Elizabeth (Libby) Barnes
Associate Professor, Department of Atmospheric Science, Colorado State University
Dr. Elizabeth (Libby) Barnes is an associate professor of Atmospheric Science at Colorado State University. She joined the CSU faculty in 2013 after obtaining dual B.S. degrees (Honors) in Physics and Mathematics from the University of Minnesota, obtaining her Ph.D. in Atmospheric Science from the University of Washington, and spending a year as a NOAA Climate & Global Change Fellow at the Lamont-Doherty Earth Observatory. Professor Barnes' research is largely focused on climate variability and change and the data analysis tools used to understand it. Topics of interest include earth system predictability, jet-stream dynamics, Arctic-midlatitude connections, subseasonal-to-decadal (S2D) prediction, and data science methods for earth system research (e.g. machine learning, causal discovery). She teaches graduate courses on fundamental atmospheric dynamics and data science and statistical analysis methods. Professor Barnes is involved in a number of research community activities. In addition to being a lead of the new US CLIVAR Working Group: Emerging Data Science Tools for Climate Variability and Predictability and a funded member of the NSF AI Institute for Research on Trustworthy AI in Weather, Climate and Coastal Oceanography (AI2ES), she recently finished being the lead of the NOAA MAPP S2S Prediction Task Force (2016-2020).
Dr. Barnes received the AGU Turco Lectureship for 2020, AMS Clarence Leroy Meisinger Award for 2020, and was awarded an NSF CAREER grant in 2018. She received the George T. Abell Outstanding Early-Career Faculty Award in 2016 and was recognized for her teaching and mentoring by being awarded an Honorable Mention for the CSU Graduate Advising and Mentorship Award in 2017 and being named the Outstanding Professor of the Year Award in 2016 by the graduate students of the Department of Atmospheric Science. In 2014 she was the recipient of an AGU James R. Holton Junior Scientist Award.
Marc Calaf
Associate Professor, Department of Mechanical Engineering, University of Utah
Marc Calaf is an Associate Professor at the Department of Mechanical Engineering at the University of Utah. He received a PhD in ME from École Polythecnique Fédérale de Lausanne (EPFL) in 2011, after spending two years as a visiting student at Johns Hopkins University. In 2019-20 he was a visiting faculty at the Karlsruhe Institute of Technology (KIT) Campus Alpine, in Garmisch-Partenkirchen as a Humboldt Scholar. His research interests include the study of atmospheric boundary-layer (ABL) flows, turbulence, and renewable energy systems that interact with the ABL, together with their corresponding representation in computational platforms.
Shu-Hua Chen
Associate Professor, Department of Land, Air, Water Resources, University of California, Davis
Dr. Chen's research involves data assimilation, heavy orographic rainfall, and pollutant transport. Remote sensing data, such as SSM/I, QuikSCAT, MODIS, and radar are used to improve severe weather simulations and forecasts. The effects of the moist Froude number and the convective available potential energy on flow regimes associated with a conditionally unstable flow over a mesoscale mountain are investigated using idealized simulations. A tracer model based on a mesoscale model has been developed to study the source-receptor relationship and long-range transport. Dr. Chen teach's weather observation and analysis (ATM110) and severe and unusual weather (ATM10) at the undergraduate level, and numerical modeling of the atmosphere (ATM255) at the graduate level.
David Peterson
Meteorologist, U.S. Naval Research Laboratory
Dr. Dave Peterson is a meteorologist at the US Naval Research Laboratory in Monterey, CA. He has broad scientific interests in both meteorology and satellite remote sensing. Dave currently supports the US Navy’s global aerosol modeling efforts, with a focus on extreme wildfires and smoke transport. He is a leading expert on thunderstorms caused by intense wildfires (pyrocumulonimbus), and the ensuing impact on stratospheric composition. Dave also serves as an interface between operational meteorologists, atmospheric chemistry scientists, and modelers, especially during large field experiments.