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Merge pull request #1 from galaxyproject/panoply
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Panoply tweaks
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Anne Fouilloux authored Mar 5, 2020
2 parents efd9fbd + 655f489 commit 0c780fa
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8 changes: 4 additions & 4 deletions _layouts/home.html
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Expand Up @@ -35,7 +35,7 @@ <h3>Galaxy for Scientists</h3>
</thead>
<tbody>
{% for topic in sorted_topics %}
{% if topic[1].type == "use" %}
{% if topic[1].type == "use" and topic[1].enable != false %}
<tr>
{% assign tutorial_number = site.pages | topic_filter:topic[1].name | topic_count %}
<td><a href="{{ site.baseurl }}/topics/{{ topic[1].name }}/">{{ topic[1].title }}</a></td>
Expand All @@ -57,7 +57,7 @@ <h3>Galaxy Tips & Tricks</h3>
</thead>
<tbody>
{% for topic in sorted_topics %}
{% if topic[1].type == "basics" %}
{% if topic[1].type == "basics" and topic[1].enable != false %}
<tr>
{% assign tutorial_number = site.pages | topic_filter:topic[1].name | topic_count %}
<td><a href="{{ site.baseurl }}/topics/{{ topic[1].name }}/">{{ topic[1].title }}</a></td>
Expand All @@ -78,7 +78,7 @@ <h3>Galaxy for Developers and Admins</h3>
</thead>
<tbody>
{% for topic in sorted_topics %}
{% if topic[1].type == "admin-dev" %}
{% if topic[1].type == "admin-dev" and topic[1].enable != false %}
<tr>
{% assign tutorial_number = site.pages | topic_filter:topic[1].name | topic_count %}
<td><a href="{{ site.baseurl }}/topics/{{ topic[1].name }}/">{{ topic[1].title }}</a></td>
Expand Down Expand Up @@ -107,7 +107,7 @@ <h3>Galaxy for Contributors and Instructors</h3>
</thead>
<tbody>
{% for topic in sorted_topics %}
{% if topic[1].type == "instructors" %}
{% if topic[1].type == "instructors" and topic[1].enable != false %}
<tr>
{% assign tutorial_number = site.pages | topic_filter:topic[1].name | topic_count %}
<td><a href="{{ site.baseurl }}/topics/{{ topic[1].name }}/">{{ topic[1].title }}</a></td>
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1 change: 1 addition & 0 deletions topics/climate/metadata.yaml
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@@ -1,5 +1,6 @@
---
name: climate
enable: false
type: use
title: Climate
summary: Learn to analyze climate data through Galaxy.
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71 changes: 36 additions & 35 deletions topics/climate/tutorials/panoply/tutorial.md
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Expand Up @@ -32,7 +32,7 @@ contributors:
>
{: .comment}

The practical aims at familiarzing you with the [Panoply](https://www.giss.nasa.gov/tools/panoply/) Galaxy interactive environment. Panoply is among the most popular tool to visualize geo-referenced data stored in [Network Common Data Form](https://en.wikipedia.org/wiki/NetCDF) (netCDF). It provides a graphical interface for inspecting (show metadata) and visualizing netCDF data. It supports many features to customize your plots and we will introduce some of them in this lesson.
The practical aims at familiarzing you with the [Panoply](https://www.giss.nasa.gov/tools/panoply/) Galaxy interactive environment. Panoply is among the most popular tool to visualize geo-referenced data stored in [Network Common Data Form](https://en.wikipedia.org/wiki/NetCDF) (netCDF). It provides a graphical interface for inspecting (show metadata) and visualizing netCDF data. It supports many features to customize your plots and we will introduce some of them in this lesson.

In this tutorial, you will learn to:
- Plot geo-referenced latitude-longitude, latitude-vertical, longitude-vertical, time-latitude or time-vertical arrays.
Expand All @@ -52,17 +52,17 @@ In this tutorial, you will learn to:

> ### {% icon comment %} Background
>
>There are many online services to get climate data, and it is often difficult to know which ones are up-to date and which resources to trust.
> Different services provide different Application Programming Interfaces (API), use different terminologies, different file formats etc., which make it difficult for new users to master them all.
>There are many online services to get climate data, and it is often difficult to know which ones are up-to date and which resources to trust.
> Different services provide different Application Programming Interfaces (API), use different terminologies, different file formats etc., which make it difficult for new users to master them all.
> Therefore in this tutorial, we will be focusing on the usage of Climate data in [Network Common data Form](https://en.wikipedia.org/wiki/NetCDF) (netCDF) because it is the most common data format for storing Climate data.
> We will be using a freely available dataset containing Essential Climate Variables (sea ice area fraction, surface temperature) from [Copernicus Climate Data Store](https://cds.climate.copernicus.eu/#!/home). We will learn to use panoply to visualize the sea ice area fraction over the poles (southern and northern poles) and surface temperatures for two different years (1979 and 2018).
{: .comment}

