Guest essay by Eric Worrall
A Team of Scientists plans to use AI to improve climate modelling of sub-grid scale phenomena such as turbulence and clouds. But there is no reason to think an AI will have any more luck than human climate modellers.
International Collaboration Will Use Artificial Intelligence to Enhance Climate Change Projections
MARCH 23, 2021 10:18 PM AEDT
A team of scientists, backed by a $10 million grant from Schmidt Futures, will work to enhance climate-change projections by improving climate simulations using artificial intelligence.
$10 million effort, backed by Schmidt Futures, to be led by NYU Courant Researcher
A team of scientists, backed by a $10 million grant from Schmidt Futures, will work to enhance climate-change projections by improving climate simulations using artificial intelligence (AI).
Led by Laure Zanna, a professor at New York University’s Courant Institute of Mathematical Sciences and NYU’s Center for Data Science, the international team will leverage advances in machine learning and the availability of big data to improve our understanding and representation in existing climate models of vital atmospheric, oceanic, and ice processes, such as turbulence or clouds. The deeper understanding and improved representations of these processes will help deliver more reliable climate projections, the scientists say.
“Despite drastic improvements in climate model development, current simulations have difficulty capturing the interactions among different processes in the atmosphere, oceans, and ice and how they affect the Earth’s climate; this can hinder projections of temperature, rainfall, and sea level,” explains Zanna, part of the Courant Institute’s Center for Atmosphere Ocean Science and a visiting professor at Oxford University. “AI and machine-learning tools excel at extracting complex information from data and will help bolster the accuracy of our climate simulations and predictions to better inform the work of policymakers and scientists.”
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Due to the complexity of the atmosphere, ocean, and ice systems, scientists rely on computer simulations, or climate models, to describe their evolution. These models divide up the climate system into a series of grid boxes, or grid cells, to mimic how the ocean, atmosphere, and ice are changing and interacting with one another. However, the number of grid boxes chosen is limited by computer power; currently, climate models for multi-decade projections use grid box sizes measuring approximately 50 km to 100 km (roughly 30 to 60 miles). Consequently, processes that happen on scales that are smaller than the grid cell–clouds, turbulence, and ocean mixing–are not well captured.
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Read more: https://www.miragenews.com/international-collaboration-will-use-artificial-532909/
Top marks for admitting model temperature projections struggle to capture important processes. Clouds, storms, ocean mixing and turbulence are likely the reason open ocean surface temperatures in the tropics are capped at 30c.
But why do I think the AI approach will struggle to improve on human efforts?
The reason is decades of effort to improve understanding the global climate has not answered basic questions, like how much does global temperature change in response to adding more CO2, and human brains are far more powerful than any AI.
AIs work best when the solution is easy to approach, when a gentle slope of improving results provides a strong indication to the AI that it is making progress.
But I do not think this is a good description of the climate system. The lack of progress over the last three decades, despite thousands of intelligent people dedicating years of their lives to the effort, implies the solution to better climate modelling is very difficult to find. Outside the narrow range of correct solutions there is likely a vast wilderness of poor quality answers, with very little indication of which direction the AI needs to travel to discover a high quality solution.
Either that, or there is something fundamental missing from the theory, and a high quality solution will not be possible until the missing piece of the puzzle is found.
Even a powerful AI struggles to search a multi-dimensional problem space when the correct answer is poorly signposted – there are many more ways to be wrong than right.
As I recall, in a previous life in a galaxy far, far away, The IPCC was tasked with finding all the bad things that would happen due to rising CO2 in the atmosphere. Chief among them was runaway Global Warming.
So Boatloads of stupid money was thrown at people to come up with all the bad things that would result from an increase in atmospheric CO2.
The way I see it, we can quit spending money on all those useless models and studies that find… sunnuva gun! Only bad things happen, including acne and halitosis, from rising atmospheric CO2.
So the good news is we can quit funding all the studies that, as requested, seek to find the negative effects of rising CO2.
Instead, for a measly $100 or $200 million or so, we can get some AI programmers to write a program that will do the same.
It will spit out all the bad things caused by CO2 (there is nothing good that will come about from rising “caaahbon”) and the AI program will reach the conclusion that we’re all gonna die.
It seems that, true to funded task, every study has shown .that it’s worse than we thought! So use AI instead to discover that it’s worse than the AI programmers thought.
Now a computer, using indisputable AI!, will say it’s so. How cool is that? And thrifty, to boot.
(Sadly, I can’t put my usual winky emoji here.)
To manipulate CMIP CAGW models to make them SScary (sic) enough to justify wasting $100’s of trillions of taxpayers’ money, Leftist alarmist MUST assume clouds have a net global warming effect…
All physics and empirical evidence show global cloud cover has a net global cooling effect…
If this $10 million AI grant would correct Leftists’ delusional assumption that clouds cause net global warming, it would be the best investment in human history, but we know that would NEVER happen…
Tax the clouds!!! and another “!”.
Paranoid-san:
Bill Gates’ brilliant idea is to seed chalk dust in the ionosphere to block solar irradiance in an effort to cool the earth from ravaged of CAGW….
What could go wrong that? LOL!
I’m going long on chalk-dust futures….
AI can’t solve theory error. What a waste of money.
$10 million? A team of scientists can use that up pretty quickly to produce a need for further work.
One simple question: What kind of “intelligence” creates the ability for “artificial intelligence” to function?
One simple follow-up question: Given the answer to the above question, why do people have any faith in the future abilities of “artificial intelligence”?
I’ve looked at clouds from both sides now
From up and down and still somehow
It’s cloud’s illusions I recall
I really don’t know clouds at all
A generalisation was made a few years ago, you would need the whole Top500 list of supercomputers to operate more than 24hrs to model 1 day into the future. It could take another 20 years before we could get the top 10 together to make simulation/model runs practical with required detail.