Ian Bradford: We have been bombarded with false computer generated climate predictions

Today’s climate models do not agree with reality and so their usefulness is extremely doubtful.  Because the current state- of- the- art general circulation models cannot simulate the trends and variances in global precipitation over the past 84 years from 1940 to 2023, their usefulness should be reconsidered. A paper published by Dr Koutsoyiannis, a hydrologist, statistically assessed the utility of today’s climate models. He documented the models’ capacity to simulate trends and variability in global precipitation since 1940. The results are not encouraging. The best computer models we have cannot accurately simulate what occurs in the real world. The precipitation simulated by the computer models does not agree with reality. When the areal scale is decreased from hemispheric to continental i.e. when Europe is examined, the model performance is poor.

Climate modellers are prominent among IPCC authors. These people are often called scientists, but their work has little in common with traditional science. The scientific method involves forming an hypothesis, testing that hypothesis in the real world, and then confirming, adjusting or abandoning the hypothesis according to what the real world tests reveal.  The problem is there is no duplicate planet Earth on which experiments may be safely conducted. No one knows for example, what will happen if the carbon dioxide in the atmosphere increases from 420 parts per million (ppm), to 600ppm. 

The total amount of carbon dioxide in the atmosphere is only about 0.04%. Barring emissions reductions, by the year 2100 that number could reach 0.06%. All this fuss is based on a hypothesis that says our planet is so unstable a slight increase in one particular trace gas will trigger disaster. 

Since there is no way to actually test this hypothesis, some “scientists” have adopted an alternative approach. They say supercomputers programmed with complex mathematical formulas confirm that a bit more carbon dioxide in the atmosphere will be really bad news.  In the view of computer modellers, these computer simulations are as good as hard evidence. But the world is chaotic and unpredictable and it rarely unfolds in the manner that even the smartest people, aided by graphs, charts, and computers think it will. 

Here’s a statement from Joseph D’Aleo, meteorologist:  Government reports, writers of opinion pieces, and bloggers posting graphs purporting to show rising or record air temperatures or ocean heat are misleading you. This is not actual raw data. It is plots of data that have been adjusted or homogenised (i.e. manipulated by scientists, or it is the output from models based on assumptions, many of them incorrect. U.K. Met. Office researcher, Chris Folland, makes no apology for this.  He says, “The data don’t matter. We are not basing our recommendations (for reductions in carbon dioxide emissions) upon the data. We’re basing them on climate models.”    

In 2017 American climatologist Judith Curry, published the report “ Climate Models for the Layman”, concluding that global climate models (GCM’s) “ are not fit for the  purpose  of justifying political policies to fundamentally alter world social, economic and energy systems for several reasons, one of which is that there is growing evidence that climate models predict too much warming from atmospheric carbon dioxide.” Another is “The climate model simulations for the 21^st century reported by the IPCC do not include key elements of climate variability, and hence are not useful as projections for how the 21^st century climate will eventually evolve.”     

The real tell tale on today’s climate models is that due to the influence of the IPCC, funding for climate scientists has ballooned out into billions of dollars per year, and since there is no money in real climate research, which takes years sometimes to get their piece of the pie now, every climate scientist finds it easier to model some piece of the climate with a computer program, which doesn’t have to produce any real information but pays well per hour. On top of that, if they can get more powerful computers authorised to run their models they can hope for pay increases. What’s really nice is that no matter how far off the models are, they never lose their jobs.     

Predicting climate change hangs its hat on computer climate models. These models have gigantic problems. According to Kevin Trembath, once in charge of modelling at the National Centre for Atmospheric Research, “None of the models correspond even remotely to the observed climate of the Earth.”  The models can’t properly model Earth’s climate, but we are supposed to believe that, if carbon dioxide has a certain effect on the imaginary earths of the many models it will have the same effect on the real earth. We should note that Kevin Trembath was one of the contributors to IPCC’s AR4 report, so what he says is very significant.   

The Wall Street Journal and Powerline report that climate models’ projections of future temperatures have become worse over time.   As new generations of supposedly improved climate models are produced and refined, the accuracy of their temperature simulations decreases.  Each new generation of global circulation models fails to track or correspond to  a greater degree with measured temperature changes and trends than the previous generation. Here are some examples.

GRAPH

The blue bars are model predictions from several countries for the period 1979 to 2014, with the red bar the average of those. The names of the countries are along the bottom row but are difficult to read. The two grey bars are the actual observations.  You can see that the modelling is vastly different from what was observed as far as temperature increase  was concerned. Of concern is that with one or two exceptions, no country agreed with any other country on what the temperature increase would be. 

