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In Autumn 2013, we—an international team of climate scientists, computer scientists, eScience researchers, and e-Infrastructure specialists—participated in the enlighten your research global competition, organized to showcase advanced lightpath technologies in support of state-of-the-art research questions. As one of the winning entries, our enlighten your research global team embarked on a very ambitious project to run an extremely high resolution climate model on a collection of supercomputers distributed over two continents and connected using an advanced 10 G lightpath networking infrastructure. Although good progress was made, we were not able to perform all desired experiments due to a varying combination of technical problems, configuration issues, policy limitations and lack of (budget for) human resources to solve these issues. In this paper, we describe our goals, the technical and non-technical barriers, we encountered and provide recommendations on how these barriers can be removed so future project of this kind may succeed.

An important contribution to future changes in regional sea level extremes is due to the changes in intrinsic ocean variability, in particular ocean eddies. Here, we study a scenario of future dynamic sea level (DSL) extremes using a high-resolution version of the Parallel Ocean Program and generalized extreme value theory. This model is forced with atmospheric fluxes from a coupled climate model which has been integrated under the IPCC-SRES-A1B scenario over the period 2000–2100. Changes in 10-year return time DSL extremes are very inhomogeneous over the globe and are related to changes in ocean currents and corresponding regional shifts in ocean eddy pathways. In this scenario, several regions in the North Atlantic experience an increase in mean DSL of up to 0.4 m over the period 2000–2100. DSL extremes with a 10-year return time increase up to 0.2 m with largest values in the northern and eastern Atlantic.

Responsible data management is part of good research, and an important prerequisite for Open Science. To promote the practice of Open Science, and the principles of FAIR data and software, the Netherlands eScience Center actively participates in the National Platform Open Science. In line with this initiative, the eScience Center strives to make the research data collected or generated in the projects it participates in to become freely and sustainably available, as much as possible, for reuse by other researchers. Furthermore, the Netherlands eScience Center aims to raise awareness among researchers that responsible data management is an essential requirement for reproducibility of scientific results, and for enhancement of the correctness and transparency thereof.

Today, software plays a crucial role in advancing and accelerating state-of-the-art academic research. It is therefore important to adhere to proven best practices when developing research software, as it will help avoid errors, improve maintenance and sustainability, while accelerating the overall development process. Also, it will help other researchers to better understand the intricacies of the software, and the analysis performed with it. This is an important prerequisite for reproducibility of scientific results, and it will allow other researchers to adopt the software into their own workflows, possibly even contributing to the software or expanding it. To promote the practice of Open Science, and the principles of FAIR data and software, the Netherlands eScience Center actively participates in the National Platform Open Science. In line with this initiative, the eScience Center strives to make the software developed in the projects it participates in to become freely and sustainably available, as much as possible, for reuse by other researchers. To this end, the Principal Investigator of every project (co-)funded by the eScience Center is required to submit a Software Sustainability Plan, i.e. a document that makes explicit the researcher’s foreseen actions regarding software sustainability.