Global Mars Atmosphere–Dust Coupled Data Assimilation Oriented to the China’s Sample Return Mission Tianwen-3

Accurate forecasting of Martian dust is essential for the success of landing operations, 18 as dust storms can cause actuator jamming and power loss. This study establishes a dust-oriented environmental forecasting system based on China’s Global Open Planetary Atmospheric Model for Mars (GoMars). Its key innovation is a physically consistent nudging scheme that first updates the model's prognostic dust mass and number concentrations by assimilating observed column dust optical depth (CDOD). These updated concentrations then drive the optimization of the atmospheric state through the fully coupled dust–radiation–dynamics processes. Validation against InSight surface pressure data confirms the system's ability to translate dust radiative forcing into realistic atmospheric response, even from a "cold start" without reanalysis initialization. Over 13 Martian years (MY25–37), the system yields analyses of temperature, zonal wind, and CDOD that are highly consistent with the benchmark OpenMARS reanalysis. Retrospective 20-sol forecasts exhibit stable skill, achieving an average CDOD RMSE of 0.032 in the Tianwen-3 candidate landing zone, with performance further improved through early-season assimilation. The system also accurately reproduces the diurnal temperature phase observed by the Perseverance rover, confirming its capability to predict high-frequency surface variability critical to lander safety. This work validates a dust-driven forecasting paradigm for Mars, demonstrating that directly constraining the primary force enables accurate environmental prediction. The system provides a reliable forecasting capability for the Tianwen-3 mission, whose performance can be further enhanced by future orbital dust monitoring with improved spatiotemporal coverage.