This application covers the needs for computational geophysical fluid dynamics and ocean modelling at Department of Marine Sciences at University of Gothenburg. Physical oceanography is a discipline that is a traditional user of supercomputing resources, as it involves solving large partial differential equation systems. This application is a direct continuation of several SNIC projects, merged together to facilitate management and make more efficient use of requested resources.
The project will include several oceanographic applications ranging from 10 m scales to 100 km scales. Thus, different models will be used for different projects, and will be described in this application. All applications are based on well-developed codes with a large international user groups, most of them being already installed and run on the supercomputer Tetralith. All applications have been developed with HPC resources in mind.
More specific we consider investigations on:
• Tidal energy is an emerging sustainable power source. In order to increase the extractable amount the power plants need to be arranged in farms as for wind power (PhD work). Here the turbulence in a tidal current and how it impact on Deep Green, which is a tidal energy extracting device developed by Swedish company Minesto. The wake and turbulence generated by Deep Green is a vital part of the project, and outstanding question is how dense packed farms of Deep Green that is optimal. Extractable power for different farm configurations will also be studied. This is a continuation on a previous large-scale project.
• Regional oceanography on the Swedish west coast and how particles such as plastic and plankton (PhD work) is transported by currents. The transport of harmful substances by shipping is also investigated.
• Large scale oceanography and what processes steers the generation of (polar) fronts between warm and salty equatorial water and cold and fresh polar water (PhD work). The dynamical features regulating the open ocean polynya that occurs on the location known as Maud Rise (PhD work). This work is funded by H2020 through the SO-CHIC consortium.
• Resources will also be allocated depending on the needs to Master students that would carry out a short internship or thesis during the project period.
Overall, this project is designed to foster better collaboration and planning amongst HPC users doing ocean and fluid modelling in the Department of Marine Sciences at University of Gothenburg, and helps develop a more rational and efficient use of computational resources.