Using AI Modeling to Predict the Impact of Cloud Seeding on Amount of Rainfall and How that Affects the Temperature in Different Regions
Year: 2025
Type: article
Abstract: Water is one of the most essential resources on Earth, yet many regions face severe water scarcity due to growing populations, in-creased land use, and climate change. To address this challenge, we employed cloud seeding as a promising technique for augment-ing water supplies. While prior research has primarily focused on increasing precipitation, this study introduces a novel angle byexamining how cloud seeding-induced rainfall may also influence regional temperature regulation over time. This dual-purpose in-vestigation is particularly relevant in arid regions like the Middle East, where water scarcity and extreme heat coexist. Using historical datasets and AI-based modeling, including lin-ear regression and neural networks, we analyzed the relationship between rainfall and temperature across different regions. Results revealed a consistent negative correlation between rainfall and tem-perature, suggesting that cloud seeding may have cooling effects in addition to boosting precipitation. This study presents early ev-idence that weather modification could play a role in mitigating long-term climate stress, offering a new perspective on the benefitsof cloud seeding.
Authors: Carvalho, Rex, Mandal, Ihita
Language: English
Subfield: Global and Planetary Change
Field: Environmental Science
Domain: Physical Sciences
SDG: Climate action
Open Access status: green
OpenAlex ID: W6912172489
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