[Needs More Information]

# Dataset Card for GFS-Reforecast

## Table of Contents
- [Dataset Description](#dataset-description)
  - [Dataset Summary](#dataset-summary)
  - [Supported Tasks](#supported-tasks-and-leaderboards)
  - [Languages](#languages)
- [Dataset Structure](#dataset-structure)
  - [Data Instances](#data-instances)
  - [Data Fields](#data-instances)
  - [Data Splits](#data-instances)
- [Dataset Creation](#dataset-creation)
  - [Curation Rationale](#curation-rationale)
  - [Source Data](#source-data)
  - [Annotations](#annotations)
  - [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
  - [Social Impact of Dataset](#social-impact-of-dataset)
  - [Discussion of Biases](#discussion-of-biases)
  - [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
  - [Dataset Curators](#dataset-curators)
  - [Licensing Information](#licensing-information)
  - [Citation Information](#citation-information)

## Dataset Description

- **Homepage:** [Needs More Information]
- **Repository:** [Needs More Information]
- **Paper:** [Needs More Information]
- **Leaderboard:** [Needs More Information]
- **Point of Contact:** [Jacob Bieker](mailto:jacob@openclimatefix.org)

### Dataset Summary

This dataset consists of various sets of historical operational GFS forecasts, and analysis files from 2016-2022. The analysis files and forecasts are initialized at 00, 06, 12, and 18 UTC every day and ran for multiple hours. Additionally, raw observations are also included, which are the observations that are used to initialize the analysis and forecasts. The dataset is being expanded over time as more historical data is processed, and more observations as well.

The `data/forecasts/GFSv16/` folder holds the historical operational forecasts out to 48 hours from initialization, on all pressure levels, and for all variables that are present in every timestep (so not any accumulated values). The data is all stored as zipped Zarr stores, openable by xarray. 

### 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 create a similar and expanded dataset to that used in Kiesler 2022 paper, where graph networks were used for weather forecasting. 

### Source Data

#### Initial Data Collection and Normalization

[Needs More Information]

#### Who are the source language producers?

[Needs More Information]

### Annotations

#### Annotation process

[Needs More Information]

#### 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(gfs,
author = {Jacob Bieker}
title = {GFS NWP Weather Dataset}
year = {2022}
}
region:us
{}
TAGS
#region-us 



# Dataset Card for GFS-Reforecast

## Table of Contents
- Dataset Description
  - Dataset Summary
  - Supported Tasks
  - Languages
- Dataset Structure
  - Data Instances
  - Data Fields
  - Data Splits
- Dataset Creation
  - Curation Rationale
  - Source Data
  - Annotations
  - Personal and Sensitive Information
- Considerations for Using the Data
  - Social Impact of Dataset
  - Discussion of Biases
  - Other Known Limitations
- Additional Information
  - Dataset Curators
  - Licensing Information
  - Citation Information

## Dataset Description

- Homepage: 
- Repository: 
- Paper: 
- Leaderboard: 
- Point of Contact: Jacob Bieker

### Dataset Summary

This dataset consists of various sets of historical operational GFS forecasts, and analysis files from 2016-2022. The analysis files and forecasts are initialized at 00, 06, 12, and 18 UTC every day and ran for multiple hours. Additionally, raw observations are also included, which are the observations that are used to initialize the analysis and forecasts. The dataset is being expanded over time as more historical data is processed, and more observations as well.

The 'data/forecasts/GFSv16/' folder holds the historical operational forecasts out to 48 hours from initialization, on all pressure levels, and for all variables that are present in every timestep (so not any accumulated values). The data is all stored as zipped Zarr stores, openable by xarray. 

### Supported Tasks and Leaderboards



### Languages



## Dataset Structure

### Data Instances



### Data Fields



### Data Splits



## Dataset Creation

### Curation Rationale

This dataset was constructed to help create a similar and expanded dataset to that used in Kiesler 2022 paper, where graph networks were used for weather forecasting. 

### Source Data

#### Initial Data Collection and Normalization



#### Who are the source language producers?



### Annotations

#### Annotation process



#### Who are the annotators?



### Personal and Sensitive Information



## Considerations for Using the Data

### Social Impact of Dataset



### Discussion of Biases



### Other Known Limitations



## Additional Information

### Dataset Curators



### Licensing Information

US Government License, no restrictions



@article(gfs,
author = {Jacob Bieker}
title = {GFS NWP Weather Dataset}
year = {2022}
}
# Dataset Card for GFS-Reforecast ## Table of Contents
- Dataset Description
  - Dataset Summary
  - Supported Tasks
  - Languages
- Dataset Structure
  - Data Instances
  - Data Fields
  - Data Splits
- Dataset Creation
  - Curation Rationale
  - Source Data
  - Annotations
  - Personal and Sensitive Information
- Considerations for Using the Data
  - Social Impact of Dataset
  - Discussion of Biases
  - Other Known Limitations
- Additional Information
  - Dataset Curators
  - Licensing Information
  - Citation Information ## Dataset Description

- Homepage: 
- Repository: 
- Paper: 
- Leaderboard: 
- Point of Contact: Jacob Bieker ### Dataset Summary

This dataset consists of various sets of historical operational GFS forecasts, and analysis files from 2016-2022. The analysis files and forecasts are initialized at 00, 06, 12, and 18 UTC every day and ran for multiple hours. Additionally, raw observations are also included, which are the observations that are used to initialize the analysis and forecasts. The dataset is being expanded over time as more historical data is processed, and more observations as well.

