Inductive Approach to Teaching of Dynamic Meteorology: Use of Thought Experiments and Technology Driven Science Inquiry

Traditionally, the teaching of dynamic meteorology follows a deductive approach, where the first step is to introduce students to the development of the theoretical framework. Subsequently, students are exposed to specific examples of atmospheric phenomena and how their behavior may be deduced using the theoretical framework. However, as in other fields, the development of dynamic meteorology was historically an iterative process through which observation of consistent patterns led to development of theories that were then tested through subsequent observation. Unfortunately, the current deductive pedagogical approach does not mimic the natural discovery-driven inductive path through which the field evolved. The type of questions that drove the development of the field is often presented as applications of the theory. The process of formulating relevant questions to investigate is a crucial skill and provides the context for theoretical development. This presentation will discuss implementations of an inquiry-driven, inductive pedagogy for the teaching of Dynamic Meteorology. Thought experiments and exploration of three-dimensional atmospheric reanalysis datasets will be used for this purpose, allowing students to drive the inquiry and increasing the probability of their developing their own inquiry-driven protocols as they prepare to enter the profession. Polaris, a discovery engine designed for operating on big data, will be utilized for exploration of large volumes of reanalysis data. Broad instructions, or "discovery scripts," will be used to guide the data exploration and to determine relationships between atmospheric flow features and relevant fields. Subsequently, guided classroom discussions will aid the students in formulating relevant questions and understanding the nature of the theoretical framework. Multiple examples of this approach will be presented at the talk.