An informal introduction to numerical weather models with low-cost hardware

Weather, climate, and other Earth system models are growing in complexity as computing resources and technologies continue to evolve with time. Thus, models are and will remain a vital tool for scientific research. Exposure and education on the workings of such models can generate interest toward atmospheric science, and it can increase scientific literacy among the general public. Additionally, studies have suggested that early exposure to these models can affect the career trajectory of students. However, gaining exposure and experience remains difficult outside of internships, research settings, and other professional endeavors. Some of these barriers can include hardware and computing costs, curriculum structure, and access to instructors. As a means of addressing these barriers, the goal of this work is to utilize low-cost hardware and abstract away some of the complexities of running a numerical weather model without sacrificing fidelity. The approach is to create a graphical user interface (GUI) where users can quickly configure the model, run it, and analyze the output without knowledge of model configuration, system architecture, or navigation via a command line interface. The Pi-WRF application is packaged such that users can download and run the model within a matter of minutes. The application is designed to promote informal learning through hands-on experience. It is targeted toward lower secondary level students, but it can scale across grade levels, and it can be adapted for general audiences.

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Copyright 2022 American Meteorological Society.


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Author Foust, William E.
Publisher UCAR/NCAR - Library
Publication Date 2022-01-01T00:00:00
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Topic Category geoscientificInformation
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Metadata Date 2023-08-18T18:18:45.701052
Metadata Record Identifier edu.ucar.opensky::articles:25450
Metadata Language eng; USA
Suggested Citation Foust, William E.. (2022). An informal introduction to numerical weather models with low-cost hardware. UCAR/NCAR - Library. http://n2t.net/ark:/85065/d7h41w5j. Accessed 24 April 2025.

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