your website name here

Content

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Vivamus viverra, eros sed ullamcorper adipiscing, dolor ante aliquam justo, sed mollis turpis augue ut nisl. Nunc id orci metus, a rhoncus massa. In hac habitasse platea dictumst. Fusce sit amet arcu a dui mattis ultricies.

Google Scholar

ORCID 0000-0001-5490-2702

Publications by year 

2021

113. Rybchuk, O., J. K. Lundquist, C. Alden, and G. Reiker, 2021, Validation of near-surface dispersion simulation of WRF-LES with Project Prairie Grass data. Monthly Weather Review , 149(5), 1619-1633, https://journals.ametsoc.org/view/journals/mwre/149/5/MWR-D-20-0233.1.xml  (First author graduate student supervised by Lundquist.)

112. Jensen, A. A., J. O. Pinto, S. C. C. Bailey, R. A. Sobash, G. de Boer, A. L. Houston, P. B. Chilson, T. Bell, G. Romine, S. W. Smith, D. A. Lawrence, C. Dixon, J. K. Lundquist, J. D. Jacob, J. Elston, S. Waugh, M. Steiner, 2021, Assimilation of a coordinated fleet of unmanned aircraft systems observations in complex terrain: EnKF system design and preliminary assessment. Monthly Weather Review. https://doi.org/10.1175/MWR-D-20-0359.1

111. Bell, T. M., P. M. Klein, J. K. Lundquist, and S. Waugh, 2021, Remote sensing and radiosonde datasets collected in the San Luis Valley during the LAPSE-RATE campaign. Earth System Science Data, 13, 1041-1051, 2021.

110. Draxl, C., R. Worsnop, G. Xia, Y. Pichugina, D.. Chand, J. K. Lundquist, J. Sharp, G. Wedam, J. M. Wilczak, and L. K. Berg, 2020, Mountain waves impact wind power generation, Wind Energy Science, 6, 45-60.

109. Tomaszewski, J. and J. K. Lundquist, 2020, Observations and Simulations of a Wind Farm Modifying a Thunderstorm Outflow Boundary. Wind Energy Science, 6, 1-13. (First author graduate student supervised by Lundquist.)

2020

108. Livingston, H. and J. K. Lundquist, 2020, How many offshore wind turbines does New England need?, Meteorological Applications, 2020; 27:e1969. (First author undergraduate student supervised by Lundquist.)

107. Xia G., C. Draxl, A. Raghavendra, and J. K. Lundquist, 2020, Validating Simulated Mountain Wave Impacts on Hub-Height Wind Speed Using SoDAR Observations, accepted for publication in Renewable Energy, https://doi.org/10.1016/j.renene.2020.10.127 

106. Englberger, A.,  J. K. Lundquist, and A. Dörnback, 2020, Changing the rotational direction of a wind turbine under veering inflow: a parameter study, Wind Energ. Sci., 5, 1623–1644, https://doi.org/10.5194/wes-5-1623-2020, 2020.

105. Bloomfield, H. C.; P. L.M. Gonzalez; J. K. Lundquist; L. P. Laurens; Jethro Browell; Roger Dargaville; Matteo De Felice; Katharina Gruber; Adriaan Hilbers; Alex Kies; Mathaios Panteli; Hazel E Thornton; Jan Wohland; Marianne Zeyringer; David J Brayshaw, 2020, The importance of weather and climate to energy systems: A workshop on Next Generation Challenges in Energy-Climate Modelling. Accepted for publication in the Bulletin of the American Meteorological Society.

104. de Boer, G., Houston, A., Jacob, J., Chilson, P. B., Smith, S. W., Argrow, B., Lawrence, D., Elston, J., Brus, D., Kemppinen, O., Klein, P., Lundquist, J. K., Waugh, S., Bailey, S. C. C., Frazier, A., Sama, M. P., Crick, C., Schmale III, D., Pinto, J., Pillar-Little, E. A., Natalie, V., and Jensen, A.: Data generated during the 2018 LAPSE-RATE campaign: an introduction and overview, Earth Syst. Sci. Data, 12, 3357–3366, https://doi.org/10.5194/essd-12-3357-2020, 2020.

103. Djalalova, I. V., Bianco, L., Akish, E., Wilczak, J. M., Olson, J. B., Kenyon, J. S., Berg, L. K., Choukulkar, A., Coulter, R., Fernando, H. J. S., Grimit, E., Krishnamurthy, R., Lundquist, J. K., Muradyan, P., Turner, D. D., & Wharton, S. (2020). Wind Ramp Events Validation in NWP Forecast Models during the Second Wind Forecast Improvement Project (WFIP2) Using the Ramp Tool and Metric (RT&M), Weather and Forecasting, 35(6), 2407-2421, https://journals.ametsoc.org/view/journals/wefo/35/6/WAF-D-20-0072.1.xml

102. Englberger, A., A. Dörnback, and J. K. Lundquist, 2020, Does the rotational direction of a wind turbine impact the wake in a stably stratified atmospheric boundary layer? Wind Energ. Sci., 5, 1359–1374, https://doi.org/10.5194/wes-5-1359-2020.