The 'data/forecasts/GFSv16/' folder holds the historical operational forecasts out to 48 hours from initialization, on all pressure levels, and for all variables that are present in every timestep (so not any accumulated values). The data is all stored as zipped Zarr stores, openable by xarray. ### Supported Tasks and Leaderboards ### Languages ## Dataset Structure ### Data Instances ### Data Fields ### Data Splits ## Dataset Creation ### Curation Rationale

This dataset was constructed to help create a similar and expanded dataset to that used in Kiesler 2022 paper, where graph networks were used for weather forecasting. ### Source Data #### Initial Data Collection and Normalization #### Who are the source language producers? ### Annotations #### Annotation process #### Who are the annotators? ### Personal and Sensitive Information ## Considerations for Using the Data ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations ## Additional Information ### Dataset Curators ### Licensing Information

US Government License, no restrictions



@article(gfs,
author = {Jacob Bieker}
title = {GFS NWP Weather Dataset}
year = {2022}
}
TAGS
#region-us 
 # Dataset Card for GFS-Reforecast ## Table of Contents
- Dataset Description
  - Dataset Summary
  - Supported Tasks
  - Languages
- Dataset Structure
  - Data Instances
  - Data Fields
  - Data Splits
- Dataset Creation
  - Curation Rationale
  - Source Data
  - Annotations
  - Personal and Sensitive Information
- Considerations for Using the Data
  - Social Impact of Dataset
  - Discussion of Biases
  - Other Known Limitations
- Additional Information
  - Dataset Curators
  - Licensing Information
  - Citation Information ## Dataset Description

- Homepage: 
- Repository: 
- Paper: 
- Leaderboard: 
- Point of Contact: Jacob Bieker ### Dataset Summary

This dataset consists of various sets of historical operational GFS forecasts, and analysis files from 2016-2022. The analysis files and forecasts are initialized at 00, 06, 12, and 18 UTC every day and ran for multiple hours. Additionally, raw observations are also included, which are the observations that are used to initialize the analysis and forecasts. The dataset is being expanded over time as more historical data is processed, and more observations as well.

The 'data/forecasts/GFSv16/' folder holds the historical operational forecasts out to 48 hours from initialization, on all pressure levels, and for all variables that are present in every timestep (so not any accumulated values). The data is all stored as zipped Zarr stores, openable by xarray. ### Supported Tasks and Leaderboards ### Languages ## Dataset Structure ### Data Instances ### Data Fields ### Data Splits ## Dataset Creation ### Curation Rationale

This dataset was constructed to help create a similar and expanded dataset to that used in Kiesler 2022 paper, where graph networks were used for weather forecasting. ### Source Data #### Initial Data Collection and Normalization #### Who are the source language producers? ### Annotations #### Annotation process #### Who are the annotators? ### Personal and Sensitive Information ## Considerations for Using the Data ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations ## Additional Information ### Dataset Curators ### Licensing Information

US Government License, no restrictions



@article(gfs,
author = {Jacob Bieker}
title = {GFS NWP Weather Dataset}
year = {2022}
}
passage: TAGS
#region-us 
# Dataset Card for GFS-Reforecast## Table of Contents
- Dataset Description
  - Dataset Summary
  - Supported Tasks
  - Languages
- Dataset Structure
  - Data Instances
  - Data Fields
  - Data Splits
- Dataset Creation
  - Curation Rationale
  - Source Data
  - Annotations
  - Personal and Sensitive Information
- Considerations for Using the Data
  - Social Impact of Dataset
  - Discussion of Biases
  - Other Known Limitations
- Additional Information
  - Dataset Curators
  - Licensing Information
  - Citation Information## Dataset Description

- Homepage: 
- Repository: 
- Paper: 
- Leaderboard: 
- Point of Contact: Jacob Bieker### Dataset Summary

This dataset consists of various sets of historical operational GFS forecasts, and analysis files from 2016-2022. The analysis files and forecasts are initialized at 00, 06, 12, and 18 UTC every day and ran for multiple hours. Additionally, raw observations are also included, which are the observations that are used to initialize the analysis and forecasts. The dataset is being expanded over time as more historical data is processed, and more observations as well.

The 'data/forecasts/GFSv16/' folder holds the historical operational forecasts out to 48 hours from initialization, on all pressure levels, and for all variables that are present in every timestep (so not any accumulated values). The data is all stored as zipped Zarr stores, openable by xarray.### Supported Tasks and Leaderboards### Languages## Dataset Structure### Data Instances### Data Fields### Data Splits## Dataset Creation### Curation Rationale

This dataset was constructed to help create a similar and expanded dataset to that used in Kiesler 2022 paper, where graph networks were used for weather forecasting.### Source Data#### Initial Data Collection and Normalization#### Who are the source language producers?### Annotations#### Annotation process#### Who are the annotators?### Personal and Sensitive Information## Considerations for Using the Data### Social Impact of Dataset### Discussion of Biases