
Mobile radio network doubles as weather indicator
How does the weather forecast get on the mobile phone? Quite clearly: via the corresponding app. But where does the app get the data from? So far, they come from the major meteorological services – in Germany, for example, from the Deutscher Wetterdienst (DWD). These services work with far-flung networks of meteorological observation stations and weather radars. But it would also be much easier. Because the mobile phone networks themselves provide the data. The reason: the performance of the network is strongly influenced by the weather; rain can significantly reduce the spread of radio waves.
This might annoy the telecommunications companies, but for meteorological research this is a stroke of luck: From the interaction between weather events and technology, researchers have developed a completely new method for measuring rain. “If a mobile network is available, we do not need a new infrastructure or additional meteorological staff,” says Harald Kunstmann from the Institute of Meteorology and Climate Research – Atmospheric Environmental Research (IMK-IFU) of the Karlsruhe Institute of Technology (KIT). Together with scientists from the University of Augsburg, his team has now succeeded in carrying out the first area-wide rain measurement with the new method in Germany. They were able to generate rain maps with high temporal resolution from the weakening of the radio link between several thousand mobile phone masts caused by precipitation. A comparison with the measured values of the weather data provider Deutscher Wetterdienst (DWD) showed a high degree of agreement (Fig 1).

The determination of precipitation was possible due to the directional radio antennas used in mobile phone masts for transmission over long distances. “A frequency of 15 to 40 gigahertz is used here, whose wavelength corresponds to the typical size of raindrops”, explains Christian Chwala from the University of Augsburg. “The more precipitation falls, the weaker the signal with which the transmission masts exchange information”. For their investigations, the researchers measured the current attenuation of 4000 microwave links throughout the country every minute for a year. This resulted in a data set that is unique due to its resolution and size.
In addition to the classic methods of data analysis, the researchers used artificial intelligence (AI) to filter out the rain signal from the noisy measured values. “Other factors such as wind or the sun can also lead to slight attenuation of the signal. With the help of our AI, we were able to detect when an attenuation is caused by rain,” says Julius Polz, another scientist in the research group. In the meantime, the researchers have trained the AI so that they can do without calibration using traditional methods of rain measurement. This makes it suitable for use in regions without significant rainfall measurements that might be suitable for training the AI, for example more remote regions of the world.
For the general weather conditions prevailing in Germany, the method does not work equally well in all seasons. Accuracy suffers especially in winter, because hail and sleetfall cause an above-average attenuation of the signals; snow cannot be taken into account at all with this method.
Several projects are currently underway by the researchers to measure rain using radio relay systems, with the focus on Germany, in cooperation with the Deutscher Wetterdienst and the Saxony State Office for the Environment. In the course of the summer, further projects will start in the Czech Republic and in Burkina Faso, where a nationwide survey of microwave links in Africa is to be established for the first time.
More information: https://www.klima-umwelt.kit.edu
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