Getting your hands-on Climate data

June 07, 2019

09:00 - 16:00

Instructors: Anne Fouilloux, Jean Iaquinta

Helpers: FIXME

General Information

The Carpentries is a volunteer organisation teaching foundational coding and data science skills to researchers worldwide. Carpentry@UiO aims to help anyone willing to learn how to get work done in less time and with less pain by teaching basic research computing skills. This hands-on workshop will cover basic concepts and give you an overview of how to make use of climate data for a wide range of applications. Participants will be encouraged to help one another and to apply what they have learned to their own research problems.

For more information on what we teach and why, please see our paper "Best Practices for Scientific Computing".

Who: The course is aimed at anyone interested in using Climate data. You don't need to have any previous knowledge of the tools that will be presented at the workshop.

Where: Vilhelm Bjerknes Hus, room 123. Get directions with OpenStreetMap or Google Maps.

When: June 07, 2019. Add to your Google Calendar.

Requirements: Participants must bring a laptop with a Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.) that they have administrative privileges on. They should have a few specific software packages installed (listed below).

Code of Conduct: Everyone who participates in Carpentries activities is required to conform to the Code of Conduct. This document also outlines how to report an incident if needed.

Accessibility: We are committed to making this workshop accessible to everybody. The workshop organizers have checked that:

Materials will be provided in advance of the workshop and large-print handouts are available if needed by notifying the organizers in advance. If we can help making learning easier for you (e.g. sign-language interpreters, lactation facilities) please get in touch (using contact details below) and we will attempt to provide them.

Contact: Please email organizers@swcarpentry.uio.no for more information.

Schedule

Day 1

09:00 Introduction to Climate data
10:30 Morning break
10:45 Copernicus Climate data store
12:00 Lunch break
13:00 Getting re-analysis and CMIP climate data
14:30 Afternoon break
15:00 Analyze and Visualize Climate Data
16:00 Wrap-up
16:30 END

We will use this collaborative document for chatting, taking notes, and sharing URLs and bits of code.

Setup

Register to Copernicus Climate Data Store

We will be using the Copernicus Climate Data Store and its Python and R API so it is important to register before the workshop.

Copernicus online learning environment (Optional)

We will be using additional training material from the Copernicus online learning environment and if you would like to consult the materials yourself, register here.

Install packages

Basic setup

Python

R

We maintain a list of common issues that occur during installation as a reference for instructors that may be useful on the Configuration Problems and Solutions wiki page.

The Bash Shell

Bash is a commonly-used shell that gives you the power to do simple tasks more quickly.

Video Tutorial
  1. Download the Git for Windows installer.
  2. Run the installer and follow the steps below:
    1. Click on "Next" four times (two times if you've previously installed Git). You don't need to change anything in the Information, location, components, and start menu screens.
    2. Select "Use the nano editor by default" and click on "Next".
    3. Keep "Use Git from the Windows Command Prompt" selected and click on "Next". If you forgot to do this programs that you need for the workshop will not work properly. If this happens rerun the installer and select the appropriate option.
    4. Click on "Next".
    5. Keep "Checkout Windows-style, commit Unix-style line endings" selected and click on "Next".
    6. Select "Use Windows' default console window" and click on "Next".
    7. Click on "Install".
    8. Click on "Finish".
  3. If your "HOME" environment variable is not set (or you don't know what this is):
    1. Open command prompt (Open Start Menu then type cmd and press [Enter])
    2. Type the following line into the command prompt window exactly as shown:

      setx HOME "%USERPROFILE%"

    3. Press [Enter], you should see SUCCESS: Specified value was saved.
    4. Quit command prompt by typing exit then pressing [Enter]

This will provide you with both Git and Bash in the Git Bash program.

The default shell in all versions of macOS is Bash, so no need to install anything. You access Bash from the Terminal (found in /Applications/Utilities). See the Git installation video tutorial for an example on how to open the Terminal. You may want to keep Terminal in your dock for this workshop.

The default shell is usually Bash, but if your machine is set up differently you can run it by opening a terminal and typing bash. There is no need to install anything.

Git

Git is a version control system that lets you track who made changes to what when and has options for easily updating a shared or public version of your code on github.com. You will need a supported web browser.

