Analysing open climate data - a case study using the MATLAB Integration for Jupyter on the ENES Data Space environment

The increasing volume and complexity of Earth and environmental data requires an efficient, interdisciplinary collaboration between scientists and data providers. This can be achieved by utilising research infrastructures providing advanced e-services exploiting data integration and interoperability, seamless machine-to-machine data exchange and HPC/ cloud facilities.  

In this contribution we will present a case study of geodata import, analysis and visualization, carried out on the ENES Data Space (https://enesdataspace.vm.fedcloud.eu), a cloud-enabled data science environment for climate data analysis built on top of the European Open Science Cloud (EOSC) Compute Platform. After joining the service by using an institutional or social media account, the site users can launch JupyterLab where they have access to a personal workspace as well as compute resources, tools and ready-to-use climate datasets, comprising past data recordings and future projections, mainly from the CMIP (Coupled Model Intercomparison Project) international effort. In this example, global precipitation data from CMCC experiments will be used. The analysis will be carried out within the ENES workspace in two different ways:

First, we will launch MATLAB Online from a web browser directly from the ENES Data Space JupyterLab where a Live Script (.mlx) will import, filter, and manipulate the data, create maps, compare results and perform hypothesis testing to evaluate the statistical significance of different outcomes. Live Scripts are notebooks that allow clear communication of research methods and objectives, combining data, hyperlinks, text and code and can include UI (User Interface) tools for point-and-click data processing and visualization, without the need for advanced programming skills.

Second, we will demonstrate the same process running the MATLAB kernel from a Jupyter notebook (.ipynb) in the same JupyterLab.

In both cases results can be exported in multiple formats (e.g., PDF, markdown, LaTeX, etc.), downloaded and shared with other researchers, students, and fellow educators. The entire process is carried out in MATLAB within the ENES Data Space environment with no need to install software or download data on the users’ local (non-cloud) devices.