate system. The IPCC climate models, therefore, have zero predictive ability, due to the failure to include complete physics, and thus must be expressly disregarded when discussing the future of the terrestrial climate. Indeed, not knowing what the EFs are and how and to what extent they affect the weather and the climate, both traditional meteorologists and IPCC modelers are unable to produce models that faithfully reproduce the behavior of the real terrestrial climate system. The consequence of this inability for the short-term predictions of the meteorological models is that their predictive ability is lost as soon as the EFs change significantly, which does happen within a couple of weeks. On the other hand, the predictive ability of the IPCC models is absent in any time interval they consider, as the EFs unknown to and unaccounted for by the modelers, along with the incorrectly parameterized known physics (as otherwise the models fail to produce the CO2 warming effects expected by the modelers) will make any prediction of such incomplete and incorrect models drift away from the state of the real climate system, to an arbitrary extent, already on the time scales much shorter than those required for climate predictions. The incorrect parameterization mentioned follows, for example, from the fact that the CO2 global warming effect deduced from the experimental data is about 1 order of magnitude lower than that following from the IPCC climate models 4.
We conclude that the Anthropogenic Global Warming hypothesis, embodied in the IPCC climate models, is not a valid theory, due to irreparable fundamental flaws in the models, namely, their failure to include complete physics. Therefore, we find no scientific justification for reducing anthropogenic emissions of CO2. On the contrary, these emissions should be kept growing, in the (probably largely vain) hope to mitigate the global cooling and the eventual new Little Ice Age, already in progress and predicted to be in full swing by the middle of this century, with the distinct solar activity patterns leading to such conclusions documented and correctly interpreted by several research groups 2,3.
1. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, 2007, Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M. Tignor and H.L. Miller (eds.), Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.
3. Kh. I. Abdusamatov, Optimal Prediction of the Peak of the Next 11-Year Activity Cycle and of the Peaks of Several Succeeding Cycles on the Basis of Long-Term Variations in the Solar Radius or Solar Constant, Kinematics and Physics of Celestial Bodies, Vol. 23, No. 3, 2007, pp. 97–100.
4. R. Lindzen, Y.-S. Choi, On the determination of climate feedbacks from ERBE data, Geophys. Res. Lett. 36, 2009, L16705, 6 pp. doi:10.1029/2009GL039628.
This paper was submitted to Nature, and rejected with the following verdict:
9th September 2010 Dear Professor Khmelinskii Thank you for submitting your manuscript entitled "Climate Change, Climate Models and Climate Predictions: Riddles Solved", for consideration. I regret that we are unable to publish it in Nature. As you may know, we decline a substantial proportion of manuscripts without sending them to referees, so that they may be sent elsewhere without delay. Decisions of this kind are made by the editorial staff when it appears that, even if certified as being technically correct during peer review, there would not be a strong case for publication in Nature. These editorial judgements are based on such considerations as the degree of advance provided, the breadth of potential interest to researchers and timeliness. In this case, we do not feel that your paper has matched our criteria for further consideration. More specifically, while we have no doubt that your findings will prove stimulating to fellow specialists, I regret that we are unable to conclude that your paper provides the sort of firm conceptual advance in our understanding of climate - or the underlying factors influencing climate change and/or variation - that would justify publication in Nature. We therefore feel that the paper would find a more suitable outlet in another journal. I am sorry that we cannot respond more positively on this occasion. Yours sincerely Dr Michael White Senior Editor Nature San Francisco