Jeff Freedman, J.D., Ph.d.

Expertise

• Uncertainty in wind and solar resource assessment;

• Remote sensing measurement systems (LiDAR and SoDAR) for renewable energy and boundary layer studies;

• Detecting trends in the wind and solar resource;

• Reliability of short-term power production forecasting; and

• Forest exchange processes and boundary layer cumulus clouds.

Impacted Sectors

• Solar Energy

• Wind Energy

• Maritime and Land Freight

• Weather forecasting

Notable Research

• Wind Forecasting Improvement Project (WFIP) funded by The Department of Energy(DOE) and the National Oceanography and Atmospheric Administration(NOAA)

• Study to demonstrate the value of additional atmospheric observations and model enhancements on wind energy production forecasts, the development of the Solar Wind Integrated Forecast Tool (SWIFT)

• Developed a state-of-the-art forecasting service for Hawaii´s electric utilities

• LiDAR-based study of the 3D wind field over Cranberry Lake in New York’s Adirondack Mountains

Background

As part of the Boundary Layer Group here at ASRC, my main research focus is on renewable energy and atmospheric boundary layer (ABL) processes. This includes work on improving wind and solar power production forecasting, weather and climate influences on resource assessment, and the interaction of wind farms (and their performance) with the ABL. I have also investigated how clouds, particularly boundary layer cumulus, are modulated by the underlying surface and how this influences forest health and the solar energy resource. A principal tool for my observational work is a Leosphere Windcube 100S scanning LiDAR.