Build a Wildfire Atmospheric Vapor Pressure Deficit Modeler
Model atmospheric drying extremes using ERA5 surface temperature and dewpoint reanalysis grids. Quantify multi-day vapor pressure deficit anomalies to evaluate parametric wildfire season ignition risk.
What you are building
The core problem, expected build, and operating context for this challenge.
Model atmospheric drying extremes using ERA5 surface temperature and dewpoint reanalysis grids. Quantify multi-day vapor pressure deficit anomalies to evaluate parametric wildfire season ignition risk.
Forestry Risk Analyst
Extract 2m temperature and 2m dewpoint temperature fields from ERA5 CDS datasets.
Compute saturation and actual vapor pressure to derive daily Vapor Pressure Deficit (VPD).
Identify prolonged consecutive days exceeding 95th percentile VPD thresholds.
Generate a parametric trigger performance report illustrating historical payout distributions.
Interactive CLI with ASCII charts and structured JSON outputs detailing VPD anomaly timelines.
Use cdsapi to retrieve 2m temperature and dewpoint data, or process synthetic multi-day meteorological arrays. Starter examples below are synthetic. They are not downloaded records.
Copernicus Climate Data Store client Extracts temperature and dewpoint variables using cdsapi retrieve queries for ERA5 reanalysis single levels.
optuna, cdsapi, scipy. Optuna optimizes trigger thresholds to balance basis risk against historical fire occurrences. Open-source local LLM or hosted Claude to generate parametric sensitivity summaries.
Submit runnable source, pinned dependencies, setup commands, a working interface, example outputs, and a recorded end-to-end demo. Include tests and an action log.
Accurately computes saturation vapor pressure using standard Tetens formula.
Computes daily maximum vapor pressure deficit (VPD) in kilopascals.
Identifies periods where continuous extreme drying exceeds defined contract duration.
```json [ { "input": { "forest_tract_id": "OR-TIMBER-04", "threshold_vpd_kpa": 3, "duration_days": 3, "vpd_daily_kpa": [ 2.8, 3.2, 3.5, 3.4, 2.1 ] }, "expected_output": { "forest_tract_id": "OR-TIMBER-04", "trigger_met": true, "max_consecutive_extreme_days": 3, "peak_vpd_kpa": 3.5 } }, { "input": { "forest_tract_id": "OR-TIMBER-05", "threshold_vpd_kpa": 3.5, "duration_days": 3, "vpd_daily_kpa": [ 2.8, 3.2, 3.4, 2.1 ] }, "expected_output": { "forest_tract_id": "OR-TIMBER-05", "trigger_met": false, "max_consecutive_extreme_days": 0, "peak_vpd_kpa": 3.4 } } ] ```
Outputs represent academic risk models and do not provide real-time forest fire warnings or binding contract payments. Use mock external writes. Require human review before any real deployment.
Participation guide
Outputs represent academic risk models and do not provide real-time forest fire warnings or binding contract payments. Use mock external writes and human review.
How work is evaluated
Accurately computes saturation vapor pressure using standard Tetens formula. Computes daily maximum vapor pressure deficit (VPD) in kilopascals. Identifies periods where continuous extreme drying exceeds defined contract duration.
Runnable source, pinned dependencies, setup commands, working interface, example outputs, recorded demo, tests, and action logs.
Challenge datasets
Public datasets, plus the private datasets you have access to.
How submissions are scored
These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.
Complete workflow
Extract 2m temperature and 2m dewpoint temperature fields from ERA5 CDS datasets. Compute saturation and actual vapor pressure to derive daily Vapor Pressure Deficit (VPD). Identify prolonged consecutive days exceeding 95th percentile VPD thresholds. Generate a parametric trigger performance report illustrating historical payout distributions.
Missing or incorrect.
Partly complete, with documented gaps.
Complete, with reproducible evidence.
Correctness and evidence
Accurately computes saturation vapor pressure using standard Tetens formula. Computes daily maximum vapor pressure deficit (VPD) in kilopascals. Identifies periods where continuous extreme drying exceeds defined contract duration.
Missing or incorrect.
Partly complete, with documented gaps.
Complete, with reproducible evidence.
Review interface
Interactive CLI with ASCII charts and structured JSON outputs detailing VPD anomaly timelines.
Missing or incorrect.
Partly complete, with documented gaps.
Complete, with reproducible evidence.
Safe execution
Outputs represent academic risk models and do not provide real-time forest fire warnings or binding contract payments.
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
What you should walk away with
Extract 2m temperature and 2m dewpoint temperature fields from ERA5 CDS datasets.
Compute saturation and actual vapor pressure to derive daily Vapor Pressure Deficit (VPD).
Identify prolonged consecutive days exceeding 95th percentile VPD thresholds.
Generate a parametric trigger performance report illustrating historical payout distributions.
Reference links and supporting material
Use cdsapi to retrieve 2m temperature and dewpoint data, or process synthetic multi-day meteorological arrays. Supplied starter examples are synthetic, not source extracts.
Challenge setup
Configuration summary for this challenge.
Challenge input
Input details are not configured.
Optuna
Hyperparameter Optimization
Evaluated output
No output checks are configured.
- Extract 2m temperature and 2m dewpoint temperature fields from ERA5 CDS datasets. Compute saturation and ac...
- Accurately computes saturation vapor pressure using standard Tetens formula. Computes daily maximum vapor p...
- Interactive CLI with ASCII charts and structured JSON outputs detailing VPD anomaly timelines.
- 2 public reference cases
- 1 configured tool
Summary shows the first task, up to three tools, and up to three evidence items. Open the technical recipe to view all configured items.
View technical recipe
Configured tools
- Optuna · Optional
Evaluation contract
- Complete workflow · Weight 40
- Correctness and evidence · Weight 30
- Review interface · Weight 20
- Safe execution · Weight 10
Reference cases
- 2 public reference cases
Workflow tasks
No workflow tasks are configured.
Recipe freeze marker
No recipe freeze time is recorded.