A Case Study on Wind Speed Oscillations Offshore the West Coast of Central Taiwan

Fang-Ching Chien aDepartment of Earth Sciences, National Taiwan Normal University, Taipei, Taiwan

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Chun-Wei Chang aDepartment of Earth Sciences, National Taiwan Normal University, Taipei, Taiwan

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Jen-Hsin Teng bCentral Weather Administration, Taipei, Taiwan

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Jing-Shan Hong bCentral Weather Administration, Taipei, Taiwan

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Abstract

This paper investigates a wind speed oscillation event that occurred near the coastline of central Taiwan in the afternoon of 17 February 2018, using data from observations and numerical simulations. The observed wind speeds at 100-m altitude displayed a fast-oscillating pattern of about 6 cycles between strong winds of approximately 21 m s−1 and weak winds of around 2 m s−1, with periods of about 10 min. The pressure anomalies fluctuated in antiphase with the wind speed anomalies. The synoptic analysis revealed the influence of a continental high pressure system, resulting in a cold-air outbreak over Taiwan. The cold north-northeasterly winds split into two branches upon encountering Taiwan’s topography, with ridging off the east coast and a lee trough off the west coast of Taiwan. Wind oscillations were detected in the low-level cold air offshore the west coast of Taiwan, depicted by wavelike structures in wind speeds, sea level pressure, and potential temperature. The perturbations were identified as Kelvin-Helmholtz billows characterized by regions of strong wind speeds, warm and dry air, sinking motions, and low pressure collocated with each other, while regions of weaker wind speeds, cooler and moister air, ascending motions, and high pressure were associated with each other. With terrain contributing to favorable conditions, the large vertical and horizontal wind shears resulted from the southward acceleration of low-level cold air and the northward movement of the lee trough played an important role in initiating the wind oscillations.

© 2024 American Meteorological Society. This published article is licensed under the terms of the default AMS reuse license. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Fang-Ching Chien, jfj@ntnu.edu.tw

Abstract

This paper investigates a wind speed oscillation event that occurred near the coastline of central Taiwan in the afternoon of 17 February 2018, using data from observations and numerical simulations. The observed wind speeds at 100-m altitude displayed a fast-oscillating pattern of about 6 cycles between strong winds of approximately 21 m s−1 and weak winds of around 2 m s−1, with periods of about 10 min. The pressure anomalies fluctuated in antiphase with the wind speed anomalies. The synoptic analysis revealed the influence of a continental high pressure system, resulting in a cold-air outbreak over Taiwan. The cold north-northeasterly winds split into two branches upon encountering Taiwan’s topography, with ridging off the east coast and a lee trough off the west coast of Taiwan. Wind oscillations were detected in the low-level cold air offshore the west coast of Taiwan, depicted by wavelike structures in wind speeds, sea level pressure, and potential temperature. The perturbations were identified as Kelvin-Helmholtz billows characterized by regions of strong wind speeds, warm and dry air, sinking motions, and low pressure collocated with each other, while regions of weaker wind speeds, cooler and moister air, ascending motions, and high pressure were associated with each other. With terrain contributing to favorable conditions, the large vertical and horizontal wind shears resulted from the southward acceleration of low-level cold air and the northward movement of the lee trough played an important role in initiating the wind oscillations.

© 2024 American Meteorological Society. This published article is licensed under the terms of the default AMS reuse license. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Fang-Ching Chien, jfj@ntnu.edu.tw
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  • Akhtar, N., B. Geyer, B. Rockel, P. S. Sommer, and C. Schrum, 2021: Accelerating deployment of offshore wind energy alter wind climate and reduce future power generation potentials. Sci. Rep., 11, 11826, https://doi.org/10.1038/s41598-021-91283-3.

    • Search Google Scholar
    • Export Citation
  • Alexander, M. J., J. R. Holton, and D. R. Durran, 1995: The gravity wave response above deep convection in a squall line simulation. J. Atmos. Sci., 52, 22122226, https://doi.org/10.1175/1520-0469(1995)052<2212:TGWRAD>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Atkins, N. T., and R. M. Wakimoto, 1991: Wet microburst activity over the southeastern United States: Implications for forecasting. Wea. Forecasting, 6, 470482, https://doi.org/10.1175/1520-0434(1991)006<0470:WMAOTS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Barnes, H. C., J. P. Zagrodnik, L. A. McMurdie, A. K. Rowe, and R. A. Houze Jr., 2018: Kelvin–Helmholtz waves in precipitating midlatitude cyclones. J. Atmos. Sci., 75, 27632785, https://doi.org/10.1175/JAS-D-17-0365.1.

