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WANG Tianyi, CHEN Xu, CHEN Yingying, et al. 2025. Comparative Analysis of Cloud Structure Detection Capabilities between Ground-based Specialized Equipment and Satellite Observations for Artificial Weather Modification in Xiangyang [J]. Climatic and Environmental Research (in Chinese), 30 (6): 1−8. DOI: 10.3878/j.issn.1006-9585.2025.25085
Citation: WANG Tianyi, CHEN Xu, CHEN Yingying, et al. 2025. Comparative Analysis of Cloud Structure Detection Capabilities between Ground-based Specialized Equipment and Satellite Observations for Artificial Weather Modification in Xiangyang [J]. Climatic and Environmental Research (in Chinese), 30 (6): 1−8. DOI: 10.3878/j.issn.1006-9585.2025.25085

Comparative Analysis of Cloud Structure Detection Capabilities between Ground-based Specialized Equipment and Satellite Observations for Artificial Weather Modification in Xiangyang

  • Based on the observational data from an air-ground joint test in the Danjiangkou Reservoir catchment area on May 10, 2024, the detection performance of ground-based specialized instruments and satellite platform for cloud base height and cloud top height in the Xiangyang region was compared: a Ka-band cloud radar, a laser ceilometer, and the FY-4B satellite. The results demonstrate that the ceilometer provides higher accuracy cloud base height measurements for single-layer and mid-to-low clouds. In contrast, the Ka-band cloud radar penetrates multilayer and high clouds more effectively. However, it is susceptible to precipitation interference, which may lead to underestimation of cloud base height. The FY-4B satellite tends to overestimate cloud top height during non-precipitation periods by misinterpreting thermal infrared radiation. Conversely, cloud top height may be underestimated during precipitation due to interference from liquid water and ice crystal signals. Severe signal attenuation during heavy precipitation can cause the radar to significantly underestimate cloud values. Given the inherent limitations of individual observation methods in complex weather, integrating multisource observations is essential to more accurately characterize cloud macrophysical characteristics.
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