Environmental Science Division (EVS)a Division of Argonne National Laboratory

EVS researchers seek to improve short-term wind forecasting in complex terrains

November 14, 2018

Forecasting the wind for tomorrow is a daily challenge to wind farm operators in places like the Columbia River Gorge in the Pacific Northwest. To more accurately predict wind in complex terrain, EVS researchers partnered in a project funded by DOE called Wind Forecast Improvement Project II (WFIP 2).

To collect data for the project, scientists completed the largest-ever deployment of technologies for measuring wind speed and wind energy generation by May 2017, moving 200 instruments into a 50,000 km2 expanse of the Columbia River Gorge, spread across northwestern Oregon and southern Washington. EVS staff have operated, monitored and serviced many of the instruments used throughout the field observation portion of the project.

Researchers involved in the WFIP 2 project improved weather prediction models for processes that drive the winds in complex terrain at heights essential to wind industry needs. To expedite their work producing physical representations of wind features, scientists analyzed much of the data using the Mira supercomputer at the Argonne Leadership Computing Facility (ALCF), a DOE Office of Science User Facility.

“Mira was critical for the success of WFIP 2,” said Paytsar Muradyan, EVS assistant atmospheric scientist. “It was initially used to run the control simulations for our analysis. This was followed by running experimental model simulations using observations collected during the field campaign. Overall, Mira allowed us to evaluate the impacts these observations and our project at large were having on forecasting skill.”

Read the full article by Greer Russell.

The more we know about how wind blows, the better we can harness the potential of wind energy. After four years of research, Argonne scientists and colleagues are helping to improve wind forecasting.
The more we know about how wind blows, the better we can harness the potential of wind energy. After four years of research, Argonne scientists and colleagues are helping to improve wind forecasting. [Source: Shutterstock / Dee Browning]
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portrait of V. Rao Kotamarthi
portrait of Paytsar Muradyan