Dr. Mani Mahdinia

Dr. Mahdinia is a postdoctoral scientist at Aquanty and University of Toronto's physics department. Dr. Mahdinia became a part of the C1W team on June 2021. Dr. Mahdinia has an extensive background in the fields of geophysical fluid dynamics and numerical modelling. Specifically, he is proficient in developing and using manually-operated and automated regional climate models for present-day and historical climate simulations as well as production of climate projections for the future. Dr. Mahdinia received his Bachelor's and Master's degrees from Sharif University of Technology, and his Doctoral degree (Ph.D.) from University of California Berkeley all in fluid dynamics, physical and numerical modeling, and mechanical engineering fields.    

 For his doctoral studies, Dr. Mahdinia developed a semi-implicit spectral code (based on an existing code) to study the dynamics and stability of oceanic vortices, showing that linear and also non-linear long-term stability can be good candidates to explain the ocean vortices’ long lifetimes. Dr. Mahdinia’s involvement at Aquanty includes investigating North America’s, and specifically Canada’s, regional climate following CORDEX guidelines using downscaling as the main tool. In this regard; Dr. Mahdinia has been collaborating closely with Dr. A. Erler, a senior climate scientist at Aquanty. The climate data generated in this way can prove extremely useful for the other teams in the C1W project (e.g. the hydrological team), as well as provide insight for the evolution of Canada’s future climate.

What is your role in the C1W project?

My involvement in the C1W project will be in the modeling of US and Canadian climate for the past, present and future periods (using CMIP6 projections). This is potentially one of the most high-resolution studies of the north-American region climate to-date. A potential coupling of the climate model with enhanced land models (e.g., CLM), enhanced lake-models (e.g. FLAKE), and enhanced hydrological models (e.g. HGS), as well as inclusion of improved scale-aware dynamics and physics schemes will help make the work more novel and accurate. In addition, this will help us better represent phenomena that are of consequence for future climate projections (e.g., snow accumulation and melting) and were poorly modelled in previous efforts. Overall, this work will produce high-quality data required for different climate applications.       

What benefits do you think C1W will bring to Canada/Canadians?

Models including land, ocean, hydrological, and climate models, and GCMs provide representations/predictions of the environment (and of course a higher quality of the representation/prediction could potentially be beneficial in adapting to climate change as well as combating it). Therefore, I think that the C1W effort can be beneficial for providing insights about the future of the environment within Canada and also help the involved communities take specific measures to adapt to the climate change, as well as alleviate its effects.