Insights from recent episode analysis
Audience Interest
Podcast Focus
Publishing Consistency
Platform Reach
Insights are generated by CastFox AI using publicly available data, episode content, and proprietary models.
Most discussed topics
Brands & references
Total monthly reach
Estimated from 5 chart positions in 5 markets.
By chart position
- 🇩🇪DE · Earth Sciences#1155K to 30K
- 🇨🇦CA · Earth Sciences#1195K to 30K
- 🇯🇵JP · Earth Sciences#6410K to 30K
- 🇮🇪IE · Earth Sciences#2510K to 30K
- 🇦🇷AR · Earth Sciences#2910K to 30K
- Per-Episode Audience
Est. listeners per new episode within ~30 days
20K to 75K🎙 ~2x weekly·48 episodes·Last published 1mo ago - Monthly Reach
Unique listeners across all episodes (30 days)
40K to 150K🇩🇪20%🇨🇦20%🇯🇵20%+2 more - Active Followers
Loyal subscribers who consistently listen
16K to 60K
Market Insights
Platform Distribution
Reach across major podcast platforms, updated hourly
Total Followers
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Total Plays
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Total Reviews
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* Data sourced directly from platform APIs and aggregated hourly across all major podcast directories.
On the show
From 10 epsHost
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No guests detected in recent episodes.
Recent episodes
Aligning artificial intelligence with climate change mitigation
May 9, 2026
19m 15s
Machine learning for the physics of climate
May 3, 2026
19m 37s
Atmospheric Transport Modeling of CO2 With Neural Networks
Apr 27, 2026
20m 31s
On the foundations of Earth foundation models
Apr 20, 2026
17m 32s
Whose weather is it? A fairness framework for data-driven weather forecasting
Apr 14, 2026
21m 31s
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| Date | Episode | Topics | Guests | Brands | Places | Keywords | Sponsor | Length | |
|---|---|---|---|---|---|---|---|---|---|
| 5/9/26 | Aligning artificial intelligence with climate change mitigation✨ | artificial intelligenceclimate change+3 | — | FacebookGoogle+1 | — | AIclimate footprint+3 | — | 19m 15s | |
| 5/3/26 | Machine learning for the physics of climate✨ | machine learningclimate physics+4 | — | Nature Reviews PhysicsEuropean Centre | — | machine learningclimate+7 | — | 19m 37s | |
| 4/27/26 | Atmospheric Transport Modeling of CO2 With Neural Networks✨ | atmospheric transport modelingCO2+4 | — | CarbonBenchSwinTransformer+7 | — | CO2 modelingneural networks+4 | — | 20m 31s | |
| 4/20/26 | On the foundations of Earth foundation models✨ | Earth foundation modelsAI in Earth science+4 | — | Communications Earth & Environment | — | Earth AI modelsfoundation models+5 | — | 17m 32s | |
| 4/14/26 | Whose weather is it? A fairness framework for data-driven weather forecasting✨ | AI in weather forecastingfairness in data+3 | — | ECMWFEnvironmental Research Letters | — | weather forecastingAI models+5 | — | 21m 31s | |
| 3/7/26 | Learning predictable and informative dynamical drivers of extreme precipitation using variational autoencoders✨ | machine learningextreme precipitation+3 | — | Weather and Climate Dynamics | — | CMM-VAEvariational autoencoder+4 | — | 18m 09s | |
| 2/28/26 | Green and intelligent: the role of AI in the climate transition✨ | AIclimate transition+3 | — | Green and intelligent: the role of AI in the climate transition | — | AIclimate change+3 | — | 18m 25s | |
| 1/26/26 | Climate Knowledge in Large Language Models✨ | climate knowledgelarge language models+4 | — | Alfred Wegener InstituteHelmholtz Centre for Polar and Marine Research | — | climatelarge language models+3 | — | 11m 57s | |
| 1/11/26 | Artificial Intelligence for Atmospheric Sciences: A Research Roadmap✨ | Artificial IntelligenceAtmospheric Sciences+4 | — | Artificial Intelligence for Atmospheric Sciences: A Research Roadmap | — | AIatmospheric sciences+5 | — | 13m 46s | |
| 12/19/25 | Differentiable and accelerated spherical harmonic and Wigner transforms✨ | spherical harmonic transformsWigner transforms+3 | — | S2FFTJAX+1 | — | spherical harmonicsWigner d-functions+5 | — | 13m 02s |
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Chart Positions
5 placements across 5 markets.
Chart Positions
5 placements across 5 markets.