Grants and Contributions

Canada's boreal forest is forecast to experience changes in precipitation, evaporation, and temperature due to climate change.

Lakes play an essential role in many economic, social and cultural activities, as well as being important for ecology and biodiversity. This research project aims to improve our knowledge of the water balance and connectivity of Canadian lakes using satellite data and to evaluate the added value of the information for hydrodynamic modeling. The integration of two data sources will be explored: the future SWOT satellite, scheduled for launch in 2022, and the RADARSAT constellation mission synthetic aperture radar.

The goal of the proposed research is to employ state-of-the-art aerosol and aerosol-cloud-interaction (ACI) models in the context of a continuing program of ground- and satellite-based remote sensing and microphysical analysis to help characterize and better understand aerosol and ACI dynamics over the Arctic.

The SWOT satellite mission will provide water level information for millions of lakes, rivers and wetlands in Canada. This project proposes to exploit this information to improve our understanding of the influence of these environments on the Earth system and to improve the quality of the hydrological forecast issued by the Canadian surface and river forecasting system.

Canada's Western Arctic is covered by lakes that range from seasonally flooded wetlands to ponds to shallow lakes to deep lakes, and which cover a large percentage of the land surface. Although these lakes are sensitive to climate change, Canada does not currently have a program to monitor these lakes, or the capacity to model future changes to these Arctic-Boreal lakes. This project will integrate a field monitoring program in Canada's Western Arctic, with AirSWOT and SWOT data, and a hydrologic lake model to improve our understanding of the current and future state of Arctic lakes.

The Arctic is vital to Canada's societal and economic well-being, yet the region faces an urgent threat from climate change. Rapidly warming temperatures in the Arctic are bringing unprecedented changes to extreme events like snowstorms, melting polar ice, and wildfires, which profoundly impact the people and ecosystems of Canada's North. This project combines data from Canadian-supported satellite instruments and other observing networks, to improve computer models that are used to make forecasts of extreme weather and climate in the Arctic, and across the globe.

Terrestrial surface parameters such as soil moisture, vegetation, together with surface roughness, play significant roles in the forecasting and prediction capabilities of hydrological and atmospheric models. The overall objective of this project is to enhance our knowledge in the Earth system sciences, through improved analysis and modelling of combined SMAP and SMOS data along with RADARSAT Constellation Mission data. The new knowledge that will be generated has the potential not only to enhance our theoretical understanding in Earth system sciences, but also to provide information for practical use (crop monitoring, water resources management, etc.).

Stratospheric aerosols—tiny particles suspended 10-30 km aloft—play an important role in atmospheric radiative transfer. Perturbations to the stratospheric aerosol layer, from volcanic eruptions or forest fires, can have a significant climate impact. While satellite observations provide invaluable information on stratospheric aerosols, their radiative forcing remains uncertain. We will use OSIRIS and MAESTRO measurements of aerosol extinction and size distribution to inform improvements to the Easy Volcanic Aerosol (EVA) simple aerosol model. EVA output will be used in the SASKTRAN radiative transfer model and the Canadian Earth System Model (CanESM) to improve understanding of stratospheric aerosol radiative forcing.

This project aims to develop a multi-variate data assimilation system to integrate the space-based soil moisture measurements from SMAP and SMOS and the terrestrial water storage observations from GRACE/GRACE-FO with hydrological modeling. The scientific objective is to exploit the potential of Earth observation, especially the scientific data collected through Canadian investments in space-based platforms in developing and advancing physically-based groundwater surface water computational models, thus providing evidence-based support for a better understanding of the physical processes that govern water movement in both the surface and subsurface domains of the Earth system.

The findings of this research will inform decision-making related to climate change adaptation and mitigation strategies across Canada