Publications
★ Denotes first authors who were graduate students supervised or co-supervised by J. K. Lundquist
■ Denotes first authors who were undergraduate students supervised or co-supervised by J. K. Lundquist
☆ Denotes first authors who were visiting students supervised by J. K. Lundquist
Denotes first authors who were postdoctoral researchers supervised by J. K. Lundquist
2024
133. Bodini, N., M. Optis, S. Redfern, D. Rosencrans, A. Rybchuk, J. K. Lundquist, V. Pronk, S. Castagneri, A. Purkayastha, C. Draxl, R. Krishnamurthy, E. Young, B. Roberts, E. Rosenlieb, and W. Musial, 2024, The 2023 National Offshore Wind data set (NOW-23), Earth System Science Data, 16, 1965–2006, https://doi.org/10.5194/essd-16-1965-2024, 2024.
132. Rosencrans★, D., J.K. Lundquist, M. Optis, A. Rybchuk, N. Bodini, M. Rossol, 2024, Seasonal Variability of Wake Impacts on US mid-Atlantic Offshore Wind Plant Deployments, Wind Energy Science, 9, 555-583, https://doi.org/10.5194/wes-9-555-2024.
2023
131. Sanchez Gomez★, J. K. Lundquist, G. Deskos, S. R. Arwade, A. T. Myers, J. F. Hajjar, 2023, Wind conditions in category 1-3 tropical cyclones are not fully represented in wind turbine design standards, Journal of Geophysical Research: Atmospheres, 128, e2023JD039233. https://doi.org/10.1029/2023JD039233
130. Sanchez Gomez★, M. J. K. Lundquist, J. D. Mirocha, and R. Arthur, 2023, Investigating the physical mechanisms that modify wind plant blockage in stable boundary layers,Wind Energy Science, 8, 1049–1069, https://doi.org/10.5194/wes-8-1049-2023.
129. Debnath, M., P. Moriarty, R. Krishnamurthy, N. Bodini, R. Newsom, E. Quon, J. K. Lundquist, S. Letizia, G. V. Iungo, and P. Klein, 2023, Characterization of wind speed and directional shear at the AWAKEN field campaign site, Journal of Renewable and Sustainable Energy 1 May 2023; 15 (3): 033308. https://doi.org/10.1063/5.0139737.
2022
128. Veers, P., K. Dykes, S. Basu, A. Bianchini, A. Clifton, P. Green, H. Holttinen, L. Kitzing, B. Kosovic, J. K. Lundquist, J. Meyers, M. O’Malley, W. J. Shaw, B. Straw, 2022: Grand Challenges: Wind energy research needs for a global energy transition, Wind Energy Science, 7, 2491–2496, https://doi.org/10.5194/wes-7-2491-2022.
127. Hartwick, Victoria, O. B. Toon, J. K. Lundquist, O. Pierpaoli, M. Kahre, 2022: Assessment of Wind Energy Resource Potential for Future Human Missions to Mars, Nature Astronomy, https://doi.org/10.1038/s41550-022-01851-4 .
126. Sanchez Gomez★, Miguel, Julie K. Lundquist, J. D. Mirocha, R. S. Arthur, D. Muñoz-Esparza, R. Robey: 2022: Can lidars assess wind plant blockage in simple terrain? A WRF-LES study, Journal of Renewable and Sustainable Energy, 14, 063303, https://doi.org/10.1063/5.0103668.
125. Rybchuk★, A., T. Juliano, and J. K. Lundquist, D. Rosencrans, N. Bodini, and M. Optis, 2022: The Sensitivity of the Fitch Wind Farm Parameterization to a Three-Dimensional Planetary Boundary Layer Scheme, Wind Energy Science, 7, 2085–2098, https://doi.org/10.5194/wes-7-2085-2022
124. Pichugina, Y. L., R. M. Banta, W. A. Brewer, J. Kenyon, J. B. Olson, D. D. Turner, J. Wilczak, S. Baidar, J. K. Lundquist, W. J. Shaw, and S. Wharton, 2022: Model Evaluation by Measurements from Collocated Remote Sensors in Complex Terrain, Weather and Forecasting, 37(10), 1829-1853. https://journals.ametsoc.org/view/journals/wefo/37/10/WAF-D-21-0214.1.xml
123. Robey★, R., J. K. Lundquist, 2022: Behavior and Mechanisms of Lidar Error in Varying Stability Regimes. Atmospheric Measurement Techniques, 15, 4585–4622, https://amt.copernicus.org/articles/15/4585/2022/.
