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:
-
-
-
-
- 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).
-
-
-
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?
130
Predictions are always difficult – especially about the future??
50
So sayeth the philosopher Berra.
Auto
00
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!
50
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.
013
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.
50
>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.
50
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).
10
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.
20
Quite right! Crap in = crap out end of story!
30
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.
140
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).
110
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.
20
Or to summarise, Andy Pitman has come out of hiding and needs more grant money.
100
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.
90
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.
60
LOL, it seems that “The Science” is NOT settled.
40
Perhaps . . . “The Science” is NOT settled when ‘we’ need more of Your Money.
Auto
50
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.
80
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
70
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.
50
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
50
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
10
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.
50
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.
60
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
10
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.
20
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/
70
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.
30
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.
20
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).
50
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.
80
We need to model BOBowen brainwaves to see if he’s got any!
40
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
20
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 –
20