Securing Water Resources through Aircraft-Based Cloud Seeding
This study reviews the principles and recent advancements in cloud seeding technology, with a focus on aircraft-based experiments for weather modification. Cloud seeding involves the artificial introduction of condensation or ice nuclei into clouds to induce or enhance rainfall, providing a valuable approach for regions facing water scarcity or seasonal drought. Beginning with the historical development of cloud seeding, this study examines key experiments conducted both domestically and internationally. Key findings indicate that, under suitable atmospheric conditions, seeding agents such as silver iodide (AgI) and calcium chloride (NaCl) effectively modify cloud characteristics, resulting in significant increases in droplet size and overall precipitation. Results from these aircraft-based experiments were validated using high-resolution radar and aerosol-cloud measurement tools, demonstrating a consistent increase in precipitation following seeding. The study also underscores the importance of modeling and observational techniques to quantify seeding effects and accurately assess outcomes, which are essential for distinguishing induced rainfall from natural precipitation. The insights gained from this research highlight the practical potential of cloud seeding and its contribution to climate adaptation and sustainable water management. By proposing strategies to enhance experimental accuracy and verify seeding effects, this study provides foundational data critical for the broader application and optimization of cloud seeding technology. Furthermore, it emphasizes the importance of refining cloud seeding practices, suggesting future directions for integrating numerical models and developing precise assessment techniques.
Authors
- Eunsil Jung (ORCID: https://orcid.org/0000-0003-0970-2730)
Publication Details
- Journal
- Journal of Korean Society of Water Science and Technology
- Published
- 2024-12-31
- DOI
- https://doi.org/10.17640/kswst.2024.32.6.351
- Primary Topic
- Air Traffic Management and Optimization
- Type
- article
- Field-Weighted Citation Impact
- 0.00