101. Bodini, N., J. K. Lundquist, and M. Optis, 2020, Can machine learning improve the model representation of TKE dissipation rate in the boundary layer for complex terrain? Geoscientific Model Development 13, 4271–4285, https://doi.org/10.5194/gmd-13-4271-2020. (First author graduate student supervised by Lundquist when the paper was written.)

100. Murphy, P., Lundquist, J. K., Fleming, P., 2020, How wind speed shear and directional veer affect the power production of a megawatt-scale operational wind turbine. Wind Energy Science, 5, 1169-1190, https://doi.org/10.5194/wes-5-1169-2020 (First author undergraduate student supervised by Lundquist).

99.
Pichugina, Y., R.M. Banta, W. A. Brewer, L. Bianco, C. Draxl, J. Kenyon, J. K. Lundquist, J. B. Olson, D. D. Turner, S. Wharton, J. Wilczak, S. Baidar, L. K. Berg, H.J.S. Fernando, B. J. McCarty, R. Rai, B. Roberts, J. Sharp, W. J. Shaw, M. T. Stoelinga, and R. Worsnop, 2020, Evaluating the WFIP2 updates to the HRRR model using scanning Doppler lidar measurements in the complex terrain of the Columbia River Basin. Journal of Renewable and Sustainable Energy, 12, 043301 (2020); https://doi.org/10.1063/5.0009138.

98. Fleming, P., King, J., Simley, E., Roadman, J., Scholbrock, A., Murphy, P., Lundquist, J. K., Moriarty, P., Fleming, K., van Dam, J., Bay, C., Mudafort, R., Jager, D., Skopek, J., Scott, M., Ryan, B., Guernsey, C., and Brake, D.: Continued Results from a Field Campaign of Wake Steering Applied at a Commercial Wind Farm: Part 2, accepted for publication in Wind Energ. Sci., https://doi.org/10.5194/wes-2019-104, 2020.

97. Luchetti, N. T., K. Friedrich, C. E. Rodell, and J. K. Lundquist, 2020, Characterizating Thunderstorm Gust Fronts Near Complex Terrain.  Monthly Weather Review 148 (8): 3267–3286. (First author student co-supervised by Lundquist)

96. Tomaszewski, J. M., and J. K. Lundquist, 2020, Simulated wind farm wake sensitivity to configuration choices in the Weather Research and Forecasting model version 3.8.1. Geoscientific Model Development, 13, 2645-2662, https://doi.org/10.5194/gmd-13-2645-2020. (First author student supervised by Lundquist)

95. Gasch, P., Wieser, A., Lundquist, J. K., and Kalthoff, N.: An LES-based airborne Doppler lidar simulator and its application to wind profiling in inhomogeneous flow conditions, Atmos. Meas. Tech., 13, 1609–1631, https://doi.org/10.5194/amt-13-1609-2020, 2020. (First author visiting student supervised by Lundquist during CU visit)

94. Siedersleben, S. K., Platis, A., Lundquist, J. K., Djath, B., Lampert, A., Bärfuss, K., Cañadillas, B., Schulz-Stellenfleth, J., Bange, J., Neumann, T., and Emeis, S.: Turbulent kinetic energy over large offshore wind farms observed and simulated by the mesoscale model WRF (3.8.1), Geosci. Model Dev., 13, 249–268, https://doi.org/10.5194/gmd-13-249-2020, 2020 (First author visiting student supervised by Lundquist during CU visit)

93. de Boer, Gijs, C.  Diehl, J. Jacob, A. Houston, S. Smith, P. Chilson, D. G. Schmale III, J. Intrieri, J. Pinto, J. Elston, David Brus, Osku Kemppinen, Alex Clark, Dale Lawrence, Sean Bailey, Amy Frazier, Victoria Natalie, Elizabeth Pillar-Little, Petra Klein, Sean Waugh, J. K. Lundquist, L. Barbieri, S. Kral, A. Jensen, C. Dixon, Steven Borenstein, Daniel Hesselius, Kathleen Human, Phillip Hall, Brian Argrow, Troy Thornberry, Ru-Shan Gao, Randy Wright, and  J. T. Kelly, 2020, Development of community, capabilities and understanding through unmanned aircraft-based atmospheric research: The LAPSE-RATE campaign. Bulletin of the American Meteorological Society 101 (5): E684–E699. https://doi.org/10.1175/BAMS-D-19-0050.1

92. Bianco, L. I.V. Djalalova, J. M. Wilczak, J. B. Olson, J. S. Kenyon, A. Choukulkar, L. K. Berg, H. J. S. Fernando, E. P. Grimit, R. Krishnamurthy, J. K. Lundquist, P. Muradyan, M. Pekour, Y. Pichugina, M. T. Stoelinga, D. D. Turner, 2019, Impact of model improvements on 80-m wind speeds during the second Wind Forecast Improvement Project (WFIP2), Geosci. Model Dev., 12, 4803–4821, https://doi.org/10.5194/gmd-12-4803-2019

91. Sanchez Gomez, M. and Lundquist, J. K.: The effect of wind direction shear on turbine performance in a wind farm in central Iowa, Wind Energ. Sci., 5, 125–139, https://doi.org/10.5194/wes-5-125-2020, 2020. (First author student supervised by Lundquist)

90. Wildmann, N., N. Bodini, J. K. Lundquist, L. Bariteau, J. Wagner, 2020. Estimation of turbulence parameters from scanning lidars and in-situ instrumentation in the Perdigão 2017 campaign. Atmospheric Measurement Techniques 12, 6401–6423, https://doi.org/10.5194/amt-12-6401-2019

89. Kapoor, A., Ouakka, S., Arwade, S. R., Lundquist, J. K., Lackner, M. A., Myers, A. T., Worsnop, R. P., and Bryan, G. H.: Hurricane eyewall winds and structural response of wind turbines, Wind Energ. Sci., 5, 89–104, https://doi.org/10.5194/wes-5-89-2020 , 2020.

