The science is settled, except when they need more money
Australia’s leading climate modeler wants a big new Climate Agency, and to make the case he admits the current models really can’t predict if rivers will rise or fall, if Antarctica will get bigger or smaller, if sea levels will rise much, or if El Ninos or La Nina will be more common or if the floods of Lismore will occur more often.
To give us some idea of how bad the current models are, he’s recommending we shift from models with 100 kilometer blocks to high resolution models with 1km cells. These new models will be at least 10,000 times bigger than current ones, and if they increase the vertical slices, they could easily be one hundred thousand or even a million times bigger.
And if they get this super model, they’ll need 10,000 to one million times the energy. Now that we’ve wrecked the grid, good luck running those monster data centers off sunlight and breezes.
Full credit to Tony Thomas for digging through pages of turgid text and webinars to uncover the truth.
Andy Pitman, November 2024
Oh Boy it’s an eye-popping list.
In the past, Pitman has admitted climate change doesn’t necessarily cause more droughts. He’s also said he wouldn’t bet his superannuation (pension fund) on the climate models. This time Pitman admits the models are low resolution, have a lot of “critical gaps”, don’t resolve the oceans or clouds well, and that using the best CMIP6 models (the same ones the expert UN has beaten us over the head with) may risk “fundamentally wrong projections of future climate and its variability.”
Shouldn’t every Australian know this? I mean we’re spending half a trillion dollars to solve “climate change” but the models might be fundamentally wrong? Doesn’t that matter. The seas might not swamp us, the rivers might keep flowing. Antarctica might not melt?
Where was Andy Pitman when Australia was wrecking its grid, destroying jobs and our lifestyles? Where were any of our climate academics when leaders of our political parties were telling us that every drought, fire and storm was caused by climate change and would only get worse?
The Ivory Tower elitists sat silently by when the government forces bricklayers, farmers and children to solve a climate problem that might be just a modeling error?
And now they want more money — and I would say we desperately need models that work, but what’s the point, if we can’t trust the modelers to be absolutely, scrupulously honest with us?
Climate Science You Can Believe
By Tony Thomas, Quadrant
Pitman even concedes that current climate models can’t predict whether natural disasters will become more or less common in the warming era. Remember his words when you next hear the ABC or Climate Council claiming that such-and-such storms and floods are “climate-fuelled”.
Using current CMIP models, or indeed the regional models that rely on them, therefore risks fundamentally wrong projections of future climate and its variability. — P17 of “The Decadal Plan“
Now they tell us? Modelers don’t know if we’ll get more wind droughts or cloudy days?
Right after we built 12,000 megawatts of weather dependent generators, we find out that the modelers have no idea whether we will get more long spells of cloudy windless days which cripple our grid. This new vulnerability is buried under the label “High impact weather events”. As if windless nights belong in the same category as storms and floods.
It’s hidden in one of the Five Key Questions of National Significance:
5. Where will changes in high impact weather events support and/or undermine net zero ambition and where can associated risks be managed effectively?
Like the rest of the document the language is obtuse, convoluted, and speaks with a forked tongue. They don’t want to come out and just say Australia badly needs models a million times bigger so we can predict the climate.
Tony Thomas sums it up:
He [Pitman et al] also admits that he and fellow climate alarmists have no idea:
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- when and where so-called “tipping points” might arise (wow, so honest!)
- whether climate change will increase or decrease the Murray Darling water flows
- whether an increase in CO2 will cause more or less rain for a given location
- how climate change will impact cities and urban landscapes (Andy, stop upsetting the Melbourne and Sydney city councils’ climate crusaders)
- how wind droughts and heavy clouding might undermine renewables and net-zero targeting (via week-long blackouts).
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In a repudiation of the “settled science” notion the climate crowd has pushed for 25 years, Pitman now acknowledges that despite decades of study, the catastrophists still have no idea if Australia will see more El Nino, rather than La Nina, climate events, or even whether more vegetation will reduce or increase greenhouse emissions (so much for tree plantings offsetting emissions). “These are not easily solvable but offer profoundly different futures for Australia,” he admits (p13). Odd that we are to invest trillions in net zero when we have no idea what’s what.
We need models thousands of times better!
Pitman lays out many shortcomings of current “expert” climate models because he’d really like a much finer resolution models of just 1km2.
