Faculty Name

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

Publications by year

2016

53. St. Martin, C., J. K. Lundquist, G. S. Poulos, A. Clifton, and S. Schreck. 2015. Wind turbine power production and annual energy production depend on atmospheric stability and turbulence. Accepted for publication in Wind Energy Science

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

51. Bryan, G. H., R. Worsnop, J. K. Lundquist, and J. A. Zhang. 2016. A simple method for simulating tropical-cyclone boundary layers. In press at Boundary-Layer Meteorology.

50. Vanderwende, B., B. Kosovic, J. K. Lundquist, and J. Mirocha. 2016. Simulating effects of a wind turbine array using LES and RANS. In press at Journal of Advances in Modeling Earth Systems. DOI: 10.1002/2016MS000652

49. Lundquist, J. K., and ~ 30 co-authors. Assessing state-of-the-art capabilities for probing the atmospheric boundary layer: the XPIA field campaign. In press at the Bulletin of the American Meteorological Society. 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. In press at the Bulletin of the American Meteorological Society.

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. To appear in J. Atmos. Ocean. Tech.

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; appeared in 2014 as discussion paper Lundquist, J. K., M. Churchfield, S. Lee, and A. Clifton. 2014. Quantifying error of remote sensing observations of wind turbine wakes using computational fluid dynamics. Atmos. Meas. Tech. Discuss., 7, 9317-9350, http://www.atmos-meas-tech-discuss.net/7/9317/2014/
doi:10.5194/amtd-7-9317-2014.

41. Lundquist, J. K. and L. Bariteau. 2015. Dissipation of turbulence in the wake of a wind turbine. Boundary-Layer Meteorology, 154, 229-241. online 6 Nov 2014 .

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.