2019

88. Veers, P., K. Dykes, E. Lantz, S. Barth, C. Bottasso, O. Carlson, A. J. Clifton, H. Holttinen, D. Laird, V. Lehtomäki, J. K. Lundquist, J. Manwell, M. Marquis, C. Meneveau, P. Moriarty, X. Munduate, M. Muskulus, J. Naughton, L. Pao, J., Paquette, J. Peinke, A. Robertson, J. Sanz-Rodrigo, A. M. Sempreviva, C. Smith, A. Tuohy, R. Wiser, 2019. Grand Challenges in the Science of Wind Energy and the Need for Integrated Research. Science. DOI: 10.1126/science.aau2027

87. Olson, J.B., J.S. Kenyon, I. Djalalova, L. Bianco, D.D. Turner, Y. Pichugina, A. Choukulkar, M.D. Toy, J.M. Brown, W.M. Angevine, E. Akish, J. Bao, P. Jimenez, B. Kosovic, K.A. Lundquist, C. Draxl, J.K. Lundquist, J. McCaa, K. McCaffrey, K. Lantz, C. Long, J. Wilczak, R. Banta, M. Marquis, S. Redfern, L.K. Berg, W. Shaw, and J. Cline, 2019: Improving Wind Energy Forecasting through Numerical Weather Prediction Model Development. Bull. Amer. Meteor. Soc., 100, 2201–2220, https://doi.org/10.1175/BAMS-D-18-0040.1.

86. Mazzaro, L., E. Koo, D. Muñoz-Esparza, J. K. Lundquist, R. R. Linn: Random force perturbations: a new extension of the cell perturbation method for turbulence generation in multi-scale atmospheric boundary layer simulations, Journal for Advances in Modeling Earth Systems, 11, 2311-2329, 2019. https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2019MS001608 (First author student supervised by Lundquist)

85. Fleming, P., King, J., Dykes, K., Simley, E., Roadman, J., Scholbrock, A., Murphy, P., Lundquist, J. K., Moriarty, P., Fleming, K., van Dam, J., Bay, C., Mudafort, R., Lopez, H., Skopek, J., Scott, M., Ryan, B., Guernsey, C., and Brake, D.: Initial Results From a Field Campaign of Wake Steering Applied at a Commercial Wind Farm: Part 1, Wind Energy Science, 4, 273–285, https://doi.org/10.5194/wes-4-273-2019

84.
Bodini, N., J. K. Lundquist, A. Kirincich, 2019. Offshore wind turbines will encounter very low atmospheric turbulence. Geophysical Research Letters  46, 5582-5591 https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2019GL082636 (First author student supervised by Lundquist)

83. Wilczak, J.M., M. Stoelinga, L.K. Berg, J. Sharp, C. Draxl, K. McCaffrey, R.M. Banta, L. Bianco, I. Djalalova, J.K. Lundquist, P. Muradyan, A. Choukulkar, L. Leo, T. Bonin, Y. Pichugina, R. Eckman, C.N. Long, K. Lantz, R.P. Worsnop, J. Bickford, N. Bodini, D. Chand, A. Clifton, J. Cline, D.R. Cook, H.J. Fernando, K. Friedrich, R. Krishnamurthy, M. Marquis, J. McCaa, J.B. Olson, S. Otarola-Bustos, G. Scott, W.J. Shaw, S. Wharton, and A.B. White, 2019: The Second Wind Forecast Improvement Project (WFIP2): Observational Field Campaign. Bull. Amer. Meteor. Soc., 100, 1701–1723, https://doi.org/10.1175/BAMS-D-18-0035.1

82. Shaw, W.J., L.K. Berg, J. Cline, C. Draxl, I. Djalalova, E.P. Grimit, J.K. Lundquist, M. Marquis, J. McCaa, J.B. Olson, C. Sivaraman, J. Sharp, and J.M. Wilczak, 2019: The Second Wind Forecast Improvement Project (WFIP2): General Overview. Bull. Amer. Meteor. Soc., 100, 1687–1699, https://doi.org/10.1175/BAMS-D-18-0036.1

81. Bodini, N., Lundquist, J. K., Krishnamurthy, R., Pekour, M., Berg, L. K., and Choukulkar, A.: Spatial and temporal variability of turbulence dissipation rate in complex terrain, Atmos. Chem. Phys., 19, 4367-4382, https://doi.org/10.5194/acp-19-4367-2019, 2019. (First author student supervised by Lundquist)

