Articles | Volume 10, issue 7
https://doi.org/10.5194/wes-10-1187-2025
https://doi.org/10.5194/wes-10-1187-2025
Research article
 | 
02 Jul 2025
Research article |  | 02 Jul 2025

Evaluating mesoscale model predictions of diurnal speedup events in the Altamont Pass Wind Resource Area of California

Robert S. Arthur, Alex Rybchuk, Timothy W. Juliano, Gabriel Rios, Sonia Wharton, Julie K. Lundquist, and Jerome D. Fast

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Cited articles

Ali, K., Schultz, D. M., Revell, A., Stallard, T., and Ouro, P.: Assessment of five wind-farm parameterizations in the Weather Research and Forecasting model: A case study of wind farms in the North Sea, Mon. Weather Rev., 151, 2333–2359, 2023. a
Archer, C. L., Wu, S., Ma, Y., and Jiménez, P. A.: Two corrections for turbulent kinetic energy generated by wind farms in the WRF model, Mon. Weather Rev., 148, 4823–4835, 2020. a, b, c
Arthur, R. S.: Evaluating mesoscale model predictions of diurnal speedup events in the Altamont Pass Wind Resource Area of California, Version v1, Zenodo [data set], https://doi.org/10.5281/zenodo.13871641, 2024. a, b, c
Arthur, R. S., Lundquist, K. A., and Olson, J. B.: Improved prediction of cold-air pools in the Weather Research and Forecasting model using a truly horizontal diffusion scheme for potential temperature, Mon. Weather Rev., 149, 155–171, 2021. a
Arthur, R. S., Juliano, T. W., Adler, B., Krishnamurthy, R., Lundquist, J. K., Kosović, B., and Jiménez, P. A.: Improved representation of horizontal variability and turbulence in mesoscale simulations of an extended cold-air pool event, J. Appl. Meteorol. Climatol., 61, 685–707, 2022. a, b, c, d, e, f, g, h, i, j, k
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This paper evaluates a new model configuration for wind energy forecasting in complex terrain. We compare model results to observations in the Altamont Pass (California, USA), where wind channeling through a mountain gap leads to increased energy production. We demonstrate that the new model configuration performs similarly to a more established approach, with some evidence of improved wind speed predictions, and provide guidance for future model testing.
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