Scientific Visualization and Mathematical Modeling of Weather Data: AnInterdisciplinary Approach to Learning with IDV

This presentation introduces an educational framework:

Interdisciplinary IDV, which combines scientific visualization and

mathematical modeling to improve the understanding of weather data.

Using the Integrated Data Viewer (IDV), the framework allows educators

and students to explore weather data through interactive

visualizations.

Building on 24 initial weather data modules, this framework includes

more weather cases and diverse data from satellites, radar, and

personal weather stations. It also makes use of enhanced IDV features,

such as access to the THREDDS Data Server and RAMADDA repository, for

real-time data and advanced analysis. Additionally, conceptual models

are introduced to help students connect theoretical knowledge with

real-world applications, making complex mathematical ideas easier to

understand.

This approach not only helps students learn about weather but also

gives teachers the tools to create their own learning modules. By

using real-time data and applying theoretical concepts to everyday

weather, students gain a deeper understanding of meteorology. The

Interdisciplinary IDV framework aims to improve weather education and

better prepare students for future challenges in the field.