End Users of Climate data have nowadays to struggle with accessing the data they need for their research because of the rapid increase in data volumes. The whole climate data archive is expected to reach a volume of 30 Pb in 2018 and up to 2000 Pb in 2022 (estimated). On-demand data processing solutions as close as possible to the data storage are emerging, thanks to newly developed standards, provenance and infrastructures. In Europe several initiatives are taking place to support scientific on-demand data analytics at the European scale. They offer the huge potential of interoperability, as for example the DARE e-science platform (http://project-dare.eu), designed for efficient and traceable development of complex experiments and domain-specific services on the Cloud. Also, the IS-ENES (https://is.enes.org) consortium has developed a platform to ease access to climate data for the climate impact community (C4I: https://climate4impact.eu). The platform is based on existing standards (ISO and OGC), such as WPS (Web Processing Service). DARE will integrate services from the EUDAT CDI, enabling generic access and cross-domain interoperability, as well as providing compliance and integration with the future EOSC platform. The DARE platform will use containerization technologies, so that it can be easily deployed on heterogeneous architectures. A scientific pilot has been designed within the DARE project for the ENES community (climate domain). The objectives are to enable delegation of on-demand computational-intensive calculations to the DARE platform, from the IS-ENES C4I interface, seamlessly. The DARE architecture and the solutions being implemented will be presented, along with the generic and agile approach taken to implement the pilot.

Researchers and end users using climate data face a challenge when they analyze the data they need. Data volumes are increasing very rapidly, and the ability to download all needed data is often no longer possible. Also, it can be complex to install, configure and use some advanced analysis tools on such large datasets. This is especially true when they are stored in a federated architecture like the ESGF. An example of a complex analysis tool used in climate research and adaptation studies is a tool to follow storm tracks. In the context of climate change, it is important to know if storm tracks will change in the future, in both their frequency and intensity. Storms can cause significant societal impacts, hence it is important to assess future patterns. Having access to this type of complex analysis tool is very useful, and integrating them with front-ends like the IS-ENES climate4impact (C4I) would enable the use of those tools by a larger number of researchers and end users. Integrating this type of complex tool is not an easy task. It requires significant development effort, especially if one of the objectives is also to adhere to FAIR principles. The DARE Platform enables research developers to faster develop the implementations of scientific workflows more rapidly. This work presents how such a complex analysis tool has been implemented to be easily integrated with the C4I platform. The DARE Platform also provides easy access to e-infrastructure services like EUDAT B2DROP, to store intermediate or final results and powerful provenance-powered tools to help researchers manage their work and data. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreements N°824084 and N°777413.