| Name | goes2go JSON |
| Version |
2024.7.0
JSON |
| download |
| home_page | None |
| Summary | Retrieve GOES Satellite data from AWS. Also proves some RGB recipes. |
| upload_time | 2024-07-06 21:53:44 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.9 |
| license | MIT License Copyright (c) 2019-2022 Brian Blaylock Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. |
| keywords |
weather
meteorology
satellite
atmosphere
goes
xarray
aws
noaa
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
cartopy
h5netcdf
matplotlib
metpy
numpy
pandas
s3fs
toml
xarray
None
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
<div
align="center"
>
# Download and display GOES-East and GOES-West data
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</div>
GOES-East and GOES-West satellite data are made available on Amazon Web Services through [NOAA's Open Data Dissemination Program](https://www.noaa.gov/information-technology/open-data-dissemination). **GOES-2-go** is a python package that makes it easy to find and download the files you want from [AWS](https://registry.opendata.aws/noaa-goes/) to your local computer with some additional helpers to visualize and understand the data.
<hr>
<br>
# 📔 [GOES-2-go Documentation](https://goes2go.readthedocs.io/)
<br>
<hr>
# Installation
The easiest way to install `goes2go` and its dependencies is with [Conda](https://docs.conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html) from conda-forge.
```
conda install -c conda-forge goes2go
```
You may also create the provided Conda environment, **[`environment.yml`](https://github.com/blaylockbk/goes2go/blob/main/environment.yml)**.
```bash
# Download environment file
wget https://github.com/blaylockbk/goes2go/raw/main/environment.yml
# Modify that file if you wish.
# Create the environment
conda env create -f environment.yml
# Activate the environment
conda activate goes2go
```
Alternatively, `goes2go` is published on PyPI and you can install it with pip, _but_ it requires some additional dependencies that you will have to install yourself:
- Python 3.8+
- [Cartopy](https://scitools.org.uk/cartopy/docs/latest/installing.html), which requires GEOS and Proj (if using `cartopy<0.22.0`).
- MetPy
- _Optional:_ [Carpenter Workshop](https://github.com/blaylockbk/Carpenter_Workshop)
When those are installed within your environment, _then_ you can install GOES-2-go with pip.
```bash
# Latest published version
pip install goes2go
# ~~ or ~~
# Most recent changes
pip install git+https://github.com/blaylockbk/goes2go.git
```
# Capabilities
- [Download GOES Data](#download-data)
- [Create RGB composites](#rgb-recipes)
- [Get the field of view](#field-of-view)
```mermaid
graph TD;
aws16[(AWS\nnoaa-goes16)] -.-> G
aws17[(AWS\nnoaa-goes17)] -.-> G
aws18[(AWS\nnoaa-goes18)] -.-> G
G((. GOES 2-go .))
G --- .latest
G --- .nearesttime
G --- .timerange
.latest --> ds[(xarray.DataSet)]
.nearesttime --> ds[(xarray.DataSet)]
.timerange --> ds[(xarray.DataSet)]
ds --- rgb[ds.rgb\naccessor to make RGB composites]
ds --- fov[ds.FOV\naccessor to get field-of-view polygons]
style G fill:#F8AF22,stroke:#259DD7,stroke-width:4px,color:#000000
```
## Download Data
Download GOES ABI or GLM NetCDF files to your local computer. Files can also be read with xarray.
First, create a GOES object to specify the satellite, data product, and domain you are interested in. The example below downloads the Multi-Channel Cloud Moisture Imagery for CONUS.
```python
from goes2go import GOES
# ABI Multi-Channel Cloud Moisture Imagry Product
G = GOES(satellite=16, product="ABI-L2-MCMIP", domain='C')
# Geostationary Lightning Mapper
G = GOES(satellite=17, product="GLM-L2-LCFA", domain='C')
# ABI Level 1b Data
G = GOES(satellite=17, product="ABI-L1b-Rad", domain='F')
```
> A complete listing of the products available are available [here](https://github.com/blaylockbk/goes2go/blob/main/goes2go/product_table.txt).
