Selected Invited Talks (last updated Apr 2024)
W Chapman, J. Berner “Deterministic and Stochastic Tendency Adjustments Derived from Data Assimilation and Nudging”, Climate Variability Working Group Annual Meeting Mar 5, 2024
W Chapman, “Advancing Weather and Climate Prediction with Data-Driven Methods”, Naval Post-Graduate School Mar 2, 2024
W Chapman, “Advancing Weather and Climate Prediction with Data-Driven Methods”, University of Washington, Allen School Colloquia Series Feb 20, 2024
W Chapman, “Leveraging DART and Nudging Increments to Address Model Bias in CAM6”, NOAA - Atmosphere-Ocean Processes and Predictability Section March, 2023.
W Chapman, J. Berner, “Comparing Data Assimilation and Nudging Increment Tendency Adjustments in Addressing Model Bias in CAM6”, University of Bergen- UIB, Bjerkness Center Lecture Series – May 15, 2023.
W Chapman, “Monthly Modulations of ENSO teleconnections”, NCAR ASP 2022 Workshop on S2S Science and prediction July, 2022.
W Chapman,“Probabilistic Weather Prediction with Neural Networks”, TRUSTWORTHY ARTIFICIAL INTELLIGENCE FOR ENVIRONMENTAL SCIENCE (TAI4ES) SUMMER SCHOOL July 27, 2021.
W Chapman, L Delle Monache, S Alessandrini, AC Subramanian, N Hayatbini, SP Xie, and FM Ralph, “Deterministic and Probabilistic Methods for Improving Atmospheric River Forecasts with Machine Learning”, Scripps Institutional Seminar – November 17, 2020
W Chapman, L Delle Monache, S Alessandrini, AC Subramanian, N Hayatbini, SP Xie, and FM Ralph, “Deterministic and Probabilistic Methods for Improving Atmospheric River Forecasts with Machine Learning”, Scripps Institutional Seminar – November 17, 2020
W Chapman, “Bayesian Neural Networks and NWP Forecast Post-Processing”, UCI/Columbia CBrain Meeting – April 21, 2020
W Chapman, Instructor: “AGU Tutorial on Machine Learning and Deep Learning for the Environmental and Geosciences”, AGU Fall Meeting – December 8, 2019
W Chapman, AC Subramanian, L Delle Monache, SP Xie, and FM Ralph, “Spatial Correction of NWP Forecasts”, National Center for Atmospheric Research RAL – November 7, 2019
W Chapman, T Kilpatrick, and SP Xie, “Comparative Field Reconstruction: Deep Learning, MCA, CCA”, National Center for Atmospheric Research - Artificial Intelligence Affinity Group (AIAG) – Oct 9, 2019
W Chapman, A Wilson, and FM Ralph, “Center for Western Weather and Water Extremes: Atmospheric River Colloquium”, Western States Water Council and the California Department of Water Resources Subseasonal to Seasonal Workshop – May 23, 2019
W Chapman, SP Xie, and FM Ralph, “High Impact Weather, Climate Extremes, and Non-Gaussian Statistics”, Climate Science Policy Ocean/Atmos Ph.D. Student Seminar – February 8, 2019
W Chapman, “No Red Meat or a New Electric Vehicle, Food Choices and Emissions”, Connecting the Dots 2015: The Food, Energy, Water and Climate Nexus, Stanford University – April 17, 2015
Conference Talks (last updated Mar 2020)
W Chapman, L Delle Monache, S Alessandrini, AC Subramanian, N Hayatbini, SP Xie, and FM Ralph, “Probabilistic Weather Prediction with Bayesian Neural Networks”, Machine Learning for Weather and Climate Modeling II - AGU Fall Meeting 2020, 2020
P Gibson, W Chapman, A Altinok, MJ Deflorio, L Delle Monache, and D Waliser, “Interpretable Machine Learning applied to Seasonal Forecasting of Western US Precipitation”, Machine Learning for Weather and Climate Modeling III - AGU Fall Meeting 2020, 2020
W Chapman, TJ Kilpatrick, “Machine Learning for inpainting QuikSCAT winds in Hawaii’s Lee Region”, AI Applied to Airborne or Spaceborne Earth Observation Datasets - 100th American Meteorological Society Annual Meeting, January 2020, 2020. AMS Student Presentation Award - 1st Place
W Chapman, “Atmospheric River Forecast Model Bias Correction”, 19th Conference on Artificial Intelligence for Environmental Science - 99th American Meteorological Society Annual Meeting, 2019.
W Chapman, S.-P.Xie, and T. Kilpatrick, “Machine Learning to Improve QuikSCAT Ambiguity Selection Near Hawaii’s Big Island”, The International Ocean Vector Science Team Meeting, May 2019.