Prairie Climate Centre Colloquium

Fri. Mar. 2 12:30 PM - Fri. Mar. 2 01:20 PM
Location: 3M69

Henry David (Hank) Venema & Jeff Diamond, Prairie Climate Centre

High Performance Computing for Climate Solutions

Advances in high performance computing and machine learning can be applied to environmental and infrastructure systems including investment planning problems for climate change mitigation and adaptation using big, georeferenced data derived from global circulation models (GCMs).  This presentation:
 
• Reviews the fundamental logic of GCMs and ensemble modelling and will discuss the biophysical impacts of climate change on the Canadian Prairies.
• Introduces a University of Winnipeg data product, climateatlas.ca as an example of ensemble GCM data
• Introduces the Manitoba Bioeconomy Atlas, a web based decision tool utilizing HPC in the back end.
• Discusses potential HPC research projects with high policy relevance that apply the climate atlas,
 
HPC methods relevant to ensemble GCM analytics include:
 
• ML-enabled classification methods for analysing terrestrial and hydrographic features
• Embarrassingly parallel geospatial simulation of agricultural systems
• Spatial optimization of agricultural systems
• Bioenergy systems logistics
• Climate risk analytics for infrastructure design
• Risk-based distributed Infrastructure systems design and investment planning