There are methods to do the following:
- List the available files for a time range
- Download data to your local drive for a specified time range
- Read the data into an xarray Dataset for a specific time
```python
# Produce a pandas DataFrame of the available files in a time range
df = G.df(start='2022-07-04 01:00', end='2022-07-04 01:30')
```
```python
# Download and read the data as an xarray Dataset nearest a specific time
ds = G.nearesttime('2022-01-01')
```
```python
# Download and read the latest data as an xarray Dataset
ds = G.latest()
```
```python
# Download data for a specified time range
G.timerange(start='2022-06-01 00:00', end='2022-06-01 01:00')
# Download recent data for a specific interval
G.timerange(recent='30min')
```
## RGB Recipes
The `rgb` xarray accessor computes various RGB products from a GOES ABI **_ABI-L2-MCMIP_** (multi-channel cloud and moisture imagry products) `xarray.Dataset`. See the [demo](https://goes2go.readthedocs.io/en/latest/user_guide/notebooks/DEMO_rgb_recipes.html#) for more examples of RGB products.
```python
import matplotlib.pyplot as plt
ds = GOES().latest()
ax = plt.subplot(projection=ds.rgb.crs)
ax.imshow(ds.rgb.TrueColor(), **ds.rgb.imshow_kwargs)
ax.coastlines()
```
## Field of View
The `FOV` xarray accessor creates `shapely.Polygon` objects for the ABI and GLM field of view. See notebooks for [GLM](https://goes2go.readthedocs.io/en/latest/user_guide/notebooks/field-of-view_GLM.html) and [ABI](https://goes2go.readthedocs.io/en/latest/user_guide/notebooks/field-of-view_ABI.html) field of view.
```python
from goes2go.data import goes_latest
G = goes_latest()
# Get polygons of the full disk or ABI domain field of view.
G.FOV.full_disk
G.FOV.domain
# Get Cartopy coordinate reference system
G.FOV.crs
```
GOES-West is centered over -137 W and GOES-East is centered over -75 W. When GOES was being tested, it was in a "central" position, outlined in the dashed black line. Below is the ABI field of view for the full disk:
The GLM field of view is slightly smaller and limited by a bounding box. Below is the approximated GLM field of view:
# How to Cite and Acknowledge
If GOES-2-go played an important role in your work, please [tell me about it](https://github.com/blaylockbk/goes2go/discussions/categories/show-and-tell)! Also, consider including a citation or acknowledgement in your article or product.
**_Suggested Citation_**
> Blaylock, B. K. (2023). GOES-2-go: Download and display GOES-East and GOES-West data (Version 2022.07.15) [Computer software]. https://github.com/blaylockbk/goes2go
**_Suggested Acknowledgment_**
> A portion of this work used code generously provided by Brian Blaylock's GOES-2-go python package (https://github.com/blaylockbk/goes2go)
### What if I don't like the GOES-2-go or Python?
As an alternative you can use [rclone](https://rclone.org/) to download GOES files from AWS. I quite like rclone. Here is a [short rclone tutorial](https://github.com/blaylockbk/pyBKB_v3/blob/master/rclone_howto.md).
<hr>
I hope you find this makes GOES data easier to retrieve and display. Enjoy!
\- Brian Blaylock
👨🏻💻 [Contributing Guidelines](https://goes2go.readthedocs.io/en/latest/user_guide/contribute.html)
💬 [GitHub Discussions](https://github.com/blaylockbk/goes2go/discussions)
🚑 [GitHub Issues](https://github.com/blaylockbk/goes2go/issues)
🌐 [Personal Webpage](http://home.chpc.utah.edu/~u0553130/Brian_Blaylock/home.html)
P.S. If you like GOES-2-go, check out my other python packages
- [🏁 Herbie](https://github.com/blaylockbk/Herbie): download numerical weather model data
- [🌡️ SynopticPy](https://github.com/blaylockbk/SynopticPy): retrieve mesonet data from the Synoptic API.
- [🌹 Pandas-rose](https://github.com/blaylockbk/pandas-rose): easly wind rose from Pandas dataframe.
