agrimanager/weather_pool_maize

WOFOST Maize Weather Pool

This repository contains the maize-only WOFOST-Gym weather-scenario pool used by AgriManager maize benchmark experiments. Each parquet row is a scenario key, not a full rollout trajectory: the crop is fixed to maize, and the year, latitude, and longitude columns identify the weather scenario consumed by WOFOST-Gym at runtime.

Intended Use

Use this dataset for maize-only WOFOST-Gym training and validation tasks, including AgriManager action-menu, reward-formulation, and cross-simulator maize-transfer experiments that need a compact fixed weather pool.

This dataset is not intended to be a standalone meteorological benchmark, a global climate product, or a source of real crop yield labels.

Provenance

• Parent pool: agrimanager/wofost-weather-pool.
• Weather source: NASA POWER meteorological data, retrieved through PCSE's NASAPowerWeatherDataProvider.
• Simulator/runtime source: WOFOST-Gym, PCSE, and WOFOST.
• Derived artifact: AgriManager selected the maize shard from the parent WOFOST weather pool and repackaged the associated PCSE weather cache archive.
• Ownership statement: this dataset does not claim ownership of NASA POWER, WOFOST, PCSE, or WOFOST-Gym.

Synthetic Data Status

croissant_rai.json sets rai:hasSyntheticData to true. The meteorological inputs are derived from NASA POWER weather data, but the released benchmark rows are generated and simulator-derived WOFOST-Gym scenario keys inherited from the parent WOFOST weather pool and curated into fixed maize train and validation splits. This disclosure applies to the benchmark scenarios and splits, not to the underlying NASA POWER source data.

Crop

The pool contains one crop shard:

maize.

The maize generation config uses:

• generation_seed: 42
• year_range: [1984, 2019]
• latitude_range: [39.0, 49.0]
• longitude_range: [-10.0, 30.0]
• min_dvs_threshold: 1.5

Files

Path	Rows	Description
train/maize.parquet	3,200	Maize training weather scenarios from the parent train split.
val/maize.parquet	640	Combined maize validation pool.
pool_manifest.json	n/a	Machine-readable manifest for this maize-only derivative: crop, schema version, parent pool, split files, source splits, and row counts.
meteo_cache.tar.gz	n/a	Bundled PCSE/NASA POWER cache files required by the scenarios.
croissant_rai.json	n/a	Croissant JSON-LD metadata with core fields and Responsible AI metadata.

The val split combines two parent-pool sources:

• 128 rows from the parent val/maize.parquet,
• 512 rows from the parent test/maize.parquet.

There is no separate test split in this maize-only repository.

pool_manifest.json is the file-level provenance record for this derived pool. It records that train/maize.parquet comes from the parent train split and that val/maize.parquet is a combined validation artifact constructed from parent validation and held-out maize rows.

Schema

All crop parquet files use the same schema:

Column	Type	Units	Description
year	int64	calendar year	Year passed into the WOFOST agromanagement/weather scenario.
latitude	float64	decimal degrees	Scenario latitude, rounded to 2 decimal places.
longitude	float64	decimal degrees	Scenario longitude, rounded to 2 decimal places.

The crop label is fixed to maize by repository scope and file name. The split label is encoded by the parent directory. The parquet files do not contain raw daily weather variables or rollout rewards.

Croissant Metadata

croissant_rai.json is the completed Croissant JSON-LD metadata file for this dataset. It contains the core Croissant metadata fields and the Responsible AI metadata fields used for NeurIPS 2026 Evaluations & Datasets review, including dataset limitations, data biases, personal or sensitive information, intended use cases, social impact, synthetic-data status, source datasets, and provenance activities.

Weather Cache

meteo_cache.tar.gz contains the PCSE NASAPowerWeatherDataProvider cache files needed by these rows. The AgriManager runtime helper agrimanager.env.wofost_gym.weather_pool.ensure_pool() downloads or locates the dataset and extracts this archive before WOFOST-Gym execution.

The cache is included so reviewers and users can:

• run the exact same weather scenarios without re-downloading from NASA POWER,
• avoid NASA POWER API failures, rate limits, or future data/version drift,
• reproduce WOFOST-Gym runs from the fixed scenario rows, and
• load the pool through AgriManager's runtime helper without manually preparing PCSE weather files.

The packaging script includes cache files for each scenario year plus a one-year padding window on both sides (year_padding=1) so WOFOST-Gym has the weather context required around each season.

Generation and Filtering

The experiment configs consume this materialized Hugging Face weather pool; they do not recompute the source-level filtering logic at training time.

The parent maize shard was generated with the AgriManager weather-pool builder:

python integrations/wofost_gym/dataset_tools/build_weather_pool.py \
  pool_crop_maize \
  --output-dir <weather_pool_dir> \
  --num-workers 32

python integrations/wofost_gym/dataset_tools/package_weather_pool.py \
  --pool-dir <weather_pool_dir> \
  --clean \
  --year-padding 1

Weather validation runs a no-op WOFOST-Gym episode for each sampled scenario and keeps only scenarios where:

• weather data can be loaded completely through PCSE/NASA POWER,
• the crop reaches at least min_dvs_threshold: 1.5, and
• the crop produces non-zero storage organ biomass (max WSO > 0).

Equivalently, the maize weather pool uses the same WOFOST viability filter as the 20-crop weather pool:

weather_complete(s) and max_DVS(s) >= 1.5 and max_WSO(s) > 0

Failed scenarios are retried and replaced. Scenario keys are deduplicated by (crop, year, latitude, longitude).

WOFOST maize experiments draw from this pool and then render the same base weather rows under the experiment-specific observation schema, action menu, reward formulation, or simulator-transfer setting.

Split Construction and Leakage Prevention

The parent WOFOST weather pool uses deterministic split-specific RNG streams derived from generation_seed: 42:

• train uses seed 42,
• validation uses seed 43,
• test uses seed 44.

The maize-only repository preserves the parent train rows and combines the parent validation and test rows into a single val split for experiments that do not expose a separate test split. Within the parent pool, train, validation, and test are generated as non-overlapping scenario keys by (crop, year, latitude, longitude).

Limitations

• The pool is simulator-oriented: it contains scenario keys and cache files for WOFOST-Gym, not observed management decisions or measured crop yields.
• The geographic window is a benchmark design choice for maize WOFOST-Gym experiments, not a claim about the full global maize-growing region.
• The WOFOST viability filter removes scenarios that fail simulator completeness or maturity/yield checks, so the pool is not an unbiased sample of all NASA POWER grid cells.
• This repository intentionally has no separate test split. Use the full parent pool if a distinct parent test/maize.parquet split is required.
• Reproduction requires compatible versions of AgriManager, WOFOST-Gym, PCSE, and their crop configuration files.

Size and Inspection Sample

The current downloadable meteo_cache.tar.gz runtime artifact for this repository resolves to 250,170,776 bytes, which is under 4 GB. The tabular scenario files are small parquet files and are previewable through the Hugging Face dataset viewer.

Because the current hosted dataset files and runtime cache artifact are under the NeurIPS 4 GB inspection-sample threshold, this repository does not require a separate size-triggered small inspection sample. Users can inspect the parquet scenario rows directly and download the full cache artifact for reproduction.

License

This dataset is released under the CC-BY-4.0 license.

Users may share and adapt the dataset with appropriate attribution.

Citation

If you use this dataset, cite the accompanying AgriManager benchmark paper or code release, NASA POWER, the parent agrimanager/wofost-weather-pool dataset, and the upstream WOFOST-Gym/PCSE/WOFOST software used to execute the scenarios.