Ocean processes operate across many scales, and eddies in the Southern Ocean transfer considerable heat and nutrients14. These eddies are also crucial to the uptake, transport and storage of carbon15. Operating at scales of order 10 km, they are too fine to be resolved in ocean models used for climate projections. This means the role that oceans play in influencing climate are poorly resolved. – p17
As a result of their poor resolution, current climate models do not faithfully represent critical weather systems, and it is the amplification of extremes by weather system processes that cause the extreme events and consequential disasters we observe. For example, the Lismore (NSW) floods in 2022 were associated with multiple weather processes, initiated over the Southern Ocean and interacting with synoptic-scale processes and moist tropical air that led to a sequence of extreme weather events and catastrophic flooding. Global climate models cannot resolve these processes, and therefore cannot tell us if such events will become more common in the future. As the weather that produces extreme events is connected globally, downscaling using high-resolution regional climate models cannot overcome the limitations introduced in the global models, as downscaling relies on the global models for information at its boundaries.-p17
These transcripts come from Andy Pitmans speech in the launch webinar
The speech and documents make tough reading. You get the feeling they just didn’t want to tell us straight how bad the models are. I wanted to capture his exact words, for the record.
All those environmental sinks might becomes sources (so much for carbon farming, eh?) Shame about that business you set up…
7:30 [Andy Pitman] Some of these questions, you might think we have answers to….
For example, many people would recognize both terrestrial and marine as providing a critical ecosystem service, it takes up human emissions of CO2, and provides enormous support for Australians Net Zero ambitions … but there’s a little problem with this, we don’t actually know to what degree our terrestrial and marine systems will continue to support our Net Zero ambitions and positive environmental outcomes. They may turn into sources of CO2 and methane, in ways that really undermine our Net Zero ambitions.
We will definitely get more water or less water, more river, or less river, more plants, or less...
9:00 In addition Australia is demonstrably at risk of abrupt changes in weather and climate. Many of you would be familiar with tipping points… It matters a great deal if we could say things about when and where these things might be realized. At the moment we really can’t.
9:30 Water is obviously fundamental to the most arid inhabited continent on Earth. But we don’t actually know whether Climate Change will increase or decrease flows of water through systems like the Murray Darling. We don’t yet know whether changes in rainfall will be helped or hindered by the way ecosystems response under higher elevated CO2 concentration. Whether the higher water use efficiency of vegetation will help the flow of water through the Murray Darling or the vegetation will suppress the flow of water in the Murray Darling….
No we don’t know what will happen to the cities:
Urban Areas, it’ It might surprise a lot of you to know that the climate modeling systems we use internationally do not represent our urban landscapes.
From the PDF Launch document
Page 13: Plants, rain, El nino, who knows?
Some major challenges have been explored for decades — whether we will see a more El Nino or La Nina state in the future, or whether vegetation will help or hinder net zero ambition.
These are not easily solvable…
Page 17 We can’t predict extreme events, and they may not be getting worse, we don’t know:
The Lismore (NSW) Floods in 2022 were associated with multiple weather process, initiated over the Southern Ocean and interacting with synoptic scale processes and moist tropical air that led to a sequence of extreme weather events and catastrophic flooding. Global climate models cannot resolve these processes and therefore cannot tell us if such events will become more common in the future.
Further there is evidence the high-resolution coupled models simulate fundamentally different historical trends in tropical and Southern Ocean sea surface temperatures, reproducing recent observed changews which courses models cannot. They also exhibit greater low-frequency variability in midlatitude regions. Compare with Coupled Model Intercomparison Project (CMIP)-class models. Using current CMIP models, or indeed the regional models that rely on them, therefore risks fundamentally wrong projections of future climate and its variability.
Page 22: The current models are low resolution and can’t do sea ice, clouds, storms, ice sheets, plants, cities and farms.
Projections on timescales of decades to centuries at low spatial detail using Earth System models. The low spatial detail is balanced by large numbers of simulations. The lower computational cost means the more components can be included (e.g. Chemistry, fire, nutrients,) but some processes which may be extremely important are difficult to resolve (eh, sea ice, topographic forcing of clouds and storms, cloud processes, some ice sheet dynamics, vegetation demography, urban landscapes, agricultural areas).
Page 25 contains Antarctic surprises like how 70 billion tonnes of snowfall accumulated across East Antarctica contributing to a net gain of mass in Antarctica — which was a reversal in the mass loss trend over the preceding 20 years..