    • Search Google Scholar
    • Export Citation
  • Bauer, H.-S., S. K. Muppa, V. Wulfmeyer, A. Behrendt, K. Warrach-Sagi, and F. Späth, 2020: Multi-nested WRF simulations for studying planetary boundary layer processes on the turbulence-permitting scale in a realistic mesoscale environment. Tellus, 72A, 1761740, https://doi.org/10.1080/16000870.2020.1761740.

    • Search Google Scholar
    • Export Citation
  • Bentamy, A., and D. C. Croizé-Fillon, 2012: Gridded surface wind fields from Metop/ASCAT measurements. Int. J. Remote Sens., 33, 17291754, https://doi.org/10.1080/01431161.2011.600348.

    • Search Google Scholar
    • Export Citation
  • Blumen, W., R. Banta, S. P. Burns, D. C. Fritts, R. Newsom, G. S. Poulos, and J. Sun, 2001: Turbulence statistics of a Kelvin–Helmholtz billow event observed in the night-time boundary layer during the cooperative atmosphere–surface exchange study field program. Dyn. Atmos. Oceans, 34, 189204, https://doi.org/10.1016/S0377-0265(01)00067-7.

    • Search Google Scholar
    • Export Citation
  • Bolgiani, P., S. Fernández-González, F. Valero, A. Merino, E. García-Ortega, J. L. Sánchez, and M. L. Martín, 2020: Simulation of atmospheric microbursts using a numerical mesoscale model at high spatiotemporal resolution. J. Geophys. Res. Atmos., 125, e2019JD031791, https://doi.org/10.1029/2019JD031791.

    • Search Google Scholar
    • Export Citation
  • Brown, A. R., M. Athanassiadou, and N. Wood, 2003: Topographically induced waves within the stable boundary layer. Quart. J. Roy. Meteor. Soc., 129, 33573370, https://doi.org/10.1256/qj.02.176.

    • Search Google Scholar
    • Export Citation
  • Chapman, D., and K. A. Browning, 1997: Radar observations of wind-shear splitting within evolving atmospheric Kelvin–Helmholtz billows. Quart. J. Roy. Meteor. Soc., 123, 14331439, https://doi.org/10.1002/qj.49712354114.

    • Search Google Scholar
    • Export Citation
  • Chemel, C., C. Staquet, and Y. Largeron, 2009: Generation of internal gravity waves by a katabatic wind in an idealized alpine valley. Meteor. Atmos. Phys., 103, 187194, https://doi.org/10.1007/s00703-009-0349-4.

    • Search Google Scholar
    • Export Citation
  • Chen, Y.-L., and N. B.-F. Hui, 1990: Analysis of a shallow front during the Taiwan Area Mesoscale Experiment. Mon. Wea. Rev., 118, 26492667, https://doi.org/10.1175/1520-0493(1990)118<2649:AOASFD>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Chen, Y.-L., and N. B.-F. Hui, 1992: Analysis of a relatively dry front during the Taiwan area mesoscale experiment. Mon. Wea. Rev., 120, 24422468, https://doi.org/10.1175/1520-0493(1992)120<2442:AOARDF>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Chen, Y.-L., Y.-X. Zhang, and N. B.-F. Hui, 1989: Analysis of a surface front during the early summer rainy season over Taiwan. Mon. Wea. Rev., 117, 909931, https://doi.org/10.1175/1520-0493(1989)117<0909:AOASFD>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Chien, F.-C., and Y.-H. Kuo, 2006: Topographic effects on a wintertime cold front in Taiwan. Mon. Wea. Rev., 134, 32973316, https://doi.org/10.1175/MWR3255.1.

    • Search Google Scholar
    • Export Citation
  • Childs, S. J., R. S. Schumacher, and R. D. Adams-Selin, 2021: High-resolution observations of a destructive macroburst. Mon. Wea. Rev., 149, 28752896, https://doi.org/10.1175/MWR-D-20-0412.1.

    • Search Google Scholar
    • Export Citation
  • Chilson, P. B., A. Muschinski, and G. Schmidt, 1997: First observations of Kelvin–Helmholtz billows in an upper level jet stream using VHF frequency domain interferometry. Radio Sci., 32, 11491160, https://doi.org/10.1029/97RS00088.