122. Jensen, A.A., J.O. Pinto, S.C.C. Bailey, R.A. Sobash, G. Romine, G. de Boer, A. L. Houston, P. B. Chilson, T. Bell, S. W. Smith, D. A. Lawrence, C. Dixon, J. K. Lundquist, J. D. Jacob, J. Elston, S. Waugh, D. Brus, M. Steiner, 2022: Assimilation of a coordinated fleet of uncrewed aircraft systems observations in complex terrain: Observing System Experiments. Monthly Weather Review, 149(5), 1459-1480.https://journals.ametsoc.org/view/journals/mwre/149/5/MWR-D-20-0359.1.xml
121. Craig, M. T., J. Wohland, L. P. Stoop, A. Kies, B. Pickering, H. C. Bloomfield, J. Browell, M. De Felice, C. J. Dent, A. Deroubaix, F. Frischmuth, P. L. M. Gonzalez, A/ Grochowicz, K. Gruber, P. Härtel, M. Kittel, L. Kotzur, I. Labuhn, J. K. Lundquist, N. Pflugradt, K. van der Wiel, M. Zeyringer, D. J. Brayshaw, 2022: Overcoming the disconnect between energy system and climate modeling. Joule, 6(7), 1405-1417. https://doi.org/10.1016/j.joule.2022.05.010.
120. Arthur, R. S., T. W. Juliano, B. Adler, R. Krishnamurthy, J. K. Lundquist, B. Kosović, and P. A. Jiménez, 2022: Improved representation of horizontal variability and turbulence in mesoscale simulations of an extended cold-air pool event. Journal of Applied Meteorology and Climatology, 61(6), 685-707. https://doi.org/10.1175/JAMC-D-21-0138.1.
119. Pronk■, V., N. Bodini, M. Optis, J. K. Lundquist, P. Moriarty, C. Draxl, A. Purkayastha, and E. Young, 2022: Can reanalysis products outperform mesoscale numerical weather prediction models in modeling the wind resource in simple terrain? Wind Energy Science, 7, 487–504, https://doi.org/10.5194/wes-7-487-2022 .
118. Wise, A. S., J. M. T. Neher, R. S. Arthur, J. D. Mirocha, J. K. Lundquist, and F. K. Chow, 2022: Meso- to microscale modeling of atmospheric stability effects on wind turbine wake behavior in complex terrain. Wind Energy Science, 7, 367–386, https://doi.org/10.5194/wes-7-367-2022 .
2021
117. Redfern★, S., J. K. Lundquist, O. B. Toon, D. Muñoz-Esparza, C. G. Bardeen, and B. Kosović, 2021: Upper Troposphere Smoke Injection From Large Areal Fires. Journal of Geophysical Research: Atmospheres, 126, e2020JD034332. https://doi.org/10.1029/2020JD034332
116. Bodini, N., J. K. Lundquist, and P. Moriarty, 2021: Wind plants can impact long-term local atmospheric conditions. Sci Rep, 11, 22939, https://doi.org/10.1038/s41598-021-02089-2.
115. Banta, R.M., Yelena L. Pichugina, Lisa S. Darby, Alan Brewer, Joseph B. Olson, Jaymes S. Kenyon, Sunil Baidar, Stanley G. Benjamin, Harinda J.S. Fernando, Kathy O. Lantz, Julie K. Lundquist, Brandi J. McCarty, Tobias Marke, Scott P. Sandberg, Justin Sharp, William J. Shaw, David D. Turner, James M. Wilczak, Rochelle Worsnop, Mark T. Stoelinga, 2021: Doppler-Lidar Evaluation of HRRR-Model Skill at Simulating Summertime Wind Regimes in the Columbia River Basin during WFIP2. Weather and Forecasting, 36, 1961-1983. https://doi.org/10.1175/WAF-D-21-0012.1
114. Sanchez Gomez★, M., J. K. Lundquist, P. M. Klein, and T. M. Bell, 2021: Turbulence Dissipation Rate Estimated from Lidar Observations During the LAPSE-RATE Field Campaign. Earth System Science Data, 13, 3539–3549, https://essd.copernicus.org/articles/13/3539/2021/.
113. Rybchuk★, A., C. B. Alden, J. K. Lundquist, and G. B. Rieker, 2021: A Statistical Evaluation of WRF-LES Trace Gas Dispersion Using Project Prairie Grass Measurements. Monthly Weather Review, 149, 1619–1633, https://doi.org/10.1175/MWR-D-20-0233.1.
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 Uncrewed Aircraft System Observations in Complex Terrain: EnKF System Design and Preliminary Assessment. Monthly Weather Review, 149, 1459–1480, 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, https://doi.org/10.5194/essd-13-1041-2021.
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, 2021: Mountain waves impact wind power generation. Wind Energy Science, 6, 45-60, https://doi.org/10.5194/wes-6-45-2021.
109. Tomaszewski★, J. and J. K. Lundquist, 2021: Observations and Simulations of a Wind Farm Modifying a Thunderstorm Outflow Boundary. Wind Energy Science, 6, 1-13, https://doi.org/10.5194/wes-6-1-2021.
2020
108. Livingston■, H. G., and J. K. Lundquist, 2020: How many offshore wind turbines does New England need? Meteorological Applications, 27, e1969, https://doi.org/10.1002/met.1969 .
