PubMed
open access
Dust storms: Hidden drivers of extreme rainfall and global precipitation shifts.
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Replication Package - Physics-Informed Machine Learning for Extreme Rainfall Nowcasting: A Rapid Review Toward Sustainable Early Warning Systems#212907
- 15 U.S.C. § 9707 — Estimates of precipitation frequency in the United States#565247
- Integrating IMDAA Regional Reanalysis and Machine Learning for Enhanced Detection of Extreme Precipitation Over Complex Himalayan Terrain#621163
- A dataset of one-dimensional idealized probabilistic fields#1061355
- Supporting Code and Data for "MAUSAM: An Observations-focused assessment of Global AI Weather Prediction Models During the South Asian Monsoon"#126987
Record · ID 146198
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive