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How do cloud seeding drones increase rainfall?

Drones deliver cloud-seeding particles that can trigger rain or ice formation, and one field test measured more large particles, higher radar reflectivity and some rainfall.

Updated 2 hours ago5 min readVersion 2
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Covers: Covers the physical mechanism of drone-based cloud seeding (glaciogenic and hygroscopic particles, delivery into clouds) and the evidence on measured rainfall effects. Does not cover weather modification history, legal issues, or non-drone seeding methods except as comparison.

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black and gray drone flying in the sky
Photo: Dileep M

The short answer

Interpretation AI-prepared starting map

Drone-based cloud seeding aims to increase rainfall by delivering small particles into clouds that trigger precipitation processes. Two families of particles are used: glaciogenic agents that promote ice formation in supercooled clouds, and hygroscopic agents that encourage droplet growth. Drones matter mainly as a delivery platform: compared with manned aircraft they are described as cheaper, more scalable and better able to target specific areas, including through coordinated swarms. Direct field evidence is limited but real: in a Korean experiment a UAV sprayed calcium chloride, after which large cloud particles increased in number and size, radar reflectivity rose by roughly 10 dBZ over the seeded area, and 0.5 mm of rain was recorded including natural and seeded precipitation. In supercooled stratus at -8 to -5 degrees C, UAV-seeded ice crystals measured 4-10 minutes downwind grew faster than laboratory work had suggested, implying quicker precipitation initiation.1234

What this rests on5 independent sources
  • Evidence 15
  • Interpretation 4

In brief

  1. Drone seeding uses the same physics as aircraft seeding: glaciogenic particles to make ice in supercooled clouds, or hygroscopic particles to grow droplets, delivered into the cloud.21

    Interpretation
  2. Drones change the delivery economics and precision, not the mechanism: cheaper, scalable, adaptable, and able to target specific areas, including as coordinated swarms.1

    Evidence-backed
  3. In one Korean field experiment, UAV-sprayed calcium chloride was followed by more and larger large cloud particles, about 10 dBZ higher radar reflectivity, and 0.5 mm of rain that included natural precipitation.3

    Evidence-backed
  4. Ice crystals seeded into supercooled stratus at -8 to -5 degrees C grew faster than laboratory work suggested, implying quicker precipitation initiation.4

    Evidence-backed
  5. Cloud seeding is best treated as an additional water-management strategy, not a comprehensive fix for drought, and its effectiveness remains hard to evaluate.2

    Evidence-backed

At a glance

The picture in numbers

Live · updated just now

Included natural and mixed precipitation, not seeding alone

0.5 mm

0.5 mm: Rain recorded in the Korean UAV seeding experiment3
Korean experiment over the southern Korean Peninsula

10 dBZ

10 dBZ: Radar reflectivity rise after UAV seeding3

The evidence behind it

5 sources
  • Other studies and data5

When it was published

Newest from 2026

20222026
Sources on this page by kind and year
SourceKindYear
Application of Drones in Pollution Mitigation through Artificial RainfallOther studies and data2025
Cloud Seeding: The Future of Weather Modification TechnologyOther studies and data2026
The modus operandi of Cloud Seeding for Rain Enhancement: An Overview for Non-Scientific AudiencesOther studies and data2026
Progressive and Prospective Technology for Cloud Seeding Experiment by Unmanned Aerial Vehicle and Atmospheric Research Aircraft in KoreaOther studies and data2022
Repurposing weather modification for cloud research showcased by ice crystal growth.Other studies and data2024

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What it means for you

Which fits you?

Pick the situation closest to yours. Each answer says what it rests on.

If you want the short version of how the mechanism works

think of it as adding particles that let a cloud make ice or grow droplets big enough to fall, with drones as the delivery method rather than a new physical process.21

Interpretation

If you are weighing drones against manned aircraft for seeding

the reported advantages are cost, scalability, adaptability and the ability to target specific areas with coordinated swarms, while aircraft remain the established method.1

Evidence-backed

If you want a concrete measured result from drone seeding

the Korean experiment reported more and larger large cloud particles, roughly 10 dBZ higher radar reflectivity, and 0.5 mm of rain including natural precipitation.3

Evidence-backed

If you are interested in the ice-formation pathway specifically

seeding supercooled stratus at -8 to -5 degrees C produced ice crystals that grew nearly linearly from 6 to 10 minutes downwind, with growth rates varying with crystal concentration and supersaturation.4

Evidence-backed

If you are judging whether seeding can solve a drought

the evidence supports it as an additional water-resource strategy rather than a comprehensive solution, and effectiveness evaluation remains an open challenge.2

Evidence-backed

If you are reading about drone swarms cleansing urban air

treat that as a proposed application of artificial rainfall, not as a demonstrated rainfall-increase result.1

Interpretation

The full story · 3 chapters

01

The physical mechanism: particles, ice and droplets

AI summary:Seeding adds particles that either make ice in supercooled clouds or help droplets grow big enough to fall.

