Synthetic methane plume bank generated from WRF-LES 4.7.0 atmospheric simulations (Gorroño et al., Zenodo doi:10.5281/zenodo.18161182). Contains 1,064,448 ΔXCH4 maps [mol/mol] at 20m resolution spanning 11 wind speeds, 12 wind directions, 9 multisource and 5 areasource plume geometries, 3 temporal snapshots, 8 Solar Zenith Angles, and 24 Solar Azimuth Angles. All plumes are normalized to a reference emission rate of 3000 kg/h and scale linearly. Intended for synthetic data augmentation in satellite-based methane plume detection models.
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Hierarchical structure showing representative samples across levels. The "..." notation indicates additional samples following the same pattern. All samples at the same level share identical structure (RSUT constraint).
| Level | Types | Total Samples | Sample IDs (preview) |
|---|---|---|---|
| Level 0 | All FILE |
1,064,448 | Root level samples |
These fields are available for querying with SQL when using TacoReader.
| Field Name | Type | Description |
|---|---|---|
| id | string | Unique sample identifier within parent scope. Must be unique among siblings. |
| type | string | Sample type discriminator (FILE or FOLDER). |
| methane:source_type | string | Simulation type: 'multi' (point sources) or 'area' (distributed) |
| methane:wind_speed | float | Geostrophic wind speed [m/s] |
| methane:wind_dir | int16 | Wind direction [degrees, 0=North] |
| methane:plume_id | int8 | Plume identifier (multi: 1-9, area: 1-5) |
| methane:snapshot | int16 | WRF-LES snapshot index (70, 90, or 110) |
| methane:sza | int8 | Solar Zenith Angle [degrees] |
| methane:saa | int16 | Solar Azimuth Angle [degrees, 0=North] |
| methane:q_ref | float | Reference emission rate [kg/h] — scale linearly for other rates |
| internal:current_id | int64 | Current sample position at this level (0-indexed). Enables O(1) random access and relational JOINs (ZIP, FOLDER, TACOCAT). |
| internal:parent_id | int64 | Foreign key referencing parent sample position in previous level (ZIP, FOLDER, TACOCAT). |
# pip install tacoreader
import tacoreader
# Load dataset
ds = tacoreader.load("methane-plume-bank.tacozip")
# Basic info
print(f"ID: {ds.id}")
print(f"Version: {ds.version}")
print(f"Samples: {len(ds.data)}")
| Name | Organization | |
|---|---|---|
| Cesar Aybar | Image and Signal Processing Group, University of Valencia | csaybar@uv.es |
If you use this dataset in your research, please cite:
@dataset{methane-plume-bank2,
title = {MethanePlumeBank: Synthetic Methane Plume Bank from WRF-LES Simulations},
author = {Cesar Aybar},
year = {2024},
version = {2.0.0},
publisher = {Image and Signal Processing Group, University of Valencia}
}