80. Menke, R., Vasiljević, N., Mann, J., and Lundquist, J. K.: Characterization of flow recirculation zones at the Perdigão site using multi-lidar measurements, Atmos. Chem. Phys., 19, 2713-2723, https://doi.org/10.5194/acp-19-2713-2019, 2019. (First author vsiting student supervised by Lundquist during CU visit)

79. Redfern, S., J. B. Olson, J. K. Lundquist, C. T. M. Clack, 2019, Incorporation of the Rotor-Equivalent Wind Speed into the Weather Research and Forecasting model’s Wind Farm Parameterization. Monthly Weather Review 147, 1029-1046. (First author student supervised by Lundquist)

78. Fernando, H. J. S., J. Mann, J. M. L. M. Palma, J. K. Lundquist, and 44 other co-authors, 2019, The Perdigão: Peering into Microscale Details of Mounain Winds, accepted for publication in the Bulletin of the American Meteorological Society.

2018

77. Siedersleben, S. K., J. K. Lundquist, A. Platis, A. Lampert, K. Bärfuss, B. Cañadillas, B. Djath, J. Schulz-Stellenfleth, T. Neumann, J. Bange, S. Emeis, 2018, Micrometeorological Impacts of Offshore Wind Farms as seen in Observations and Simulations, Environmental Research Letters 13, 124012. (First author visiting student supervised by Lundquist during CU visit)

76. Lundquist, J. K., K.K. DuVivier, D. Kaffine, J. M. Tomaszewski, 2018. Costs and consequences of wind turbine wake effects arising from uncoordinated wind energy development. Nature Energy, https://doi.org/10.1038/s41560-018-0281-2.

75. Lee, J. C.-Y., M. J. Fields, J. K. Lundquist, 2018, Assessing Variability of Wind Speed: Comparison and Validation of 27 Methodologies. Wind Energy Science, 3, 845-868, https://doi.org/10.5194/wes-3-845-2018. (First author student supervised by Lundquist)

74. Tomaszewski, J.M., J. K. Lundquist, M. J. Churchfield, and P. Moriarty. 2018. Do wind turbines pose roll hazards to light aircraft? Wind Energy Science, 3, 833-843, https://doi.org/10.5194/wes-3-833-2018. (First author student supervised by Lundquist)

73. Siedersleben, S. K., A. Platis, J. K. Lundquist, A. Lampert, K. Bärfuss, B. Canadillas, B.  Djath, J. Schulz-Stellenfleth, J. Bange, T. Neumann, S. Emeis: Evaluation of a Wind Farm Parametrization for Mesoscale Atmospheric Flow Models with Aircraft Measurements, Met. Zeit., 2018, DOI: 10.1127/metz/2018/0900 (First author visiting student supervised by Lundquist during CU visit)

72. Bodini, N., Lundquist, J. K., and Newsom, R. K.: Estimation of turbulence dissipation rate and its variability from sonic anemometer and wind Doppler lidar during the XPIA field campaign, Atmos. Meas. Tech., 11, 4291-4308, https://doi.org/10.5194/amt-11-4291-2018, 2018. (First author student supervised by Lundquist)

71. Worsnop, R., M. Scheuerer, T. Hamill, and J. K. Lundquist, 2018: Generating wind power scenarios for probabilistic ramp event prediction using multivariate statistical post-processing. Wind Energy Science, 3, 371-393. https://doi.org/10.5194/wes-3-371-2018. (First author student supervised by Lundquist)

70. Muñoz-Esparza, D., R.D. Sharman, and J.K. Lundquist, 2018: Turbulence Dissipation Rate in the Atmospheric Boundary Layer: Observations and WRF Mesoscale Modeling during the XPIA Field Campaign. Mon. Wea. Rev., 146, 351–371, https://doi.org/10.1175/MWR-D-17-0186.1

69. Karnauskas, K. B., J. K. Lundquist, L. Zhang, 2018. Southward shift of the global wind energy resource under high carbon dioxide emissions. Nature Geoscience, 11, 38-43 (2018). doi:10.1038/s41561-017-0029-9

2017

68. Marjanovic, N., J. D. Mirocha, B. Kosović, J. K. Lundquist, F. K. Chow. 2017. Implementation of a generalized actuator line model for wind turbine parameterization in the Weather Research and Forecasting model. Journal of Renewable and Sustainable Energy 9, 063308 (2017); https://doi.org/10.1063/1.4989443

67. Williams, P. D., and 14 co-authors including J. K. Lundquist, 2017. A census of atmospheric variability from seconds to decades. Geophysical Research Letters, 44, 11,201–11,211. https://doi.org/10.1002/2017GL075483.