# Related Content
- [🙋🏻♂️ Brian's AWS GOES Web Downloader](https://home.chpc.utah.edu/~u0553130/Brian_Blaylock/cgi-bin/goes16_download.cgi)
- [📔 GOES-R Series Data Book](https://www.goes-r.gov/downloads/resources/documents/GOES-RSeriesDataBook.pdf)
- [🎠 Beginner's Guide](https://www.goes-r.gov/downloads/resources/documents/Beginners_Guide_to_GOES-R_Series_Data.pdf)
- [🖥 Rammb Slider GOES Viewer](https://rammb-slider.cira.colostate.edu)
- [💾 GOES on AWS](https://registry.opendata.aws/noaa-goes/)
- [🐍 Unidata Plot GOES Data](https://unidata.github.io/python-training/gallery/mapping_goes16_truecolor/)
- [🗺 Plotting tips form geonetcast blog](https://geonetcast.wordpress.com/2019/08/02/plot-0-5-km-goes-r-full-disk-regions/)
- [🐍 `glmtools`](https://github.com/deeplycloudy/glmtools/)
- [🐍 `satpy`](https://github.com/pytroll/satpy)
- [🖥 CSPPGEO](http://cimss.ssec.wisc.edu/csppgeo/) | [Gridded GLM software package](https://download.ssec.wisc.edu/files/csppgeo/)
Raw data
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"description": "<div\n align=\"center\"\n>\n\n\n\n# Download and display GOES-East and GOES-West data\n\n<!-- Badges -->\n\n[](https://pypi.python.org/pypi/goes2go/)\n[](https://anaconday.org/conda-forge/goes2go)\n[](https://zenodo.org/badge/latestdoi/296737878)\n\n\n[](https://github.com/astral-sh/ruff)\n[](https://github.com/blaylockbk/goes2go/actions/workflows/tests-python.yml)\n[](https://goes2go.readthedocs.io/?badge=latest)\n[](https://pypi.org/project/goes2go/)\n[](https://anaconda.org/conda-forge/goes2go)\n[](https://anaconda.org/conda-forge/goes2go)\n[](https://anaconda.org/conda-forge/goes2go)\n\n<!--(Badges)-->\n\n</div>\n\nGOES-East and GOES-West satellite data are made available on Amazon Web Services through [NOAA's Open Data Dissemination Program](https://www.noaa.gov/information-technology/open-data-dissemination). **GOES-2-go** is a python package that makes it easy to find and download the files you want from [AWS](https://registry.opendata.aws/noaa-goes/) to your local computer with some additional helpers to visualize and understand the data.\n\n<hr>\n\n<br>\n\n# \ud83d\udcd4 [GOES-2-go Documentation](https://goes2go.readthedocs.io/)\n\n<br>\n\n<hr>\n\n# Installation\n\nThe easiest way to install `goes2go` and its dependencies is with [Conda](https://docs.conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html) from conda-forge.\n\n```\nconda install -c conda-forge goes2go\n```\n\nYou may also create the provided Conda environment, **[`environment.yml`](https://github.com/blaylockbk/goes2go/blob/main/environment.yml)**.\n\n```bash\n# Download environment file\nwget https://github.com/blaylockbk/goes2go/raw/main/environment.yml\n\n# Modify that file if you wish.\n\n# Create the environment\nconda env create -f environment.yml\n\n# Activate the environment\nconda activate goes2go\n```\n\nAlternatively, `goes2go` is published on PyPI and you can install it with pip, _but_ it requires some additional dependencies that you will have to install yourself:\n\n- Python 3.8+\n- [Cartopy](https://scitools.org.uk/cartopy/docs/latest/installing.html), which requires GEOS and Proj (if using `cartopy<0.22.0`).\n- MetPy\n- _Optional:_ [Carpenter Workshop](https://github.com/blaylockbk/Carpenter_Workshop)\n\nWhen those are installed within your environment, _then_ you can install GOES-2-go with pip.