Objectives

The objective of this applied course is to provide the theoretical and technical context of terrestrial modeling in high-performance scientific computing (HPSC) environments utilizing stand-alone and coupled hydrologic, land surface, and atmospheric models.
Utilizing the Terrestrial Systems Modeling Platform (TSMP), the course will take a complete tour of terrestrial modeling and HPSC in connection with real-world observations and data assimilation including:

• setting up a terrestrial model and performing simulations in massively parallel supercomputer environments at the Jülich Supercomputing Centre,
• parallel performance analysis and profiling,
• parallel data assimilation using TerrSysMP-PDAF (Parallel Data Assimilation Framework), and
• post-processing and visualization in the age of big data.

Learning Outcomes

Completion of the course will provide the participants with the generic capabilities of terrestrial modeling and data assimilation in supercomputing environments with a focus on TSMP(-PDAF) including parallel performance analysis and profiling utilizing freely available software tools, and handling of very large data sets in the analyses and visualization process.

Target Audience and Prerequisites

• Master or PhD students, PostDocs with a deep interest in terrestrial modeling (hydrology, land surface, atmosphere)
• Basic knowledge of LINUX/UNIX and programming languages such as R, Python, C/C++, or FORTRAN as well as data formats such as NetCDF is an advantage

In cooperation with: