A Public-Private Partnership for Radar Meteorology Education

Research and education in radar meteorology have been a cornerstone of the Texas A&M Meteorology/Atmospheric Sciences program for decades. A key aspect to education has been the inclusion of onsite radar hardware and use of real-time and archived radar data in various courses, including the senior-level Radar Meteorology course. Texas A&M University has recently added to its rich history in radar meteorology research and education through a new partnership with Climavision. In summer 2024, the Aggie Doppler Radar (ADRAD), atop the 15-story Eller Oceanography and Meteorology building was replaced with a state-of-the-art X-band, dual-polarization radar system owned and operated by Climavision as part of their gap-filling weather radar network. The emergence of new hybrid weather radar networks will require future radar meteorologists to be well versed in understanding capabilities and limitations of various radar designs, so as to develop multi-radar, integrated products and insights that can be valuable to the forecaster. In this unique collaboration, Texas A&M students get a front row seat, with a radar on campus, engaging with the Climavision radar science and operations team, as they build out the first such network in the US, to learn how to lead/innovate in this new future.

This presentation describes the collaboration between Texas A&M and Climavision from an educational perspective as a roadmap for other public-private partnerships in atmospheric science education. We present how real-time and archived radar data are being used in the classroom to enrich student learning on the fundamentals of radar meteorology. In particular, we describe how unique Climavision radar technology (X-band, solid state, pulse compression) are compared with other operational radar networks to educate students on the selection various radar hardware choices for varying applications, and how these choices influence data quality in a variety of weather scenarios. We also describe how collaboration between Climavision’s science team and Texas A&M can lead to improvements in operational data quality through project-based learning approaches comparing derived radar products between radars and with supplemental rain gauge, disdrometer, and radiosonde observations.