    • Search Google Scholar
    • Export Citation
  • Chimonas, G., and C. J. Nappo, 1987: A thunderstorm bow wave. J. Atmos. Sci., 44, 533541, https://doi.org/10.1175/1520-0469(1987)044<0533:ATBW>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Chlond, A., and A. Wolkau, 2000: Large-eddy simulation of a nocturnal stratocumulus-topped marine atmospheric boundary layer: An uncertainty analysis. Bound.-Layer Meteor., 95, 3155, https://doi.org/10.1023/A:1002438701638.

    • Search Google Scholar
    • Export Citation
  • Clark, T. L., T. Hauf, and J. P. Kuettner, 1986: Convectively forced internal gravity waves: Results from two-dimensional numerical experiments. Quart. J. Roy. Meteor. Soc., 112, 899925, https://doi.org/10.1002/qj.49711247402.

    • Search Google Scholar
    • Export Citation
  • Colle, B. A., and C. F. Mass, 1998: Windstorms along the western side of the Washington Cascade Mountains. Part I: A high-resolution observational and modeling study of the 12 February 1995 event. Mon. Wea. Rev., 126, 2852, https://doi.org/10.1175/1520-0493(1998)126<0028:WATWSO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Conrick, R., C. F. Mass, and Q. Zhong, 2018: Simulated Kelvin–Helmholtz waves over terrain and their microphysical implications. J. Atmos. Sci., 75, 27872800, https://doi.org/10.1175/JAS-D-18-0073.1.

    • Search Google Scholar
    • Export Citation
  • Cotton, W. R., J. F. Weaver, and B. A. Beitler, 1995: An unusual summertime downslope wind event in Fort Collins, Colorado, on 3 July 1993. Wea. Forecasting, 10, 786797, https://doi.org/10.1175/1520-0434(1995)010<0786:AUSDWE>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Couto, A., and A. Estanqueiro, 2022: Enhancing wind power forecast accuracy using the Weather Research and Forecasting numerical model-based features and artificial neuronal networks. Renewable Energy, 201, 10761085, https://doi.org/10.1016/j.renene.2022.11.022.

    • Search Google Scholar
    • Export Citation
  • de Freitas, N. C. A., M. P. d. S. Silva, and M. S. Sakamoto, 2018: Wind speed forecasting: A review. Int. J. Eng. Sci., 8, 49, https://doi.org/10.9790/9622-0801010409.

    • Search Google Scholar
    • Export Citation
  • Draxl, C., and Coauthors, 2021: Mountain waves can impact wind power generation. Wind Energy Sci., 6, 4560, https://doi.org/10.5194/wes-6-45-2021.

    • Search Google Scholar
    • Export Citation
  • Durran, D. R., 1986: Another look at downslope windstorms. Part I: The development of analogs to supercritical flow in an infinitely deep continuously stratified fluid. J. Atmos. Sci., 43, 25272543, https://doi.org/10.1175/1520-0469(1986)043<2527:ALADWP>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Einaudi, F., A. J. Bedard Jr., and J. J. Finnigan, 1989: A climatology of gravity waves and other coherent disturbances at the boulder atmospheric observatory during March–April 1984. J. Atmos. Sci., 46, 303329, https://doi.org/10.1175/1520-0469(1989)046<0303:ACOGWA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Feltz, W. F., K. M. Bedka, J. A. Otkin, T. Greenwald, and S. A. Ackerman, 2009: Understanding satellite-observed mountain wave signatures using high-resolution numerical model data. Wea. Forecasting, 24, 7686, https://doi.org/10.1175/2008WAF2222127.1.

    • Search Google Scholar
    • Export Citation
  • Friedrich, K., D. E. Kingsmill, C. Flamant, H. V. Murphy, and R. M. Wakimoto, 2008: Kinematic and moisture characteristics of a nonprecipitating cold front observed during IHOP. Part II: Alongfront structures. Mon. Wea. Rev., 136, 37963821, https://doi.org/10.1175/2008MWR2360.1.

    • Search Google Scholar
    • Export Citation
  • Geerts, B., and Q. Miao, 2010: Vertically pointing airborne Doppler radar observations of Kelvin–Helmholtz billows. Mon. Wea. Rev., 138, 982986, https://doi.org/10.1175/2009MWR3212.1.