107. 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, 2220–2230, https://doi.org/10.1016/j.renene.2020.10.127.
106. Englberger, A., J. K. Lundquist, and A. Dörnbrack, 2020: Changing the rotational direction of a wind turbine under veering inflow: a parameter study. Wind Energy Science, 5, 1623–1644, https://doi.org/10.5194/wes-5-1623-2020 .
105. Bloomfield, H. C., Paula L.M. Gonzalez, Julie K Lundquist, Laurens P. Stoop; 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, 2021: The Importance of Weather and Climate to Energy Systems: A Workshop on Next Generation Challenges in Energy–Climate Modeling. Bulletin of the American Meteorological Society, 102, E159–E167, https://doi.org/10.1175/BAMS-D-20-0256.1.
104. de Boer, G., A. Houston, J. Jacob, P. B. Chilson, S. W. Smith, B. Argrow, D. Lawrence, JJ. Elston, D. Brus, O. Kemppinen, P. Klein, J.K. Lundquist, S. Waugh, S. C. C. Bailey, A. Frazier, M. P. Sama, C. Crick, D. Schmale III, E. A. Pillar-Little, V. Natalie, and A. Jensen, 2020: Data generated during the 2018 LAPSE-RATE campaign: an introduction and overview. Earth System Science Data, 12, 3357–3366, https://doi.org/10.5194/essd-12-3357-2020 .
103. Djalalova, I. V., L. Bianco, E. Akish, J. M. Wilczak, J. B. Olson, J. S. Kenyon, L. K. Berg, A. Choukulkar, R. Coulter, H. J. S. Fernando, E. Grimit, R. Krishnamurthy, J.K Lundquist, P. Muradyan, D. D. Turner, and S. Wharton, 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, 2407–2421, https://doi.org/10.1175/WAF-D-20-0072.1.
102. Englberger, A., A. Dörnbrack, and J. K. Lundquist, 2020: Does the rotational direction of a wind turbine impact the wake in a stably stratified atmospheric boundary layer? Wind Energy Science, 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 turbulent kinetic energy dissipation rate in the boundary layer for complex terrain? Geoscientific Model Development, 13, 4271–4285, https://doi.org/10.5194/gmd-13-4271-2020 .
100. Murphy■, P., J. K. Lundquist, and P. Fleming, 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.
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, https://doi.org/10.1063/5.0009138.
98. Fleming, P., J. King, E. Simley, J. Roadman, A. Scholbrock, P. Murphy, J. K. Lundquist, P. Moriarty, K. Fleming, J. van Dam, C. Bay, R. Mudafort, J. Skopek, M. Schott, B. Ryan, C. Guernsey, and D. Brake, 2020: Continued results from a field campaign of wake steering applied at a commercial wind farm – Part 2. Wind Energy Science, 5, 945–958, https://doi.org/10.5194/wes-5-945-2020.
97. Luchetti, N. T., K. Friedrich, C. E. Rodell, and J. K. Lundquist, 2020: Characterizing Thunderstorm Gust Fronts near Complex Terrain. Mon. Wea. Rev., 148, 3267–3286, https://doi.org/10.1175/MWR-D-19-0316.1.
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.
95. Gasch☆, P., A. Wieser, J. K. Lundquist, and N. Kalthoff, 2020: An LES-based airborne Doppler lidar simulator and its application to wind profiling in inhomogeneous flow conditions. Atmospheric Measurement Techniques, 13, 1609–1631, https://doi.org/10.5194/amt-13-1609-2020.
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., 2020: Turbulent kinetic energy over large offshore wind farms observed and simulated by the mesoscale model WRF (3.8.1). Geoscientific Model Development, 13, 249–268, https://doi.org/10.5194/gmd-13-249-2020.
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 Lawrence1 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, E684–E699, https://doi.org/10.1175/BAMS-D-19-0050.1.
2019
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). Geoscientific Model Development, 12, 4803–4821, https://doi.org/10.5194/gmd-12-4803-2019 .
91. Sanchez Gomez★, M., and J. K. Lundquist, 2020: The effect of wind direction shear on turbine performance in a wind farm in central Iowa. Wind Energy Science, 5, 125–139, https://doi.org/10.5194/wes-5-125-2020.
90. Wildmann, N., N. Bodini, J. K. Lundquist, L. Bariteau, and J. Wagner, 2019: Estimation of turbulence dissipation rate from Doppler wind lidars and in situ instrumentation for the Perdigão 2017 campaign. Atmospheric Measurement Techniques, 12, 6401–6423, https://doi.org/10.5194/amt-12-6401-2019.
89. Kapoor, A., S. Ouakka, S. R. Arwade, J. K. Lundquist, M. A. Lackner, A. T. Myers, R. P. Worsnop, and G. H. Bryan, 2020: Hurricane eyewall winds and structural response of wind turbines. Wind Energy Science, 5, 89–104, https://doi.org/10.5194/wes-5-89-2020.
