Rodrigo Almeida
@rodrigo-gtiff.bsky.social
🛰️ 🌍 🤖 Climate and Weather AI researcher @aifraunhoferhhi.bsky.social
🌈 he/him
🌈 he/him
If you’ll be attending NeurIPS—or are interested in AI for weather and climate—feel free to reach out. I’d be very happy to connect!
@aifraunhoferhhi.bsky.social
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@aifraunhoferhhi.bsky.social
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November 26, 2025 at 3:53 PM
If you’ll be attending NeurIPS—or are interested in AI for weather and climate—feel free to reach out. I’d be very happy to connect!
@aifraunhoferhhi.bsky.social
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@aifraunhoferhhi.bsky.social
/end
We’ve also released a pre-print, which not only includes this case study but also an extended analysis of the August 2022 China heatwave, offering a broader evaluation. 📄 Read the full pre-print here: arxiv.org/abs/2511.171...
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On the Predictive Skill of Artificial Intelligence-based Weather Models for Extreme Events using Uncertainty Quantification
Accurate prediction of extreme weather events remains a major challenge for artificial intelligence based weather prediction systems. While deterministic models such as FuXi, GraphCast, and SFNO have ...
arxiv.org
November 26, 2025 at 3:53 PM
We’ve also released a pre-print, which not only includes this case study but also an extended analysis of the August 2022 China heatwave, offering a broader evaluation. 📄 Read the full pre-print here: arxiv.org/abs/2511.171...
3/
3/
Using the 2022 Pakistan floods as a case study, we evaluate state-of-the-art deterministic AI models and examine how different perturbation methods can extend them toward trustworthy probabilistic forecasts for extreme precipitation, which is essential for future early warning systems.
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On the Predictive Skill of Artificial Intelligence-based Weather Models for Extreme Events using Uncertainty Quantification
Accurate prediction of extreme weather events remains a major challenge for artificial intelligence based weather prediction systems. While deterministic models such as FuXi, GraphCast, and SFNO have ...
arxiv.org
November 26, 2025 at 3:52 PM
Using the 2022 Pakistan floods as a case study, we evaluate state-of-the-art deterministic AI models and examine how different perturbation methods can extend them toward trustworthy probabilistic forecasts for extreme precipitation, which is essential for future early warning systems.
2/
2/