Resources
Resources¶
This page provides a list of resources related to working with large and challenging climate datasets. Brief descriptions and links to the resources are provided.
Documentation
Name |
Description |
|---|---|
Lots of info/links from Computation Modelling Systems team at the Climate Extremes ARC Centre of Excellence |
|
Experimental service providing cloud-based data science environments |
|
List of all datasets available on Pangeo Cloud |
|
Tool for extracting data from traditional repositories and adding them to the cloud |
|
Data cataloging utility for Earth System Models (ESMs) |
|
Tips for xarray + dask analysis |
|
Recorded presentations on climate analysis / model runs |
|
Python package for working with labelled, multi-dimensional arrays |
|
Distributed computing |
Training
Name |
Description |
Type |
|---|---|---|
CLEX Training |
ARC Centre of Excellence computing training sessions |
|
Research Software Engineering with Python |
By Damien Irving et al |
|
Project Pythia |
An education and training hub for the geoscientific Python community |
|
PyAOS Training Resource Guide |
Python for Atmosphere and Ocean Scientists - training materials |
|
An Introduction to Earth and Environmental Data Science |
Course materials from Ryan Abernathey |
|
Xarray tutorial |
90-minute course introducing data scientists already familiar with Numpy to Xarray |
|
Intro to Dask |
In Pangeo Gallery |
Notebook (interactive via Binder or noninteractive on website) |
Intake-ESM – Making It Easier To Consume Climate Data |
By Anderson Banihirwe (NCAR) |
Example workflows
Name |
Description |
Type |
|---|---|---|
Blog posts (usually as non-interactive Jupyter notebooks) |
||
Collections of notebooks with workflow examples; notebooks can be run interactively on Binder or viewed directly on the website |
Website with links to notebooks |
Other resources
Name |
Description |
Type |
|---|---|---|
Github repo with scripts and written advice |