Smartphones may one day do more than deliver weather forecasts. They could also help make those forecasts better. A new study shows that pressure measurements collected by smartphones can improve forecasts of a severe hailstorm over Beijing, suggesting that millions of smartphones could someday support a dense, low-cost observing network for faster and more accurate severe-weather warnings.
This research was published in Advances in Atmospheric Sciences on July 25.
Severe thunderstorms can develop quickly, bringing hail, damaging winds, and intense rainfall. Yet predicting exactly where and when these hazards will occur remains difficult. One reason is that the traditional weather stations that meteorologists rely on are often too far apart to capture the small and rapidly changing atmospheric signals that drive these storms. Researchers at Peking University therefore wondered whether part of the solution might already be in people's pockets. The idea rests on a simple fact: many smartphones contain barometric pressure sensors. If their measurements can be collected and carefully processed, the smartphones people carry every day could both contribute data to weather prediction and receive forecasts.
To test the idea, the researchers examined a damaging hailstorm that struck Beijing on June 30, 2021. Using anonymized pressure readings collected with users' consent through the Moji Weather mobile application, the team corrected the raw data with machine-learning methods and fed them into a high-resolution weather model. Smartphone pressure data improved hail forecast skill by 14% to 17% and produced a better simulation of where the hail fell and how the storm evolved. In this case, the smartphone observations performed better overall than data from traditional weather stations.
"Surface pressure contains useful information about the development and movement of convective storms, but traditional station networks cannot always observe these features in sufficient detail," said Rumeng Li, the study's corresponding author. "That is what makes smartphones so promising. Unlike new weather stations, which require time and funding to install, sensors in smartphones are already widely distributed across cities in numbers that conventional observing networks cannot easily match. For regions that lack dense weather infrastructure, that could mean the difference between receiving an early warning and receiving no warning at all."
The Beijing case is only a first demonstration, and the researchers are careful about its limits. Smartphone observations tend to be concentrated where people live, while this particular storm formed over sparsely populated mountains, where far fewer readings were available. The method improved the forecast once the storm reached the city but could not fully correct errors in the storm's earlier development. Testing across more events and regions is still needed.
Even so, the researchers see the study as an early step toward a much broader role for smartphones in severe-weather early warning. "The United Nations has set a goal of ensuring that everyone on Earth is protected by an early warning system," said Qinghong Zhang, the project leader. "Reaching that goal will require both better observations and forecasts detailed enough to capture hazards at the local scale. Smartphones could help fill part of that gap by contributing pressure observations to forecast models, as this study demonstrates, while also serving as a direct channel for delivering warnings to users. In the long term, we hope smartphones can work alongside conventional weather stations and radar to support better short-term forecasts and earlier warnings for hailstorms and other rapidly developing convective events."
