Skip to main content
Challenge

Build a Reanalysis Heatwave Parametric Trigger Simulator

Simulate parametric heat index trigger performance for agricultural contracts using ERA5 reanalysis thermal datasets. Model historical trigger frequencies and calculate simulated seasonal payouts.

Data ScienceHosted by Vera
Challenge brief

What you are building

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

Simulate parametric heat index trigger performance for agricultural contracts using ERA5 reanalysis thermal datasets. Model historical trigger frequencies and calculate simulated seasonal payouts.

Parametric Product Structurer

Define parametric trigger rules with temperature thresholds and duration days.

Retrieve ERA5 daily temperature series via Copernicus CDS client scripts.

Calculate continuous degree-day exceedances over contract active windows.

Output simulated trigger events with uncertainty intervals for actuary review.

Jupyter Notebook interface with parametric trigger configuration and exceedance plot charts.

Execute CDS API queries for ERA5 reanalysis pressure levels or use cached mock NetCDF/GRIB temperature records. Starter examples below are synthetic. They are not downloaded records.

Copernicus Climate Data Store client Leverages the CDS API retrieval parameter structure (variable, product_type, date, format) for reanalysis-era5 datasets.

mlflow, cdsapi, xarray, numpy. MLflow tracks simulation run parameters, threshold variants, and payout distribution metrics across trial batches. Local numeric compute environment with optional local LLM to summarize simulation run parameters.

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.

Properly constructs CDS API retrieval request dictionaries.

Identifies consecutive days exceeding the specified parametric trigger threshold.

Calculates simulated payout percentage without creating real policy liabilities.

```json [ { "input": { "contract_id": "PAR-HEAT-2024", "threshold_temp_k": 308.15, "duration_days": 3, "series": [ 309, 308.5, 309.2, 305 ] }, "expected_output": { "contract_id": "PAR-HEAT-2024", "triggered": true, "consecutive_exceedance": 3, "simulated_payout_pct": 100 } }, { "input": { "contract_id": "PAR-HEAT-2025", "threshold_temp_k": 310, "duration_days": 3, "series": [ 309, 308.5, 307, 306 ] }, "expected_output": { "contract_id": "PAR-HEAT-2025", "triggered": false, "consecutive_exceedance": 0, "simulated_payout_pct": 0 } } ] ```

Outputs simulated parametric scenarios only; explicitly disclaims commercial policy underwriting validity. Use mock external writes. Require human review before any real deployment.

Rules

Participation guide

Outputs simulated parametric scenarios only; explicitly disclaims commercial policy underwriting validity. Use mock external writes and human review.

Delivery guide

How work is evaluated

Evaluation

Properly constructs CDS API retrieval request dictionaries. Identifies consecutive days exceeding the specified parametric trigger threshold. Calculates simulated payout percentage without creating real policy liabilities.

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

Define parametric trigger rules with temperature thresholds and duration days. Retrieve ERA5 daily temperature series via Copernicus CDS client scripts. Calculate continuous degree-day exceedances over contract active windows. Output simulated trigger events with uncertainty intervals for actuary review.

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

Properly constructs CDS API retrieval request dictionaries. Identifies consecutive days exceeding the specified parametric trigger threshold. Calculates simulated payout percentage without creating real policy liabilities.

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

Jupyter Notebook interface with parametric trigger configuration and exceedance plot charts.

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 simulated parametric scenarios only; explicitly disclaims commercial policy underwriting validity.

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

  • Define parametric trigger rules with temperature thresholds and duration days.

  • Retrieve ERA5 daily temperature series via Copernicus CDS client scripts.

  • Calculate continuous degree-day exceedances over contract active windows.

  • Output simulated trigger events with uncertainty intervals for actuary review.

Resources and assets

Reference links and supporting material

Dataset notes

Execute CDS API queries for ERA5 reanalysis pressure levels or use cached mock NetCDF/GRIB temperature records. Supplied starter examples are synthetic, not source extracts.

Challenge setup

Configuration summary for this challenge.

Challenge input

Input details are not configured.

MLflow

MLOps

Evaluated output

No output checks are configured.

Evaluation checks
  • Define parametric trigger rules with temperature thresholds and duration days. Retrieve ERA5 daily temperat...
  • Properly constructs CDS API retrieval request dictionaries. Identifies consecutive days exceeding the speci...
  • Jupyter Notebook interface with parametric trigger configuration and exceedance plot charts.
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
  • MLflow · 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 Reanalysis Heatwave Parametric Trigger Simulator