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. Science, 366, eaau2027, https://doi.org/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, and R. R. Linn, 2019: Random Force Perturbations: A New Extension of the Cell Perturbation Method for Turbulence Generation in Multiscale Atmospheric Boundary Layer Simulations. Journal of Advances in Modeling Earth Systems, 11, 2311–2329, https://doi.org/10.1029/2019MS001608.
85. Fleming, P., J. King, K. Dykes, E. Simley, J. Roadman, A. Scholbrock, P. Murphy, J. K. Lundquist, P. Moriarty, K. Fleming, J. van Dam, C. Bay, R. Mudafort, H. Lopez, J. Skopek, M. Scott, B. Ryan, C. Guernsey, and D. Brake, 2019: 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, and A. Kirincich, 2019: U.S. East Coast Lidar Measurements Show Offshore Wind Turbines Will Encounter Very Low Atmospheric Turbulence. Geophysical Research Letters, 46, 5582–5591, https://doi.org/10.1029/2019GL082636.
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., J. K. Lundquist, R. Krishnamurthy, M. Pekour, L. K. Berg, and A. Choukulkar, 2019: Spatial and temporal variability of turbulence dissipation rate in complex terrain. Atmospheric Chemistry and Physics, 19, 4367–4382, https://doi.org/10.5194/acp-19-4367-2019.
80. Menke☆, R., N. Vasiljević, J. Mann, and J. K. Lundquist, 2019: Characterization of flow recirculation zones at the Perdigão site using multi-lidar measurements. Atmospheric Chemistry and Physics, 19, 2713–2723, https://doi.org/10.5194/acp-19-2713-2019.
79. Redfern★, S., J. B. Olson, J. K. Lundquist, and 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.
78. Fernando, H. J. S., J. Mann, J. M. L. M. Palma, J. K. Lundquist, R. J. Barthelmie, M. Belo-Pereira, W. O. J. Brown, F. K. Chow, T. Gerz, C. M. Hocut, P. M. Klein, L. S. Leo, J. C. Matos, S. P. Oncley, S. C. Pryor, L. Bariteau, T. M. Bell, N. Bodini, M. B. Carney, M. S. Courtney, E. D. Creegan, R. Dimitrova, S. Gomes, M. Hagen, J. O. Hyde, S. Kigle, R. Krishnamurthy, J. C. Lopes, L. Mazzaro, J. M. T. Neher, R. Menke, P. Murphy, L. Oswald, S. Otarola-Bustos, A. K. Pattantyus, C. Veiga Rodrigues, A. Schady, N. Sirin, S. Spuler, E. Svensson, J. Tomaszewski, D. D. Turner, L. van Veen, N. Vasiljević, D. Vassallo, S. Voss, N. Wildmann, and Y. Wang, 2019: The Perdigão: Peering into Microscale Details of Mountain Winds. Bulletin of the American Meteorological Society, 100, 799–819, https://doi.org/10.1175/BAMS-D-17-0227.1.
77. Lundquist, J. K., K. K. DuVivier, D. Kaffine, and J. M. Tomaszewski, 2019: Costs and consequences of wind turbine wake effects arising from uncoordinated wind energy development. Nature Energy, 4, 26–34, https://doi.org/10.1038/s41560-018-0281-2.
2018
76. Siedersleben☆, S. K., J. K. Lundquist, A. Platis, A. Lampert, K. Bärfuss, B. Cañadillas, B. Djath, J. Schulz-Stellenfleth, T. Neumann, J. Bange, and S. Emeis, 2018: Micrometeorological impacts of offshore wind farms as seen in observations and simulations. Environ. Res. Lett., 13, 124012, https://doi.org/10.1088/1748-9326/aaea0b .
75. Lee★, J. C.-Y., M. J. Fields, and 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.
74. Tomaszewski★, J., J. K. Lundquist, M. J. Churchfield, and P. J. 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.
73. Siedersleben☆, S. K., A. Platis, J. K. Lundquist, A. Lampert, K. Bärfuss, B. Canadillas, B. Djath, J. Schulz-Stellenfleth, T. Neumann, J. Bange, and S. Emeis Evaluation of a Wind Farm Parametrization for Mesoscale Atmospheric Flow Models with Aircraft Measurements. Meteorologische Zeitschrift, 27, 401–415, https://doi.org/10.1127/metz/2018/0900.
72. Bodini★, N., Lundquist, J. K., and R. K. Newsom, 2018: Estimation of turbulence dissipation rate and its variability from sonic anemometer and wind Doppler lidar during the XPIA field campaign. Atmospheric Measurement Techniques, 11, 4291–4308, https://doi.org/10.5194/amt-11-4291-2018 .