A future with more ARs [atmospheric rivers] leading to a larger accumulation of snow on the Antarctic continent would be experienced very differently in Australia to a future with fewer ARS. Specifically projections o
The modelers didn’t see that coming either.
REFERENCES
A Decadal Plan for Australian Earth System Science 2024–2033, released November 25th, 2024
The launch webinar
— This one is for Julian. —
Turtle Model by SAIF 4 from Pixabay
Models are not evidence. Models are not science – the discovery of new phenomena. Models might have a little more science at their basis than an astrology chart, but at the end of the day, are predictions.
Look at how often Governments get their budgets wrong – and they are short-term predictions of public spending – ie. money, a man-made concept.
So when can we get our lightbulbs back please?
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Predictions are always difficult – especially about the future??
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So sayeth the philosopher Berra.
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And our multi-use plastic bags which supermarkets gave away for free – all the ones I began stashing 5 years ago have finally given up the ghost through over-usage. Just Say Plastic!
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The models have correctly forecast global temperature rise, in stark contract to commentators like Jo and Willie Soon and David Evans who keep getting it wrong.
Everybody uses models, some are useful and some aren’t. Your brain is using models of the outside world that you are only vaguely aware of.
The physical equations that govern weather are well understood but they are nonlinear. Averages are straightforward to predict, but one-off extreme events are localised and chaotic in nature. Small climate changes in mean and standard deviation radically change the probability of extreme events, which is why weather seems to be more erratic. Higher precision models will help up to a point. They can give us more advance warning at times when we really need it.
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To be fair it is a 50/50 chance. To put it simply…….they got lucky. Global temps at any given interval are either rising a little or falling a little. Even this current slight warming phase is only a small blip on a longer cooling period that has been in train since the peak warming period known as the Holocene Climatic Optimum, where places, like the Sahara was a verdant woodland. Ice core data clearly points to the Earth inextricably entering another cold glacial period. CO2 will not save humanity from that.
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>The models have correctly forecast global temperature rise, in stark contract(sic) to commentators like Jo and Willie Soon and David Evans who keep getting it wrong.
>some are useful and some aren’t
Models predicted catastrophic global temperature rises which were used to justify and scare the population into acquiescing in the face of enormous hoovering of taxpayer money which would have been far better spent elsewhere. The models’ forecasts of catastrophic temperature rises subsequently failed to eventuate.
Models are used as evidence for atmospheric CO2 reduction efforts but the models do not prove global temperature changes are driven by changes in concentration of atmospheric CO2.
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Global temperatures will continue to rise until net greenhouse gas emissions are reduced to zero. That is undeniable fact. The opportunity to restrain temperature rise to < +1.5°C rise since pre-industrial is all but gone. +2°C is unlikely given current Governments' motivation. +3°C will be distinctly unpleasant and will result in massive human translocation. The question is, how do you define catastrophic?
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The question is, how do you define catastrophic?
Scientists (or should I say modelers) that create models which ignore the largest “green house gas” (aka water vapor) in their models.
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Simon,
Nice to see that you accept the basic point about models not being able to produce useful predictions. So confirming that models, in themselves, are simply reflections of the biases of their producers).
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Well the models “didn’t correctly forecast global temperature rise”, at best they thought that the temperature would rise from 1990 onwards.
That was after the rise in 1975/6 etc in northern Europe after several decades of colder weather much like the 1860-70 after 1855, or the 1910-1940 rise after the colder weather in the 1880-1890s. Hardly inspired thinking.
And after 1990? Buckingham Palace isn’t under 7 foot of water, children in the UK now know about snow, the Arctic (& Antarctic) ice hasn’t melted and sea levels haven’t risen and flooded islands (nor Florida beaches like Trump’s home).
Simon, why not do something useful – like going off and feeding those ‘starving’ polar bears.
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Oh dear – what a silly statement – the recent rise in global temperatures has purely been due to the extra 10% of water vapour in the atmosphere – and that is the result of a volcano HTHH – not – CO2 – so you speak nonsense
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If a coupled, non-linear, chaotic system, that lacks many salient variables, and hasn’t got every single initial condition, simultaneously and exactly provided at the first iteration, then no amount of precision is going to make any difference at all.
The lack of understanding of differential equations and numerical methods is a continuing source of amusement.
An unbridled faith in fantasy is alarming. This is how witches got burnt.
Ignorance is nothing to be proud of.
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Quite right! Crap in = crap out end of story!
