Education & Training

Annual Fall School

HPSC TerrSys annual Fall School provides the theoretical and technical context of terrestrial modeling in high-performance scientific computing (HPSC) environments for terrestrial system science.

In this edition, we focused on utilizing a stand-alone land surface model, and in combination with a subsurface and atmospheric model.

Utilizing the Community Land Model (eCLM), the course focused on land surface processes and land surface modeling with an outlook to coupled modeling involving the atmosphere and deeper subsurface. The students applied this model in a high-performance computing infrastructure, while also focusing on data science aspects of land surface modelling: data management, machine learning and data assimilation.

The activities included

• setting up a land surface model and performing simulations in massively parallel supercomputer environments at the Jülich Supercomputing Centre,

• land surface model simulations involving biogeochemical cycles and dynamic simulation of vegetation states,

• management of (big) data and machine learning methods,

• parallel data assimilation using TSMP-PDAF (Parallel Data Assimilation Framework),

• post-processing and visualization in the age of big data,

• outlook to coupled atmosphere-land surface-subsurface modelling with the Terrestrial Systems Modelling Platform version 2.