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README.md

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----
-license: cc-by-4.0
----
+---
+license: cc-by-4.0
+pretty_name: Thermur WRF-SFIRE Sample Data
+tags:
+- wildfire
+- simulation
+- climate
+- fire-dynamics
+- wrf-sfire
+size_categories:
+- n<1K
+---
+
+# Dataset Card for Thermur WRF-SFIRE Sample Data
+
+This dataset provides a sample from the Moisseeva (2020) WRF-SFIRE LES Synthetic Wildfire Plume Dataset, specifically curated for development and testing of the Thermur project - an imitation learning system for coordinating drone swarms in wildfire monitoring scenarios.
+
+## Dataset Details
+
+### Dataset Description
+
+This sample contains a representative slice of high-fidelity wildfire simulation data, capturing active fire spread with well-developed plume dynamics. The data represents minutes 3-4 of a 20-minute simulation, providing realistic thermal gradients and turbulence patterns essential for algorithm development.
+
+- **Curated by:** Thermur Project Contributors
+- **Original data by:** Nadya Moisseeva and Roland Stull (2020)
+- **Language(s) (NLP):** Not applicable (numerical simulation data)
+- **License:** CC-BY-4.0 (following original dataset license)
+
+### Dataset Sources
+
+- **Repository:** [Thermur Project](https://github.com/YOUR_USERNAME/Thermur)
+- **Paper:** [Original dataset publication](https://doi.org/10.20383/102.0314)
+- **Full dataset:** [FRDR Repository](https://www.frdr-dfdr.ca/repo/dataset/uuid:8f2e7e7a-5a95-4d5a-a93e-80e9e4f8f8f8)
+
+## Uses
+
+### Direct Use
+
+This dataset is intended for:
+- **Algorithm development**: Testing thermal navigation algorithms for autonomous agents
+- **Visualization development**: Creating 3D renderings of fire plumes and thermal fields
+- **Machine learning**: Training models to predict safe flight paths through fire environments
+- **Education**: Understanding wildfire dynamics and plume behavior
+
+### Out-of-Scope Use
+
+This dataset should **not** be used for:
+- Real-time wildfire response without validation on current conditions
+- Direct deployment to production drone systems without extensive testing
+- Climate modeling (single scenario only)
+- Predictive modeling of actual wildfire events
+
+## Dataset Structure
+
+The dataset contains a single NetCDF file (`samples.tar.gz` → `data/samples/wrf_sample.nc`) with the following structure:
+
+```
+Dimensions:
+  Time: 4 (timesteps at 15-second intervals)
+  bottom_top: 50 (vertical levels)
+  south_north: 250 (y-direction, 10 km)
+  west_east: 500 (x-direction, 20 km)
+  
+Variables:
+  - U, V, W: 3D wind velocity components (m/s)
+  - T: Perturbation potential temperature (K)
+  - P, PB: Perturbation and base pressure (Pa)
+  - QVAPOR: Water vapor mixing ratio (kg/kg)
+  - GRNHFX: Ground heat flux from fire (W/m²)
+  - FGRNHFX: Fine-mesh ground heat flux (W/m²)
+  - tr17_1: PM2.5-like passive tracer (μg/kg)
+```
+
+### Physical Scenario
+
+**Moderate-intensity wildfire**:
+- Wind: 5 m/s uniform horizontal (moderate breeze)
+- Fuel: Southern rough (dense brushy understory)
+- Fire intensity: ~10-20 MW/m fireline
+- Domain: 10 km × 20 km × 3 km
+- Resolution: 40 m horizontal, 4 m fire mesh
+
+## Dataset Creation
+
+### Curation Rationale
+
+This sample was extracted to provide a manageable dataset (468 MB) that still captures the essential complexity of wildfire plume dynamics. The selected timeframe (minutes 3-4) represents established fire behavior with active spread and well-developed thermal structures.
+
+### Source Data
+
+#### Data Collection and Processing
+
+The data comes from Large Eddy Simulations (LES) using WRF-SFIRE, a coupled atmosphere-fire modeling system. The original simulation:
+- Used real atmospheric profiles from North American soundings
+- Implemented Anderson fuel models for realistic fire behavior
+- Ran at 40m atmospheric resolution with 4m fire mesh refinement
+
+#### Who are the source data producers?
+
+Original simulations by Nadya Moisseeva and Roland Stull at the University of British Columbia, using WRF-SFIRE developed by NCAR and University of Colorado Denver.
+
+## Bias, Risks, and Limitations
+
+- **Single scenario**: This sample represents only one of 147 available scenarios
+- **Idealized conditions**: Simulations use simplified terrain (flat) and uniform fuels
+- **Temporal snapshot**: Only 1 minute of a 20-minute simulation
+- **Model limitations**: LES approximations may not capture all fine-scale turbulence
+
+### Recommendations
+
+- Use this data for algorithm development and testing only
+- Validate algorithms on multiple scenarios before deployment
+- Consider environmental variability not captured in this single sample
+- Combine with real-world data when available
+
+## Citation
+
+**BibTeX:**
+```bibtex
+@dataset{moisseeva2020wrfsfire,
+  author    = {Moisseeva, Nadya and Stull, Roland},
+  title     = {WRF-SFIRE LES Synthetic Wildfire Plume Dataset},
+  year      = {2020},
+  publisher = {Federated Research Data Repository},
+  doi       = {10.20383/102.0314},
+  url       = {https://doi.org/10.20383/102.0314}
+}
+```
+
+**APA:**
+Moisseeva, N., & Stull, R. (2020). WRF-SFIRE LES Synthetic Wildfire Plume Dataset. Federated Research Data Repository. https://doi.org/10.20383/102.0314
+
+## More Information
+
+For detailed variable descriptions, safety thresholds, and processing examples, see the full README included in the tar.gz file. The Thermur project documentation provides extensive examples of using this data for drone swarm coordination algorithms.