A new Cornell study could help inform the development of offshore wind farms by providing detailed models characterizing the frequency, intensity and height of low-level jet streams over the Atlantic... Read more about Low-level jet models inform US offshore wind development
Sara C. Pryor is an atmospheric scientist who uses a combination of field measurements and numerical tools to improve understanding of the climate system. She completed her PhD at the University of East Anglia in the UK during which she spent time at Scripps Institute of Technology in San Diego and the Desert Research Institute in Reno, Nevada. She then took a position as a Post Doctoral Fellow at the University of British Columbia, Canada. She joins Cornell from Indiana University where she held the rank of Provost's Professor. Professor Pryor has courtesy appointments at Aarhus University in Denmark and the Pervasive Technology Institute at Indiana University.
Prof. Pryor is part of a new generation of scientists who are conducting research across traditional disciplinary boundaries and engaging in work to address societal grand challenges in climate science and energy science using a wide suite of big data analytics on experimental data collected by her group and also high-resolution, high-fidelity atmospheric simulations.
Prof. Pryor has taught across the spectrum of atmospheric science courses including air pollution meteorology, climate science and climate change mitigation, and physical meteorology and climatology.
She currently teaches:
- EAS 2500 Meteorological Observations and Instruments
- EAS 3340 Microclimatology
- EAS 4350/5350 Statistical Methods in Meteorology and Climatology
- Pryor S.C., Coburn J.J., Barthelmie R.J. and Shepherd T. (2023): Projecting future energy production from operating wind farms in North America: Part 1: Dynamical downscaling. Journal of Applied Meteorology and Climatology 62 63-80 doi: 10.1175/JAMC-D-22-0044.1
- Coburn J.J. and Pryor S.C. (2023): Evolution of the internal climate modes under future warming. Journal of Climate 36 511-529 doi: 10.1175/JCLI-D-22-0200.1
- Coburn J.J. and Pryor S.C. (2022): Do machine learning approaches offer skill improvement for short-term forecasting of wind gust occurrence and magnitude? Weather and Forecasting 37 525-543
- Pryor S.C., Barthelmie R.J. and Shepherd T.J. (2021): Wind power production from very large offshore wind farms. Joule 5 2663-2886 doi: 10.1016/j.joule.2021.09.002
- Pryor S.C. and Barthelmie R.J. (2021): A global assessment of extreme wind speeds for wind energy applications. Nature Energy 6 268-276 doi: 10.1038/s41560-020-00773-7
- Pryor S.C., Barthelmie R.J., Bukovsky M.S., Leung L.R. and Sakaguchi K. (2020): Climate change impacts on wind power generation. Nature Reviews: Earth and Environment 1 627-643 doi: 10.1038/s43017-020-0101-7
- Pryor S.C., Barthelmie R.J. and Shepherd T.J. (2020): 20% of US electricity from wind will have limited impacts on system efficiency and regional climate. Nature: Scientific Reports 10 541 doi: 10.1038/s41598-019-57371-1
- Pryor S.C., Shepherd T.J., Volker P., Hahmann A.N. and Barthelmie R.J. (2020): ‘Wind theft’ from onshore wind turbine arrays: Sensitivity to wind farm parameterization and resolution. Journal of Applied Meteorology and Climatology 59 153-174
- Letson F., Barthelmie R.J., Hu W., and Pryor S.C. (2019): Characterizing wind gusts in complex terrain.Atmospheric Chemistry and Physics 19 3797-3819
- Sullivan R.C., Crippa P., Matsui H., Leung, L.R., Zhao C., Thota A., and Pryor S.C. (2018): New particle formation leads to cloud dimming. npj Climate and Atmospheric Science 1:9 doi:10.1038/s41612-018-0019-7
- Sullivan R.C., Levy R., da Silva A. and Pryor S.C. (2017): Developing and diagnosing climate change indicators of regional aerosol optical properties. Nature: Scientific Reports 7 art # 18093, doi: 10.1038/s41598-017-18402-x
- Pryor S.C., Sullivan R.C. and Schoof J.T. (2017): Modeling the contributions of global air temperature, synoptic-scale phenomena and soil moisture to near-surface static energy variability using artificial neural networks. Atmospheric Chemistry and Physics 17 14457-14471
- Pryor, Sara C., J T Schoof. 2016. "Evaluation of near-surface temperature, humidity, and equivalent temperature from regional climate models applied in type II downscaling." Journal of Geophysical Research-Atmospheres 121 (7): 3326-3338.
- Crippa, Paola, Ryan C. Sullivan, A. Thota, Sara C Pryor. 2016. "Evaluating the skill of high-resolution WRF-Chem simulations in describing drivers of aerosol direct climate forcing on the regional scale.." Atmospheric Chemistry and Physics 16 (1): 397-416.
- Pryor, Sara C., K. E. Hornsby, K. A. Novick. 2014. "Forest canopy interactions with nucleation mode particles." Atmospheric Chemistry and Physics 14 (21): 11985-11996.
- Pryor, Sara C., R. Conrick, C. Miller, J. Tytell, R. J. Barthelmie. 2014. "Intense and extreme wind speeds observed by anemometer and seismic networks: An eastern U.S. case study." Journal of Applied Meteorology and Climatology 53: 2417-2429.
- Schoof, J. T., Sara C Pryor. 2014. "Assessing the fidelity of AOGCM-simulated relationships between large-scale modes of climate variability and wind speeds." Journal of Geophysical Research-Atmospheres 119 (16): 9719-9734.
Selected Awards and Honors
- Fellow of the American Meteorological Society (AMS) 2021
- Research and Extension Award for Outstanding Accomplishments in Research (CALS, Cornell University) 2018
- Fellow of the American Association for the Advancement of Science 2014 (AAAS) 2014
- North American representative; CORDEX-ESD ((CORDEX-Coordinated Regional Downscaling Experiment is an international project under the World Climate Research programme. ESD - Empirical Statistical Downscaling) 2014
- Convening Lead Author (Midwest Region for the National Climate Assessment) 2011
- National Climate Assessment and Development Advisory Committee (NCADAC) (U.S. Department of Commerce's National Oceanic & Atmospheric Administration) 2011
- Editor (Journal of Geophysical Research-Atmospheres) 2010