Global wind resource assessments have benefitted in recent years from re-analysis datasets, which rely on a diverse collection of measurements and a global circulation model to reconstruct complete wind profiles. With high wind energy penetration, short-term and localized fluctuations are increasingly important relative to average annual availability for power systems planning and operation. Re-analysis methods have difficulty resolving these fluctuations, which are primarily driven by boundary layer atmospheric stability [1]. Leading methods to improve their accuracy such as downscaling are computationally expensive and geographically constrained [2]. Hence, tractable methods using available meso-scale data able to appropriately capture the fine temporal variability of wind farms distributed across large regions could improve siting, operation and policy for power systems.

Wind power densities were constructed from Modern Era Retrospective-analysis for Research and Applications (MERRA) boundary layer flux data produced by NASA at hourly resolution over a thirty-one-year period (1979-2009) [3]. We compared these data to several unassimilated wind measurement series and identified errors attributable to diurnal changes in boundary layer stability.


  1. Emeis, Stefan. 2013. Wind Energy Meteorology. Green Energy and Technology. Berlin, Heidelberg: Springer Berlin Heidelberg.
  2. Gryning, Sven-Erik, Jake Badger, Andrea N. Hahmann, and Ekaterina Batchvarova. 2014. “Current Status and Challenges in Wind Energy Assessment.” In Weather Matters for Energy, edited by Alberto Troccoli, Laurent Dubus, and Sue Ellen Haupt, 275–93. New York, NY: Springer New York.
  3. Zhang, D., M.R. Davidson, B. Gunturu, XL Zhang, and V.J. Karplus. 2014. “An Integrated Assessment of China’s Wind Energy Potential.” Report No. 261. Cambridge, MA: MIT Joint Program on the Science and Policy of Global Change.


Recommended citation:

Davidson, M. R. and Qi, T. (2015). “Re-Analysis Data for Fine Temporal Resolution Wind Power Estimation: A Comparison of Boundary Layer Parameterizations.” Graduate Climate Conference, Woods Hole Oceanographic Institution. Woods Hole, MA.