71. Worsnop★ , M. Scheuerer, T. M. 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.
70. Karnauskas, K. B., J. K. Lundquist, and L. Zhang, 2018: Southward shift of the global wind energy resource under high carbon dioxide emissions. Nature Geoscience, 11, 38. https://www.nature.com/articles/s41561-017-0029-9
2017
69. Muñoz-Esparza, D., R. D. Sharman, and J. K. Lundquist, 2017: Turbulent 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.
68. Marjanovic, N., J. D. Mirocha, B. Kosović, J. K. Lundquist, and 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, https://doi.org/10.1063/1.4989443.
67. Williams, P.D., M. J. Alexander, E. A. Barnes, A. H. Butler, H. C. Davies, C. I. Garfinkel, Y. Kushnir, T. P. Lane, J. K. Lundquist, O. Martius, R. N. Maue, W. R. Peltier, K. Sato, A. A. Scaife, C. Zhang, 2017: A Census of Atmospheric Variability From Seconds to Decades. Geophysical Research Letters, 44, 11, 201-11, https://doi.org/10.1002/2017GL075483.
66. Lee★, J. C.-Y, and J. K. Lundquist, 2017: Evaluation of the wind farm parameterization in the Weather Research and Forecasting model (version 3.8.1) with meteorological and turbine power data. Geosci. Model Dev., 10, 4229–4244, https://doi.org/10.5194/gmd-10-4229-2017.
65. Bodini★, N., D. Zardi, and J. K. Lundquist, 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.
64. Mazzaro★, L. J., D. Muñoz-Esparza, J. K. Lundquist, and R. R. Linn, 2017: Nested Mesoscale-to-LES modeling of the atmospheric boundary layer in the presence of under-resolved convective structures. J. Adv. Model. Earth Syst., 9, 1795–1810, https://doi.org/10.1002/2017MS000912.
63. Worsnop★, R., J. K. Lundquist, G. H. Bryan, R. Damiani, and W. Musial, 2017: Gusts and shear within hurricane eyewalls can exceed offshore wind turbine design standards. Geophys. Res. Lett., 44, 2017GL073537, https://doi.org/10.1002/2017GL073537.
62. Worsnop★, R., G. H. Bryan, J. K. Lundquist, and J. A. Zhang, 2017a: Using Large-Eddy Simulations to Define Spectral and Coherence Characteristics of the Hurricane Boundary Layer for Wind-Energy Applications. Boundary-Layer Meteorol, 165, 55–86, https://doi.org/10.1007/s10546-017-0266-x.
61. Lee★, J. C.-Y. and J. K. Lundquist, 2017: Observing and Simulating Wind-Turbine Wakes During the Evening Transition. Boundary-Layer Meteorol, 164, 449–474, https://doi.org/10.1007/s10546-017-0257-y.
60. Bianco, L., K. Friedrich, J. M. Wilczak, D. Hazen, D. Wolfe, R. Delgado, S. P. Oncley, and J. K. Lundquist, 2017: Assessing the accuracy of microwave radiometers and radio acoustic sounding systems for wind energy applications. Atmos. Meas. Tech., 10, 1707–1721, https://doi.org/10.5194/amt-10-1707-2017.
59. St. Martin★, C.M., J. K. Lundquist, A. Clifton, G. S. Poulos, and S. J. Schreck, 2017: Atmospheric turbulence affects wind turbine nacelle transfer functions. Wind Energy Science, 2, 295–306, https://doi.org/10.5194/wes-2-295-2017.
58. Muñoz-Esparza, D., J. K. Lundquist, J. A. Sauer, B. Kosović, and R. R. Linn, 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., 9, 1572–1594, https://doi.org/10.1002/2017MS000960.
57. Newsom, R. K., W. A. Brewer, J. M. Wilczak, D. E. Wolfe, S. P. Oncley, and J. K. Lundquist, 2017: Validating precision estimates in horizontal wind measurements from a Doppler lidar. Atmos. Meas. Tech., 10, 1229–1240, https://doi.org/10.5194/amt-10-1229-2017.
56. Debnath, M., G. V. Iungo, W. A. Brewer, A. Choukulkar, R. Delgado, S. Gunter, J. K. Lundquist, J. L. Schroeder, J. M. Wilczak, and D. Wolfe, 2017: Assessment of virtual towers performed with scanning wind lidars and Ka-band radars during the XPIA experiment. Atmos. Meas. Tech., 10, 1215–1227, https://doi.org/10.5194/amt-10-1215-2017.
55. Debnath, M., G. V. Iungo, R. Ashton, W. A. Brewer, A. Choukulkar, R. Delgado, J. K. Lundquist, W. J. Shaw, J. M. Wilczak, and D. Wolfe, 2017: 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, https://doi.org/10.5194/amt-10-431-2017.
