Students will collaborate with local meteorologists and environmental NGOs to gather insights on the physical properties of fluids affecting local weather, empathize with community needs regarding climate challenges, and document their findings and reflections in their digital portfolios.

Students will analyze their empathy work to clearly define the specific local weather-related problem affected by climate change, synthesizing their findings into a clear problem statement to guide the next phase of ideation.

Students will brainstorm and generate diverse ideas for weather prediction models and community presentations, using research insights from past weather events and climate impacts, setting the stage for prototypes that integrate fluid dynamics and local data.

Students will create low-fidelity prototypes of their weather prediction models using real-time data, incorporating feedback from peers and community partners, and refine their digital portfolios with reflections on the design process to prepare for the upcoming testing phase.

Students will present their interactive digital maps and weather prediction models to community partners and peers, gather feedback through surveys and Q&A sessions, and refine their projects based on the input received, culminating in polished presentations for the 'SuperWeather Event TV Announcement' exhibition.