A Hybrid Approach to Online and Traditional Learning during a Boundary Layer Meteorology Course

Abstract:

This project discusses a case study, where eight graduate students in a Boundary Layer Meteorology course at Plymouth State University collected observation data and ran the WRF model in order to explore the relationships between model output, observation data, and boundary layer theory. At the end of the course, the students drafted a paper highlighting their findings, which has been submitted for publication.

As a part of the course, the students were provided with a unique learning opportunity to collect meteorological data for a boundary layer phenomenon of their choice, analyze the data and compare it to theory learned in class, and run a numerical model to test the model forecast skill of the observations. Students had access to the Plymouth State University (PSU) radiosonde system and the Mount Washington Observatory Mesonet stations that measure wind, temperature, and relative humidity. Additionally, they had access to the NCAR Yellowstone supercomputer to run their WRF model simulations.

This course used a hybrid approach to learning about running the WRF model, which included the in-class material and an online WRF modelling course. For the purposes of this class, the hybrid approach included having the students take the online tutorial and have weekly videoconference meetings with the online course tutor, who lives in Norway. This, in conjunction with the traditional in-class portion, provided multiple modes of learning WRF, access to more expertise in running numerical models, and an opportunity to meet a foreign researcher.

Survey results indicate that the students found it helpful to run the model as a part of understanding the atmosphere. A few students recognized that having experience running a model could help them in their future research if they ever need to run WRF or any other atmospheric research model. Most students report that it was useful to compare model data to observed data in order to evaluate the model and compare their findings to what the “expected” outcome would be based on theory. Having students recognize the inconsistencies but not discount the usefulness of the model and the data is an extremely important learning outcome from this course. In sharing our classroom experience, we hope to inspire other instructors to try utilizing both observation and modeling techniques in the classroom.