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Challenge

Build an Agricultural Drought Parametric Index Simulator

Simulate parametric drought contract settlement thresholds using ECMWF ERA5 reanalysis precipitation datasets. Model historical payout triggers and calculate contract basis risk for regional crop cooperatives.

Data ScienceHosted by Vera
Challenge brief

What you are building

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

Simulate parametric drought contract settlement thresholds using ECMWF ERA5 reanalysis precipitation datasets. Model historical payout triggers and calculate contract basis risk for regional crop cooperatives.

Agricultural Risk Analyst

Ingest ERA5 daily total precipitation grids via Copernicus CDS client.

Compute cumulative rainfall deficit indices against seasonal historical baselines.

Simulate parametric threshold breach scenarios across multi-year intervals.

Generate basis risk reports contrasting simulated triggers with crop stress logs.

Multi-year simulation dashboard plotting cumulative precipitation curves, trigger thresholds, and parametric settlement timelines.

Use cdsapi client to pull monthly or daily ERA5 reanalysis single levels for localized coordinates, or replay local mock NetCDF/GRIB fixtures. Starter examples below are synthetic. They are not downloaded records.

Copernicus Climate Data Store client Uses cdsapi.Client retrieve interface targeting reanalysis-era5 single levels with variable parameter 'total_precipitation'.

mlflow, cdsapi, xarray, numpy. Tracks parametric trigger simulation parameters, threshold variations, and basis risk metrics across runs. Local Python analytics runtime paired with hosted Claude or OpenAI API for synthetic report summarization.

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.

cdsapi retrieve query parameters match valid CDS API syntax.

Simulation accurately detects cumulative rainfall breach points.

Logs all contract runs and trigger metrics to MLflow experiment tracking.

```json [ { "input": { "contract_id": "AGRI-PARAM-DROUGHT-01", "region": "CornBelt-West", "trigger_threshold_mm": 120, "season_total_precip_mm": 88.5, "historical_mean_mm": 210 }, "expected_output": { "contract_id": "AGRI-PARAM-DROUGHT-01", "trigger_breached": true, "deficit_severity": "SEVERE", "simulated_payout_ratio": 1, "basis_risk_indicator": "LOW" } }, { "input": { "contract_id": "AGRI-PARAM-DROUGHT-02", "region": "CornBelt-East", "trigger_threshold_mm": 120, "season_total_precip_mm": 135.2, "historical_mean_mm": 205 }, "expected_output": { "contract_id": "AGRI-PARAM-DROUGHT-02", "trigger_breached": false, "deficit_severity": "MILD", "simulated_payout_ratio": 0, "basis_risk_indicator": "MODERATE" } } ] ```

Outputs simulated parametric settlement indicators; executes no actual financial transfers or legal underwriting binds. Use mock external writes. Require human review before any real deployment.

Rules

Participation guide

Outputs simulated parametric settlement indicators; executes no actual financial transfers or legal underwriting binds. Use mock external writes and human review.

Delivery guide

How work is evaluated

Evaluation

cdsapi retrieve query parameters match valid CDS API syntax. Simulation accurately detects cumulative rainfall breach points. Logs all contract runs and trigger metrics to MLflow experiment tracking.

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

Ingest ERA5 daily total precipitation grids via Copernicus CDS client. Compute cumulative rainfall deficit indices against seasonal historical baselines. Simulate parametric threshold breach scenarios across multi-year intervals. Generate basis risk reports contrasting simulated triggers with crop stress logs.

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

cdsapi retrieve query parameters match valid CDS API syntax. Simulation accurately detects cumulative rainfall breach points. Logs all contract runs and trigger metrics to MLflow experiment tracking.

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

Multi-year simulation dashboard plotting cumulative precipitation curves, trigger thresholds, and parametric settlement 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 simulated parametric settlement indicators; executes no actual financial transfers or legal underwriting binds.

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

  • Ingest ERA5 daily total precipitation grids via Copernicus CDS client.

  • Compute cumulative rainfall deficit indices against seasonal historical baselines.

  • Simulate parametric threshold breach scenarios across multi-year intervals.

  • Generate basis risk reports contrasting simulated triggers with crop stress logs.

Resources and assets

Reference links and supporting material

Dataset notes

Use cdsapi client to pull monthly or daily ERA5 reanalysis single levels for localized coordinates, or replay local mock NetCDF/GRIB fixtures. 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
  • Ingest ERA5 daily total precipitation grids via Copernicus CDS client. Compute cumulative rainfall deficit...
  • cdsapi retrieve query parameters match valid CDS API syntax. Simulation accurately detects cumulative rainf...
  • Multi-year simulation dashboard plotting cumulative precipitation curves, trigger thresholds, and parametri...
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 an Agricultural Drought Parametric Index Simulator