ECASLab is one of the thematic services included in the EOSC-hub service portfolio, one of the services of the EOSC marketplace, as well as one of the IS-ENES Compute Services.
ECASLAb provides a virtual research environment exploiting a server-side approach and integrating both data and analysis tools to support scientists in their daily research activities.
It consists of several components like an ECAS cluster, a JupyterHub instance jointly with a large set of pre-installed Python libraries for running data manipulation, analysis and visualization, and a data publication service.
CMCC provides access to a set of specific CMIP variable-centric collections.
Data are downloaded and kept in sync with the ESGF federated data archive within a disk space of about 20 TB. In particular, about 11TB of CMIP6 data for multiple models and scenarios (e.g., historical, ssp585 and ssp245) for the precipitation and the temperature variable with a high temporal resolution (hourly or daily) are immediately available for the users.
Users can request new data by contacting the user support.
The data pool is efficiently accessible from cluster resources as well as JupyterHub.
A JupyterHub environment is equipped with a set of ready-to-use Python modules for data management, analytics, machine learning and visualization to support end-users data analysis.
Check here the predefined Notebooks that can be executed within the CMCC Analytics Hub to perform different kinds of analysis on scientific data.