\n\n```bash\n# Latest published version\npip install goes2go\n\n# ~~ or ~~\n\n# Most recent changes\npip install git+https://github.com/blaylockbk/goes2go.git\n```\n\n# Capabilities\n\n- [Download GOES Data](#download-data)\n- [Create RGB composites](#rgb-recipes)\n- [Get the field of view](#field-of-view)\n\n```mermaid\n graph TD;\n aws16[(AWS\\nnoaa-goes16)] -.-> G\n aws17[(AWS\\nnoaa-goes17)] -.-> G\n aws18[(AWS\\nnoaa-goes18)] -.-> G\n G((. GOES 2-go .))\n G --- .latest\n G --- .nearesttime\n G --- .timerange\n .latest --> ds[(xarray.DataSet)]\n .nearesttime --> ds[(xarray.DataSet)]\n .timerange --> ds[(xarray.DataSet)]\n ds --- rgb[ds.rgb\\naccessor to make RGB composites]\n ds --- fov[ds.FOV\\naccessor to get field-of-view polygons]\n\n style G fill:#F8AF22,stroke:#259DD7,stroke-width:4px,color:#000000\n```\n\n## Download Data\n\nDownload GOES ABI or GLM NetCDF files to your local computer. Files can also be read with xarray.\n\nFirst, create a GOES object to specify the satellite, data product, and domain you are interested in. The example below downloads the Multi-Channel Cloud Moisture Imagery for CONUS.\n\n```python\nfrom goes2go import GOES\n\n# ABI Multi-Channel Cloud Moisture Imagry Product\nG = GOES(satellite=16, product=\"ABI-L2-MCMIP\", domain='C')\n\n# Geostationary Lightning Mapper\nG = GOES(satellite=17, product=\"GLM-L2-LCFA\", domain='C')\n\n# ABI Level 1b Data\nG = GOES(satellite=17, product=\"ABI-L1b-Rad\", domain='F')\n```\n\n> A complete listing of the products available are available [here](https://github.com/blaylockbk/goes2go/blob/main/goes2go/product_table.txt).\n\nThere are methods to do the following:\n\n- List the available files for a time range\n- Download data to your local drive for a specified time range\n- Read the data into an xarray Dataset for a specific time\n\n```python\n # Produce a pandas DataFrame of the available files in a time range\n df = G.df(start='2022-07-04 01:00', end='2022-07-04 01:30')\n```\n\n```python\n # Download and read the data as an xarray Dataset nearest a specific time\n ds = G.nearesttime('2022-01-01')\n```\n\n```python\n # Download and read the latest data as an xarray Dataset\n ds = G.latest()\n```\n\n```python\n # Download data for a specified time range\n G.timerange(start='2022-06-01 00:00', end='2022-06-01 01:00')\n\n # Download recent data for a specific interval\n G.timerange(recent='30min')\n```\n\n## RGB Recipes\n\nThe `rgb` xarray accessor computes various RGB products from a GOES ABI **_ABI-L2-MCMIP_** (multi-channel cloud and moisture imagry products) `xarray.Dataset`. See the [demo](https://goes2go.readthedocs.io/en/latest/user_guide/notebooks/DEMO_rgb_recipes.html#) for more examples of RGB products.\n\n```python\nimport matplotlib.pyplot as plt\nds = GOES().latest()\nax = plt.subplot(projection=ds.rgb.crs)\nax.imshow(ds.rgb.TrueColor(), **ds.rgb.imshow_kwargs)\nax.coastlines()\n```\n\n\n\n## Field of View\n\nThe `FOV` xarray accessor creates `shapely.Polygon` objects for the ABI and GLM field of view. See notebooks for [GLM](https://goes2go.readthedocs.io/en/latest/user_guide/notebooks/field-of-view_GLM.html) and [ABI](https://goes2go.readthedocs.io/en/latest/user_guide/notebooks/field-of-view_ABI.html) field of view.\n\n```python\nfrom goes2go.data import goes_latest\nG = goes_latest()\n# Get polygons of the full disk or ABI domain field of view.