AI Extreme Weather and Climate
Zhi Li
Publishing Details
About This Podcast
Brace yourself for a deep dive into the science of how artificial intelligence is revolutionizing our understanding of extreme weather and climate change. Each episode brings you cutting-edge research and insights on how AI-powered tools are being used to predict and mitigate natural disasters like floods, droughts, and wildfires. We'll unravel the complexities of climate models, explore the frontiers of AI-powered early warning systems, and discuss the ethical implications of AI-driven solutions. Join us as we break down the science and uncover the transformative potential of AI in tackling our planet's most pressing challenges.
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Recent Episodes
S1E14 Target Concept Tuning: Solving the AI Blindspot in Extreme Weather Forecasting
In this episode of AI Extreme Weather and Climate, Allen and Sydney explore a major breakthrough in meteorological AI: predicting rare but high-impact events like typhoons. While foundation models…
S1E13 NeuralGCM: Observation-Based Hybrid Modeling for Global Precipitation Forecasting
This paper introduces NeuralGCM, a hybrid atmospheric model that integrates machine learning with traditional differentiable physics to improve global precipitation simulations. Unlike older models…
S1E12 Flow-Matched Neural Operators for Continuous PDE Dynamics
The episode describes the Continuous Flow Operator (CFO), a novel neural framework for learning the continuous-time dynamics of Partial Differential Equations (PDEs), aimed at overcoming limitations…
S1E11 Ep. 11: Principals of Diffusion Models
This episode provides a comprehensive monograph on diffusion models, detailing their foundational principles through three unifying perspectives: the Variational View (related to VAEs and DDPMs), the…
S1E10 Ep 10. RainSeer: Physics-Guided Fine-Grained Rainfall Reconstruction
This episode introduces RainSeer, a novel, structure-aware framework for reconstructing high-resolution rainfall fields by treating radar reflectivity as a physically grounded structural prior. The…
S1E9 Ep. 9: FlowCast-ODE Cntinuous Hourly Weather Forecasting with Dynamic Flow Matching and ODE Integration
This episode dives into FlowCast-ODE, a novel deep learning framework designed to achieve accurate and continuous hourly weather forecasting. The model tackles critical challenges in high-frequency…
S1E8 Ep.8 AQUAH: An Automatic Quantification and Unified Agent in Hydrology
Welcome to a new episode where we dive into AQUAH, the Automatic Quantification and Unified Agent in Hydrology! This groundbreaking system is the first end-to-end language-based agent specifically…
S1E7 Ep 7. cBottle: Climate in a bottle - foundational AI weather prediction
cBottle, developed by NVIDIA, is a generative diffusion-based framework that acts as a generative foundation model for the global atmosphere. It directly tackles the challenge of petabyte-scale…
S1E6 Ep.6 How to fine tune a weather foundation model to hydrological variables?
This research evaluates the performance of the Aurora weather foundation model by using lightweight decoders to predict hydrological and energy variables not included in its original training. The…
S1E5 Ep.5 What is foundation model - drawing from numerical simulation
When we talk about foundation models, what are we talking about? This is a reflection piece on foundation models by drawing an analogy from numerical solutions in fluid dynamics. This paper explore…
S1E4 Ep.4 Any-to-any Earth Observation Generation and Thinking - TerraMind
IBM recently released the first-of-its-kind geospatial intelligence any-to-any model TerraMind. In this podcast, we feature this new generative model and learn its capability of multi-modality. I…
S1E3 Ep.3 Geospatial foundation model - Prithvi
Today, we are featuring a geospatial foundation model Prithvi, produced by NASA and IBM, one of the first foundation model in this space. Trained on a large global dataset of NASA’s Harmonized…
S1E2 Ep.2 AI models for flood forecasting - HydrographNet
This research article introduces HydroGraphNet, a novel physics-informed graph neural network for improved flood forecasting. Traditional hydrodynamic models are computationally expensive, while…
Ep.1 AI models for weather forecasting
We are featuring three papers:Mardani, M., Brenowitz, N., Cohen, Y., Pathak, J., Chen, C., Liu, C., Vahdat, A., Nabian, M. A., Ge, T., Subramaniam, A., Kashinath, K., Kautz, J., & Pritchard, M.…
Frequently Asked Questions
AI Extreme Weather and Climate has published 14 episodes since March 2025, covering topics in Earth Sciences, Education.
AI Extreme Weather and Climate is currently highly active with new episodes monthly. Average episode length is 19m.
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