Use of a Simple Graphics Viewer for Gridded Data to Improve Data Literacy

Graphics packages commonly available to undergraduate meteorology students often have a substantial learning curve and require some understanding of graphics and computer programming before they can generate much more than a basic contour plot. In response to a need for students to quickly gain basic data literacy by interacting with real data in a variety of contexts, I have developed a simplified graphics package for viewing a variety of commonly used meteorological displays. The package, MADS (Meteorological Analysis and Diagnosis Software) provides archived data and graphical software to produce maps, cross-sections, vertical profiles (e.g., model soundings), time series (including meteograms and climographs) and climatological displays of a wide variety of basic and derived quantities. It is intuitive and easy to use and produces publication quality graphical output in most commonly used formats. Students in the Applied Meteorology program at Embry-Riddle Aeronautical University in Prescott Arizona use MADS for classroom assignments, for viewing current model runs and for synoptic or climatological studies. Students can interact with real-time model data downloaded twice daily from the NOMADS server, archived NCEP/NCAR global reanalyses, and higher-resolution ERA-Interim data from notable past storms. Each year, several students use MADS for their senior research project on topics as diverse as sea ice variability, climate change, ENSO influence on Arizona precipitation and Superstorm Sandy. In this context, MADS has some labor-saving features like formatting of multi-panel plots (for import into Word) and “remembers” each user's scripts, so students can easily take up where they left off from a previous MADS session. Students frequently comment on how easy the software is to use, which translates into more time spent discussing atmospheric dynamics and reduced faculty overhead. This talk will highlight features of this package, including sample plots that demonstrate possible pedagogical applications.