But the IPCC simply averages up the 29 major climate models to come up with the forecast for warming in the 21^st century, a practice rarely done in operational weather forecasting. Viktoria Eyring from the University of Bremen and 28 co-authors now say there is evidence that giving equal weight to each available model projection is less than the desired standard. The authors show that the aggregate models are making huge errors in three places on earth that are critical to our understanding of climate. One big error is the entire Southern Ocean. The 29 models calculate on average the temperature to be 2.7 Deg F warmer than reality.

But one of the models actually works. The Russian model  INM-CM4 gets things right But it is not used because it shows LESS global warming than the others. Its successor INM-CM5 is so good that it is the only one that diagnoses the PAUSE in warming from 2002 to 2014. That the pause was real, and is obvious in the global surface temperature record that the IPCC relies on most heavily, from the Climate Research Unit at the University of East Anglia. 

Jochem Marotzke director of the Max Planck Institute in Hamburg Says: “ We knew that the surface temperature of the earth has been stagnant for 15 years, whereas the models show progressive warming.”   

Averaging up a large number of models that don’t work well is guaranteed to produce an unreliable forecast. 

 In the early 1990’s most climate modellers developed models projecting a 0.35 degree C rise in temperature. Since 1979, Christy and colleague Dick McNider projected that amount of carbon dioxide being added to the atmosphere should cause the earth to warm on average by about 0.09 degrees C per decade. That’s about one quarter of the level projected by prevailing models used by the IPCC and government agencies such as NASA. They report that: “The warming trend we found suggests that we are having a relatively minor impact on global temperatures. (John Christy, “The tropical skys: falsifying climate alarm, Global Warming Policy Forum  May 23, 2019.)

Priceton physicist Freeman Dyson has harsh critical words for climate scientists and models they rely on. He calls the science of climate modelling a very dangerous game. He adds “When you work with a computer model for years and years, always improving the model, in the end you end up believing it. It is very difficult to remain objective. 

On why we should not trust models Dyson says “because they are wrong, it’s very simple, they are wrong.”  He adds that “models are very bad tools for predicting climate and these scientists live by scaring the public.”   

What about sea surface temperatures?  Observations in recent decades show that changes in sea surface temperatures vary greatly by region. That geographic variation suggest that end of century global warming may be less severe than most climate models suggest. It highlights the importance of regular comparisons between climate models and the real world observations they aspire to reflect. 

Observations show a strong cooling trend in the Eastern pacific and Southern Ocean which goes against what the models predicted. Because the Eastern Pacific is cooling while the Western pacific is warming, it will yield a very different global warming outcome than if the ocean warmed more uniformly. 

David Battisti, a Professor of Atmospheric Sciences at the University of Washington has this to say about clouds: “While all clouds have the potential to reflect the sun’s radiation, the clouds in the Eastern Pacific are lower altitude clouds and reflect more solar radiation back into space than their taller, colder counterparts in the Western Pacific. Less cloud cover means the Eastern Pacific would continue to warm, effectively reducing the absolute temperature difference between each side of the Pacific Ocean.  That would weaken the Walker circulation-the circulation that maintains clouds in the Eastern Pacific.” 

“We found models cannot reproduce observations.” “That should be a big problem because it tells us there will be something wrong with future projections.”     

Based on observed Eastern Pacific cooling, the models are very likely overshooting the end- of- century, global warming estimates. 

Modelers continue tuning climate models until they match a known 20^th century temperature or precipitation record. Yet at that point we will have to ask whether these models are more subjective than objective. If a model shows a decline in Arctic sea ice, for example, and we know that Arctic sea ice has in fact declined, is the model telling us something new or just regurgitating the adjustments. 

Before we put much credence in any climate model, we need to assess its predictions. The following highlights some of the difficulties of current models. 

Vancouver, British Columbia, warmed by a full degree in the first 20 years of the 20^th century, then cooled by 2 degrees over the next 40 years, and then warmed to the end of the century, ending almost where it started. None of the six climate models tested by the IPCC reproduced this pattern. Further, according to Patrick Frank in a 2015 article in Energy and Environment, the projected temperature trends of the models, which all employed the same theories and historical data, were as far apart as 2.5 Deg C.  

The ultimate test for a climate model is the accuracy of its predictions. But the models predicted that there would be much greater warming between 1998 and 2014 than actually happened. If the models were doing a good job their predictions would cluster symmetrically around the actual measured temperatures. This was not the case here.  A mere 2.4% of the predictions undershot actual temperatures  and 97.65 overshot, according to  Cato Institute climatologist Patrick Michaels, former MIT meteorologist Richard Lindzen and Cato Institute climate researcher Chip Knappenburger. Climate models as a group have been “running hot” predicting 2.2 times as much warming as has actually occurred over the period 1998 to 2014. Clearly the models’ forecasts have been highly exaggerated.    

Ian Bradford, a science graduate, is a former teacher, lawyer, farmer and keen sportsman, who is writing a book about the fraud of anthropogenic climate change.