HPC and natural hazards: modelling tsunamis and volcanic plumes using European flagship codes

Course/Event Essentials

Event/Course Start
Event/Course End
Event/Course Format
In person

Venue Information

Country: Spain
Venue Details: Click here

Training Content and Scope

Scientific Domain
Level of Instruction
Intermediate
Advanced
Sector of the Target Audience
Research and Academia
Industry
Public Sector
HPC Profile of Target Audience
Application Users
Application Developers
Language of Instruction

Other Information

Organiser
Supporting Project(s)
PRACE
ChEESE
Event/Course Description

Objectives

This course focuses on modelling two of the highest impact natural hazards, volcanic eruptions and tsunamis. The objective is to give a succinct theoretical overview and then introduce students on the use of different HPC flagship codes included in the Center of Excellence for Exascale in Solid Earth (ChEESE). ASHEE is a volcanic plume and PDC simulator based on a multiphase fluid dynamic model conceived for compressible mixtures composed of gaseous components and solid particle phases. FALL3D is a Eulerian model for the atmospheric transport and ground deposition of volcanic tephra (ash) used in operational volcanic ash dispersal forecasts routinely used to prevent aircraft encounters with volcanic ash clouds and to perform re-routings avoiding contaminated airspace areas. T-HySEA solves the 2D shallow water equations on hydrostatic and dispersive versions. Based on a high-order Finite Volume (FV) discretisation (hydrostatic) with Finite Differences (FD) for the dispersive version on two-way structured nested meshes in spherical coordinates. Together with hands-on sessions, the course will also tackle post-process strategies based on python. In recent years, the Python programming language has become one of the most popular choice for geoscientists. Python is a modern, interpreted, object-oriented, open-source language easy to learn, easy to read, and fast to write. The proliferation of multiple open-source projects with libraries available every day, have facilitated a rapid scientific development in the geoscience community. In addition, the modern data structures and object-oriented nature of the language along with an elegant syntax, enable Earth scientists to write more robust and less buggy code.

Requirements

-At least University degree in progress on Earth Sciences, Computer Sciences or related area.
-Basic knowledge of LINUX
-Knowledge of C, FORTRAN, MPI or openMP is recommended
-Knowledge of Earth Sciences data formats is recommended (grib, netcdf, hdf,…)
-Basic knowledge of python

Learning Outcomes

Participants will learn and gain experience in installing SE codes and related utilities and libraries, running numerical simulations, monitoring the execution of supercomputing jobs, analyzing and visualizing model results.