Useful resources

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This place is to create a library of links to external resources that might be useful to the Centre's staff and students.

Data services

| NASA Earthdata: this is a portal to NASA datasets. The User Resources tab also have a list of recorded | webinars around the use of these datasets.


| MARVL - Marine virtual Laboratory : The Australian Marine Virtual Laboratory (MARVL) is a new development in modelling frameworks for researchers in Australia, co-funded by NeCTAR (| MARVL allows a non-specialist user to configure and run a model, automating many of the modelling preparation steps needed to bring the researcher faster to the stage of simulation and analysis. The tool is seen as enhancing the efficiency of researchers and marine managers, and is being considered as a educational aid in teaching. Most researchers, students and academic staff with have access to MARVL via their | AAF(Australian Access Federation) identity, in most cases this is your normal login identity at your local university, institute or federal agency.

| MetPy : MetPy is an Open Source project aimed at providing a Pythonic library for meteorological data analysis that meshes well with the rest of the scientific Python ecosystem.

Tutorials and other tips and tricks

| help to start: a blog post written by Oliver Angélil, a PhD student at the CCRC. It goes through a few practical tips and tricks to help with what to know when starting working in the field of climate science.

CMS blog: [[1]]

CMS training: | Publishing

CMS training: | Storage management and a separate document with| links for the training

CMS training: | Shell tips and tricks

CMS training: | Debugging 101

CMS training: | Debugging - Run time checks

CMS training: | Xarray dask training GitHub

CMS training: | Introduction to 3D visualisation with ParaView by Martin Jucker (youtube video)

CMS training: | Introduction to CleF: Climate Finder a tool to discover ESGF datasets (youtube video)

CMS training: | Python: transitioning from 2 to 3

cheat sheets:

Professional development

Data science: | Dataquest and | its blog.