66. Lee, J. C.-Y, and J. K. Lundquist, 2017. Evaluation of the WRF Wind Farm Parameterization with meteorological and turbine power data. Geosci. Model Dev., 10, 4229-4244, https://doi.org/10.5194/gmd-10-4229-2017, 2017. (First author student supervised by Lundquist)

65. Bodini, N., J. K. Lundquist,and D. Zardi. 2017. Three-dimensional structure of wind turbine wakes as measured by scanning lidar, Atmos. Meas. Tech., 10, 2881-2896, https://doi.org/10.5194/amt-10-2881-2017. (First author student supervised by Lundquist)

64. Mazzaro, L. J., D. Muñoz-Esparza, J. K. Lundquist, R. R. Linn, 2017. Nested Mesoscale-to-LES Modeling of the Atmospheric Boundary Layer in the Presence of Under-Resolved Convective Structures. Journal of Advances in Modeling Earth Systems 9, 1795–1810, doi:10.1002/2017MS000912. (First author student supervised by Lundquist)

63. Worsnop, R., J. K. Lundquist, G. H. Bryan, R. Damiani, W. Musial. 2017. Gusts and Shear Within Hurricane Eyewalls Can Exceed Offshore Wind-Turbine Design Standards. Geophysical Research Letters, 44, doi:10.1002/2017GL073537. (First author student supervised by Lundquist)

62. Worsnop, R., G. Bryan, J. K. Lundquist, and J. A. Zhang. 2017. Spectral and coherence characteristics of an LES-modeled hurricane boundary layer for wind energy applications. Boundary-Layer Meteorology. http://dx.doi.org/10.1007/s10546-017-0266-x (First author student supervised by Lundquist)

61. Lee, J. C.-Y. and J. K. Lundquist. 2017.  Observing and Simulating Wind Turbine Wakes During the Evening Transition. Boundary-Layer Meteorology https://doi.org/10.1007/s10546-017-0257-y. (First author student supervised by Lundquist)

60. Bianco, L., Friedrich, K., Wilczak, J. M., Hazen, D., Wolfe, D., Delgado, R., Oncley, S. P., and Lundquist, J. K.: Assessing the accuracy of microwave radiometers and radio acoustic sounding systems for wind energy applications, Atmos. Meas. Tech., 10, 1707-1721, doi:10.5194/amt-10-1707-2017, 2017.

59. St. Martin, C. M., Lundquist, J. K., Clifton, A., Poulos, G. S., and Schreck, S. J.: Atmospheric turbulence affects wind turbine nacelle transfer functions, Wind Energ. Sci., 2, 295-306, https://doi.org/10.5194/wes-2-295-2017, 2017. (First author student supervised by Lundquist)

58. Muñoz-Esparza, D., Lundquist, J. K., Sauer, J. A., Kosović, B. and Linn, R. R. (2017), Coupled mesoscale-LES modeling of a diurnal cycle during the CWEX-13 field campaign: From weather to boundary-layer eddies. J. Adv. Model. Earth Syst. doi:10.1002/2017MS000960.

57. Newsom, R. K., Brewer, W. A., Wilczak, J. M., Wolfe, D. E., Oncley, S. P., and Lundquist, J. K.: Validating precision estimates in horizontal wind measurements from a Doppler lidar, Atmos. Meas. Tech., 10, 1229-1240, doi:10.5194/amt-10-1229-2017, 2017.

56. Debnath, M., Iungo, G. V., Brewer, W. A., Choukulkar, A., Delgado, R., Gunter, S., Lundquist, J. K., Schroeder, J. L., Wilczak, J. M., and Wolfe, D.: Assessment of virtual towers performed with scanning wind lidars and Ka-band radars during the XPIA experiment, Atmos. Meas. Tech., 10, 1215-1227, doi:10.5194/amt-10-1215-2017, 2017.

55. Debnath, M., Iungo, G. V., Ashton, R., Brewer, W. A., Choukulkar, A., Delgado, R., Lundquist, J. K., Shaw, W. J., Wilczak, J. M., and Wolfe, D.: Vertical profiles of the 3-D wind velocity retrieved from multiple wind lidars performing triple range-height-indicator scans, Atmos. Meas. Tech., 10, 431-444, doi:10.5194/amt-10-431-2017, 2017.

54. McCaffrey, K., Quelet, P. T., Choukulkar, A., Wilczak, J. M., Wolfe, D. E., Oncley, S. P., Brewer, W. A., Debnath, M., Ashton, R., Iungo, G. V., and Lundquist, J. K. 2017. Identification of tower-wake distortions using sonic anemometer and lidar measurements. Atmos. Meas. Tech., 10,  393-407, doi:10.5194/amt-10-393-2017.

53. Choukulkar, A., Brewer, W. A., Sandberg, S. P., Weickmann, A., Bonin, T. A., Hardesty, R. M., Lundquist, J. K., Delgado, R., Iungo, G. V., Ashton, R., Debnath, M., Bianco, L., Wilczak, J. M., Oncley, S., and Wolfe, D.: Evaluation of single and multiple Doppler lidar techniques to measure complex flow during the XPIA field campaign, Atmos. Meas. Tech., 10, 247-264, doi:10.5194/amt-10-247-2017, 2017.

2016

53. St. Martin, C., J. K. Lundquist, G. S. Poulos, A. Clifton, and S. Schreck. 2016. Wind turbine power production and annual energy production depend on atmospheric stability and turbulence. Wind Energy Science. 1, 221-236, doi: doi:10.5194/wes-1-221-2016 (First author student supervised by Lundquist)

52. Bodini, N., J. K. Lundquist, D. Zardi, and M. Handschy. 2016. Year-to-year correlation, record length, and overconfidence in wind resource assessment. Wind Energy Science. 1, 115-128, doi:10.5194/wes-2016-11 (First author student supervised by Lundquist)

51. Bryan, G. H., R. Worsnop, J. K. Lundquist, and J. A. Zhang. 2017. A simple method for simulating tropical-cyclone boundary layers. Boundary-Layer Meteorology, 162(3), 475-502. doi:10.1007/s10546-016-0207-0.

