@article{glotfelty_alapaty_he_hawbecker_song_zhang_2020, title={Studying Scale Dependency of Aerosol-Cloud Interactions Using Multiscale Cloud Formulations}, volume={77}, ISSN={["1520-0469"]}, DOI={10.1175/JAS-D-19-0203.1}, abstractNote={AbstractThe Weather Research and Forecasting Model with Aerosol–Cloud Interactions (WRF-ACI) configuration is used to investigate the scale dependency of aerosol–cloud interactions (ACI) across the “gray zone” scales for grid-scale and subgrid-scale clouds. The impacts of ACI on weather are examined across regions in the eastern and western United States at 36, 12, 4, and 1 km grid spacing for short-term periods during the summer of 2006. ACI impacts are determined by comparing simulations with current climatological aerosol levels to simulations with aerosol levels reduced by 90%. The aerosol–cloud lifetime effect is found to be the dominant process leading to suppressed precipitation in regions of the eastern United States, while regions in the western United States experience offsetting impacts on precipitation from the cloud lifetime effect and other effects that enhance precipitation. Generally, the cloud lifetime effect weakens with decreasing grid spacing due to a decrease in relative importance of autoconversion compared to accretion. Subgrid-scale ACI are dominant at 36 km, while grid-scale ACI are dominant at 4 and 1 km. At 12 km grid spacing, grid-scale and subgrid-scale ACI processes are comparable in magnitude and spatial coverage, but random perturbations in grid-scale ACI impacts make the overall grid-scale ACI impact appear muted. This competing behavior of grid- and subgrid-scale clouds complicate the understanding of ACI at 12 km within the current WRF modeling framework. The work implies including subgrid-scale cloud microphysics and ice/mixed-phase-cloud ACI processes may be necessary in weather and climate models to study ACI effectively.}, number={11}, journal={JOURNAL OF THE ATMOSPHERIC SCIENCES}, author={Glotfelty, Timothy and Alapaty, Kiran and He, Jian and Hawbecker, Patrick and Song, Xiaoliang and Zhang, Guang}, year={2020}, month={Nov}, pages={3847–3868} }
 @article{lu_hawbecker_basu_manuel_2019, title={On Wind Turbine Loads During Thunderstorm Downbursts in Contrasting Atmospheric Stability Regimes}, volume={12}, ISSN={["1996-1073"]}, DOI={10.3390/en12142773}, abstractNote={Severe winds produced by thunderstorm downbursts pose a serious risk to the structural integrity of wind turbines. However, guidelines for wind turbine design (such as the International Electrotechnical Commission Standard, IEC 61400-1) do not describe the key physical characteristics of such events realistically. In this study, a large-eddy simulation model is employed to generate several idealized downburst events during contrasting atmospheric stability conditions that range from convective through neutral to stable. Wind and turbulence fields generated from this dataset are then used as inflow for a 5-MW land-based wind turbine model; associated turbine loads are estimated and compared for the different inflow conditions. We first discuss time-varying characteristics of the turbine-scale flow fields during the downbursts; next, we investigate the relationship between the velocity time series and turbine loads as well as the influence and effectiveness of turbine control systems (for blade pitch and nacelle yaw). Finally, a statistical analysis is conducted to assess the distinct influences of the contrasting stability regimes on extreme and fatigue loads on the wind turbine.}, number={14}, journal={ENERGIES}, author={Lu, Nan-You and Hawbecker, Patrick and Basu, Sukanta and Manuel, Lance}, year={2019}, month={Jul} }
 @article{glotfelty_alapaty_he_hawbecker_song_zhang_2019, title={The Weather Research and Forecasting Model with Aerosol-Cloud Interactions (WRF-ACI): Development, Evaluation, and Initial Application}, volume={147}, ISSN={["1520-0493"]}, DOI={10.1175/MWR-D-18-0267.1}, abstractNote={Abstract
               The Weather Research and Forecasting Model with Aerosol–Cloud Interactions (WRF-ACI) is developed for studying aerosol effects on gridscale and subgrid-scale clouds using common aerosol activation and ice nucleation formulations and double-moment cloud microphysics in a scale-aware subgrid-scale parameterization scheme. Comparisons of both the standard WRF and WRF-ACI models’ results for a summer season against satellite and reanalysis estimates show that the WRF-ACI system improves the simulation of cloud liquid and ice water paths. Correlation coefficients for nearly all evaluated parameters are improved, while other variables show slight degradation. Results indicate a strong cloud lifetime effect from current climatological aerosols increasing domain average cloud liquid water path and reducing domain average precipitation as compared to a simulation with aerosols reduced by 90%. Increased cloud-top heights indicate a thermodynamic invigoration effect, but the impact of thermodynamic invigoration on precipitation is overwhelmed by the cloud lifetime effect. A combination of cloud lifetime and cloud albedo effects increases domain average shortwave cloud forcing by ~3.0 W m−2. Subgrid-scale clouds experience a stronger response to aerosol levels, while gridscale clouds are subject to thermodynamic feedbacks because of the design of the WRF modeling framework. The magnitude of aerosol indirect effects is shown to be sensitive to the choice of autoconversion parameterization used in both the gridscale and subgrid-scale cloud microphysics, but spatial patterns remain qualitatively similar. These results indicate that the WRF-ACI model provides the community with a computationally efficient tool for exploring aerosol–cloud interactions.}, number={5}, journal={MONTHLY WEATHER REVIEW}, author={Glotfelty, Timothy and Alapaty, Kiran and He, Jian and Hawbecker, Patrick and Song, Xiaoliang and Zhang, Guang}, year={2019}, month={May}, pages={1491–1511} }
 @article{hawbecker_basu_manuel_2017, title={Realistic simulations of the July 1, 2011 severe wind event over the Buffalo Ridge Wind Farm}, volume={20}, number={11}, journal={Wind energy}, author={Hawbecker, P. and Basu, S. and Manuel, L.}, year={2017}, pages={1803–1822} }