The record
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- Climate scientist Tapio Schneider advocates for expanding early warning systems to include non-rainfall triggers like high-altitude ice and rock collapses.
- Recent flash floods in Nepal, caused by such a collapse, resulted in significant loss of life.
- These systems could provide vital minutes of warning for downstream populations.
- Advancements in climate modeling and artificial intelligence offer new opportunities to improve predictive capabilities globally.
- Schneider emphasizes that climate modeling and risk assessment no longer need to be restricted to wealthier nations.
What to watch next
- Development of new Earth system models by the Climate Modelling Alliance.
- Potential integration of AI models with India Meteorological Department data for improved rainfall prediction.
- Evolution of AI systems in providing understandable mathematical proofs and scientific research.
Who said what2
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Tapio Schneider
climate scientist
2 quotes · 1 outlet
“Early warning systems are important. We probably need to expand them beyond events triggered by rainfall to such events so that you can have at least a few minutes of warning for people downstream and save some lives that way”
In the article
…aftermath of August 26 flash floods, triggered by a high-altitude ice and rock collapse. The disaster sent debris flowing from Tibet through central Nepal, leaving over 1,200 people dead and thousands more missing. " Early warning systems are important. We probably need to expand them beyond events triggered by rainfall to such events so that you can have at least a few minutes of warning for people downstream and save some lives that way ," Schneider told PTI in an interview. He added that permafrost is melting as the climate warms and one can expect more such events "even though any individual event will have different proximate causes". The climate…
“AI can help there. Right now, the output of the AI systems is pretty messy and not easy to comprehend so, it requires human work to make this into something that contributes”
In the article
…point of a mathematical proof is not just to give a yes-or-no answer, its point is to "enhance the global mathematical knowledge" and "enlarge the canon of what we understand about math and that needs to remain true". " AI can help there. Right now, the output of the AI systems is pretty messy and not easy to comprehend so, it requires human work to make this into something that contributes ," Schneider said. "... They might get better at producing better explanations and then I would say, 'it's an accelerator to progress in math, just as it's an accelerator to progress for what we do in climate modelling…
Coverage1
All filed from India
Named United States · India · Nepal · China · Ashoka University · California Institute of Technology · Climate Modelling Alliance · India Meteorological Department · Massachusetts Institute of Technology · NASA · OpenAI · Tapio Schneider
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