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School of Geography

Using smartphones to crowdsource meteorological data

Supervisor: Dr Guy Ziv (g.ziv(at)

Development of climate-related early warning systems (EWS) requires accurate, frequent and fine resolution meteorological data on temperature, wind, pressure, rainfall and humidity. The proliferation of Internet-connected mobile devices has created an opportunity for crowdsourcing smartphone sensor data for environmental research and EWS. For example, previous research (Overeem et al. Geophys. Res. Let. 40, 4081–4085) showed how battery temperature predicts daily averaged air temperatures. This project aims to explore further applications of crowdsourced mobile sensor data, collected via the WeatherSignal App. The project is suited for a student with good computational/statistical skills and ideally some programming experience, with an interest in Big Data use for environmental research.