Evidence-backed

Evidence-backed: Cloud seeding works by introducing particles into a cloud that let water change phase or grow into precipitation-sized drops. Glaciogenic seeding uses particles that promote ice formation, which matters in clouds that are supercooled (liquid water below 0 degrees C). Hygroscopic seeding uses particles that take up water vapour and encourage droplets to grow large enough to fall. The techniques are described as requiring knowledge across cloud physics, meteorology and atmospheric chemistry, and are hard to explain in plain language, which is why overviews aimed at non-scientific audiences exist.25

Evidence-backed

Evidence-backed: A concrete look inside the ice pathway comes from seeding supercooled stratus clouds at -8 to -5 degrees C with an uncrewed aerial vehicle and measuring the resulting ice crystals 4-10 minutes downwind using in-situ and ground-based remote sensing instruments. Ice crystal growth rates varied substantially within the natural clouds, linked to differences in ice crystal number concentration and supersaturation. For the experiments at -5.2 degrees C, the ice crystal populations grew nearly linearly between 6 and 10 minutes. The authors read this as implying faster precipitation initiation than previously thought, and note that such variability is hard to reproduce in the laboratory.4

02

Why drones rather than aircraft

AI summary:Drones change the cost, scale and precision of delivering seeding particles, not the underlying physics.

Evidence-backed

Evidence-backed: The case for drones is about delivery, not about a different physical mechanism. Manned aircraft dispersing silver iodide or sodium chloride are described as effective but costly, labour-intensive and imprecise, which makes frequent or small-scale operations impractical, especially where budgets are tight. Drones are described as cost-effective, scalable and adaptable, with coordinated swarms able to target specific areas and improve the accuracy and efficiency of agent dispersion, and autonomous operation reducing the need for extensive personnel and infrastructure.1

Evidence-backed

Evidence-backed: In practice, drone seeding has been paired with monitoring aircraft. In the Korean experiment a UAV sprayed calcium chloride while a research aircraft observed the clouds, and the aircraft's instruments recorded the changes in cloud particles and radar reflectivity that followed.3

03

What has actually been measured

AI summary:A Korean UAV test saw more and larger cloud particles, about 10 dBZ higher radar reflectivity, and 0.5 mm of rain.

Evidence-backed

Evidence-backed: The Korean UAV experiment on 25 April 2019 over the southern Korean Peninsula reported, after seeding: an increase in the number concentration and average particle size of large cloud particles; weather radar reflectivity up by approximately 10 dBZ above the experimental area due to cloud and precipitation development; and rain observed after seeding, with 0.5 mm recorded including natural and mixed precipitation from the cloud seeding. A rapid increase in raindrop number and vertical reflectivity of roughly 10 dBZ was also reported. The authors present these as showing the possibility of cloud seeding using UAVs and research aircraft, with effects indicated by cloud particle counts and size, radar reflectivity and ground-based precipitation detection.3

Evidence-backed

Evidence-backed: Reviews of the wider field report that significant field experiments and operational initiatives globally show both good outcomes and ongoing challenges in evaluating effectiveness, and conclude that cloud seeding is not a comprehensive solution for drought management but a valuable additional strategy for water resource management in a changing climate.2

Evidence-backed

Evidence-backed: One proposed application goes beyond rainfall totals: using artificial rainfall to cleanse urban air of particulate matter and harmful gases, with drone swarms targeting specific urban areas. This is framed as a potential solution to air pollution rather than as a demonstrated rainfall-increase result.1