## NetCDF format

[NetCDF](https://en.wikipedia.org/wiki/NetCDF) data format is a binary format and to be able to read or visualize it, we would need to use dedicated software or libraries that can handle this "special" format. It is self-describing and machine-independent data format that supports the creation, access, and sharing of array-oriented scientific data. NetCDF files usually have the extension *.nc* or *.netcdf*.
[NetCDF](https://en.wikipedia.org/wiki/NetCDF) data format is a binary format and to be able to read or visualize it, we would need to use dedicated software or libraries that can handle this "special" format. It is self-describing and machine-independent data format that supports the creation, access, and sharing of array-oriented scientific data. NetCDF files usually have the extension *.nc* or *.netcdf*.

For climate and forecast data stored in NetCDF format there are (non-mandatory) conventions on metadata ([CF Convention](http://cfconventions.org/)).
For climate and forecast data stored in NetCDF format there are (non-mandatory) conventions on metadata ([CF Convention](http://cfconventions.org/)).

In this tutorial, we will be using data from the [Copernicus Climate Data Store](https://zenodo.org/record/3695482/files/era5-land.nc?download=1) and more precisely a [reanalysis ERA5-Land monthly averaged dataset](https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-land-monthly-means?tab=overview) for 2019. Data from Copernicus Climate Data Store is freely available but may require [free registration](https://cds.climate.copernicus.eu/user/register?destination=%2Fcdsapp%23!%2Fdataset%2Freanalysis-era5-land-monthly-means%3Ftab%3Doverview) and license agreement.