54. McCaffrey, K., P. T. Quelet, A. Choukulkar, J. M. Wilczak, D. E. Wolfe, D. E., S. P. Oncley, W. A. Brewer, M. Debnath, R. Ashton, G. V. Iungo, and J. K. Lundquist, 2017: Identification of tower-wake distortions using sonic anemometer and lidar measurements. Atmos. Meas. Tech., 10, 393–407, https://doi.org/10.5194/amt-10-393-2017.
53. Choukulkar, A., W. A. Brewer, S. P. Sandberg, A. Weickmann, T. A. Bonin, R. M. Hardesty, J. K. Lundquist, R. Delgado, G. V. Iungo, R. Ashton, M. Debnath, L. Bianco, J. M. Wilczak, S. Oncley, and D. Wolfe, 2017: Evaluation of single and multiple Doppler lidar techniques to measure complex flow during the XPIA field campaign. Atmos. Meas. Tech., 10, 247–264, https://doi.org/10.5194/amt-10-247-2017.
2016
52. St. Martin★, C. M., J. K. Lundquist, A. Clifton, G. S. Poulos, and S. J. Schreck, 2016: Wind turbine power production and annual energy production depend on atmospheric stability and turbulence. Wind Energ. Sci., 1, 221–236, https://doi.org/10.5194/wes-1-221-2016.
51. 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, https://doi.org/10.5194/wes-1-115-2016.
50. Bryan, G. H., R. P. Worsnop★,J. K. Lundquist, and J. A. Zhang, 2016: A Simple Method for Simulating Wind Profiles in the Boundary Layer of Tropical Cyclones. Boundary-Layer Meteorology, https://doi.org/10.1007/s10546-016-0207-0.
49. Vanderwende★, B., B. Kosović, J. K. Lundquist, and J. D. Mirocha, 2016: Simulating effects of a wind-turbine array using LES and RANS. J. Adv. Model. Earth Syst., 8, 1376–1390, https://doi.org/10.1002/2016MS000652.
48. Lundquist, J. K, J. M. Wilczak, R. Ashton, L. Bianco, W. A. Brewer, A. Choukulkar, A, Clifton, M. Debnath, R. Delgado, K. Friedrich, S. Gunter, A. Hamidi, G.V. Iungo, A. Kaushik, B. Kosović, P. Langan, A. Lass, E. Lavin, J. C.-Y. Lee, K. L. McCaffrey, R. K. Newsom, D. C. Noone, S. P. Oncley, P. T. Quelet, S. P. Sandberg, J. L. Schroeder, W. J. Shaw, L. Sparling, C. St. Martin, A. St. Pé, E. Strobach, K. Tay, B. J. Vanderwende, A. Weickmann, D. Wolfe, and R. Worsnop, 2017: Assessing State-of-the-Art Capabilities for Probing the Atmospheric Boundary Layer: The XPIA Field Campaign. Bull. Amer. Meteor. Soc., 98, 289–314, https://doi.org/10.1175/BAMS-D-15-00151.1.
47. Emanuel, K., F. Hoss, D. W. Keith, Z. Kuang, J. K. Lundquist, and L. M. Miller, 2016: Workshop on Climate Effects of Wind Turbines. Bulletin of the American Meteorological Society, 97, ES57-58.
46. Vanderwende★, B. and J. K. Lundquist, 2016: Could Crop Height Affect the Wind Resource at Agriculturally Productive Wind Farm Sites? Boundary-Layer Meteorol, 158, 409–428, https://doi.org/10.1007/s10546-015-0102-0.
2015
45. Mirocha, J. D., D. A. Rajewski, N. Marjanovic, J. K. Lundquist, B. Kosović, 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, https://doi.org/10.1063/1.4928873.
44. St. Martin★, C. M., J. K. Lundquist, and M. A. Handschy, 2015: Variability of interconnected wind plants: correlation length and its dependence on variability time scale. Environmental Research Letters, 10, 044004, https://doi.org/10.1088/1748-9326/10/4/044004.
43. Vanderwende★, B. J., J. K. Lundquist, M. E. Rhodes, E. S. Takle, and S. L. Irvin, 2015: Observing and Simulating the Summertime Low-Level Jet in Central Iowa. Monthly Weather Review, 143, 2319–2336, https://doi.org/10.1175/MWR-D-14-00325.1
42. Banta, R. M., Y. L. Pichugina, W. A. Brewer, Julie K. Lundquist, Neil D. Kelley, Scott P. Sandberg, Raul J. Alvarez II, R. Michael Hardesty, and Ann M. Weickmann, 2015: 3D Volumetric Analysis of Wind Turbine Wake Properties in the Atmosphere Using High-Resolution Doppler Lidar. J. Atmos. Oceanic Technol., 32, 904–914, https://doi.org/10.1175/JTECH-D-14-00078.1.
41. Lundquist, J. K., M. J. 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, https://doi.org/10.5194/amt-8-907-2015.