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That statement identifies the emerging problem for Australia. The union super funds and government wealth fund are heavily invested in the climate scam. No flavour of government is going to stop the transfer of wealth from the poor consumers tio the wealthy retirees.
Pitman is just after more money from other people. Climate modelling is conceptually flawed. They cannot even model the basic processes of cloud formation using fundamental physics.
Earth has done quite well for 4Gy without models. All the evidence is pointing toward the effort of humans, led by China, to restore the CO2 balance is entirely beneficial. The current climate change is well explained by the precession cycle and that will eventually lead to glaciation across much of the NH.
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On the contrary, most pension funds are predicated on business as usual. That’s not going to happen. There is a lot of crystal ball gazing going on and the climate models are not great at predicting the extent of one-off extreme events. It is a mandatory requirement for many organisations in Australia to report climate-related financial disclosures.
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Nope – the union super funds are Federal wealth fund are deep into the woke world of climate emergency and the “renewable” energy saviour:
https://www.abc.net.au/news/2024-11-21/future-fund-ordered-to-invest-in-housing-renewables/104628032
https://www.cbussuper.com.au/about-us/news/media-release/cip-partners-with-cbus
The funding sources for all the new AEMO tenders will be difficult to track down. If you have the list of who is funding all this taxpayer guaranteed income streams please provide.
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I think the point Rick was trying to make initially is that Pitman isn’t willing to gamble a large amount of money on the climate models being accurate, ie he doesn’t have much faith in their long term accuracy.
Good gamblers have a knack of identifying a “sure thing”. We can assume Pitman doesn’t think the models his agency have been using are a sure thing.
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Jo,
Sorry, but I couldn’t disagree more. We need *weather* models.
Climate is weather averaged over 30 years isn’t it? What the hell use is that in predicting droughts, floods, heatwaves, cold snaps? It’s utterly, utterly useless.
If we get *really* good weather models, we can predict thirty years into the future and, voila, you have your climate model (much good may it do you).
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I also have a suggestion for the weather model problem. It might be one of the few important applications for the current fad of AI.
LLM AI works in a very stupid way. It’s amazing anyone thinks it can be intelligent. Roughly, what it does is to choose the word most likely to follow the words you have so far. So if I ask it What is the best way to skin a cat?, a non-AI program munges my question into The best way to skin a cat is, and then it’s fed to the word predictor algorithm, which spews out “most likely words” until some sort of ending condition is satisfied. The “most likely words” are pre-conditioned from the training data.
How about, instead of “words”, we train it with all historical weather readings: air pressures, temperatures, wind speeds, wind direction, etc., along with time of year … whatever we can lay our hands on? Now if we feed it the last few day’s weather readings, we can ask it what weather readings are most likely to follow these? and you’d hope the LLM would come up with something pretty good.
I’m not a meteorologist, but I guess there may be a few different types of model currently being used.
LLM ought to be more reliable than physics-based models trying to simulate the chaotic atmosphere because the result is based on historical results. Empirical, not theoretical.
LLM ought to be far better than linear regression type models. I don’t know if any meteorologists use these, but they’re at the centre of the climatologists’ toolkit, so I’m guessing…
LLM might help improve existing empirical models. An existing model would have been the result of an analyst choosing a set of statistics as being likely predictors and then use those in a “similar records” database search. The training of LLM is agnostic on which things are influential. Analysis after training might reveal the most important predictors.
It would be correct to say that a historical search for similar records isn’t modelling at all, but we can still call it that if it’s good for marketing.
As we’re often told, there’s only one Earth. Indeed. We should use its results rather than pretending we can create another Earth inside a computer.
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Or to summarise, Andy Pitman has come out of hiding and needs more grant money.
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How about taking the Earth’s orbit around the Sun and the Sun’s variable energy output into account. Or is that way too obvious.
I’m not a scientist just a long suffering Taxpayer.
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I predict that Lismore will always get flooded. Just look at the Geography there. The town needs to be moved and re-built at a better place. Simple.
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Correct me if I’m wrong, but I believe that Lismore is built in the bend of a river. Many towns along the Mississippi had to be abandoned as they were also built in river bends.
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LOL, it seems that “The Science” is NOT settled.
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Perhaps . . . “The Science” is NOT settled when ‘we’ need more of Your Money.
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Why did it take Pitman so long to realise what all of us here have known for decades?
