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Challenge

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.

Data ScienceHosted by Vera
Challenge brief

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.

Rules

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.

Delivery guide

How work is evaluated

Evaluation

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.

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

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.

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

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.

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

Interactive CLI with ASCII charts and structured JSON outputs detailing VPD anomaly timelines.

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

Outputs represent academic risk models and do not provide real-time forest fire warnings or binding contract payments.

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

  • 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.

Resources and assets

Reference links and supporting material

Dataset notes

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.

Evaluation checks
  • 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.
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 a Wildfire Atmospheric Vapor Pressure Deficit Modeler