Mesoscale model evaluation with coherent Doppler lidar for wind farm assessment

Raghavendra Krishnamurthy, Ronald Calhoun, Brian Billings, James D. Doyle

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


Wind measurements are fundamental inputs for wind resource assessment and the performance of wind farms. Common approaches for wind energy yield assessment are based on (1) observational data from surface station networks and (2) high-resolution computational fluid dynamic or mesoscale models. In this letter, we investigate the potential of applying a high-resolution nested mesoscale model, Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS), to predict low-level wind characteristics for wind farm domains. The model results are compared to scanning coherent Doppler lidar and tower measurements for a wind energy development. This letter focuses on the magnitude of difference between observations and simulations used for wind energy assessment. The results highlight the challenge for straight-forward application of mesoscale models, even well-established models with a relatively fine resolution on the inner nest (333 m), to produce wind predictions of sufficient fidelity and accuracy appropriate for resource assessment or operational support for individual wind farms.While many of the average wind flow features are captured by the model, their detailed spatial and temporal evolution may be improved through tighter integration with local sensor data.

Original languageEnglish (US)
Pages (from-to)579-588
Number of pages10
JournalRemote Sensing Letters
Issue number6
StatePublished - 2013

ASJC Scopus subject areas

  • Earth and Planetary Sciences (miscellaneous)
  • Electrical and Electronic Engineering


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