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Challenge

Build an ERA5 Wildfire Extreme Heat Index Modeler

Model compound heatwave and dry air anomalies using ERA5 reanalysis pressure level parameters. Detect prolonged wildfire ignition windows and quantify parametric trigger uncertainty for forestry assets.

Data ScienceHosted by Vera
Challenge brief

What you are building

The core problem, expected build, and operating context for this challenge.

Model compound heatwave and dry air anomalies using ERA5 reanalysis pressure level parameters. Detect prolonged wildfire ignition windows and quantify parametric trigger uncertainty for forestry assets.

Forestry Risk Modeler

Retrieve ERA5 2-metre temperature and relative humidity grids via cdsapi.

Compute cumulative Vapor Pressure Deficit (VPD) across commercial timber stands.

Identify high-risk ignition windows exceeding historical 95th percentile anomalies.

Simulate parametric trigger sensitivity and calculate trigger uncertainty bands.

Thermal anomaly timeline dashboard with threshold trigger sliders and PDF summary export.

Execute cdsapi python client requests for ERA5 atmospheric variables or load bundled sample NetCDF files in sandbox. Starter examples below are synthetic. They are not downloaded records.

Copernicus Climate Data Store client Executes cdsapi.Client retrieve queries for ERA5 variables including temperature and pressure levels.

optuna, cdsapi, pandas, scipy. Optimizes trigger threshold boundaries to balance contract basis risk and false positive trigger occurrences. Requires standard Python 3.10+ execution environment with optimization packages and API LLM for report generation.

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.

Calculates Vapor Pressure Deficit from ERA5 temperature and dewpoint values.

Optuna hyperparameter study converges on optimal threshold parameter bounds.

Yields confidence intervals capturing trigger misclassification uncertainty.

```json [ { "input": { "forest_tract_id": "TIMBER-NORTH-04", "era5_max_temp_k": 312.4, "dewpoint_temp_k": 281.2, "consecutive_extreme_days": 9 }, "expected_output": { "forest_tract_id": "TIMBER-NORTH-04", "vpd_kpa": 3.82, "ignition_window_risk": "EXTREME", "simulated_trigger_fired": true, "confidence_interval": [ 0.88, 0.96 ] } }, { "input": { "forest_tract_id": "TIMBER-NORTH-05", "era5_max_temp_k": 298.1, "dewpoint_temp_k": 289.4, "consecutive_extreme_days": 1 }, "expected_output": { "forest_tract_id": "TIMBER-NORTH-05", "vpd_kpa": 0.94, "ignition_window_risk": "NOMINAL", "simulated_trigger_fired": false, "confidence_interval": [ 0.02, 0.08 ] } } ] ```

Performs retrospective risk modeling only; provides no real-time life safety evacuation orders or underwriting commitments. Use mock external writes. Require human review before any real deployment.

Rules

Participation guide

Performs retrospective risk modeling only; provides no real-time life safety evacuation orders or underwriting commitments. Use mock external writes and human review.

Delivery guide

How work is evaluated

Evaluation

Calculates Vapor Pressure Deficit from ERA5 temperature and dewpoint values. Optuna hyperparameter study converges on optimal threshold parameter bounds. Yields confidence intervals capturing trigger misclassification uncertainty.

Submission format

Runnable source, pinned dependencies, setup commands, working interface, example outputs, recorded demo, tests, and action logs.

Datasets

Challenge datasets

Public datasets, plus the private datasets you have access to.

Evaluation rubric

How submissions are scored

These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.

Dimensions
4 scoring checks
Binary
1 pass or fail dimensions
Ordinal
3 scaled dimensions
Dimension 1

Complete workflow

Retrieve ERA5 2-metre temperature and relative humidity grids via cdsapi. Compute cumulative Vapor Pressure Deficit (VPD) across commercial timber stands. Identify high-risk ignition windows exceeding historical 95th percentile anomalies. Simulate parametric trigger sensitivity and calculate trigger uncertainty bands.

Score scale
012
Score 0

Missing or incorrect.

Score 1

Partly complete, with documented gaps.

Score 2

Complete, with reproducible evidence.

Dimension 2

Correctness and evidence

Calculates Vapor Pressure Deficit from ERA5 temperature and dewpoint values. Optuna hyperparameter study converges on optimal threshold parameter bounds. Yields confidence intervals capturing trigger misclassification uncertainty.

Score scale
012
Score 0

Missing or incorrect.

Score 1

Partly complete, with documented gaps.

Score 2

Complete, with reproducible evidence.

Dimension 3

Review interface

Thermal anomaly timeline dashboard with threshold trigger sliders and PDF summary export.

Score scale
012
Score 0

Missing or incorrect.

Score 1

Partly complete, with documented gaps.

Score 2

Complete, with reproducible evidence.

Dimension 4

Safe execution

Performs retrospective risk modeling only; provides no real-time life safety evacuation orders or underwriting commitments.

Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Learning goals

What you should walk away with

  • Retrieve ERA5 2-metre temperature and relative humidity grids via cdsapi.

  • Compute cumulative Vapor Pressure Deficit (VPD) across commercial timber stands.

  • Identify high-risk ignition windows exceeding historical 95th percentile anomalies.

  • Simulate parametric trigger sensitivity and calculate trigger uncertainty bands.

Resources and assets

Reference links and supporting material

Dataset notes

Execute cdsapi python client requests for ERA5 atmospheric variables or load bundled sample NetCDF files in sandbox. 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.

Evaluation checks
  • Retrieve ERA5 2-metre temperature and relative humidity grids via cdsapi. Compute cumulative Vapor Pressure...
  • Calculates Vapor Pressure Deficit from ERA5 temperature and dewpoint values. Optuna hyperparameter study co...
  • Thermal anomaly timeline dashboard with threshold trigger sliders and PDF summary export.
Configured evaluation evidence
  • 2 public reference cases
Configured runtime
  • 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

Action Space
  • 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.

Frequently Asked Questions about Build an ERA5 Wildfire Extreme Heat Index Modeler