annotations_creators:

• machine-generated language_creators:
• machine-generated languages: [] licenses:
• mit multilinguality: [] pretty_name: Mutli-Radar/Multi-System Precipitation Radar size_categories:
• 1M<n<10M source_datasets:
• original task_categories:
• time-series-forecasting
• image-classification
• image-segmentation
• other task_ids:
• univariate-time-series-forecasting
• multi-label-image-classification
• semantic-segmentation

Dataset Card for MRMS

Dataset Summary

Multi-Radar/Multi-System Precipitation Rate Radar data for 2016-2022. This data contains precipitation rate values for the continental United States.

Supported Tasks and Leaderboards

[Needs More Information]

Languages

[Needs More Information]

Dataset Structure

Data Instances

[Needs More Information]

Data Fields

[Needs More Information]

Data Splits

[Needs More Information]

Dataset Creation

Curation Rationale

This dataset was constructed to help recreate the original dataset used for MetNet/MetNet-2 as well as Deep Generative Model of Radar papers. The datasets were not pubicly released, but this dataset should cover the time period used plus more compared to the datasets in the papers.

Source Data

Initial Data Collection and Normalization

[Needs More Information]

Who are the source language producers?

[Needs More Information]

Annotations

Annotation process

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Who are the annotators?

[Needs More Information]

Personal and Sensitive Information

[Needs More Information]

Considerations for Using the Data

Social Impact of Dataset

[Needs More Information]

Discussion of Biases

[Needs More Information]

Other Known Limitations

[Needs More Information]

Additional Information

Dataset Curators

[Needs More Information]

Licensing Information

US Government License, no restrictions

Citation Information

@article(ocf:mrms, author = {Jacob Bieker} title = {MRMS Precipitation Rate Dataset} year = {2022} }