The American Meteorological Society (AMS) held its annual meeting Feb. 2 to 6 in Atlanta. The nationally recognized conference hosted a total of 3,456 attendees and included industry professionals, scholars from various disciplines of meteorological sciences and students from 34 countries around the world, including 41 students from Penn State.
The students from Penn State’s Department of Meteorology in the College of Earth and Minerals Sciences were able to learn about other research in their field, present their research findings, and network with industry professionals and academic colleagues.
The theme of the conference was “Extreme Weather — Climate and the Built Environment: New Perspectives, Opportunities and Tools.” The conference examined weather related issues such as severe storms, droughts, floods and wildfires that caused disasters for millions of people globally and addressed societal response to these natural disasters.
"The conference was amazing,” recounted conference attendee Dakota Smith, a senior in meteorology and president of the College of Earth and Mineral Sciences undergraduate student council. “During the main conference there were dozens of presentations occurring simultaneously. It was awesome. You could pick almost any topic in meteorology and find a talk to go to. I really learned a lot,” said Smith.
Three undergraduate and four graduate students presented their research, including Christopher Hanlon, doctoral candidate in meteorology, who presented “Algorithmic Decision-Making Under Weather Uncertainty in Atmospheric Science Field Campaigns: A Summary.”
Hanlon, advised by George Young and Johannes Verlinde, both professors of meteorology, and Arthur Small III, president and CEO of Venti Risk Management, discussed how using algorithmic decision-making under weather uncertainty offers added value to human forecasts, statistical forecasts and numerical weather prediction forecasts, and provides a means of integrating human forecasting knowledge with advances in computing.
“Using automated, calibrated, probabilistic weather forecasts, automated decision-making algorithms have shown the ability to outperform the traditional heuristic method of forecasting and decision-making,” said Hanlon.