AARMS Data Assimilation CRG
The AARMS CRG in the Advanced Simulation of Mathematical Models with Data Assimilation
Personnel
Primary Applicant: Ronald Haynes, Ӱɴý
CRG members from AARMS member universities:
Acadia: Angus Creech, Richard Karsten
Dalhousie: Mike Dowd
MUN: JC Loredo-Osti, Scott MacLachlan, Alison Malcolm
CRG members from other institutions:
Geneva: Martin Gander
Heriot-Watt: Wolf-Gerrit Fr¨uh
Kansas: Weizhang Huang
Eindhoven: Jemima Tabeart
Proposed Research Area
Traditionally, computer simulations of physical systems have started from models that describe the system at hand and run forward to make predictions about future states based on prescribed forces and initial conditions. When these models are based on PDEs, those simulations involve choosing meshes in space and time, discretizing the PDEs on those meshes with appropriate numerical techniques, and then solving linear or nonlinear systems of equations at each timestep to evolve the system forward from initial conditions (hopefully an accurate description of the current status of the system), providing approximations to the future states of the system. Over the past decades, substantial effort in computer simulation has moved from these so-called “forward” simulations to settings where the simulation is used to answer some bigger question, such as optimizing device designs, or quantifying propagation of uncertainties through these simulations. One aspect of this bigger picture is data assimilation (DA), which attempts to use observations at later times to steer the model forecasts closer to reality. This proposal is motivated by five application areas where mature simulation technology exists, but data assimilation can play a key role in advancing our understanding of the underlying physical systems.
Past Activities:
1. Kickoff Workshop (January 2026)
Upcoming Activities:
1. Data Assimilation in Firedrake (November 2026)