arXiv (All)
open access
AEGIS: Differentiable Mars Climate Model with Neural Closures
General circulation models (GCMs) are the primary tool for simulating planetary atmospheres. They play a vital role in understanding Mars's atmosphere, as forecasting its unique weather is mission-critical for operations such as entry, descent, and landing. Mars poses unusual challenges for these mo
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
- 3D Global Climate Simulations of Synthetic Mars Warming#1354235
- MarsCast: Transfer Learning of AI Weather Foundation Models to Planetary Atmospheres#429360
- Independent Verification of Mars-GRAM 2010 with Mars Climate Sounder Data#636155
- Improved Precipitation Variability in the Community Atmosphere Model through Implementation of a Neural-Network Deep Convection Scheme#1355329
- Graph-Based Learning for Multi-Horizon Martian Atmospheric Forecasting#1129644
Record · ID 1199355
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