And as for models (climate,economic etc) I tend to close the page as soon as they are mentioned.
Just get on with life with a bit of common sense.
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Thanks for highlighting the Dr Pitman revelations Jo and thanks also to Tony Thomas for his hard work.
But why do we believe co2 is a problem? Rather it is the best plant food in the world and yet some donkeys think it is a poison. Here Dr Happer tells Sky News we need more co2 and growers now pay to pump more co2 into their greenhouses to produce better flowers and fruits etc all over the world today. Just watch the first few minutes of this video to understand the wonders of this trace co2 gas .
And today at higher levels co2 is helping to Green the planet and we Aussies benefit as well. Free plant food and all animals and plants are now getting a bigger slice of the pie.
Professor William Happer on integrity in climate science on Sky News Australia – 17 September 2023
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Stand and deliver! The pursuing of public money again in the hope that a computer with a few more cogs can determine how a system will behave in the area of a football field. Ridiculous stuff.
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Again more proof that our Aussie rainfall has been much better over the last 74 years.
Australia is the driest continent on Earth and yet our so called scientists can’t read or understand a BOM rainfall graph from 1900 to 1950 and compare it to 1950 to 2023? They are as dumb as they come.
http://www.bom.gov.au/cgi-bin/climate/change/timeseries.cgi?graph=rranom&area=aus&season=0112&ave_yr=8&ave_period=6190
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And NSW had a terrible drought period over the first half of the 20th century.
http://www.bom.gov.au/cgi-bin/climate/change/timeseries.cgi?graph=rranom&area=nsw&season=0112&ave_yr=8&ave_period=6190
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It’s great that someone like Pitman is willing to speak candidly from time to time. Even if it might be motivated by the seeking of funding, if not simply to let people know where things are at.
It’s a tricky tightrope because we use his admissions of ‘we don’t know’ to show the common public narratives are often made up. But we know using his statements against the narrative will have people coming down on him to say, “Ssshhhh. Keep the cat in the bag”. Or worse.
This is why science should run the conversations and not activists. The latter will always suppress information.
Activists come in many forms. Unfortunately including journalists, politicians, educators, and some in science.
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Back in the day, you used to make real world observations and then formulate an hypothesis then develop and test a model to see if it fitted the observations. If the data didn’t fit you revised the model, not the data.
With woke Leftist “science” you develop a model and then adjust the observed data to fit it. In Australia the BoM does this by the mysterious undocumented (and hence unscientific) process they call “homogenisation”. Tony Heller in the US has documented how NASA and NOAA make such adjustments.
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The state of WA has had much higher rainfall since 1974.
But the SW of WA has had lower rainfall over the last 30 years.
But the recent O’Donnell study has found that rainfall in the WA wheat belt area has been the highest for the last 400 years.
http://www.bom.gov.au/cgi-bin/climate/change/timeseries.cgi?graph=rranom&area=wa&season=0112&ave_yr=8&ave_period=6190
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I believe part of the problem with this reduced rainfall is the runoff. The water corp has allowed the catchment areas to become heavily vegetated, thus absorbing a lot more of the rainwater than previously. Originally the catchment areas in the hills were used for timer cutting, so the undergrowth was managed and reduced. Now the undergrowth has been allowed to flourish, thus absorbing more rainfall.
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I sense a multi hundred million dollar request for a Super Dooper computer and a coal, gas or …gasp… a nuclear power station to run it.
The big woke socialist media and similar like Amazon are already buying nuclear powered data centres with Super Dooper computers.
https://www.ans.org/news/article-5842/amazon-buys-nuclearpowered-data-center-from-talen/
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But the BOM has a supercomputer now so they’ll be able to predict weather 72 hours out more accurately than your elderly neighbour’s dicky knee.
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Tricky knee Odds On. Supercomputer 5 to 1 against unless the current We can control Climate Believers program it when the odds go out to 24 to 1.
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Since when did the primary focus of “science” become modelling?
Do these people ever bother to look out the window to see what’s actually going on?
And what are they trying to prove with these models anyway?
The only models that will be accepted for funding will be those that predict catastrophic global boiling. Anything that predicts a more likely scenario such as global cooling as we come to the 10,000+ year rare interglacial will be ignored, not funded and any researcher that comes to such a conclusion will be sacked (fired).
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I think the “expert climate modeller” is trying to secure funding before:
1) Labor gets kicked out at the next election. The Liberals (fake conservatives) will be slightly less bad than Labor.
