Hydroclimatic Projection: Statistical Learning And Downscaling Model For Rainfall And Runoff Forecasting
Shweta Kodihal; M. P. Akhtar; Satya Prakash Maurya · 2024-02-01
Climate change projections for the study area predict reduced rainfall and surface runoff, indicating a future water-stressed scenario, especially under SSP (Shared Socioeconomic Pathways) 4.5 and SSP 8.5 scenarios.
Shweta Kodihal; M. P. Akhtar; Satya Prakash Maurya. 2024-02-01. Hydroclimatic Projection: Statistical Learning And Downscaling Model For Rainfall And Runoff Forecasting. https://doi.org/10.2166/wcc.2024.562 (AI & Environment Resource Hub; record paper-095; collection snapshot 2026-09-15).
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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; 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.
Journal of Water and Climate Change
Shared topics: Climate and greenhouse gases; Water; Oceans and coasts
AI tools to support physical and digital technologies, enhancing monitoring, understanding, modeling, and forecasting of climate change, extreme events, and marine species management.
Aiforoceansfree
Shared topics: Climate and greenhouse gases; Water; 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.
