Grants and Contributions

Advances exploratory research under the New Beginnings Initiative

This contribution builds capacity within Mississaugas of the Credit First Nation to guide and participate in the co-design of various interpretive and experiential elements for the future visitor, learning and community centre at Rouge National Urban Park and other Rouge Park establishment projects.

This project addresses the overarching goal of Improving Space Weather Radiation Belt and Ring Current Loss Models. In particular, the project will focus on utilizing GO Canada data, and additional supporting data sets, to deliver a better understanding of a new and previously ignored “missing loss process” impacting electron ring current and radiation belt dynamics. The overall goal will be to develop models for this new loss process which will be incorporated into, and improve, current space radiation models. This research is expected to have significant impacts, advancing state-of-the-art space weather models.

Through its provision of key instrumentation to the European Space Agency’s Swarm satellite mission, now operating at the upper reaches of Earth’s atmosphere for nearly a decade, Canada has extensive experience in the study of Earth’s space plasma environment. Swarm’s observations have contributed significantly to the understanding of the Sun-Earth connection and its impact on humanity. The project proposed here is designed to leverage this expertise and Swarm’s scientific findings to contribute to the development and operation of NASA’s Geospace Dynamics Constellation mission, which will probe the coupled magnetosphere-ionosphere-atmosphere system beginning in the early 2030’s.

The objective of this research is to develop a forecast model for the probability of scintillation occurrence in GNSS signals over the Canadian Arctic with a high temporal and spatial resolution during quiet and disturbed geomagnetic conditions. The model will use 15 years of Canadian High Arctic Ionospheric Network (CHAIN) GNSS scintillation monitors collected data to infer statistical patterns, and solar wind parameters measured at the Lagrange point to propagate predictions into the future. The model code will be publicly available for use in scientific research and navigation systems operations worldwide.

The objective of this research is to develop an atmospheric drag model that incorporates the effects of solar activity, atmospheric density, satellite altitude and geomagnetic activity. Atmospheric drag effects cause large and unpredictable uncertainties in orbit determination/prediction, particularly during periods of highly active space weather. By analyzing and modeling the atmospheric drag forces acting on the CASSIOPE satellite, the researchers seek to understand the temporal and spatial variability of these forces and their effects on satellite orbit, altitude decay and lifetime. These findings will contribute to a better understanding of the dynamics of the Earth's atmosphere and its impact on space-based assets.

The proposal will further develop a novel machine learning model of geomagnetic disturbances which will aid stakeholders and forecasters in making operational decisions to limit the impact of space weather.

By utilizing new ground-based observations, ionospheric modelling, employing various in-situ measurements and machine learning techniques, it will enhance the understanding of the magnetosphere-ionosphere system and pave the way for practical applications in space weather monitoring and prediction.

This project will focus on analysis of data from the CSA-supported OSIRIS instrument. We will analyze the retrieved aerosol and investigate the systematic impacts in order to understand the limitations of the OSIRIS measurements of Hunga Tonga aerosol. This research responds directly to CSA objectives by applying satellite data analysis of this record breaking volcanic eruption to improve understanding of extreme events and climate change. This work will transfer knowledge to government to improve climate prediction and adaptation. This project will train young researchers and contribute to new understanding of satellite remote sensing and the study of climate from space.

Overshooting deep convection is an extreme weather condition that is affected by but also feeds back to climate change. Its complex nature makes it difficult to represent it in global climate models and to observe it with satellites. We propose to integrate satellite measurements with high-resolution numerical modeling to improve the characterization of the cloud, humidity, temperature (including that inside clouds) and radiation fields associated with overshooting convection. The research will help improve Canada’s capacity for climate and weather prediction and strengthen its leadership role in Satellite Earth Observation.