AI & Environment Resource HubGirtsou et al. · 2025-01-19
Self-supervised learning enhances 3D cloud reconstruction, improving climate predictions by reducing uncertainties in climate models.
Girtsou et al.. 2025-01-19. 3D Cloud Reconstruction Through Geospatially-Aware Masked Autoencoders. https://ml4physicalsciences.github.io/2024/files/NeurIPS_ML4PS_2024_255.pdf (AI & Environment Resource Hub; record paper-026; collection snapshot 2026-09-15).
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Source sheet: Scientific Paper · Row 30 · Original ID: paper-026.
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Shared topics: Research tools and geospatial methods; Climate and greenhouse gases; Weather, hazards, and adaptation
This study showcases a machine learning hackathon in France where a CNN-based model accurately predicted flood risk evolution using geospatial and climate data, even without streamflow input, emphasizing trustworthy AI in data-scarce regions.
Shared topics: Research tools and geospatial methods; Climate and greenhouse gases; Weather, hazards, and adaptation
This study presents a new machine learning (Light Gradient Boosting Machine) approach to generate high-resolution, hourly maps of gross primary productivity (GPP) for East Asia (2020–2021). The paper highlights clear diurnal patterns across different land cover types and latitudes, offering valuable insights for ecosystem monitoring and carbon cycle modeling.
Shared topics: Research tools and geospatial methods; Climate and greenhouse gases; Weather, hazards, and adaptation
This study uses machine learning and geospatial analysis to assess how climate change has altered flood patterns in downstream Nigeria between 2018 and 2024, revealing shifts in flood frequency, intensity, and spatial distribution.
Shared topics: Research tools and geospatial methods; Climate and greenhouse gases; Weather, hazards, and adaptation
A new family of spatial-extent coefficients assesses extreme georeferenced events by measuring spatial spread from threshold exceedances, with a semiparametric model enabling statistical extrapolation, demonstrated through simulations and gridded temperature data in France.