| The Perdigão: peering into microscale details of mountain winds HJS Fernando, J Mann, J Palma, JK Lundquist, RJ Barthelmie, ... Bulletin of the American Meteorological Society 100 (5), 799-819, 2019 | 158 | 2019 |
| Three-dimensional structure of wind turbine wakes as measured by scanning lidar N Bodini, D Zardi, JK Lundquist Atmospheric Measurement Techniques 10 (8), 2881-2896, 2017 | 89 | 2017 |
| The second wind forecast improvement project (WFIP2): Observational field campaign JM Wilczak, M Stoelinga, LK Berg, J Sharp, C Draxl, K McCaffrey, ... Bulletin of the American Meteorological Society 100 (9), 1701-1723, 2019 | 80* | 2019 |
| Estimation of turbulence dissipation rate and its variability from sonic anemometer and wind Doppler lidar during the XPIA field campaign N Bodini, JK Lundquist, RK Newsom Atmospheric Measurement Techniques 11 (7), 4291-4308, 2018 | 63 | 2018 |
| US East Coast lidar measurements show offshore wind turbines will encounter very low atmospheric turbulence N Bodini, JK Lundquist, A Kirincich Geophysical Research Letters 46 (10), 5582-5591, 2019 | 60 | 2019 |
| Spatial and temporal variability of turbulence dissipation rate in complex terrain N Bodini, JK Lundquist, R Krishnamurthy, M Pekour, LK Berg, ... Atmospheric Chemistry and Physics 19 (7), 4367-4382, 2019 | 40 | 2019 |
| New methods to improve the vertical extrapolation of near-surface offshore wind speeds M Optis, N Bodini, M Debnath, P Doubrawa Wind Energy Science Discussions 2021, 1-26, 2021 | 37 | 2021 |
| Wind plants can impact long-term local atmospheric conditions N Bodini, JK Lundquist, P Moriarty Scientific reports 11 (1), 22939, 2021 | 33 | 2021 |
| Extreme wind shear events in US offshore wind energy areas and the role of induced stratification M Debnath, P Doubrawa, M Optis, P Hawbecker, N Bodini Wind Energy Science 6 (4), 1043-1059, 2021 | 32 | 2021 |
| Estimation of turbulence dissipation rate from Doppler wind lidars and in situ instrumentation for the Perdigão 2017 campaign N Wildmann, N Bodini, JK Lundquist, L Bariteau, J Wagner Atmospheric Measurement Techniques 12 (12), 6401-6423, 2019 | 29 | 2019 |
| The importance of round-robin validation when assessing machine-learning-based vertical extrapolation of wind speeds N Bodini, M Optis Wind Energy Science 5 (2), 489-501, 2020 | 26 | 2020 |
| Offshore wind turbines will encounter very low atmospheric turbulence N Bodini, JK Lundquist, A Kirincich Journal of Physics: Conference Series 1452 (1), 012023, 2020 | 24 | 2020 |
| Can reanalysis products outperform mesoscale numerical weather prediction models in modeling the wind resource in simple terrain? V Pronk, N Bodini, M Optis, JK Lundquist, P Moriarty, C Draxl, ... Wind Energy Science 7 (2), 487-504, 2022 | 20 | 2022 |
| Can machine learning improve the model representation of turbulent kinetic energy dissipation rate in the boundary layer for complex terrain? N Bodini, JK Lundquist, M Optis Geoscientific Model Development 13 (9), 4271-4285, 2020 | 19 | 2020 |
| offshore wind resource assessment for the California Pacific outer continental shelf M Optis, O Rybchuk, N Bodini, M Rossol, W Musial Strategic Partnership Project, National Renewable Energy Laboratory …, 2020 | 19 | 2020 |
| The Perdigao: Peering into microscale details of mountain winds, B. Am. Meteorol. Soc., 100, 799–819 HJS Fernando, J Mann, J Palma, JK Lundquist, RJ Barthelmie, ... | 19 | 2019 |
| The sensitivity of the Fitch wind farm parameterization to a three-dimensional planetary boundary layer scheme A Rybchuk, TW Juliano, JK Lundquist, D Rosencrans, N Bodini, M Optis Wind Energy Science Discussions 2021, 1-39, 2021 | 17 | 2021 |
| Design of the American Wake Experiment (AWAKEN) field campaign M Debnath, AK Scholbrock, D Zalkind, P Moriarty, E Simley, N Hamilton, ... Journal of Physics: Conference Series 2265 (2), 022058, 2022 | 14 | 2022 |
| How accurate is a machine learning-based wind speed extrapolation under a round-robin approach? N Bodini, M Optis Journal of Physics: Conference Series 1618 (6), 062037, 2020 | 14 | 2020 |
| Assessing boundary condition and parametric uncertainty in numerical-weather-prediction-modeled, long-term offshore wind speed through machine learning and analog ensemble N Bodini, W Hu, M Optis, G Cervone, S Alessandrini Wind Energy Science 6 (6), 1363-1377, 2021 | 12 | 2021 |