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  1. 1
    Application of Drones in Pollution Mitigation through Artificial Rainfall
    International Journal of Advance Research and Innovation (Divyanshu et al.)Published Mar 31, 2025Checked Oct 7, 2026
    “Air pollution is a critical global challenge, with urban areas experiencing hazardous levels of particulate matter and harmful gases. Artificial rainfall via cloud seeding offers a potential solution by inducing precipitation to cleanse the atmosphere. Traditional methods rely on manned aircraft to disperse agents like silver iodide or sodium chloride into clouds, stimulating rain. While effective, this approach is costly, labor-intensive, and lacks precision, making it impractical for frequent or small-scale operations, especially in budget-constrained regions. Drones present a transformative alternative for cloud seeding. Compared to aircraft, drones are cost-effective, scalable, and highly adaptable. Coordinated drone swarms can target specific urban areas, enhancing the accuracy and efficiency of agent dispersion. Their autonomous capabilities reduce the need for extensive personnel or infrastructure. By leveraging drone technology, artificial rainfall becomes a more practical, flexible, and environmentally friendly method to address air pollution”
  2. 2
    Cloud Seeding: The Future of Weather Modification Technology
    International Journal of Creative and Open Research in Engineering and Management (Khan & Kulsum)Published Aug 17, 2026Checked Oct 7, 2026
    “We examine the basic principles and methodologies of cloud seeding, including glaciogenic and hygroscopic techniques, and highlight current advancements such as enhanced atmospheric modeling, drone-based delivery systems, and novel seeding materials. This report examines the results of significant field experiments and operational initiatives globally, highlighting both good outcomes and ongoing challenges in effectiveness evaluation. The matter of governance and ethics is addressed, necessitating robust scientific evaluation, environmental safety monitoring, transparency among stakeholders, and international cooperation in weather modification efforts. We conclude that while cloud seeding is not a comprehensive solution for drought management, it serves as a valuable additional strategy for water resource management in a changing climate. Subsequent research and technological progress, together with judicious regulatory frameworks that address ethical considerations and environmental consequences, will be pivotal in realizing the complete potential of cloud seeding as a future weather manipulation technology.”
  3. 3
    Progressive and Prospective Technology for Cloud Seeding Experiment by Unmanned Aerial Vehicle and Atmospheric Research Aircraft in Korea
    Advances in Meteorology (Jung et al.)Published Jun 22, 2022Checked Oct 7, 2026
    “This study applies a novel cloud seeding method using an unmanned aerial vehicle (UAV) and a research aircraft in Korea. For this experiment, the UAV sprayed a cloud seeding material (calcium chloride), and the aircraft monitored the clouds in the southern part of the Korean Peninsula on April 25, 2019. Cloud observation equipment in the aircraft indicated an increase in the number concentration and average particle size of large cloud particles after the seeding. Weather radar reflectivity increased by approximately 10 dBZ above the experimental area due to the development of clouds and precipitation systems. Rain was observed after seeding, and 0.5 mm was recorded, including natural and mixed precipitation from the cloud seeding. In addition, it showed that the rapid increase in the number of raindrops and vertical reflectivity was approximately 10 dBZ. Therefore, these results showed the possibility of cloud seeding using UAVs and atmospheric research aircraft. The effects of cloud seeding are indicated through the increased number concentration and size of cloud particles, radar reflectivity, and ground-based precipitation detection.”
  4. 4
    Repurposing weather modification for cloud research showcased by ice crystal growth.
    PNAS nexus (Ramelli et al.)Published Sep 18, 2024Checked Oct 7, 2026
    “To bridge this gap, here we leverage weather modification, specifically glaciogenic cloud seeding, to investigate ice growth rates within natural clouds. Seeding experiments were conducted in supercooled stratus clouds (at -8 to -5∘ C) using an uncrewed aerial vehicle, and the created ice crystals were measured 4-10 min downwind by in situ and ground-based remote sensing instrumentation. We observed substantial variability in ice crystal growth rates within natural clouds, attributed to variations in ice crystal number concentrations and in the supersaturation, which is difficult to reproduce in the laboratory and which implies faster precipitation initiation than previously thought. We found that for the experiments conducted at -5.2∘ C, the ice crystal populations grew nearly linearly during the time interval from 6 to 10 min. Our results demonstrate that the targeted use of weather modification techniques can be employed for fundamental cloud research (e.g. ice growth processes, aerosol-cloud interactions), helping to advance cloud microphysics parameterizations and to improve weather forecasts and climate projections.”
  5. 5
    The modus operandi of Cloud Seeding for Rain Enhancement: An Overview for Non-Scientific Audiences
    International Journal of Innovative Science and Research Technology (IJISRT) (Fernando)Published Apr 13, 2026Checked Oct 7, 2026
    “Cloud seeding is a weather modification technique that requires mastery of a myriad of disciplines, including cloud physics, cloud studies, meteorology, atmospheric physics, and chemistry. The process of cloud seeding, as described in current literature, is complex in both its practice and terminology. It is often difficult for lay audiences, such as the public, policymakers, the media, and local stakeholders, to understand cloud seeding methods, and there is no single comprehensive work that explains them. Additionally, the governance of cloud seeding involves legal, economic, and political considerations that cross disciplines. It is important to explain its techniques in simple language to raise public awareness and support policymaking, and to involve legal, economic, and political experts outside the sciences. Therefore, the knowledge deficit model, using a qualitative approach, is used in this article to explain how cloud seeding works to larger non-scientific audiences.”

How it changed

Published 1 time since Oct 7, 2026.

  1. Version 2Oct 7, 2026Live now

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Open questions

  • How much of the rain recorded after drone seeding is genuinely added rainfall rather than natural precipitation, given that the Korean 0.5 mm figure explicitly mixes natural and seeded rain?

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  • How do rainfall effects scale with the amount, type and placement of seeding particles delivered by drones across different cloud types and temperatures?

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  • Do coordinated drone swarms actually improve targeting and dispersion accuracy in operational settings, as opposed to in concept?

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  • Can drone-induced rainfall reliably reduce urban particulate matter and harmful gases, and by how much?

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