40. Lundquist, J. K., and L. Bariteau, 2015: Dissipation of Turbulence in the Wake of a Wind Turbine. Boundary-Layer Meteorology, 154, 229–241, https://doi.org/10.1007/s10546-014-9978-3.
2014
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. Journal of Renewable and Sustainable Energy, 6, 033137, https://doi.org/10.1063/1.4885111.
38. Aitken★, M. L. and J. K. Lundquist, 2014: Utility-Scale Wind Turbine Wake Characterization Using Nacelle-Based Long-Range Scanning Lidar. Journal of Atmospheric and Oceanic Technology, 31, 1529–1539, https://doi.org/10.1175/JTECH-D-13-00218.1.
37. Rajewski, D., E. S. Takle, J. K. Lundquist, J. H. Prueger, R. L. 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 and Forest Meteorology, 194, 175–187, https://doi.org/10.1016/j.agrformet.2014.03.023.
36. Aitken★, M. L., R. M. Banta, Y. L. Pichugina, and J. K. Lundquist, 2014: Quantifying Wind Turbine Wake Characteristics from Scanning Remote Sensor Data. Journal of Atmospheric and Oceanic Technology, 31, 765–787, https://doi.org/10.1175/JTECH-D-13-00104.1.
35. Mirocha, J., B. Kosović, M. L. Aitken, and J. K. Lundquist, 2014: Implementation of a generalized actuator disk wind turbine model into the weather research and forecasting model for large-eddy simulation applications. Journal of Renewable and Sustainable Energy, 6, 013104, https://doi.org/10.1063/1.4861061.
2013
34. Archer, C. L., B. A. Colle, L. Delle Monache, M. J. Dvorak, J. K. Lundquist, B. H. Bailey, P. Beaucage, M. J. Churchfield, A. C. Fitch, B. Kosovic, S. Lee, P. J. Moriarty, H. Simao, R. J. A. M. Stevens, D. Veron, and J. Zack, 2013: Meteorology for Coastal/Offshore Wind Energy in the United States: Recommendations and Research Needs for the Next 10 Years. Bull. Amer. Meteor. Soc., 95, 515–519, https://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 US Midwest Atmospheric Wind Profiles as Observed with Ground-Based Doppler Lidar. Boundary-Layer Meteorology, 149, 85–103, https://doi.org/10.1007/s10546-013-9834-x.
32. Hu, Xiao-Ming, P. M. Klein, M. Xue, J. K. Lundquist, F. Zhang, and Y. Qi, 2013: Impact of Low-Level Jets on the Nocturnal Urban Heat Island Intensity in Oklahoma City. J. Appl. Meteor. Climatol., 52, 1779–1802, https://doi.org/10.1175/JAMC-D-12-0256.1.
31. Clifton, A., L. Kilcher, J. K. Lundquist, and P. Fleming, 2013a: Using machine learning to predict wind turbine power output. Environ. Res. Lett., 8, 024009, https://doi.org/10.1088/1748-9326/8/2/024009.
30. Fitch★, A. C., J. B. Olson, and J. K. Lundquist, 2013: Parameterization of Wind Farms in Climate Models. Journal of Climate, 26, 6439–6458, https://doi.org/10.1175/JCLI-D-12-00376.1.
29. Smalikho, I. N., V. A. Banakh, Y. L. Pichugina, W. A. Brewer, R. M. Banta, J. K. Lundquist, and N. D. Kelley, 2013: Lidar Investigation of Atmosphere Effect on a Wind Turbine Wake. Journal of Atmospheric and Oceanic Technology, 30, 2554–2570, https://doi.org/10.1175/JTECH-D-12-00108.1.
28. Fitch★, A. C., J. K. Lundquist, and J. B. Olson, 2013a: Mesoscale Influences of Wind Farms throughout a Diurnal Cycle. Monthly Weather Review, 141, 2173–2198, https://doi.org/10.1175/MWR-D-12-00185.1.
27. Clifton, A., S. Schreck, G. Scott, N. Kelley, and J. K. Lundquist, 2013: Turbine Inflow Characterization at the National Wind Technology Center. J. Sol. Energy Eng, 135, 031017-031017–11, https://doi.org/10.1115/1.4024068.
26. Rajewski, D. A., E. S. Takle, J. K. Lundquist, S. Oncley, J. H. Prueger, T. W. Horst, M. E. Rhodes, R. Pfeiffer, J. L. 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, https://doi.org/10.1175/BAMS-D-11-00240.1.
2012
25. Vanderwende★, B. and J. K. Lundquist, 2012: The modification of wind turbine performance by statistically distinct atmospheric regimes. Environmental Research Letters, 7, 034035, https://doi.org/10.1088/1748-9326/7/3/034035.
24. Lundquist, K. A., F. K. Chow, and J. K. Lundquist, 2012: An Immersed Boundary Method Enabling Large-Eddy Simulations of Flow over Complex Terrain in the WRF Model. Monthly Weather Review, 140, 3936–3955, https://doi.org/10.1175/MWR-D-11-00311.1.
