Andrew has been an atmospheric scientist at NREL since 2017 and is currently a PhD candidate at the University of Colorado Boulder in the Atmospheric and Oceanic Sciences department. Previous research has involved wind and solar resource assessment and forecasting, with a recent focus on offshore wind energy. His research spans various temporal and spatial scales, using tools such as numerical weather prediction and machine learning to help fill the gaps in our knowledge of the atmospheric boundary layer as it relates to wind energy.
Research Interests
Wind resource assessment and forecasting
Offshore wind energy
Numerical weather prediction
Machine learning
Climate and climate change
Education
Ph.D., Atmospheric and Oceanic Sciences, University of Colorado Boulder (in progress)
M.S., Atmospheric Sciences, University of Illinois Urbana-Champaign
B.S., Atmospheric Sciences; Earth Systems, Environment, and Society, University of Illinois Urbana-Champaign
Professional Experience
Research Scientist, NREL (2017–Present)
Associate Scientist, CIRES (2015–2017)
Associations and Memberships
Member, American Meteorological Society
Featured Work
A Physics-based Smart Persistence Model for Intra-Hour Forecasting of Solar Radiation (PSPI) Using GHI Measurements and a Cloud Retrieval Technique, Solar Energy (2019)
Inter-Annual Variability of Wind and Solar Electricity Generation and Capacity Values in Texas, Environmental Research Letters (2019)
Quantifying Sensitivity in Numerical Weather Prediction-Modeled Offshore Wind Speeds Through an Ensemble Modeling Approach, Wind Energy (2021)
Validation of RU-WRF, the Custom Atmospheric Mesoscale Model of the Rutgers Center for Ocean Observing Leadership, NREL Technical Report (2020)
Consequences of Neglecting the Interannual Variability of the Solar Resource: A Case Study of Photovoltaic Power Among the Hawaiian Islands, Solar Energy (2018)
Software
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