ble_wind_field
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Historical wind field dataset for the Balloon Learning Environment.
4D wind fields, where the dimensions are latitude, longitude, altitude, and
time. Each entry contains two float values (u and v) which indicate the wind
direction and magnitude at the specified location, altitude, and time.
Acknowledgements:
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A.,
Muñoz‐Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A.,
Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G.,
Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M.,
Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L.,
Healy, S., Hogan, R.J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P.,
Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F.,
Villaume, S., Thépaut, J-N. (2017): Complete ERA5: Fifth generation of ECMWF
atmospheric reanalyses of the global climate. Copernicus Climate Change Service
(C3S) Data Store (CDS). (Accessed on 01-04-2021)
FeaturesDict({
'field': Tensor(shape=(21, 21, 10, 9, 2), dtype=float32),
})
Feature |
Class |
Shape |
Dtype |
Description |
|
FeaturesDict |
|
|
|
field |
Tensor |
(21, 21, 10, 9, 2) |
float32 |
|
@software{ble2021,
author = {Greaves, Joshua and Candido, Salvatore and Dumoulin, Vincent and Goroshin, Ross and Ponda, Sameera S. and Bellemare, Marc G. and Castro, Pablo Samuel},
month = {12},
title = { {Balloon Learning Environment} },
url = {https://github.com/google/balloon-learning-environment},
version = {1.0.0},
year = {2021}
}
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A.,
Muñoz‐Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A.,
Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G.,
Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M.,
Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L.,
Healy, S., Hogan, R.J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P.,
Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F.,
Villaume, S., Thépaut, J-N. (2017): Complete ERA5: Fifth generation of ECMWF
atmospheric reanalyses of the global climate. Copernicus Climate Change Service
(C3S) Data Store (CDS). (Accessed on 01-04-2021)
ble_wind_field/full (default config)
Split |
Examples |
'train' |
290,000 |
ble_wind_field/small
Split |
Examples |
'train' |
256 |
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Last updated 2022-11-23 UTC.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2022-11-23 UTC."],[],[],null,["# ble_wind_field\n\n\u003cbr /\u003e\n\n- **Description**:\n\nHistorical wind field dataset for the Balloon Learning Environment.\n\n4D wind fields, where the dimensions are latitude, longitude, altitude, and\ntime. Each entry contains two float values (*u* and *v*) which indicate the wind\ndirection and magnitude at the specified location, altitude, and time.\n\nAcknowledgements:\n\nHersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A.,\nMuñoz‐Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A.,\nSoci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G.,\nBidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M.,\nDragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L.,\nHealy, S., Hogan, R.J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P.,\nLopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F.,\nVillaume, S., Thépaut, J-N. (2017): Complete ERA5: Fifth generation of ECMWF\natmospheric reanalyses of the global climate. Copernicus Climate Change Service\n(C3S) Data Store (CDS). (Accessed on 01-04-2021)\n\n- **Homepage** :\n \u003chttps://github.com/google/balloon-learning-environment\u003e\n\n- **Source code** :\n [`tfds.datasets.ble_wind_field.Builder`](https://github.com/tensorflow/datasets/tree/master/tensorflow_datasets/datasets/ble_wind_field/ble_wind_field_dataset_builder.py)\n\n- **Versions**:\n\n - **`1.0.0`** (default): Initial release.\n- **Download size** : `Unknown size`\n\n- **Feature structure**:\n\n FeaturesDict({\n 'field': Tensor(shape=(21, 21, 10, 9, 2), dtype=float32),\n })\n\n- **Feature documentation**:\n\n| Feature | Class | Shape | Dtype | Description |\n|---------|--------------|--------------------|---------|-------------|\n| | FeaturesDict | | | |\n| field | Tensor | (21, 21, 10, 9, 2) | float32 | |\n\n- **Supervised keys** (See\n [`as_supervised` doc](https://www.tensorflow.org/datasets/api_docs/python/tfds/load#args)):\n `None`\n\n- **Figure**\n ([tfds.show_examples](https://www.tensorflow.org/datasets/api_docs/python/tfds/visualization/show_examples)):\n Not supported.\n\n- **Citation**:\n\n @software{ble2021,\n author = {Greaves, Joshua and Candido, Salvatore and Dumoulin, Vincent and Goroshin, Ross and Ponda, Sameera S. and Bellemare, Marc G. and Castro, Pablo Samuel},\n month = {12},\n title = { {Balloon Learning Environment} },\n url = {https://github.com/google/balloon-learning-environment},\n version = {1.0.0},\n year = {2021}\n }\n\n Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A.,\n Muñoz‐Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A.,\n Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G.,\n Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M.,\n Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L.,\n Healy, S., Hogan, R.J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P.,\n Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F.,\n Villaume, S., Thépaut, J-N. (2017): Complete ERA5: Fifth generation of ECMWF\n atmospheric reanalyses of the global climate. Copernicus Climate Change Service\n (C3S) Data Store (CDS). (Accessed on 01-04-2021)\n\nble_wind_field/full (default config)\n------------------------------------\n\n- **Config description**: The entire historical wind field dataset.\n\n- **Dataset size** : `79.53 GiB`\n\n- **Auto-cached**\n ([documentation](https://www.tensorflow.org/datasets/performances#auto-caching)):\n No\n\n- **Splits**:\n\n| Split | Examples |\n|-----------|----------|\n| `'train'` | 290,000 |\n\n- **Examples** ([tfds.as_dataframe](https://www.tensorflow.org/datasets/api_docs/python/tfds/as_dataframe)):\n\nDisplay examples... \n\nble_wind_field/small\n--------------------\n\n- **Config description**: Small sample of 256 fields from the dataset.\n\n- **Dataset size** : `71.91 MiB`\n\n- **Auto-cached**\n ([documentation](https://www.tensorflow.org/datasets/performances#auto-caching)):\n Yes\n\n- **Splits**:\n\n| Split | Examples |\n|-----------|----------|\n| `'train'` | 256 |\n\n- **Examples** ([tfds.as_dataframe](https://www.tensorflow.org/datasets/api_docs/python/tfds/as_dataframe)):\n\nDisplay examples..."]]