    • Search Google Scholar
    • Export Citation
  • Gong, Y., Y. Li, and D.-L. Zhang, 2018: A statistical study of unusual tracks of tropical cyclones near Taiwan Island. J. Appl. Meteor. Climatol., 57, 193206, https://doi.org/10.1175/JAMC-D-17-0080.1.

    • Search Google Scholar
    • Export Citation
  • Grasmick, C., and B. Geerts, 2020: Detailed dual-Doppler structure of Kelvin–Helmholtz waves from an airborne profiling radar over complex terrain. Part I: Dynamic structure. J. Atmos. Sci., 77, 17611782, https://doi.org/10.1175/JAS-D-19-0108.1.

    • Search Google Scholar
    • Export Citation
  • Groch, M., and H. J. Vermeulen, 2019: Modeling high wind speed shut-down events using meso-scale wind profiles and survival analysis. IEEE Trans. Power Syst., 34, 49554963, https://doi.org/10.1109/TPWRS.2019.2921940.

    • Search Google Scholar
    • Export Citation
  • Groch, M., and H. J. Vermeulen, 2022: Forecasting wind speed events at a utility-scale wind farm using a WRF-ANN model. Wind Eng., 46, 102119, https://doi.org/10.1177/0309524X211010758.

    • Search Google Scholar
    • Export Citation
  • Hald, C., M. Zeeman, P. Laux, M. Mauder, and H. Kunstmann, 2019: Large-eddy simulations of real-world episodes in complex terrain based on ERA-reanalysis and validated by ground-based remote sensing data. Mon. Wea. Rev., 147, 43254343, https://doi.org/10.1175/MWR-D-19-0016.1.

    • Search Google Scholar
    • Export Citation
  • Heath, N. K., H. E. Fuelberg, S. Tanelli, F. J. Turk, R. P. Lawson, S. Woods, and S. Freeman, 2017: WRF nested large-eddy simulations of deep convection during SEAC4RS. J. Geophys. Res. Atmos., 122, 39533974, https://doi.org/10.1002/2016JD025465.

    • Search Google Scholar
    • Export Citation
  • Hjelmfelt, M. R., 2010: Microbursts and macrobursts: Windstorms and blowdowns. Plant Disturbance Ecology: The Process and the Response, E. Johnson and K. Miyanishi, Eds., Academic Press, 59–101.

  • Hong, S.-Y., Y. Noh, and J. Dudhia, 2006: A new vertical diffusion package with an explicit treatment of entrainment processes. Mon. Wea. Rev., 134, 23182341, https://doi.org/10.1175/MWR3199.1.

    • Search Google Scholar
    • Export Citation
  • Hu, X., X. Lee, D. E. Stevens, and R. B. Smith, 2002: A numerical study of nocturnal wavelike motion in forests. Bound.-Layer Meteor., 102, 199223, https://doi.org/10.1023/A:1013167228992.

    • Search Google Scholar
    • Export Citation
  • Jiang, Q., Q. Wang, S. Wang, and S. Gaberšek, 2020: Turbulence adjustment and scaling in an offshore convective internal boundary layer: A CASPER case study. J. Atmos. Sci., 77, 16611681, https://doi.org/10.1175/JAS-D-19-0189.1.

    • Search Google Scholar
    • Export Citation
  • Kain, J. S., and J. M. Fritsch, 1990: A one-dimensional entraining/detraining plume model and its application in convective parameterization. J. Atmos. Sci., 47, 27842802, https://doi.org/10.1175/1520-0469(1990)047<2784:AODEPM>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Karim, S. M. S., Y.-L. Lin, and M. L. Kaplan, 2022: Formation mechanisms of the mesoscale environment conducive to a downslope windstorm over the Cuyamaca Mountains associated with Santa Ana wind during the Cedar Fire (2003). J. Appl. Meteor. Climatol., 61, 17971818, https://doi.org/10.1175/JAMC-D-22-0025.1.

    • Search Google Scholar
    • Export Citation
  • Lawson, J., and J. Horel, 2015: Analysis of the 1 December 2011 Wasatch downslope windstorm. Wea. Forecasting, 30, 115135, https://doi.org/10.1175/WAF-D-13-00120.1.

