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

The theme of this year's AMS meeting is “Fulfilling the Vision of Weather, Water, Climate information for Every Need, Time, and Place”, which our project is striving to accomplish by making knowledge about authentic science more accessible in the atmospheric science classroom. 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's forecast skill of the observed boundary layer phenomenon. 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 to measure a boundary layer phenomenon. Additionally, they had access to the NCAR Yellowstone supercomputer to run their WRF model simulations.

Running the WRF model as a part of the class is a very important opportunity because computer models play an extremely important role in scientific research and in developing our understanding of the atmosphere. Current research in the field of science education indicates that the best way for students to understand complex computer models is to have them work with, experiment with, modify, and apply models in a way that is significant and informative to the learner. This course used a hybrid approach to learning about running the WRF model, which included the in-class material as well as an online modelling course. The online course is a modification of a free tutorial that teaches novice modellers how to set up and run the WRF model for regional climate modelling. 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 was located 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. The PSU students taking this course practiced using the WRF model on the PSU cluster, and ran final case study simulations on NCAR's Yellowstone supercomputer. If a class wanted to try this hybrid approach, but computing power and a full version of WRF is not available, the online course is free and comes with a version of WRF that is modified for educational purposes (located at m2lab.org), which is easier to install and can be run on a desktop computer (Mesquita 2013).

Reference: Mesquita, M.d.S. (2013) e-WRF: WRF for Educational Purposes [Computer program]. Available at m2lab.org