AI tools to support physical and digital technologies, enhancing monitoring, understanding, modeling, and forecasting of climate change, extreme events, and marine species management.
Aiforoceans. Date unknown. AI for Oceans. https://www.aiforoceans.org/ (AI & Environment Resource Hub; record atlas-75272289b702; collection snapshot 2026-09-15).
Classification and context
Included in the original Tool collection. Labels below are metadata based suggestions. They are not verified findings, claims of effectiveness, or endorsements.
Inclusion does not establish effectiveness, maintenance, or endorsement. Check access and current documentation. Source link reachable · checked 2026-09-15. Source identity and required metadata verified. The import date is not the original date added.
This study introduces a new foundation model based on the Prithvi-EO Vision Transformer, pre-trained on Sentinel-3 ocean color data, to enhance marine Earth observation. By fine-tuning on chlorophyll and primary production tasks, the model outperforms traditional baselines, showing that self-trained AI can extract detailed spatial patterns from limited labeled data and improve monitoring of ocean ecosystems and climate processes.
arXiv
Shared topics: Climate and greenhouse gases; Water; Biodiversity and ecosystems; Oceans and coasts
This study develops a deep learning–based coral identification and tracking algorithm for autonomous underwater vehicles, enabling real-time monitoring of reef health to support climate-informed conservation efforts.
Current Science
Shared topics: Climate and greenhouse gases; Water; Biodiversity and ecosystems; Oceans and coasts
This study highlights the impact of climate change on water balance in the Upper Bhima River, revealing reduced monsoon precipitation and baseflow sensitivity, with implications for agriculture, biodiversity, and water management.
Journal of Water and Climate Change
Shared topics: Climate and greenhouse gases; Water; Oceans and coasts
Severe flash floods in Charikar, Afghanistan, on August 26, 2020, were driven by extreme atmospheric instability, deep low-level convergence, and local topography, with climate change intensifying frontal activity and baroclinicity in the region.