    • Search Google Scholar
    • Export Citation
  • Lee, X., H. H. Neumann, G. Hartog, J. D. Fuentes, T. A. Black, R. E. Mickle, P. C. Yang, and P. D. Blaken, 1997: Observation of gravity waves in a boreal forest. Bound.-Layer Meteor., 84, 383398, https://doi.org/10.1023/A:1000454030493.

    • Search Google Scholar
    • Export Citation
  • Li, L., and Y.-L. Chen, 2017: Numerical simulations of two trapped mountain lee waves downstream of Oahu. J. Appl. Meteor. Climatol., 56, 13051324, https://doi.org/10.1175/JAMC-D-15-0341.1.

    • Search Google Scholar
    • Export Citation
  • Lyulyukin, V., and Coauthors, 2019: Sodar observation of the ABL structure and waves over the Black Sea offshore site. Atmosphere, 10, 811, https://doi.org/10.3390/atmos10120811.

    • Search Google Scholar
    • Export Citation
  • Mass, C. F., N. Weber, R. Conrick, and J. P. Zagrodnik, 2019: The Quinault blowdown: A microscale wind event driven by a mountain-wave rotor. Bull. Amer. Meteor. Soc., 100, 977986, https://doi.org/10.1175/BAMS-D-18-0232.1.

    • Search Google Scholar
    • Export Citation
  • Medina, S., and R. A. Houze Jr., 2016: Kelvin–Helmholtz waves in extratropical cyclones passing over mountain ranges. Quart. J. Roy. Meteor. Soc., 142, 13111319, https://doi.org/10.1002/qj.2734.

    • Search Google Scholar
    • Export Citation
  • Mitchell, M. J., B. Ancell, J. A. Lee, and N. H. Smith, 2020: Configuration of statistical postprocessing techniques for improved low-level wind speed forecasts in West Texas. Wea. Forecasting, 35, 129147, https://doi.org/10.1175/WAF-D-18-0186.1.

    • Search Google Scholar
    • Export Citation
  • Nakanishi, M., R. Shibuya, J. Ito, and H. Niino, 2014: Large-eddy simulation of a residual layer: Low-level jet, convective rolls, and Kelvin–Helmholtz instability. J. Atmos. Sci., 71, 44734491, https://doi.org/10.1175/JAS-D-13-0402.1.

    • Search Google Scholar
    • Export Citation
  • Newsom, R. K., and R. M. Banta, 2003: Shear-flow instability in the stable nocturnal boundary layer as observed by Doppler lidar during CASES-99. J. Atmos. Sci., 60, 1633, https://doi.org/10.1175/1520-0469(2003)060<0016:SFIITS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Parodi, A., and S. Tanelli, 2010: Influence of turbulence parameterizations on high-resolution numerical modeling of tropical convection observed during the TC4 field campaign. J. Geophys. Res., 115, D00J14, https://doi.org/10.1029/2009JD013302.

    • Search Google Scholar
    • Export Citation
  • Plant, R. S., and G. J. Keith, 2007: Occurrence of Kelvin–Helmholtz billows in sea-breeze circulations. Bound.-Layer Meteor., 122 (1), 115, https://doi.org/10.1007/s10546-006-9089-x.

    • Search Google Scholar
    • Export Citation
  • Plougonven, R., and F. Zhang, 2014: Internal gravity waves from atmospheric jets and fronts. Rev. Geophys., 52, 3376, https://doi.org/10.1002/2012RG000419.

    • Search Google Scholar
    • Export Citation
  • Raasch, S., and M. Schröter, 2001: PALM–A large-eddy simulation model performing on massively parallel computers. Meteor. Z., 10, 363372, https://doi.org/10.1127/0941-2948/2001/0010-0363.

    • Search Google Scholar
    • Export Citation
  • Rogers, R. E., A. Deng, D. R. Stauffer, B. J. Gaudet, Y. Jia, S.-T. Soong, and S. Tanrikulu, 2013: Application of the weather research and forecasting model for air quality modeling in the San Francisco Bay Area. J. Appl. Meteor. Climatol., 52, 19531973, https://doi.org/10.1175/JAMC-D-12-0280.1.

    • Search Google Scholar
    • Export Citation
  • Romanic, R., M. Taszarek, and H. Brooks, 2022: Convective environments leading to microburst, macroburst and downburst events across the United States. Wea. Climate Extremes, 37, 100474, https://doi.org/10.1016/j.wace.2022.100474.

