Long-term Data Assimilative, Temperature and Currents

his project is creating a long-term temperature and currents database for lakes Erie and Michigan by assimilating data collected from the SOAR network, moorings and gliders into a Great Lakes forecast model. The combined data-model approach offers the most accurate three-dimensional temperature and currents reanalysis and simulations to support GLRI management and restoration efforts in the Great Lakes region. Once completed, this long-term, data-assimilative reanalysis will allow decision makers and coastal managers to evaluate various planning and restoration scenarios due to climate change.

Existing data management tools used as part of the GLRI adaptive management process provide access to limited monitoring locations, with very few instruments measuring the physical conditions of the lakes (e.g., temperature, currents, waves, wind), thus making it difficult to develop and validate decision support tools. This project will enhance these data sets by assimilating field data collected from the SOAR project, Coastal Hypoxia Research Project (CHRP), and other measurements blending with high-resolution, three-dimensional hydrodynamic modell to generate long-term temperature reanalysis of lakes Erie and Michigan. This unique dataset will enable decision makers, coastal managers and ecosystem/ecological modelers to plan and evaluate restoration efforts for the Great Lakes at a much longer time horizon, providing the necessary baseline physical information from which to inform historical assessments and scenario projections.

GLRI Funding:
FY 2024: $250,000

FY 2023: $250,000

FY 2022: $250,000

FY 2019: $250,000

FY 2018: $250,000