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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).
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