| # FuXi-CFD Dataset |
|
|
| ## Overview |
|
|
| This dataset accompanies the paper: |
|
|
| **Reconstructing fine-scale 3D wind fields with terrain-informed machine learning** |
|
|
| It contains large-scale CFD-generated wind field simulations used for training and evaluating the FuXi-CFD model described in the paper. |
|
|
| The dataset includes over **12,000 cases**. |
|
|
| --- |
|
|
| ## Dataset Organization |
|
|
| The dataset is distributed as compressed archive files: |
|
|
| FuXi-CFD-dataset-part01.tar |
| FuXi-CFD-dataset-part02.tar |
| ... |
| FuXi-CFD-dataset-part13.tar |
|
|
| Each case follows the structure: |
|
|
| case_000001/ |
| inputs.npz |
| outputs.npz |
| |
| --- |
| |
| ## Inputs (inputs.npz) |
| |
| The `inputs.npz` file contains four variables: |
| |
| ### dem |
| |
| - Shape: (300, 300) |
| - Unit: meters (m) |
| - Horizontal resolution: 30 m |
| |
| Digital Elevation Model (DEM) representing terrain elevation. |
| |
| --- |
| |
| ### roughness |
| |
| - Shape: (300, 300) |
| - Unit: meters (m) |
| - Horizontal resolution: 30 m |
| |
| Surface roughness length (z₀) map representing aerodynamic terrain roughness. |
| |
| --- |
| |
| ### u_100m |
|
|
| - Shape: (9, 9) |
| - Unit: m s⁻¹ |
| - Horizontal resolution: approximately 1 km |
|
|
| Coarse-resolution zonal wind component at 100 m height. |
|
|
| --- |
|
|
| ### v_100m |
| |
| - Shape: (9, 9) |
| - Unit: m s⁻¹ |
| - Horizontal resolution: approximately 1 km |
| |
| Coarse-resolution meridional wind component at 100 m height. |
| |
| --- |
| |
| ## Outputs (outputs.npz) |
| |
| The `outputs.npz` file contains four high-resolution 3D variables. |
| |
| All output variables have shape: |
| |
| (27, 300, 300) |
| |
| where: |
| |
| - 27 corresponds to the number of vertical levels (in meters above ground level). |
| - 300 × 300 corresponds to 30 m horizontal resolution |
| |
| The 27 vertical levels are: |
| |
| 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, |
| 106.5, 114.95, 125.94, 140.22, 158.78, 182.91, 214.29 |
| |
| --- |
| |
| ### u |
| |
| - Unit: m s⁻¹ |
| |
| Zonal wind component (east–west). |
| |
| --- |
| |
| ### v |
| |
| - Unit: m s⁻¹ |
| |
| Meridional wind component (north–south). |
| |
| --- |
| |
| ### w |
| |
| - Unit: m s⁻¹ |
| |
| Vertical wind component. |
| |
| --- |
| |
| ### k |
| |
| - Unit: m² s⁻² |
| |
| Turbulent kinetic energy (TKE). |
| |
| --- |
| |
| ## Resolution Summary |
| |
| | Variable | Horizontal Resolution | Vertical Levels | |
| | -------------- | --------------------- | --------------- | |
| | dem | 30 m | — | |
| | roughness | 30 m | — | |
| | u_100m, v_100m | 1 km | single level | |
| | u, v, w, k | 30 m | 27 levels | |
| |
| --- |
| |
| ## Data Split |
| |
| The dataset is provided as a single collection without predefined splits. |
| |
| The official train/validation/test split used in the paper can be found in the associated publication. |
| |
| Users are free to define custom splits for their own applications. |
| |
| --- |
| |
| ## License |
| |
| CC BY-NC 4.0 |
| |
| --- |
| |
| ## Citation |
| |
| If you use this dataset, please cite: |
| |
| Lin, C., et al. *Reconstructing fine-scale 3D wind fields with terrain-informed machine learning*, Nature Communications (2026). |
| |