\nG.FOV.full_disk\nG.FOV.domain\n# Get Cartopy coordinate reference system\nG.FOV.crs\n```\n\nGOES-West is centered over -137 W and GOES-East is centered over -75 W. When GOES was being tested, it was in a \"central\" position, outlined in the dashed black line. Below is the ABI field of view for the full disk:\n\n\nThe GLM field of view is slightly smaller and limited by a bounding box. Below is the approximated GLM field of view:\n\n\n# How to Cite and Acknowledge\n\nIf GOES-2-go played an important role in your work, please [tell me about it](https://github.com/blaylockbk/goes2go/discussions/categories/show-and-tell)! Also, consider including a citation or acknowledgement in your article or product.\n\n**_Suggested Citation_**\n\n> Blaylock, B. K. (2023). GOES-2-go: Download and display GOES-East and GOES-West data (Version 2022.07.15) [Computer software]. https://github.com/blaylockbk/goes2go\n\n**_Suggested Acknowledgment_**\n\n> A portion of this work used code generously provided by Brian Blaylock's GOES-2-go python package (https://github.com/blaylockbk/goes2go)\n\n### What if I don't like the GOES-2-go or Python?\n\nAs an alternative you can use [rclone](https://rclone.org/) to download GOES files from AWS. I quite like rclone. Here is a [short rclone tutorial](https://github.com/blaylockbk/pyBKB_v3/blob/master/rclone_howto.md).\n\n<hr>\n\nI hope you find this makes GOES data easier to retrieve and display. Enjoy!\n\n\\- Brian Blaylock\n\n\ud83d\udc68\ud83c\udffb\u200d\ud83d\udcbb [Contributing Guidelines](https://goes2go.readthedocs.io/en/latest/user_guide/contribute.html) \n\ud83d\udcac [GitHub Discussions](https://github.com/blaylockbk/goes2go/discussions) \n\ud83d\ude91 [GitHub Issues](https://github.com/blaylockbk/goes2go/issues) \n\ud83c\udf10 [Personal Webpage](http://home.chpc.utah.edu/~u0553130/Brian_Blaylock/home.html)\n\nP.S. If you like GOES-2-go, check out my other python packages\n\n- [\ud83c\udfc1 Herbie](https://github.com/blaylockbk/Herbie): download numerical weather model data\n- [\ud83c\udf21\ufe0f SynopticPy](https://github.com/blaylockbk/SynopticPy): retrieve mesonet data from the Synoptic API.\n- [\ud83c\udf39 Pandas-rose](https://github.com/blaylockbk/pandas-rose): easly wind rose from Pandas dataframe.\n\n# Related Content\n\n- [\ud83d\ude4b\ud83c\udffb\u200d\u2642\ufe0f Brian's AWS GOES Web Downloader](https://home.chpc.utah.edu/~u0553130/Brian_Blaylock/cgi-bin/goes16_download.cgi)\n- [\ud83d\udcd4 GOES-R Series Data Book](https://www.goes-r.gov/downloads/resources/documents/GOES-RSeriesDataBook.pdf)\n- [\ud83c\udfa0 Beginner's Guide](https://www.goes-r.gov/downloads/resources/documents/Beginners_Guide_to_GOES-R_Series_Data.pdf)\n- [\ud83d\udda5 Rammb Slider GOES Viewer](https://rammb-slider.cira.colostate.edu)\n- [\ud83d\udcbe GOES on AWS](https://registry.opendata.aws/noaa-goes/)\n- [\ud83d\udc0d Unidata Plot GOES Data](https://unidata.github.io/python-training/gallery/mapping_goes16_truecolor/)\n- [\ud83d\uddfa Plotting tips form geonetcast blog](https://geonetcast.wordpress.com/2019/08/02/plot-0-5-km-goes-r-full-disk-regions/)\n- [\ud83d\udc0d `glmtools`](https://github.com/deeplycloudy/glmtools/)\n- [\ud83d\udc0d `satpy`](https://github.com/pytroll/satpy)\n- [\ud83d\udda5 CSPPGEO](http://cimss.ssec.wisc.edu/csppgeo/) | [Gridded GLM software package](https://download.ssec.wisc.edu/files/csppgeo/)\n",
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"license": "MIT License Copyright (c) 2019-2022 Brian Blaylock Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the \"Software\"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. ",
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