23. Clifton, A. and J. K. Lundquist, 2012: Data Clustering Reveals Climate Impacts on Local Wind Phenomena. J. Appl. Meteor. Climatol., 51, 1547–1557, https://doi.org/10.1175/JAMC-D-11-0227.1.
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, 140, 3017–3038, https://doi.org/10.1175/MWR-D-11-00352.1.
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. J. Atmos. Oceanic Technol., 29, 347–355, https://doi.org/10.1175/JTECH-D-11-00033.1.
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, https://doi.org/10.1029/2011GL050413.
19. Wharton, S. and J. K. Lundquist, 2012: Atmospheric stability affects wind turbine power collection. Environmental Research Letters, 7, 014005, https://doi.org/10.1088/1748-9326/7/1/014005.
18. Wharton, S. and J. K. Lundquist, 2012: Assessing atmospheric stability and its impacts on rotor‐disk wind characteristics at an onshore wind farm. Wind Energy, 15, 525–546, https://doi.org/10.1002/we.483.
2011
17. Maxwell, R. M., J. K. Lundquist, J. D. Mirocha, S. G. Smith, C. S. Woodward, and A. F. B. Tompson, 2011: Development of a Coupled Groundwater–Atmosphere Model. Monthly Weather Review, 139, 96–116, https://doi.org/10.1175/2010MWR3392.1.
2010
16. Mirocha, J. D., J. K. Lundquist, and B. Kosović, 2010: Implementation of a Nonlinear Subfilter Turbulence Stress Model for Large-Eddy Simulation in the Advanced Research WRF Model. Mon. Wea. Rev., 138, 4212–4228, https://doi.org/10.1175/2010MWR3286.1.
15. Lundquist★, K. A., F. K. Chow, and J. K. Lundquist, 2010: An Immersed Boundary Method for the Weather Research and Forecasting Model. Monthly Weather Review, 138, 796–817, https://doi.org/10.1175/2009MWR2990.1.
2009
14. Shaw, W. J., J. K. Lundquist, and S. J. Schreck, 2009: Research needs for wind resource characterization. Bulletin of the American Meteorological Society, 90, 535–538, https://doi.org/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 Prediction Errors by a Transport and Dispersion Model. Journal of Atmospheric and Oceanic Technology, 26, 22–32, https://doi.org/10.1175/2008JTECHA1134.1.
2008
12. Delle Monache, L., J. K. Lundquist, B. Kosović, G. Johannesson, K. M. Dyer, R. D. Aines, F. K. Chow, R. D. Belles, W. G. Hanley, S. C. Larsen, G. A. Loosmore, J. J. Nitao, G. A. Sugiyama, and P. J. Vogt, 2008: Bayesian Inference and Markov Chain Monte Carlo Sampling to Reconstruct a Contaminant Source on a Continental Scale. Journal of Applied Meteorology and Climatology, 47, 2600–2613, https://doi.org/10.1175/2008JAMC1766.1.
11. Teixeira, J., B. Stevens, C. S. Bretherton, R. Cederwall, S. A. Klein, J. K. Lundquist, J. D. Doyle, J. C. Golaz, A. A. M. Holtslag, 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. Bulletin of the American Meteorological Society, 89, 453–458, https://doi.org/10.1175/BAMS-89-4-453.
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. J. Appl. Meteor. Climatol., 47, 44–58, https://doi.org/10.1175/2007JAMC1581.1.
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, https://doi.org/10.1175/JAM2514.1.
8. Simpson, M., S. Raman, J. K. Lundquist, and M. Leach, 2007: A study of the variation of urban mixed layer heights. Atmospheric Environment, 41, 6923–6930, https://doi.org/10.1016/j.atmosenv.2006.08.029
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, 247–272, https://doi.org/10.1007/s10546-004-2820-6.
2004
6. Piper, M. and J. K. Lundquist, 2004: Surface layer turbulence measurements during a frontal passage. Journal of the Atmospheric Sciences, 61, 1768–1780, https://journals.ametsoc.org/view/journals/atsc/61/14/1520-0469_2004_061_1768_sltmda_2.0.co_2.xml
2003
5. Lundquist, J. K., 2003: Intermittent and Elliptical Inertial Oscillations in the Atmospheric Boundary Layer. Journal of the Atmospheric Sciences, 60, 2661–2673, https://doi.org/10.1175/1520-0469(2003)060<2661:IAEIOI>2.0.CO;2.
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. Bull. Amer. Meteor. Soc., 83, 555–581, https://doi.org/10.1175/1520-0477(2002)083<0555:CACIOT>2.3.CO;2.
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, 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, 219–237, https://doi.org/10.1016/S0377-0265(00)00062-2.
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, 757–780, https://doi.org/10.1175/1520-0477(2000)081<0757:LIRERA>2.3.CO;2