50. Vanderwende, B., B. Kosovic, J. K. Lundquist, and J. Mirocha. 2016. Simulating effects of a wind turbine array using LES and RANS. It Journal of Advances in Modeling Earth Systems, 8, 1376–1390, doi:10.1002/2016MS000652 (First author student supervised by Lundquist)

49. Lundquist, J. K., and ~ 30 co-authors. Assessing state-of-the-art capabilities for probing the atmospheric boundary layer: the XPIA field campaign. Bulletin of the American Meteorological Society, 98, 289-314. DOI: http://dx.doi.org/10.1175/BAMS-D-15-00151.1

48. Emanuel, K., F. Hoss, D. Keith, Z. Kuang, J. K. Lundquist, and L. Miller. 2016. Workshop on Climate Effects of Wind Turbines.  Bulletin of the American Meteorological Society, 97, ES57-ES58.

47. Vanderwende, B. and J. K. Lundquist. 2016. Could crop height impact the wind resource at agriculturally-productive wind farm sites? Boundary-Layer Meteorology, 158, 409-428. DOI: 10.1007/s10546-015-0102-0 (First author student supervised by Lundquist)

2015

46. Mirocha, J. D., D. A. Rajewski, N. Marjanovic, J. K. Lundquist, B. Kosovic, C. Draxl, and M. J. Churchfield. 2015. Investigating wind turbine impacts on near-wake flow using profiling lidar data and large-eddy simulations with an actuator disk model. Journal of Renewable and Sustainable Energy 7, 043143 (2015)

45. St. Martin, C., J. K. Lundquist, M. Handschy. 2015. Variability of interconnected wind plants: correlation length and its dependence on variability time scale. Environmental Research Letters, 10, 044004. (First author student supervised by Lundquist)

44. Vanderwende, B., J. K. Lundquist, M. E. Rhodes, G. S. Takle, and S. I. Purdy. 2015. Observing and simulating the summertime low-level jet in central Iowa. Monthly Weather Review 143, 2319–2336. (First author student supervised by Lundquist)

43. Banta, R. M., Y. L. Pichugina, W. A. Brewer, J. K. Lundquist, and co-authors. 2015. 3-D Volumetric Analysis of Wind-Turbine Wake Properties in the Atmosphere using High-Resolution Doppler Lidar.  J. Atmos. Ocean. Tech. 32, 904-914, DOI: 10.1175/JTECH-D-14-00078.1

42. Lundquist, J. K., M. Churchfield, S. Lee, and A. Clifton. 2015. Quantifying error of lidar and sodar Doppler beam swinging measurements of wind turbine wakes using computational fluid dynamics. Atmos. Meas. Tech., 8, 907-920, 2015, doi:10.5194/amt-8-907-2015.

41. Lundquist, J. K. and L. Bariteau. 2015. Dissipation of turbulence in the wake of a wind turbine. Boundary-Layer Meteorology, 154, 229-241.

2014

40. Takle E.S., Rajewski D.A., Lundquist J.K., W. A. Gallus, Jr., and A. Sharma. 2014. Measurements in support of wind farm simulations and power forecasts: The Crop/Wind-energy Experiments (CWEX). J Phys Conf Ser 524:012174. doi: 10.1088/1742-6596/524/1/012174

39.    Aitken, M. L., B. Kosovic, J. D. Mirocha, and J. K. Lundquist. 2014. Large eddy simulation of wind turbine wake dynamics in the stable boundary layer using the Weather Research and Forecasting Model. J. Renewable and Sustainable Energy 6, 033137 (2014); http://dx.doi.org/10.1063/1.4885111 (First author student supervised by Lundquist)

38.    Aitken, M. L., J. K. Lundquist. 2014. Utility-scale wind turbine wake characterization using nacelle-based long-range scanning lidar.  Jo. Atmos. Ocean. Tech. 31, 1529-1539. (First author student supervised by Lundquist)

37.   Rajewski, D., E. S. Takle, J. K. Lundquist, J. H. Prueger, R. Pfeiffer, J. L. Hatfield, K. K. Spoth, and R. K. Doorenbos. 2014. Changes in fluxes of heat, H2O, and CO2 caused by a large wind farm.  Agricultural & Forest Meteorology 194, 175-187.

36.    Aitken, M. L., J. K. Lundquist, Y. L. Pichugina, and R. M. Banta. 2014. Quantifying wind turbine wake characteristics from scanning remote sensor data. J. Atmos. Ocean. Tech. 31, 765-787. 10.1175/JTECH-D-13-00104.1 (First author student supervised by Lundquist)

35.    Mirocha, J., B. Kosovic, M. Aitken, and J. K. Lundquist. 2014. Implementation of a generalized actuator disk wind turbine model into WRF for large-eddy simulation applications. J. Renewable Sustainable Energy 6, 013104 (2014); http://dx.doi.org/10.1063/1.4861061.

