Article

Graph-Based Learning for Multi-Horizon Martian Atmospheric Forecasting

2026-06-22

Abstract excerpt

<title>Abstract</title> <p>Purpose. Martian weather forecasting is important for future exploration, but atmospheric behaviour on Mars combines spatial, temporal, vertical, and dust-driven processes in ways that challenge current modelling and forecasting approaches. Existing machine learning studies often reduce this structure to local time series, which limits their ability to capture wider atmospheric dynamics...

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Literature Corpus work: 3d4c3f2a-a5d1-534c-bab1-3ab9e2ace7d8
DOI: 10.21203/rs.3.rs-9943010/v1

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