Advancing Mars space weather forecasting: multi-point validation during a major solar storm

As Mars becomes a key target for sustained robotic and future human missions, reliable space weather forecasting is increasingly critical. This study presents the first practical, validated predictive plasma modeling at Mars, using simultaneous multi-point observations during both an extreme solar storm and a relatively quiet period. The physics based global model accurately reproduces the key plasma and magnetic features of the near-Mars environment, from the magnetosheath to the ionosphere, with unprecedented agreement to MAVEN and Tianwen-1 magnetometer data (normalized root mean square error <15%). It also captures the dynamic Martian current system, shaped by the interplanetary magnetic field and the rotating crustal fields, which particularly affects the tail current configuration. This work marks a crucial step toward practical space weather forecasting at Mars.
, , # Advancing Mars space weather forecasting: multi-point validation during a major solar storm

Dataset DOI: [10.5061/dryad.bnzs7h4q8](https://doi.org/10.5061/dryad.bnzs7h4q8)

**Description of the data and file structure**

**File: Fig1_2_sat_TW20240517_18_n000000.sat**

**Description:** ascii file for MHD model results along Tianwen-1 orbit for Event1.

VARIABLES=\"it\" \"Year\" \"mn\" \"day\" \"hour\" \"min\" \"Sec\" \"ms\" \"X [R]\" \"Y [R]\" \"Z [R]\" \"`r [amu/cm^3]\"  \"`r^H^p [amu/cm^3]\" \"`r^O^2^p [amu/cm^3]\" \"`r^O^p [amu/cm^3]\" \"`r^C^O^2^p [amu/cm^3]\" \"U_x [km/s]\" \"U_y [km/s]\" \"U_z [km/s]\"\"B_x [nT]\" \"B_y [nT]\" \"B_z [nT]\" \"p [nPa]\" \"B1_x [nT]\" \"B1_y [nT]\" \"B1_z [nT]\" \"e\" \"J_x [`mA/m^2]\" \"J_y [`mA/m^2]\" \"J_z [`mA/m^2]\"

Of these variables:

* **it** — iteration number
* **Year, mn, day, hour, min, Sec, ms** — date and time (year, month, day, hour, minute, second, millisecond)

- **X [R], Y [R], Z [R]** — position in the MSO coordinate system
- **r [amu/cm³]** — total mass density
- \"`r^H^p [amu/cm^3]\" \"`r...,