2) The Trump Revolution reaches Australia and catastrophic anthropogenic global warming is revealed to all for the scam that it is.
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We need to model BOBowen brainwaves to see if he’s got any!
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Thanks to Tony Thomas and to Jo Nova.
I have not read all of the mentioned reports, but have read enough to confirm the presence of a strong trait that seems widespread in climate research.
It is to promote the negatives and to downplay the positives. Example, the cover of Andy Pitman’s report has images of flood and bushfire. There is seldom mention of the increased global vegetation or higher crop yields that most regard as benefits.
Some years ago, we read of the concept of “Social Cost of Carbon” without a balance from any “Social Benefit of Carbon”. Some economists did calculations using SCC without even noting that it was only about half of the carbon dioxide budget.
The serious consequence is that the lack of mention of benefits will produce a distorted analysis. While society should be concerned about how good models are, there also needs to be a light shone on the factors that are purposely left out of model inputs, which tend to be beneficial factors. Science has to be rejected when inputs are purposely silenced. Geoff S
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It’s not the number of the models. Rather, it is the number of variables inside the models. When you get too many of the darned things, you can prove anything. Cheers –
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More solid scientific proof if they’d only understand it.
Here’s all the poorest to richest countries’ death rates from fires and burns. Since 1980.
And all have dropped over the last 42 years and Aussies are still the lowest and yet we always have to endure very dangerous fire conditions.
When will they start to think and wake up?
Of course just 4.45 billion in 1980, but about 8 billion people at risk in 2021.
More solid scientific proof that we live in a much SAFER world today. Does anyone not understand these very simple sums?
https://ourworldindata.org/grapher/fire-death-rates?tab=chart&country=OWID_WRL~Low-income+countries~High-income+countries~Upper-middle-income+countries~Lower-middle-income+countries~AUS
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Something this thread has highlighted is the supposed link of El Nino /La Nina to our climate and rainfall variations. I still have not seen any “science” as to what controls whether we are in a neutral, El Nino or La Nina period. My personal opinion as a geologist is that it is driven by undersea volcanic activity (of which there is plenty and not taken into account). When activity is low – we tend towards La Nina or neutral – when it is high – then heating of the oceans is occurring and La Nino forms. That would divorce that whole process from anything to do with weather or climate influence and is rather a driver of climatic changes than being driven by them. The other thing that has bothered me for a long time is the linking of extreme weather to climatic temperature changes that seem to conclude that more heat means wilder weather. In fact the opposite is the case. The worst storms in British History have happened in colder periods such as the little ice age (My Great Great Great Grandfather’s ship was run ashore in Cardigan Bay by one such storm in the little Victorian Ice Age) – and that appears to be because the differential between barometric pressure in the northern (and southern) hemispheres and the tropics is greater giving the driver for wild weather, whilst if it is warmer in those northern or southern latitudes, the differential is much less. So it makes no sense that we should expect more wild weather during warmer periods which give us much more benign weather.
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Again more solid scientific proof that we live in the safest period in Human history.
Lomborg in the NY Post cites the latest scientific proof that deaths from “extreme weather events” have dropped by 99% over the last 124 years.
Dr Koonin easily wins his CC debates and cites that extreme weather deaths today are one fiftieth the deaths in 1920.
Anyone not understand this data yet? And the same data are used by OWI Data and the UN, CIA etc.
https://nypost.com/2022/04/30/deaths-in-climate-disasters-declined-99-from-a-century-ago/
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This surprises me! I thought the whole idea was for our climate gurus to tell us what the future climate would be … and then back-engineer the models to produce the results they desire. I mean, surely they must already have the computing technology to populate the thousands of new virtual weather stations that would be required to provide data at a kilometer scale … and then generate the data that those stations will be recording in the future to fit their model predictions right out until 2100 and beyond?
I always thought it was a case of “The future is certain … only the past is uncertain”
I find it rather unsettling to discover that they havent all decided what the future climate will be.
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No resolution of model scales can provide good information about future conditions if the models contains incorrect premises, such as for instance, it may be that more, even much more (relatively speaking) CO2 in the atmosphere will have no measurable effect upon any of the article’s mentioned weather aspects (although there is actual evidence that more CO2 will help produce more fuel load for big fires). Any model that calculates increased temperatures or other weather effects with increasing CO2 (or methane or nitrous oxides, etc.) may be introducing large errors into its results whether on the 100km scale or the 1 meter scale. We don’t actually know because that premise lacks significant real world evidence.
