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Here's the non paywalled article.
The title is a little baity but the article is quite logical. It doesn't directly fool us about global warming but goes on to suggest radically what scientist think about this rise in temperatures over the past 2 years.

Is there evidence of acceleration?

Some say that the massive temperature spike might end up being a blip in the climate data, owing in large part to new regulations covering air pollution from ocean-going ships. In 2020, the United Nations International Maritime Organisation implemented a rule requiring an 80% reduction in sulfur emissions from ships sailing in international waters. One analysis of satellite imagery, published in August, suggests that there has been a clear reduction in ship tracks, which are formed when sulfur-containing pollution particles seed low-lying mists. The changes seem to correlate with the broader reduction in cloud cover pinpointed by Goessling’s team.
Not everyone is convinced, however. If the pollution reduction was the primary explanation, warmer temperatures should coincide with the areas most frequented by ships, says Yoko Tsushima, a climate scientist at the Met Office in Exeter, UK. “We do not see that pattern,” she says. “The warming is almost everywhere.”
Nor do the numbers necessarily add up. It is clear that shipping regulations have played a part, Goessling says. But his calculations suggest that, to explain the 2023 temperature spike, all forms of air pollution on Earth, rather than just shipping pollution, would need to be almost completely eliminated.
This leaves the possibility that warmer temperatures are somehow driving reductions in low-lying cloud cover, which in turn promotes further warming — a positive feedback loop.
This is some kind of a new definition about the rise in temperatures. Do you believe in this new narration or it's another blip?
What I would like is a way to be able to assess a climate scientist's ability at
  • doing good math
  • having a deep understanding of statistics
  • assessing the limitations of a specific model
  • quantifying the impact a certain simplification may have on the model
  • double-checking their student's calculation results
  • ...
In my own field, which is quite theoretical and does not have a big impact on policy decisions, I am fairly able to do that. In the field, we know who are the people to trust and who are the ones that are just good marketers and will do anything to raise funds. I also know it's possible to tune the parameters of the models and theories used in my field to make it say whatever I want it to say. Also, I know that we all somehow trust whatever calculation a student or postdoc has carried as the cost to reproduce the calculations is not worth it.
I'm sure there are good and bad climate scientists too, but I don't know their relative proportion, and so it's hard to judge the outcome of any of these types of studies.
I do believe in climate change, but I wish I could find a way to be better informed and assess the level of confidence I can have in that belief.
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142 sats \ 0 replies \ @000w2 19h
The issue was kind of laid bare during covid. When there is a lot of money and power behind one side, dissenting voices are simply pressured/censored/deplatformed/defunded to make it seem like there is overwhelming consensus.
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I do believe in climate change, but I wish I could find a way to be better informed and assess the level of confidence I can have in that belief.
I agree 💯. This is very problematic. You can't get everyone saying the same thing, the foundation of science lies on proof but climate science is running it on assumptions.
They see a rise in temperatures, they go tto ocean, mountains, plains and everywhere and start studying what's causing it. The outcome is different assumptions to why it's increased/increasing.
For my faith, I believe that climate change is real but the cause is not anything except the deforestation.
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