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Chapman, William

Assistant Professor

Positions

Research Areas research areas

Research

research overview

  • My research focuses on advancing the predictability of weather and climate systems through innovative applications of machine learning, data assimilation, and hybrid modeling approaches.

Publications

selected publications

Teaching

courses taught

  • ATOC 4815 - Scientific Programming, Data Analysis and Visualization Laboratory
    Primary Instructor - Spring 2026
    Teaches programming in python, as well as analysis skills for accessing, analyzing and visualizing data that are commonly used in the atmospheric and oceanic sciences. Basic data analysis includes curve fitting and re-gridding/aggregation of satellite observations or meteorological data for global climatologies. The course content is primarily conveyed through hands-on code development. A final project, involving the independent analysis and visualization of a scientific data set, integrates skills acquired throughout the course. Recommended requisites: prior experience with Python or a basic programming course such as CSCI 1300 or equivalent, basic knowledge of calculus and algebra. Same as ATOC 5815.
  • ATOC 5815 - Scientific Programming, Data Analysis and Visualization Laboratory
    Primary Instructor - Spring 2026
    Teaches programming in python, as well as analysis skills for accessing, analyzing and visualizing data that are commonly used in the atmospheric and oceanic sciences. Basic data analysis includes curve fitting and re-gridding/aggregation of satellite observations or meteorological data for global climatologies. The course content is primarily conveyed through hands-on code development. A final project, involving the independent analysis and visualization of a scientific data set, integrates skills acquired throughout the course. Same as ATOC 4815.
  • ATOC 5860 - Objective Data Analysis Laboratory
    Primary Instructor - Fall 2025
    Teaches the extraction of information from data using statistical methods via a computer program. The goals of this course are: 1) to learn and apply tools to objectively analyze atmospheric and oceanic data, 2) to critically evaluate research using these tools. The course covers hypothesis testing, compositing, regression, principal component analysis, time series analysis, filtering, and data assimilation. This �learning-by-doing� course is aimed at advanced graduate students conducting ATOC-related research. Recommended prerequisite: ATOC 4810 or 5810, and familiarity with linear algebra, basic calculus, github and jupyter.
  • ATOC 6020 - Seminar in Atmospheric and Oceanic Sciences
    Primary Instructor - Fall 2025 / Spring 2026
    Studies an area of current research in the atmospheric and oceanic sciences. Students read selected papers from the literature. Students and faculty give presentations and participate in discussions. May be repeated for a total of 6 credit hours within the degree. May be repeated for a total of 3 credit hours within a semester.

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