Developing world-leading multi-beam X-band and C-band dual-polarization phased array radars, conducting collaborative observation tests of multiple equipment types, overcoming the challenges of insufficient spatiotemporal resolution in tornado monitoring, and achieving intelligent identification and rapid warning of tornadoes are the "hard bones" that the Guangdong Provincial Meteorological Bureau's meteorological detection innovation team must tackle now and in the next few years. In 2020, under the leadership of Ao Zhenlang, the chief technical officer of the Guangdong Provincial Meteorological Bureau, the Provincial Meteorological Detection Data Center, in collaboration with Guangdong Naruida Radar Technology Co., Ltd. 、 and the Chinese Academy of Meteorological Sciences formed a project team to conduct scientific research under the Guangdong Provincial Key R&D Program, aiming to develop multi-beam dual-polarization phased array radars and apply them to tornado detection operations, focusing on solving "bottleneck" technical problems in tornado detection equipment, observation methods, intelligent identification, and rapid warning.   Facing the challenges, striving for international advanced levels is the belief and determination of the team members, but they understand that the various challenges in radar development need to be tackled one by one.

To date, the Guangdong Provincial new generation S-band weather radar network observation (12 sets have been built) covers a number of key technological innovations, including the development of network radar synchronous control system software, hardware transformation, and engineering construction. The Guangdong-Hong Kong-Macao Greater Bay Area X-band dual-polarization phased array weather radar monitoring network (22 sets have been built) completed in the past two years has also gradually achieved significant results in the monitoring and early warning of small- and medium-scale strong convective weather, and will "cooperate" with the new generation S-band weather radar network observation to weave a network to capture tornadoes, typhoons, rainstorms, and other strong convective weather. Currently, the Guangdong-Hong Kong-Macao Greater Bay Area X-band dual-polarization phased array weather radar monitoring network has been fully networked and applied, playing an important role in disaster weather monitoring and early warning.

"The existing S-band new generation weather radar is designed to be more suitable for large-scale detection and early warning. Due to the influence of the earth's curvature, there is a blind area in the low-altitude area, especially in the airspace below 1000 meters. The X-band dual-polarization phased array weather radar has ultra-high spatiotemporal resolution detection capabilities, which can effectively compensate for the shortcomings of low-altitude detection, effectively covering the low-altitude areas where small- and medium-scale strong convection frequently occurs, ensuring that rapidly changing hazardous weather is not missed, and also helping to make quantitative precipitation estimation more accurate and reliable," said Ao Zhenlang.

Based on the complementary advantages of the S-band new generation weather radar network and the X-band dual-polarization phased array weather radar network, the project team broke through tradition and launched an "offensive" against tornado detection operations.
Application scenarios of Naruida radar-X-band dual-polarization phased array weather radar products in the "Guangdong-Hong Kong-Macao Greater Bay Area" refined weather observation network

  The "Multi-beam dual-polarization phased array radar development and tornado detection business application" project utilizes the advantages of X-band in particle sensitivity and measurement accuracy and the balanced performance of C-band in detection distance, rain attenuation, and phase sensitivity to design a "4+1+1+N" network layout mode, consisting of X-band refined radar, C-band high-speed search radar, and auxiliary monitoring equipment; designs a collaborative adaptive observation strategy and synchronous observation algorithm to achieve precise synchronization of echo in the radar detection cross-area, forming a three-dimensional grid field to solve the problems of ultra-fine spatiotemporal resolution, seamlessness, full coverage, and intelligent identification in tornado monitoring and early warning detection. In addition, the project team has also developed two types of tornado-specific radars, achieving a double breakthrough in ultra-fine time and space detection capabilities, which is the team's proposed "hunting dog detection method" - establishing a collaborative observation network composed of multiple devices to jointly monitor tornadoes; using multi-source observation data fusion technology to study the macro and micro characteristics of tornadoes, extracting characteristic parameters, establishing a strong convective identification model, and using fuzzy logic to achieve intelligent identification of tornadoes based on this model; proposing a new concept of tornado grading early warning based on intelligent identification results, designing an all-media direct-through real-time early warning release system based on monitoring results; using numerical simulation technology to reveal the fine three-dimensional structure of tornadoes and study and analyze the formation mechanism of tornadogenic supercells.

With the rapid development of the economy and society, the economic losses and casualties caused by strong convective weather such as tornadoes, which are characterized by sudden onset, have gradually increased, and the pressure to cope with sudden hazardous weather is increasing day by day, making disaster prevention and mitigation work arduous. Collaborative network observation and tornado detection business research will greatly improve the early warning timeliness of strong convective systems such as tornadoes and disastrous winds in specific areas, providing real-time monitoring information for government emergency command, enabling them to effectively organize the defense of such meteorological disasters, timely evacuate people in affected areas, and thus minimize the loss of life and property.

随着经济社会的快速发展，突发性强的龙卷风等灾害性天气造成的经济损失和人员伤亡逐渐增多，应对灾害性突发天气的压力与日俱增，防灾减灾工作任务艰巨。协同组网观测及龙卷风探测业务研究，将大大提高特定区域的龙卷风和致灾大风等强对流系统的预警时效，为政府部门应急指挥提供实时监测信息，促使其有效组织此类气象灾害的防御，及时疏散受灾区域人员，从而最大限度减少人民生命财产损失。