Tools to support climate researchers for long-tail research data in a FAIR context

Doing high quality research involves complex workflows and intermediate datasets. An important part is also sharing of those datasets, software tools and workflows among researchers, and tracking provenance and lineage. It also needs to be stored in a citable permanent repository in order to be referenced in papers and reused subsequently by other researchers. Supporting this research data life cycle properly is a very challenging objective for research infrastructures. This is especially true with rapidly evolving technologies, sustainable funding problems and human expertise. 

In the climate research infrastructure, many efforts have been made to support end-users and long tail research. There is the basic data distribution, the ESGF data nodes, but this is to support mainly specialized researchers in climate science. This basic infrastructure implements quite strict standards to enable proper data sharing in the research community. This is far from FAIR compliance, but this has proven to be extremely beneficial for collaborative research. Of course, high level components and services can be built on top. This is not an easy task, and a layered approach is always better to hide the underlying complexity and also to prevent technology locking and too complex codes. One example is the IS-ENES C4I 2.0 platform (https://dev.climate4impact.eu/ ), a front-end that eases very much data access, and is acting like a bridge between the data nodes and computing services. The C4I platform provides a very much enhanced Jupyter-la like interface (SWIRRL), with many services to support sharing of data and common workflow for data staging and preprocessing, as well as the  development of new analysis methods in a research context. Advanced tools that can calculate end-user products are also made available along with some example notebooks implementing popular workflows. One of these tools is icclim (https://github.com/cerfacs-globc/icclim), a python software package. C4I also includes high-level services such as on-the-fly inter-comparisons between climate simulations with ESMValTool (https://github.com/ESMValGroup/ESMValTool). All this work is also including large efforts to standardize and to become closer to FAIR for data, workflows and software.

Another way of helping researchers is to pre-compute end-users products like climate indices. This is extremely useful for users because it can be really complex and time consuming to calculate those products. One example is to provide those users datasets of climate indices pre-computed on CMIP6 simulations would be very valuable for those users. Of course all specific needs cannot be taken into account but the most general ones can be fulfilled. The European Open Science Cloud (EOSC) is providing computing and storage resources through the EGI-ACE project, enabling the possibility to compute several climate indices. In this EGI-ACE Use Case, icclim will be used to compute 49 standard climate indices on a large number of CMIP6 simulations, starting with the most used ones. It could also be extended to ERA5 reanalysis, CORDEX and CMIP5 datasets.

This project (IS-ENES3) has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement N°824084.