You will need an account at github.com for parts of the Git lesson. Basic GitHub accounts are free. We encourage you to create a GitHub account if you don't have one already. Please consider what personal information you'd like to reveal. For example, you may want to review these instructions for keeping your email address private provided at GitHub.

Git should be installed on your computer as part of your Bash install (described above).

Video Tutorial

For OS X 10.9 and higher, install Git for Mac by downloading and running the most recent "mavericks" installer from this list. Because this installer is not signed by the developer, you may have to right click (control click) on the .pkg file, click Open, and click Open on the pop up window. After installing Git, there will not be anything in your /Applications folder, as Git is a command line program. For older versions of OS X (10.5-10.8) use the most recent available installer labelled "snow-leopard" available here.

If Git is not already available on your machine you can try to install it via your distro's package manager. For Debian/Ubuntu run sudo apt-get install git and for Fedora run sudo dnf install git.

Text Editor

When you're writing code, it's nice to have a text editor that is optimized for writing code, with features like automatic color-coding of key words. The default text editor on macOS and Linux is usually set to Vim, which is not famous for being intuitive. If you accidentally find yourself stuck in it, hit the Esc key, followed by :+Q+! (colon, lower-case 'q', exclamation mark), then hitting Return to return to the shell.

nano is a basic editor and the default that instructors use in the workshop. It is installed along with Git.

Others editors that you can use are Notepad++ or Sublime Text. Be aware that you must add its installation directory to your system path. Please ask your instructor to help you do this.

nano is a basic editor and the default that instructors use in the workshop. See the Git installation video tutorial for an example on how to open nano. It should be pre-installed.

Others editors that you can use are BBEdit or Sublime Text.

nano is a basic editor and the default that instructors use in the workshop. It should be pre-installed.

Others editors that you can use are Gedit, Kate or Sublime Text.

Anaconda Package Manager

Installing Anaconda will allow give you to easily install Python and R. Both Python and R are popular languages for research computing, and great for general-purpose programming as well. Installing additional research packages individually can be a bit difficult, so we recommend Anaconda, an all-in-one installer.

Regardless of how you choose to install it, please make sure you install Python version 3.x (e.g., 3.6 is fine).

  1. Open https://www.anaconda.com/download/#linux with your web browser.
  2. Download the Python 3 installer for Linux.
    (The installation requires using the shell. If you aren't comfortable doing the installation yourself stop here and request help at the workshop.)
  3. Open a terminal window.
  4. Type 
    bash Anaconda3-
    and then press Tab. The name of the file you just downloaded should appear. If it does not, navigate to the folder where you downloaded the file, for example with: 
    cd Downloads
    Then, try again.
  5. Press Return. You will follow the text-only prompts. To move through the text, press Spacebar. Type yes and press enter to approve the license. Press enter to approve the default location for the files. Type yes and press enter to prepend Anaconda to your PATH (this makes the Anaconda distribution the default Python).
  6. Close the terminal window.

Python

If you have followed the previous section and installed Anaconda then you are ready to go with Python.

We will teach Python using the Jupyter notebook, a programming environment that runs in a web browser. For this to work you will need a reasonably up-to-date browser. The current versions of the Chrome, Safari and Firefox browsers are all supported (some older browsers, including Internet Explorer version 9 and below, are not).

Install additional Python packages

To install additional Python packages/libraries, you need to follow the instructions below.
  1. Open a terminal
  2. Download environment.yml
  3. Install environment.yml: 
    conda env create -f environment.yml
  4. Close the terminal window.
  1. Open a terminal
  2. Download environment.yml
  3. Install environment.yml: 
    conda env create -f environment.yml
  4. Close the terminal window
For more information, refer to Managing environments in the Anaconda documentation.

R

R is a programming language that is especially powerful for data exploration, visualization, and statistical analysis. To interact with R, we use RStudio.

To install R and rstudio, use Anaconda navigator and follow these instructions to create a conda R environment called esm-r-analysis.

Install additional R libraries

The following 
R
packages are used in the lessons. Start RStudio with Anaconda Navigator and the newly created R environment. Then install the following packages: 
  install.packages(c("installr","dplyr", "ggplot2", "raster", "rgdal", "rasterVis", "sf", "ncdf4", "tmap", "mapview", "maps", "plotly", "leaflet", "ecmwfr"))