    • Search Google Scholar
    • Export Citation
  • Samelson, R. M., and E. D. Skyllingstad, 2016: Frontogenesis and turbulence: A numerical simulation. J. Atmos. Sci., 73, 50255040, https://doi.org/10.1175/JAS-D-16-0145.1.

    • Search Google Scholar
    • Export Citation
  • Schumacher, R. S., S. J. Childs, and R. D. Adams-Selin, 2023: Intense surface winds from gravity wave breaking in simulations of a destructive macroburst. Mon. Wea. Rev., 151, 775793, https://doi.org/10.1175/MWR-D-22-0103.1.

    • Search Google Scholar
    • Export Citation
  • Skamarock, W. C., and Coauthors, 2019: A description of the Advanced Research WRF model version 4. NCAR Tech. Note NCAR/TN-556+STR, 145 pp., https://doi.org/10.5065/1dfh-6p97.

  • Tao, W.-K., J. Simpson, and M. McCumber, 1989: An ice-water saturation adjustment. Mon. Wea. Rev., 117, 231235, https://doi.org/10.1175/1520-0493(1989)117<0231:AIWSA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Taylor, J. W., 2017: Probabilistic forecasting of wind power ramp events using autoregressive logit models. Eur. J. Oper. Res., 259, 703712, https://doi.org/10.1016/j.ejor.2016.10.041.

    • Search Google Scholar
    • Export Citation
  • Teixeira, M. A. C., and P. M. A. Miranda, 2004: The effect of wind shear and curvature on the gravity wave drag produced by a ridge. J. Atmos. Sci., 61, 26382643, https://doi.org/10.1175/JAS3282.1.

    • Search Google Scholar
    • Export Citation
  • Wakimoto, R. M., and B. L. Bosart, 2001: Airborne radar observations of a warm front during FASTEX. Mon. Wea. Rev., 129, 254274, https://doi.org/10.1175/1520-0493(2001)129<0254:AROOAW>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Wang, Y., R. Zou, F. Liu, L. Zhang, and Q. Liu, 2021: A review of wind speed and wind power forecasting with deep neural networks. Appl. Energy, 304, 117766, https://doi.org/10.1016/j.apenergy.2021.117766.

    • Search Google Scholar
    • Export Citation
  • Wang, Z., and W. Liu, 2021: Wind energy potential assessment based on wind speed, its direction and power data. Sci. Rep., 11, 16879, https://doi.org/10.1038/s41598-021-96376-7.

    • Search Google Scholar
    • Export Citation
  • Xia, G., C. Draxl, A. Raghavendra, and J. K. Lundquist, 2021: Validating simulated mountain wave impacts on hub-height wind speed using SoDAR observations. Renewable Energy, 163, 22202230, https://doi.org/10.1016/j.renene.2020.10.127.

    • Search Google Scholar
    • Export Citation
  • Xue, H., J. Li, T. Qian, and H. Gu, 2020: A 100-m-scale modeling study of a gale event on the lee side of a long narrow mountain. J. Appl. Meteor. Climatol., 59, 2345, https://doi.org/10.1175/JAMC-D-19-0066.1.

    • Search Google Scholar
    • Export Citation
  • Zhang, X., and Coauthors, 2019: Improving lake-breeze simulation with WRF nested LES and lake model over a large shallow lake. J. Appl. Meteor. Climatol., 58, 16891708, https://doi.org/10.1175/JAMC-D-18-0282.1.

    • Search Google Scholar
    • Export Citation
  • Zhou, B., and F. K. Chow, 2013: Nighttime turbulent events in a steep valley: A nested large-eddy simulation study. J. Atmos. Sci., 70, 32623276, https://doi.org/10.1175/JAS-D-13-02.1.

    • Search Google Scholar
    • Export Citation
  • Zhou, B., and F. K. Chow, 2014: Nested large-eddy simulations of the intermittently turbulent stable atmospheric boundary layer over real terrain. J. Atmos. Sci., 71, 10211039, https://doi.org/10.1175/JAS-D-13-0168.1.

    • Search Google Scholar
    • Export Citation
  • Zhu, P., B. A. Albrecht, V. P. Ghate, and Z. Zhu, 2010: Multiple-scale simulations of stratocumulus clouds. J. Geophys. Res., 115, D23201, https://doi.org/10.1029/2010JD014400.

    • Search Google Scholar
    • Export Citation
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