Data from smartphones could be harnessed to forecast weather patterns that lead to flash floods and other natural disasters, according to a study. Smartphones measure raw data, such as atmospheric pressure, temperatures and humidity, to assess atmospheric conditions, said researchers from Tel Aviv University (TAU) in Israel. To understand how the smartphone sensors work, they placed four smartphones around TAU campus under controlled conditions.
The study, published in the Journal of Atmospheric and Solar-Terrestrial Physics, analysed the data to detect phenomena such as “atmospheric tides,” which are similar to ocean tides. The researchers also analysed data from a UK-based app called WeatherSignal. “The sensors in our smartphones are constantly monitoring our environment, including gravity, the earth’s magnetic field, atmospheric pressure, light levels, humidity, temperatures, sound levels and more,” said Professor Colin Price from TAU.
“Vital atmospheric data exists today on some 3 to 4 billion smartphones worldwide. This data can improve our ability to accurately forecast the weather and other natural disasters that are taking so many lives every year,” Price said. By 2020, there will be more than six billion smartphones in the world, researchers said.
“Compare this with the paltry 10,000 official weather stations that exist today. The amount of information we could be using to predict weather patterns, especially those that offer little to no warning, is staggering,” Price said.
“In Africa, for example, there are millions of phones but only very basic meteorological infrastructures. Analysing data from 10 phones may be of little use, but analysing data on millions of phones would be a game changer. Smartphones are getting cheaper, with better quality and more availability to people around the world,” he said. The same smartphones may be used to provide real-time weather alerts through a feedback loop, Price said. The public can provide atmospheric data to the “cloud” via a smartphone application. This data would then be processed into real-time forecasts and returned to the users with a forecast or a warning to those in danger zones.
The study may lead to better monitoring and predictions of hard-to-predict flash floods. “We’re observing a global increase in intense rainfall events and downpours, and some of these cause flash floods,” Price said. “The frequency of these intense floods is increasing. We can’t prevent these storms from happening, but soon we may be able to use the public’s smartphone data to generate better forecasts and give these forecasts back to the public in real time via their phones,” he said.
