Conceptio › Archive › Infoscience
Infoscience metadata only

A Deep-Learning Parameterization of Vertical Velocity Variability (Wnet) Tested Across Contrasting Atmospheric Regimes: From the Arctic to the Mediterranean

Irfan, Muhammed et al.
Infoscience · Papers
Open Source ↗
engineeringsciencetechnology
Subgrid-scale vertical velocity variability (σw) plays a key role in aerosol activation, cloud droplet number concentration (CDNC), and cloud microphysical evolution. Despite its importance, σw remains one of the highly uncertain parameters in climate models, particularly under extreme atmospheric c
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

Record · ID 1492865
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