Preparing Atmospheric Science Students for Today's Workforce: Increasing Data Science and Scientific Computing Skills for Undergraduates

As the atmospheric sciences have become more dependent on the computational sciences, software engineering, algorithmic problem solving and data-rich research skills have now become necessary tools to maintain high levels of competitiveness and productivity (Henderson et.al. 2007). In nearly all aspects of science today, open and transparent access to both the research inputs (data) and outputs (code, papers, models, etc.) is becoming the expected norm (Fecher and Friesike 2014, Gezelter 2015, Molley 2011, Kaiser 2015). Graduates with working computing knowledge and an understanding of open software platforms, data and tools are in high demand; thus we have identified a need for students to gain tangible skills in using and developing computer programs to (a) access, manipulate and manage large data sets, (b) visualize, explore and reason about data, and (c) manage research artifacts and source code. To address this need, this summer the Significant Opportunities in Atmospheric Research and Science (SOARS) program, an undergraduate research opportunity program directed by the National Center for Atmospheric Research (NCAR), added a scientific computing and data science workshop to explore how these new skills would be integrated into the skills SOARS protégés were already developing through their summer research experiences. This computing and data science workshop, developed and taught by NCAR, provided 8 hours of hands-on training (spread over four two-hour summer sessions) that focused on using the Python programming language for manipulating and visualizing data, to provision the students with skills in programming, data manipulation and quality control, data sharing, and source code documentation. This paper will present the structure and content of the workshop and share its impact as measured with pre- and post surveys. We found that the workshop supplemented the on-the-job training provided by intern’s research groups and computing mentors, and provided the protégés with an additional skill-set that is in demand by employers and graduate schools in the field. In addition to the practical skill-set, the workshop provided training in working in a collaborative environment, with interns working in small groups, and each group moving towards a common goal.