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Merge pull request #13 from dopplershift/cleanup
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Clean up and reorganize
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dcamron authored Jun 14, 2024
2 parents 8674d6f + 1a0af4a commit 02d6a93
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6 changes: 2 additions & 4 deletions README.md
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<div class="row">
<div class="column">
<img src="pythia.png" alt="Project Pythia Logo" width="35%"/>
<img src="_static/NSF-Unidata_lockup_horizontal_2023_light.png" alt="NSF-Unidata Logo" width="35%"/>
</div>
<div class="column">
<img src="unidata.png" alt="Unidata Logo" width="35%"/>
<img src="_static/metpy_150x150.png" alt="MetPy Logo" width="35%"/>
</div>
</div>

**:warning: THIS COOKBOOK IS UNDER CONSTRUCTION :warning:**

# MetPy Cookbook

[![nightly-build](https://github.com/ProjectPythia/metpy-cookbook/actions/workflows/nightly-build.yaml/badge.svg)](https://github.com/ProjectPythia/metpy-cookbook/actions/workflows/nightly-build.yaml)
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title: The MetPy Cookbook
author: MetPy Maintainers
logo: pythia.png
logo: _static/metpy_150x150.png
email: [email protected]
copyright: "2024"

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36 changes: 19 additions & 17 deletions _toc.yml
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- file: notebooks/how-to-cite
- caption: The MetPy Gallery
chapters:
- file: notebooks/notebook-template
title: What organization
- file: notebooks/synoptic/index
title: Synoptic Analysis
sections:
- glob: notebooks/gallery/*
- file: notebooks/gallery/index1
title: do we want
- file: notebooks/gallery/index2
title: for these "chapters"?
- caption: Skew-T Notebooks
chapters:
- file: notebooks/Foundational_Sounding
- file: notebooks/Advanced_Sounding
- file: notebooks/Skew-T_Hodograph_Inset
- file: notebooks/Skew-T_Layout_Hodograph
- file: notebooks/Skew-T_Analysis
- file: notebooks/Sounding_LCL_Dataset
- file: notebooks/Sounding_Plotter
- file: notebooks/Sounding_Calculations
- glob: notebooks/synoptic/*
- file: notebooks/skewt/index
title: Skew-T Analysis
sections:
- glob: notebooks/skewt/*
- file: notebooks/convective/index
title: Convective Calculations
sections:
- glob: notebooks/convective/*
- file: notebooks/specialty/index
title: Specialty Plotting
sections:
- glob: notebooks/specialty/*
- file: notebooks/declarative/index
title: Simplified Plotting
sections:
- glob: notebooks/declarative/*
14 changes: 13 additions & 1 deletion notebooks/MUCAPE.ipynb → notebooks/convective/MUCAPE.ipynb
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"cell_marker": "\"\"\"",
"lines_to_next_cell": 0
},
"source": [
"Most-Unstable Convective Available Potential Energy (MUCAPE)\n",
"======================\n",
"Calculate MUCAPE on a grid of netCDF data using MetPy."
]
},
{
"cell_type": "code",
"execution_count": 10,
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"source": [
"## opening NetCDF file using xarray \n",
"\n",
"ds = xr.open_mfdataset(\"/home/jovyan/metpy-cookbook/NETCDF_FILE.nc\",combine = \"nested\", concat_dim=\"time\",decode_times=True)"
"ds = xr.open_dataset(\"NETCDF_FILE.nc\", decode_times=True)"
]
},
{
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14 changes: 13 additions & 1 deletion notebooks/TCPW.ipynb → notebooks/convective/TCPW.ipynb
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"cell_marker": "\"\"\"",
"lines_to_next_cell": 0
},
"source": [
"Total Column Precipitable Water (TCPW)\n",
"======================\n",
"Calculate TCPW on a grid of netCDF data using MetPy."
]
},
{
"cell_type": "code",
"execution_count": 10,
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"source": [
"## opening NetCDF file using xarray \n",
"\n",
"ds = xr.open_mfdataset(\"/home/jovyan/metpy-cookbook/NETCDF_FILE.nc\",combine = \"nested\", concat_dim=\"time\",decode_times=True)"
"ds = xr.open_dataset(\"NETCDF_FILE.nc\", decode_times=True)"
]
},
{
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3 changes: 3 additions & 0 deletions notebooks/convective/index.md
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# Convective Calculations

This section covers how to perform a variety of calculations around analyzing convection and severe weather.
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3 changes: 3 additions & 0 deletions notebooks/declarative/index.md
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# MetPy's Simplified Plotting Interface

TBD
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"<img src=\"images/ProjectPythia_Logo_Final-01-Blue.svg\" width=250 alt=\"Project Pythia Logo\"></img>"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# MetPy Skew-T Cookbook"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"---"
]
},
{
"cell_type": "markdown",
"metadata": {},
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"| Concepts | Importance | Notes |\n",
"| --- | --- | --- |\n",
"| [Intermediate NumPy](https://foundations.projectpythia.org/core/numpy/intermediate-numpy.html)| Necessary | |\n",
"| [Matplotlib Basis](https://foundations.projectpythia.org/core/matplotlib/matplotlib-basics.html) | Necessary |\n",
"| [Matplotlib Basics](https://foundations.projectpythia.org/core/matplotlib/matplotlib-basics.html) | Necessary |\n",
"\n",
"- **Time to learn**: 30 minutes\n"
]
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"> [Unidata Main Website](https://www.unidata.ucar.edu) <br>\n",
"> [Unidata GitHub](https://github.com/Unidata) <br>\n",
"> [Unidata YouTube Channel](https://www.youtube.com/user/unidatanews) <br>\n",
"> [Matplotlib Documentation](https://matplotlib.org) <br>\n",
"> [Unidata Python Training](https://unidata.github.io/python-training/) <br>\n"
"> [Matplotlib Documentation](https://matplotlib.org) <br>\n"
]
}
],
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10 changes: 10 additions & 0 deletions notebooks/skewt/index.md
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# Skew-T Analysis

The Skew-T Log-P diagram, or "Skew-T\" for short, is a type of plot specific
to meteorology that is frequently used in the analysis of vertical profiles of
temperature and humidity. For instance, the data collected by weather balloons
in 12-hourly soundings are often shown with such plots, as they foster an
understanding of e.g. the stability of the atmosphere above a location.

The units in this chapter show ways to use MetPy to generate skew-T plots and
customize them with various pieces of information.
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3 changes: 3 additions & 0 deletions notebooks/specialty/index.md
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# Specialty Plotting

This section shows how to accomplish some specialty plotting, such as cross-sections and smoothing, using MetPy.
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"cell_marker": "\"\"\"",
"lines_to_next_cell": 0
},
"source": [
"Geostrophic Wind and Other Calcuations\n",
"======================================\n",
"\n",
"Demonstrate a variety of calculations in MetPy."
]
},
{
"cell_type": "code",
"execution_count": 1,
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"source": [
"## opening NetCDF file using xarray \n",
"\n",
"ds = xr.open_mfdataset(\"/home/jovyan/metpy-cookbook/NETCDF_FILE.nc\",combine = \"nested\", concat_dim=\"time\",decode_times=True)"
"ds = xr.open_dataset(\"../convective/NETCDF_FILE.nc\", decode_times=True)"
]
},
{
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3 changes: 3 additions & 0 deletions notebooks/synoptic/index.md
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# Synoptic Analysis

This section covers how to perform a variety of analyses traditionally used in synoptic meteorolgy, ranging from basic plots on isobaric surfaces to Q-vectors and frontogenesis.
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