Abstract: Ecological monitoring is an important part of environmental protection. To monitor the movement and abundance of animals in the airspace, an Aerial Ecological Monitoring System (AEMS) is developed by CMA Meteorological Observation Center for China's next-generation weather radar (CINRAD) network. Characteristics of weather radar clear air echo data and airborne biological scattering data are studied to identify biological echoes through fuzzy logic algorithm, and the system can monitor real-time ecological activities of insects such as biological density, migration path and space-time distribution.Weather Radar Airborne Ecological Monitoring System has been put into trial operation since May 2022. During the real-time monitoring period, it's found that the insect activity shows obvious spatial and temporal distribution characteristics. From August to September, pests are of large quantity and wide range, indicating urgent need of insect disaster prevention and control. In May, June, September, and October, insect activity gradually increases from 2000 BT every day, reaches its peak from 2200 BT to 2300 BT, gradually decreases thereafter, and disappears mostly by 0600 BT. In July and August, insect activity gradually increases from 2000 BT every day, with a peak from 2100 BT to 2200 BT. Insect activity begins during the daytime, increases at 0600 BT, becomes more frequent at 1300 BT, and gradually decreases thereafter. From May to July, there is a significant shift from south to north (i.e., northward migration process), and in late August, it quickly changes into a to southward migration. The southward migration process of insects is larger and more numerous than the northward migration process. It's verified that the system can effectively monitor real-time aerial ecology, providing technology and data support for precise pest control.However, characteristics of pests need further research and clear distribution of pests is an urgent need. Therefore, in-depth research will be carried out on aerial ecological classification technology, combined with other direct observation means such as real-time monitoring by drones to explore the relationship between radar detection and different pests, and improve the ability to identify different kinds of insects.