The Evolution of an AgI Cloud‐Seeding Track in Central China as Seen by a Combination of Radar, Satellite, and Disdrometer Observations

Jin, Wang; Yue, Zhiguo; Zhang, Lei; Zhu, Yannian; Dai, Jianlong; Yu, Xiangyao; Li, Jinhui

doi:10.1029/2020jd033914

Cited by 11 publications

(5 citation statements)

References 35 publications

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“…Rosenfeld et al [7,8] analyzed an aircraft artificial precipitation enhancement operation on 14 March 2000 in Shaanxi, China, and found that cloud seeding caused the formation of a cloud track from the NOAA satellite cloud-top observation maps. Analysis of an aircraft artificial precipitation enhancement operation in Shanxi on 15 December 2017 by Wang et al [9] also identified cloud tracks formed at cloud top portions after cloud seeding from the FY-3C polar-orbiting and TERRA satellites. Until now, all the "cloud tracks" discovered have been based on polar-orbiting satellites, which are not capable of monitoring the temporal evolution of the cloud tracks caused by cloud seeding.…”

Section: Introductionmentioning

confidence: 99%

FY-4A Measurement of Cloud-Seeding Effect and Validation of a Catalyst T&D Algorithm

Yan,

Zhou,

et al. 2024

Atmosphere

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The transport and dispersion (T&D) of catalyst particles seeded by weather modification aircraft is crucial for assessing their weather modification effects. This study investigates the capabilities of the Chinese geostationary weather satellite FY-4A for identifying the physical response of cloud seeding with AgI-based catalysts and continuously monitoring its evolution for a weather event that occurred on 15 December 2019 in Henan Province, China. Satellite measurements are also used to verify an operational catalyst T&D algorithm. The results show that FY-4A exhibits a remarkable capability of identifying the cloud-seeding tracks and continuously tracing their evolution for a period of over 3 h. About 60 min after the cloud seeding, the cloud crystallization track became clear in the FY-4A tri-channel composite cloud image and lasted for about 218 min. During this time period, the cloud track moved with the cloud system about 153 km downstream (northeast of the operation area). An operational catalyst T&D model was run to simulate the cloud track, and the outputs were extensively compared with the satellite observations. It was found that the forecast cloud track closely agreed with the satellite observations in terms of the track widths, morphology, and movement. Finally, the FY-4A measurements show that there were significant differences in the microphysical properties across the cloud track. The effective cloud radius inside the cloud track was up to 15 μm larger than that of the surrounding clouds; the cloud optical thickness was about 30 μm smaller; and the cloud-top heights inside the cloud track were up to 1 km lower. These features indicate that the cloud-seeding catalysts led to the development of ice-phase processes within the supercooled cloud, with the formation of large ice particles and some precipitation sedimentation.

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Section: Introductionmentioning

confidence: 99%

FY-4A Measurement of Cloud-Seeding Effect and Validation of a Catalyst T&D Algorithm

Yan,

Zhou,

et al. 2024

Atmosphere

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“…However, no single cloud-seeding strategy can be applied worldwide because environmental conditions differ between countries. Two main strategies of cloud seeding are frequently adopted: ice cloud seeding (Seto et al, 2011;Geresdi et al, 2017;Tessendorf et al, 2019;Wang et al, 2021) and warm cloud seeding (Jung et al, 2015;Wang et al, 2019;Tonttila et al, 2021;Tessendorf et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Evaluation of hygroscopic cloud seeding in warm rain process by a hybrid microphysics scheme on WRF model: a real case study

Lin

Chung

Wang

et al. 2023

Preprint

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Abstract. To evaluate the hygroscopic cloud seeding in reality, this study develops a hybrid microphysics scheme on WRF model, WDM6–NCU, which involves 43 bins of seeded cloud condensation nuclei (CCN) in the WDM6 bulk method scheme. This scheme can describe the size distribution of seeded CCNs and explain the process of the CCN imbedding, cloud and raindrop formation in detail. Furthermore, based on the observational CCN size distribution applied in the modelling, a series of tests on cloud seeding was conducted during the seeding periods of 21–22 October, 2020 with stratocumulus clouds. The model simulation results reveal that seeding at in-cloud regions with an appropriate CCN size distribution can yield greater rainfall and that spreading the seeding agents over an area of 40–60 km2 is the most efficient strategy to create a sufficient precipitation rate. With regard to the microphysical processes, the main process that causes the enhancement of precipitation is the strengthening of the accretion process of raindrops. In addition, hygroscopic particles larger than 0.4 μm primarily contribute to cloud-seeding effects. The study results could be used as references for model development and warm cloud seeding operations.

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“…At present, ground-based and aircraft observations are widely used around the world to obtain microphysical characteristics of clouds to study the possible evolutionary trends of clouds, which are widely used in weather modification operations. Recent attempts to evaluate cloud seeding include coherent Doppler wind lidar, satellite, weather radar, and disdrometer [8,9]. Yang investigates the response of mixed-phase cloud microphysical properties to cloud seeding near the cloud top with an aircraft observation during the cloudseeding period [10].…”

Section: Introductionmentioning

confidence: 99%

Analysis of Precipitation Process and Operational Precipitation Enhancement in Panxi Region Based on Cloud Parameters Retrievals from China’s Next−Generation Geostationary Meteorological Satellite FY−4A

2023

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Geostationary meteorological satellite data with high spatial and temporal resolution can be used to retrieve cloud physical parameters, which has significant advantages in tracking cloud evolution and development. Based on satellite multispectral RGB composite image and cloud physical analysis methods, we quantitatively analyze the evolution characteristics of cloud parameters in the pre-, mid- and post-artificially influenced weather process, explore the application potential benefits of satellite data in monitoring the operating conditions of the artificially influenced weather in the Panxi region, and verify the feasibility analysis of the evaluation of their effects. In this study, cloud parameters such as cloud particle effective radius (Re), cloud liquid water path (LWP), cloud ice water path (IWP), and cloud top height and temperature (CTH and CTT) are retrieved using FY−4A satellite data. For the Panxi region, the evolution characteristics of typical cloud parameters in the affected area before and after two aircraft artificial operational precipitation enhancements are analyzed. The results show that the satellite retrieval of cloud characteristic parameters in the Panxi region has good application value, which can be used to guide the artificial Operational Precipitation Enhancement. In this precipitation process, there are solid particles in the upper layer cloud and supercooled water in the lower layer cloud. After the cold cloud catalysis, the cloud top height, liquid water and ice water content, particle effective radius and ground precipitation in the operational area increased, and the cloud top temperature decreased. Thus, it effectively alleviated the drought in the Panxi region. The satellite retrieval of cloud characteristic parameters in the Panxi region has a good application value, which can provide a basis and guidance for future weather modification operations in the Panxi region.

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The Evolution of an AgI Cloud‐Seeding Track in Central China as Seen by a Combination of Radar, Satellite, and Disdrometer Observations

Cited by 11 publications

References 35 publications

FY-4A Measurement of Cloud-Seeding Effect and Validation of a Catalyst T&D Algorithm

FY-4A Measurement of Cloud-Seeding Effect and Validation of a Catalyst T&D Algorithm

Evaluation of hygroscopic cloud seeding in warm rain process by a hybrid microphysics scheme on WRF model: a real case study

Analysis of Precipitation Process and Operational Precipitation Enhancement in Panxi Region Based on Cloud Parameters Retrievals from China’s Next−Generation Geostationary Meteorological Satellite FY−4A

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