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Molly Smith

Molly grew up in a desert part of California, and became interested in weather after the 1997-1998 El Niño turned her normally dry hometown into a lake. When it was time for college, she left Southern California for a more meteorologically active part of the country, getting a bachelor’s degree from Cornell University and then a master’s degree from the University at Albany, where she specialized in tropical cyclone modeling. Because one move across the country was not enough, Molly then applied for a job with NOAA’s Global Systems Laboratory and moved to Colorado. She is now happily ensconced and working on model verification, but also makes sure there’s time for reading piles of books and taking her cat on walks around the neighborhood.

Research Interests

  • Tropical cyclones
  • Tropical-midlatitude interactions
  • Model verification

Education

  • M.S. in Atmospheric Science from University at Albany, 2017
  • B.S. in Atmospheric Science from Cornell University, 2014

Experience

  • 2017 – present: Member of the GSL model verification team.
  • 2014 – 2017: Grad student studying ensemble rainfall variability in extratropically transitioning tropical cyclones.
  • 2012 – 2017: Teaching assistant at both Cornell University and the University at Albany. Assisted with or taught ten weather/climate undergraduate courses.
  • 2012-2014: Did honors research at Cornell University on interannual variability of mineral aerosols.
  • 2010-2012: Student assistant at the Northeast Regional Climate Center. Performed quality control on recently digitized historical weather records and collected field observations for research.

Professional Activities

  • Member of the American Meteorological Society

Honors and Awards

  • GSL Team Member of the Month, September 2018

Publications

Smith, M., Torn, R., Corbosiero, K., Pegion, P., 2020: Ensemble variability in rainfall forecasts of Hurricane Irene (2011). Weather and Forecasting, 35(5), 1761–1781, doi: 10.1175/WAF-D-19-0239.1.

Smith, M. B., Mahowald, N. M., Albani, S., Perry, A., Losno, R., Qu, Z., Marticorena, B., Ridley, D. A., and Heald, C. L., 2017: Sensitivity of the interannual variability of mineral aerosol simulations to meteorological forcing dataset. Atmospheric Chemistry and Physics, 17(5), 3253-3278, doi: 10.5194/acp-17-3253-2017.

Our Mission

Lead research and directed development through the transition of environmental data, models, products, tools, and services to support commerce, protect life and property, and promote a scientifically literate public.

Research Areas

Organizational Excellence, Earth System Prediction, Advanced Technologies, and Decision Support are the foundation to achieving the GSL Grand Challenge: Deliver actionable global storm-scale prediction and environmental information through advanced technologies to serve society.

Global Systems Laboratory