It’s not actually all that difficult

Climate models have accurately predicted global heating for the past 50 years, a study by climate scientists from the University of California, Berkeley, the Massachusetts Institute of Technology and NASA has found.

It’s building a model that tells us the future, not the past, which is the difficult thing.

23 thoughts on “It’s not actually all that difficult”

  1. A pack of ecofreak lies. The greenscum couldn’t predict that opening their flies would cause their dicks to drop out.

  2. Anthony Watts regularly puts up a graph of various mainstream models versus reality. The only one that comes close is Russian, all the rest rocketed up while we enjoyed an eighteen year hiatus.

  3. Climate models from the 70s would include the one’s predicted the coming to a close of the current interglacial. So some cherry picking?

  4. It’s building a model that tells us the future, not the past, which is the difficult thing.

    Perhaps if you placed “For the past fifty years” at the beginning, you’d understand it better?


    Ten of the 17 the models the team examined came close to the temperatures that actually occurred, Dr Hausfather said. However the input scenarios in nearly half of those examined was significantly different from the real-life greenhouse gas emissions that occurred.

    suggests that they got somewhere close to the right answer for wholly the wrong reasons which is as good as saying the forecasts are bunk.

  5. Creating models to forecast changes in the climate is so difficult because it relies on two main assumption of what will happen in the future – one is the physics of the atmosphere and how it reacts to heat-trapping gases, the other is the amount of greenhouse gases emitted.

    Indeed, hence: If CO2 emissions are A, temperature should be X; if B, then Y; if C, then Z; etc. After all, CO2 is supposed to be a driver…

    “We did not focus on how well their crystal ball predicted future emissions of greenhouse gases, because that is a question for economists and energy modelers, not climate scientists,” Dr Hausfather said. “It is impossible to know exactly what human emissions will be in the future. Physics we can understand, it is a deterministic system; future emissions depend on human systems, which are not necessarily deterministic.”

    So Dr Hausfather and his colleagues … also looked at how well the models did on just the pure science, taking out the emissions factor.

    TMB has it – as it reads, this is utter bollocks!

    including NASA climate scientist Gavin Schmidt

    Ah, the penny drops……

  6. so what’s the measurable market effects of this over 50 years? Beachfront property falling? Insurance rates in Worcester? Wine regions moving away from where it’s too hot?

    I’d like to see a measure that should be occurring outside of measuring temperature. A secondary effect just to validate it all.

  7. Didn’t someone examine the models and find they used a lot of parameterisation. That is they use numbers for the effect of volcanoes, aerosols, clouds, ocean cycles etc. etc.

    The problem was that although the models ‘predicted’ past temperatures fairly accurately, they got there by very different means. Where Model A used value X to simulate say aerosol effects, Model B used Y, (and Y was very different to X). All the models used different values for the various parameters and were tuned to give the ‘right’ answer.

    The answer they produce is the ‘average global temperature’ but if you break down this number and look at say the Northern Hemisphere temp, each model gives a very different value. Similarly, some have the Southern Ocean much hotter than it could possibly be while the North Atlantic is greatly cooled.

    So although they give an ‘accurate’ value for the global temp, their local temps are mostly complete rubbish which clearly shows that the models are also complete rubbish.

  8. “It’s building a model that tells us the future, not the past, which is the difficult thing.”

    Whilst that’s true – even if Neils Bohr said it better a hundred years ago – the article is not true on its face – the models can’t even hindcast properly. None of them predicted the pause.

  9. “Ten of the 17 the models the team examined came close to the temperatures that actually occurred, Dr Hausfather said. However the input scenarios in nearly half of those examined was significantly different from the real-life greenhouse gas emissions that occurred. ”

    Note the latter bit… A model is only accurate if the input values for your variables are real-world values or projected values based on real-world values, and then proceeds to produce answers that actually match ( within %) what is actually happening.

    If the input is “significally different” , yet the model comes up with the “right” answer, it just tells you the model is bollocks and you just got lucky with the answer.

  10. “Physics we can understand, it is a deterministic system”: ‘can’ perhaps, ‘do’ certainly not – it’s just too complicated.

    When I first looked into this decades ago I realised that the climate modellers were behaving in a way that I might expect of people who had little or no experience of modelling physico-chemical systems with just a few variables and parameters – and who had experimental observations against which their models could be tested. Because if they had had that experience they would have been intellectually humbler.

    Also they came across as none too bright, So much research money now comes in for “Climate Science” that it has doubtless attracted brighter people, especially those of a sociopathic inclination.

  11. I saw it in the college boys of the 1980s reliance on brute force computing. As computers got bigger, software design got crappier. Climate modeling (sic) is the ultimate example.

    We simply don’t know enough to model climate. There are known unknowns, and probably unknown unknowns.

    Hind casting is all parameterization. The models fail hindcasting. Tweaks are made to adjust the results. With successive approximation, they eventually get the parameterization to work somewhat. These adjustments are made because they work, not because they have been intellectually derived. An example could be, “Multiply everything by 1.5, and let’s see what happens.”

    The idea that these tweaks will make their future predictions accurate is childish.

  12. I recall reading somewhere that Florida has an average elevation of 30 metres and the highest point is only 100 metres and yet there don’t seem to be constant US concerns and stories about Florida disappearing under the rising sea levels, however there’s plenty of poor countries looking for ‘aid’ that seem quite happy to bemoan their fate and blame the west for it

  13. We now know enough to be able to say with high confidence that (a) the Science is Not Settled, and (b) claims that we have only 9, 10, 12 years to save the planet are flat-out erroneous. But the Beautiful People who fly their private jets to Davos are not interested in what we have learned.

    Germany builds subsidized bird-whackers while shutting down their CO2-free nuclear power plants — and then builds dirty brown coal CO2-producing power plants to keep the lights on when the wind is not blowing. This is apparently what “environmentally conscious” means in German. Meanwhile, China and Russia are charging ahead building nuclear power plants — most likely because they want to reduce pollution and be ready for the time when resource exhaustion pushes up the price of fossil fuel.

    Europe’s future in a few generations will be as a quaint backwards vacation destination for rich Chinese and Russian tourists. And the climate will not be much different then than now.

  14. I don’t think Russia will be rich in the future. Take gas and oil out and they’ve got nothing. It’s a Potemkin economy.

    They’re not even getting richer now, let alone into the future.

  15. Worth watching, especially from @5m50s

    Viscount Christopher Monckton Speech – Climate Change: Debunking the Myths – 40min

    Monckton: Dear IPCC et al, what is optimum global mean temperature?

    IPCC: Err, hmm, dunno, but change is bad

  16. Physics we can understand, it is a deterministic system
    Any non-linear system is liable to chaotic (in the technical sense) outcomes. That’s why weather forecasts are less than perfect. Even the movement of the planets within the solar system is chaotic (when viewed over periods of many millions of years), as was proved by Poincaré over a century ago,

  17. Chris hit the nail on the head.
    Even in a deterministic system the way all the variables interact can produce chaotic outcomes. That is a small change in input can produce a large and unpredictable effect on outcomes.
    This is why with even the fastest computers on the planet, producing accurate weather forecasts can be extremely difficult. In a relatively easily modelled climate like California you can be quite accurate, but the weather round Britain can and is very turbulent and hence hard to model accurately.
    We all know for a fact that most of these climate models have been massaged by hand to give the results required, hence we know that the science isn’t understood. The models are bunk, and the exhortations about the climate politically driven bullshit.
    That people are trying to fundamentally change the basis of our economy and our way of life on basis of this junk science is criminal. Its just sad that so many are taken in by this rubbish.

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