SHENZHEN, July 27 (Xinhua) -- Meteorologists have conducted a drone swarm observation experiment in south China's Guangdong Province during the landfall of Typhoon Noul, seeking to improve weather forecasts for typhoon conditions, according to the China Meteorological Administration (CMA).
The exercise involved continuous monitoring throughout the entire landfall process of this year's 12th typhoon early Sunday along the coast of Guangdong. It brought gales and heavy rain to many parts of the province.
Starting July 24, a team from the Chinese Academy of Meteorological Sciences under the CMA, in collaboration with the Shenzhen National Climate Observatory, carried out the observations on the Dapeng Peninsula in Shenzhen. The experiment obtained vertical profile data on key meteorological parameters, including low-altitude temperature, humidity, wind field, and turbulence before, during, and after the typhoon's passage.
According to Guo Jianping, the leader of the experiment, China has established a comprehensive three-dimensional meteorological observation network comprising Fengyun meteorological satellites, weather radars, ground-based remote sensing vertical observation systems, and surface weather stations.
However, challenges remain in observing the thermodynamic structure of the lower atmosphere beneath coastal typhoon clouds, due to factors such as cloud cover and large blind zones in low-altitude detection, Guo said.
The drones were equipped with devices for wind, temperature and humidity sensing, turbulence monitoring, and all-sky imaging, allowing for comparative evaluation of the observation stability and detection accuracy of different meteorological devices under typhoon conditions.
In addition, a multi-model drone networked observation array was established to achieve synchronized collaborative detection at multiple altitudes and horizontal points, filling the observational gap in low-altitude meteorology beneath coastal typhoon cloud layers.
The observation adopted an hourly high-frequency and three-dimensional detection mode, tracking the entire typhoon passage. This approach effectively addresses shortcomings in coastal low-altitude observation and provides critical real-time data to support more accurate assessments of typhoon intensity and forecasts of wind and rainfall impact zones, Guo said.
The observation network also collected operational parameters, including drone flight attitudes, trajectory deviations and battery power consumption, systematically exploring the conditions for safe drone flight under extreme meteorological conditions.
"Besides enabling the drone swarm to precisely detect the typhoon boundary layer structure, we also need to observe how weather affects the flight attitudes of different drone models," Guo said.
At present, low-altitude economy sectors such as low-altitude logistics, aerial inspection, and emergency rescue are rapidly expanding in the country, with growing demand for accurate low-altitude meteorological services.
According to Guo, the experiment helps meteorologists reveal how storm environments affect the flight attitudes, trajectories, and energy consumption of different drone models, and quantify the meteorological boundary conditions for safe low-altitude flight in extreme weather. It also provides core data for building a three-dimensional observation system for passing typhoons, advancing typhoon monitoring and forecasting technologies, and ensuring low-altitude flight safety. ■