2013

34.    Archer, C. L., B. Colle, L. Delle Monache, M. Dvorak, J. K. Lundquist, and eleven other co-authors. 2013. Meteorology for Coastal/Offshore Wind Energy in the US: Recommendations and Research Needs for the next Ten Years. To appear Bull. Amer. Meteorol. Soc. http://dx.doi.org/10.1175/BAMS-D-13-00108.1

33.    Rhodes, M. E., and J. K. Lundquist. 2013. The Effect of Wind Turbine Wakes on Summertime Midwest Atmospheric Wind Profiles. Boundary-Layer Meteorology 149, 85-103. doi:10.1007/s10546-013-9834-x (First author student supervised by Lundquist)

32.     Hu, Xiao-Ming, Petra M. Klein, Ming Xue, Julie K. Lundquist, Fuqing Zhang, Youcun Qi, 2013: Impact of Low-Level Jets on the Nocturnal Urban Heat Island Intensity in Oklahoma City. J. Appl. Meteor. Climatol., 52, 1779–1802.
doi: http://dx.doi.org/10.1175/JAMC-D-12-0256.1.

31.    Clifton, A., L. Kilcher, J. K. Lundquist, and P. Fleming. 2013. Using machine-learning to predict wind turbine power output. Environmental Research Letters. 8 024009 doi:10.1088/1748-9326/8/2/024009.

30.    Fitch, A., J. B. Olson, and J. K. Lundquist. 2013. Parameterization of wind farms in climate models. Journal of Climate, 26, 6439-6458. (First author student co-supervised by Lundquist)

29.     Smalikho, I. N., V. A. Banakh, Y. L. Pichugina, W. A. Brewer, R. M. Banta, J. K. Lundquist, N. D. Kelley, 2013: Lidar Investigation of Atmosphere Effect on a Wind Turbine Wake. J. Atmos. Oceanic Technol., 30, 2554–2570.
doi: http://dx.doi.org/10.1175/JTECH-D-12-00108.1
.

28.    Fitch, A., J. K. Lundquist, and J. B. Olson. 2013. Mesoscale Influences of Wind Farms throughout a diurnal cycle. Monthly Weather Review, 141, 2173-2198. doi: http://dx.doi.org/10.1175/MWR-D-12-00185.1 (First author student co-supervised by Lundquist)

27.    Clifton, A., S. Schreck, D. Jager, N. Kelley, and J. K. Lundquist. 2013. Meteorological tower observations at the National Renewable Energy Laboratory. Journal of Solar Energy Engineering. 135(3), 031017 (May 31, 2013) doi:10.1115/1.4024068

26.    Rajewski, D., G. Takle, J. K. Lundquist, M. E. Rhodes, S. Oncley, J. H. Prueger, T. Horst, M.E. Rhodes, R. Pfeiffer, J. Hatfield, K. K. Spoth, and R. K. Doorenbos. 2013. Crop Wind Energy Experiment (CWEX): Observations of Surface-Layer, Boundary Layer, and Mesoscale Interactions with a Wind Farm. Bull Amer Meteor Soc 94: 655–672.

2012

25.    Vanderwende, B. and J. K. Lundquist. 2012. The modification of wind turbine performance by statistically distinct atmospheric regimes. Environmental Research Letters 7 (2012) 034035 doi:10.1088/1748-9326/7/3/034035 (First author student supervised by Lundquist)

24.    Lundquist, K.A., F. K. Chow, and J. K. Lundquist. 2012. An Immersed Boundary Method Enabling Large-Eddy Simulations of Urban Terrain in the WRF model. Monthly Weather Review. 140, 3936-3955. 

23.    Clifton, A., and J. K. Lundquist. 2012. Data clustering reveals climate impacts on local wind phenomena. Journal of Applied Meteorology and Climatology 51, 1547-1557.

22.    Fitch, A. C., J. B. Olson, J. K. Lundquist, J. Dudhia, A. K. Gupta, J. Michalakes, and I. Barstad.  2012. Local and Mesoscale Impacts of Wind Farms as Parameterized in a Mesoscale NWP Model. Monthly Weather Review. Vol. 140, No. 9, 3017-3038. (First author student co-supervised by Lundquist)  Note the Corrigendum to this paper: https://doi.org/10.1175/MWR-D-12-00341.1

21.    Aitken, M., L., M. E. Rhodes, and J. K. Lundquist. 2012. Performance of a wind-profiling lidar in the region of wind turbine rotor disks. Journal of Atmospheric and Oceanic Technology 29, 347-355. (First author student supervised by Lundquist)

20.    Friedrich, K., J. K. Lundquist, M. Aitken, E. A. Kalina, and R. F. Marshall (2012), Stability and turbulence in the atmospheric boundary layer: A comparison of remote sensing and tower observations, Geophys. Res. Lett., 39, L03801, doi:10.1029/2011GL050413.

19.    Wharton, S. and J. K. Lundquist. 2012b. Atmospheric Stability Affects Wind Turbine Power Collection. Environ. Res. Lett. 7 014005 doi:10.1088/1748-9326/7/1/014005

18.    Wharton, S. and J. K. Lundquist. 2012a. Assessing atmospheric stability and its impacts on rotor-disk wind characteristics at an onshore wind farm. Wind Energy,15, 525–546, DOI: 10.1002/we.483

2011

17.    Maxwell, R. M., J. K. Lundquist, J. Mirocha, S. G. Smith, C. S. Woodward, and A. F. B. Tompson. 2011. Development of a coupled groundwater-atmospheric model. Monthly Weather Review, 139, 96-116.