Expand Down Expand Up @@ -109,7 +109,7 @@ In this tutorial, we will be using data from the [Copernicus Climate Data Store]
> > 4. The tool will start running and will stay running permanently
> > 5. Click on the "User" menu at the top and go to "Active Interactive Tools" and locate the Panoply instance you started.
> > 6. Click on your Panoply instance
> > ![Panoply dataset selection](../../images/select_dataset.png "Select dataset")
> > ![Panoply dataset selection](../../images/select_dataset.png "Select dataset")
> > 7. Click on **ecv_1979.nc** dataset
> {: .tip}
{: .hands_on}
Expand All @@ -120,7 +120,7 @@ In this tutorial, we will be using data from the [Copernicus Climate Data Store]
>
> 1. Inspect the sea ice area fraction (**siconc**)
>
> ### {% icon question %} Question
> > ### {% icon question %} Question
> >
> > what is the unit of this variable?
> >
Expand All @@ -130,10 +130,10 @@ In this tutorial, we will be using data from the [Copernicus Climate Data Store]
> > {: .solution}
> {: .question}
>
>
>
> 2. Inspect the surface temperature (**t2m**) variable
>
> ### {% icon question %} Question
> > ### {% icon question %} Question
> >
> > what is the unit of this variable and its shape?
> >
Expand All @@ -150,35 +150,35 @@ In this tutorial, we will be using data from the [Copernicus Climate Data Store]
> ### {% icon hands_on %} Hands-on: geographical map
>
> 1. Double click on the variable **t2m** and click on **Create**
> ![Panoply create Latitude longitude map](../../images/panoply_t2m_map_default.png "Create map")
> ![Panoply create Latitude longitude map](../../images/panoply_t2m_map_default.png "Create map")
>
> ### {% icon question %} Question
> > ### {% icon question %} Question
> >
> > a) What does it show?
> > b) What is the date of the generated plot?
> > c) Can you plot other dates?
> > 1. What does it show?
> > 2. What is the date of the generated plot?
> > 3. Can you plot other dates?
> >
> > > ### {% icon solution %} Solution
> > >
> > > a) The plot represent the surface temperature over the entire world.
> > > ![Panoply Latitude longitude map](../../images/panoply_geomap.png "Plot map")
> > > 1. The plot represent the surface temperature over the entire world.
> > > ![Panoply Latitude longitude map](../../images/panoply_geomap.png "Plot map")
> > >
> > > 2. The date of the default plot is 1st January 1979 at 00:00:00.
> > >
> > > b) The date of the default plot is 1st January 1979 at 00:00:00.
> > >
> > > c) To plot another date, change either:
> > > 3. To plot another date, change either:
> > > - Initial time of forecast (give a value between 1 and 12, corresponding to each month of year 1979.
> > > - Click on the date and scroll down to select the date of your choice.
> > {: .solution}
> {: .question}
>
>
> 2. Save your plot
> - Click on the tab **File** (from your plot window) to store your plot by selecting **Save Image As**
> - Double click on the folder *outputs* to enter this folder and save your plot.
> - Double click on the folder *outputs* to enter this folder and save your plot.
> You need to make sure to save all your plot in the *outputs* folder otherwise you can loose all your plots once to close panoply.
>
> 3. Change colormap
> **Always make sure you use color blind friendly palettes.**
> - To change the default colormap, click on tab "**Scale**" (bottom of your plot wind) and select another "**Color Table**" (you can scroll down to go through all the different available colormap).
> - To change the default colormap, click on tab "**Scale**" (bottom of your plot wind) and select another "**Color Table**" (you can scroll down to go through all the different available colormap).
> - Save your plot using **Save Image As** and make sure to choose another name to avoid overwritting your preceding plot.
> ![Panoply colormap](../../images/panoply_colormap.png "Plot colormap")
{: .hands_on}
Expand All @@ -189,21 +189,22 @@ In this tutorial, we will be using data from the [Copernicus Climate Data Store]
> ### {% icon hands_on %} Hands-on: Change projection
>
> 1. From your previous plot window, click on Tab **Map** and change **Projection**. Try a few of them and save each of your plot with **File** --> **Save Image As**.
> ![Panoply change projection](../../images/panoply_robinson.png "Change projection")
>
> ![Panoply change projection](../../images/panoply_robinson.png "Change projection")
>
> 2. Create another plot window for sea ice area fraction (**siconc**) and make a new geo-referenced map
>
> ### {% icon question %} Question
> > ### {% icon question %} Question
> >
> > a) What kind of colormap could you use to highlight the extent of sea-ice?
> > b) What projection would be best to use for showing the extent of sea-ice over the two poles?
> > 1. What kind of colormap could you use to highlight the extent of sea-ice?
> > 2. What projection would be best to use for showing the extent of sea-ice over the two poles?
> >
> > > ### {% icon solution %} Solution
> > >
> > > a) Any colormap that shows low values (close to 0) in light color so we can focus on values that are close to 1. For instance, **CP_PuBu_08.cpt**.
> > > ![Panoply sea-ice colormap](../../images/panoply_sea-ice_colormap.png "Sea-ice colormap")
> > > b) Using *Orthographic* projection is best for showing the northern and southern poles. One advantage is that you can choose to center the plot over 90 degrees latitude. To have both the northern and southern poles at the same time, choose **Stereographic (Two hemispheres)**.
> > >
> > > 1. Any colormap that shows low values (close to 0) in light color so we can focus on values that are close to 1. For instance, **CP_PuBu_08.cpt**.
> > > ![Panoply sea-ice colormap](../../images/panoply_sea-ice_colormap.png "Sea-ice colormap")
> > > 2. Using *Orthographic* projection is best for showing the northern and southern poles. One advantage is that you can choose to center the plot over 90 degrees latitude. To have both the northern and southern poles at the same time, choose **Stereographic (Two hemispheres)**.
> > >
> > > ![Panoply ortho plot](../../images/panoply_sea-ice_ortho.png "Plot sea-ice using orthographic projection")
> > {: .solution}
> {: .question}
Expand All @@ -225,15 +226,15 @@ In this tutorial, we will be using data from the [Copernicus Climate Data Store]
> 1. Double click on the variable **t2m**, click on **Create** and select **Create horizontal line plot along time axis** (make sure to switch to **time**).
> ![Panoply create 1D plot](../../images/panoply_create_1D.png "Create 1D plot")
>
> ### {% icon question %} Question
> > ### {% icon question %} Question
> >
> > a) What was the maximum temperature in Oslo (latitude: 60 degrees North, longitude: 10.75 East) in 1979?
> > b) Which month was the warmest in Oslo?
> > 1. What was the maximum temperature in Oslo (latitude: 60 degrees North, longitude: 10.75 East) in 1979?
> > 2. Which month was the warmest in Oslo?
> >
> > > ### {% icon solution %} Solution
> > >
> > > a) The maximum temperature is about 288 K so about 15 degrees Celsius (`288 - 273.15`).
> > > b) The warmest month in 1979 was July.
> > > 1. The maximum temperature is about 288 K so about 15 degrees Celsius (`288 - 273.15`).
> > > 2. The warmest month in 1979 was July.
> > > ![Panoply 1D plot](../../images/panoply_t2m_oslo.png "Plot surface temperature Oslo")
> > {: .solution}
> {: .question}
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