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and another thing – I studied Geology – which is the science of earth systems – including rocks, ancient continents, sea floor movements, volcanism, plate tectonics and paleo-climates. When did that morph into Earth System Science? I have read some of the document from the process chaired by Andy Pitman and whilst it is heavily biased to more and bigger modelling – it seemed to me to be more focused on adaption to climate changes – rather than preventing them. maybe there is hope yet? I havent checked yet – but were any of the illustrious people on the committee geologists?
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More UN data as used by OWI Data and proves that we live in the SAFEST period in Human history.
Life expectancy in 1770 just 28.5 years, under 1 billion population.
in 1900 just 32 years, 1.7 billion.
in 1950 46.4 years, 2.5 billion.
and in 2023 L Exp 73.2 years,8.1 billion.
I’ve included Australia in with the other continents and always has the highest life expectancy.
Today we are the healthiest and wealthiest Humans in our 300,000 + year history. So where’s their dangerous CC BS and fra-d?
https://ourworldindata.org/grapher/life-expectancy?country=OWID_WRL~Americas~OWID_EUR~OWID_AFR~OWID_ASI~OWID_OCE~AUS
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That the models are “low-resolution “ is not surprising. If the informing data ( actual measurements) are low- resolution then, surprise surprise, that will be the outcome. The answer is not to make more highly resolved models. They will be poor because the underlying data is wide-spaced and won’t include all the variables.
It’s a bit like estimating a mineral resource deposit. Wide-spaced samples will not result in an estimate that will get the approval of financiers. Only more and more closely spaced samples will get to a “bankable” resource estimate.
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this is the committee:
Chair: Professor Andy Pitman AO FAA – UNSW – specialist Climate Change Processes
Professor Julie Arblaster : Physical Geography and Climate Scientist – Monash
Dr Pep Canadell FTSE Chief Research Scientist CSIRO – Biology and Terrestrial Ecology – greenhouse Gas specialist
Professor John Finnigan FAA – ANU/CSIRO Mathematician and Fluid Mechanics – Research School of Bilogical Sciences
Dr Will Howard Hon Prof at ANU Institute for Climate Energy and Disaster Solutions, Phd in Geological Sciences and studied sedimentary basins and researches Marin climate Change
Dr Chloe Mackallah – CSIRO – Climate Data Scientist – PHD in Astrophysics – specialist in large climate datasets
Dr Felicity McCormack Monash – specialist in Ice melt losses – Antarctic Run-off
Dr Negin Nazarian UNSW – specialist Urban Climatology microscale Climate Modelling
A/Professor Christoph Rudiger – Civil Engineer – water at Monash
Dr Claire Vincent – Melbourne Uni – Lecturer Atmospheric Scientist – Geography Earth and Atmospheric Sciences
Dr Jan David Zika – UNSW Climate scientist, modeller etc
Only one with geological credentials and that in sedimentology – and overall a heavy preponderance of modellers – so not surprising their conclusions
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Ever heard of a Competent Person in the mining industry trotting out such claims the models are all wrong when they are getting sued by investors who relied on Resource and Reserve Estimates?
Time these charlatans in the climate blob became personally liable for losses sustained by people using these models.
We would see an improvement in the models quick smart, and also get a much better idea of the risks of using them.
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All weather comes from the oceans. All water comes from the oceans. All the surface heat is in the oceans while the atmosphere can lose the lot in a night.
So what do they model? The air.
As I understand it, the models are models of the thin atmosphere. Therefore they are measuring effects and not causes. You spot cycles but not make predictions, just like the overpowering El Nino/La Nina cycle. Which is a complete mystery.
So they are good for predicting air flows and thus very short term weather. And that is improving.
However they are useless for predicting climate. Which of course means the impact of increased CO2 is a complete mystery.
And incidentally, by far the greatest greenhouse gas is water itself, both as liquid water clouds and as gas, humidity. At 1% to 4% humidity even in a clear sky is 100x the concentration of CO2.
And those people who model on the sun and the ocean get it right.
These expert retired mathematicians used real thermometer measurements for the last 250 years in six cities in Europe. And nailed the temperature fit with just one solar cycle and one ocean oscillation.
https://www.youtube.com/watch?v=xSgCsb34Bfs&t=1009s
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