Scalable visualization of Climate data using Paraview
Location: Irish Centre for High-End Computing (ICHEC) – Galway, Ireland
Project Abstract:
Scientific visualizations play a very important role in analyzing and understanding the data and the results after processing them, especially if the datasets are huge, as is the case with weather data. Meteorological phenomena can be represented naturally in three dimensions and scientists have the ability to watch them progress over time and make their conclusions.
Of course for all these data to be manipulated and visualized a huge amount of computation is needed. Actually weather data analysis is a field of High Performance Computing (HPC) itself. Huge supercomputers are needed in order to analyze these data and produce results in a reasonable amount of time.
The aim of this project was to create some visualizations of weather data using the ParaView. It involves deploying and running ParaView on a visualization cluster as well as creating animations of some weather phenomena that will aid scientists in drawing their conclusions.
ICHEC Director Prof. J.C Desplat showing the visualization of climate results to Irish Govt. Minister, Seán Sherlock, TD. The visualization is using the 3-D visualization system from ICHEC to examine the output of the Harmonie weather model.
Project Mentor: Alastair McKinstry
Site Co-ordinator: Simon Wong
Learning Outcomes:
The student will:
- Visualize climate data with 3-D tools such as Paraview
- Build and profile large HPC applications (Paraview)
- Interact with vendors e.g. working with DDN
- Understand High-end storage and visualisation hardware, provided by HPC suppliers such as DDN and NVIDIA
- Interact with Academic groups, such as Dr. Tecks’ climate group in NUI Maynooth
Student Prerequisites (Compulsory):
The student must have basic programming skills, preferably in C / C++, but also in another scientific programming language, (e.g. Python, used in Paraview). After the first weeks’ training the student should have picked up some of the key concepts of parallel computing, such as MPI.
Student Prerequisites (Desirable):
The student should have an interest in data storage and visualization, or climate. Experience with MPI would be desirable.
Training Materials:
The OPeNDAP website: http://www.opendap.org
Paraview : http://www.paraview.org
The Climate and Forecasting metadata conventions http://cf-pcmdi.llnl.gov/
Project Application Reference: Ireland – ICHEC – Visualisation of Climate Data
Applications are now closed