2010

16.    Mirocha, J. D., J. K. Lundquist, and B. Kosovic. 2010. Implementation of nonlinear subfilter turbulence stress models for large-eddy simulations in the Advanced Research WRF Model. Monthly Weather Review, 138, 4212-4228.

15.    Lundquist, K. A., F. K. Chow, and J. K. Lundquist. 2010. Implementation of an Immersed Boundary Method in the Weather Research and Forecasting Model. Monthly Weather Review, 138, 796-817.

2009

14.    Shaw, W. J., J. K. Lundquist, S. Schreck. 2009. Workshop on Research Needs for Wind Resource Characterization. Bulletin of the American Meteorological Society, 90, 535-538, doi: 10.1175/2008BAMS2729.1

13.    White, J.M., J. F. Bowers, S.R. Hanna, and J. K. Lundquist. 2009.  Importance of Using Observations of Mixing Depths in order to Avoid Large Underpredictions by a Transport and Dispersion Model. Journal of Atmospheric and Oceanic Technology, 26, 22-32.

2008

12.    Delle Monache, L., J. K. Lundquist, B. Kosovic, G. Johannesson, K. M. Dyer, R. D. Aines, R. D. Belles, W. G. Hanley, S. C. Larsen, G. A. Loosmore, A. A. Mirin, J. J. Nitao, G. A. Sugiyama, P. J. Vogt. 2008. Bayesian inference and Markov Chain Monte Carlo sampling to reconstruct a contaminant source at continental scale. Journal of Applied Meteorology and Climatology, 47, 2600-2613.

11.    Teixeira, J., B. Stevens, C.S. Bretherton, R. Cederwall, J. D. Doyle, J. C. Golaz, A. Holtslag, S. Klein, J. K. Lundquist, D. A. Randall, A. P. Siebesma, and P. M. M. Soares. 2008. Parameterization of the atmospheric boundary layer: a view from just above the inversion. Bull. Amer. Meteorol. Soc., 89, 453-458.

10.    Lundquist, J. K. and J. D. Mirocha. 2008. Interaction of Nocturnal Low-Level Jets with Urban Geometries as seen in Joint URBAN 2003 Data. Journal of Applied Meteorology and Climatology 47, 44-58.

2007

9.    Lundquist, J.K. and S. T. Chan. 2007. Consequences of Urban Stability Conditions for Computational Fluid Dynamics Simulations of Urban Dispersion. Journal of Applied Meteorology and Climatology 46, 1080-1097.

8.    Simpson, M., S. Raman, J. K. Lundquist, M. Leach. 2007. A study of the variation of urban mixed layer heights.  Atmospheric Environment 41, 6923-6930.

2006

7.    Beare, R. J., M. K. MacVean, A. A. M. Holtslag, J. Cuxart, I. Esau, J. C. Golaz, M. A. Jimenez, M. Khairoutdinov, B. Kosovic, D. Lewellen, T. S. Lund, J. K. Lundquist, A. McCabe, A. F. Moene, Y. Noh, S. Raasch, and P. Sullivan. 2006. An intercomparison of large-eddy simulations of the stable boundary layer. Boundary-Layer Meteorology 118 (2), 247-272.

2004

6.    Piper, M., and J. K. Lundquist. 2004. Surface layer turbulence measurements during a frontal passage. Journal of the Atmospheric Sciences 61 (14), 1768-1780.

2003

5.    Lundquist, J. K. 2003. Intermittent and elliptical inertial oscillations in the atmospheric boundary layer. Journal of the Atmospheric Sciences 60 (21), 2661-2673.

2002

4.    Poulos, G. S., W. Blumen, D. C. Fritts, J. K. Lundquist, J. Sun, S. P. Burns, C. Nappo, R. Banta, R. Newsom, J. Cuxart, E. Terradellas, B. Balsley, and M. Jensen. 2002. CASES-99: A comprehensive investigation of the stable nocturnal boundary layer. Bulletin of the American Meteorological Society 83 (4), 555-581.

3.    Banta, R. M., R. K. Newsom, J. K. Lundquist, Y. L. Pichugina, R. L. Coulter, and L. Mahrt. 2002. Nocturnal low-level jet characteristics over Kansas during CASES-99. Boundary-Layer Meteorology 105 (2), 221-252.

2001

2.    Blumen, W., and J. K. Lundquist. 2001. Spin-up and spin-down in rotating fluid exhibiting inertial oscillations and frontogenesis. Dynamics of Atmospheres and Oceans 33 (3), 219-237.

2000

1.    LeMone, M. A., R. L. Grossman, R. L. Coulter, M. L. Wesley, G. E. Klazura, G. S. Poulos, W. Blumen, J. K. Lundquist, R. H. Cuenca, S. F. Kelly, E. A. Brandes, S. P. Oncley, R. T. McMillen, and B. B. Hicks. 2000. Land-atmosphere interaction research, early results, and opportunities in the Walnut River Watershed in southeast Kansas: CASES and ABLE. Bulletin of the American Meteorological Society 81 (4), 757-779.