ETH Zurich’s Researchers Utilize Meteomatics’ Weather Drones for Cloud Seeding Experiments
Technology Category
- Sensors - Environmental Sensors
- Sensors - Utility Meters
Applicable Industries
- Aerospace
- Agriculture
Applicable Functions
- Maintenance
- Product Research & Development
Use Cases
- Agricultural Drones
- Intelligent Urban Water Supply Management
Services
- Cloud Planning, Design & Implementation Services
- Training
About The Customer
The customer in this case study is the Atmospheric Physics group at the Swiss Federal Institute of Technology in Zurich (ETH Zurich), led by Professor Ulrike Lohmann. The group is involved in climate research, with a focus on studying the formation and evolution of clouds, especially cloud-aerosol interactions. One of their projects, CLOUDLAB, is dedicated to improving the understanding of cloud microphysical processes and precipitation formation to better simulate and predict precipitation events. The group conducts cloud seeding experiments in wintertime stratus clouds to study ice crystal formation and growth, using a multi-dimensional set of observations and numerical modeling.
The Challenge
Clouds play a crucial role in regulating Earth’s climate, and understanding their microphysics is key to more accurate climate projections. However, clouds and cloud-aerosol interactions are major sources of uncertainties in these projections. Questions such as how clouds will change in a warming climate and their influence on Earth’s radiation budget are yet to be fully answered. The Atmospheric Physics group at the Swiss Federal Institute of Technology in Zurich (ETH Zurich) is dedicated to studying the formation and evolution of clouds, particularly cloud-aerosol interactions. Their project, CLOUDLAB, aims to improve understanding of cloud microphysical processes and precipitation formation. However, the data collection process for cloud particles, wind, and aerosol concentration has evolved over the years, with each method presenting its own challenges. Ground-based measurements were influenced by the ground and blowing snow, while measurements on a cable car and tethered balloons offered limited vertical structure and location possibilities.
The Solution
To overcome these challenges, the CLOUDLAB team adopted Meteomatics’ Weather Drones, or Meteodrones. These drones offered more flexible measurement paths using integrated atmospheric measurement sensors and allowed the team to perform targeted cloud seeding experiments. The Meteodrones were engineered to resist very low temperatures and high wind speeds, making them ideal for flying into supercooled clouds for cloud seeding. The team could control exactly where to inject particles into the cloud and directly measure the downstream ice crystals to infer ice crystal growth rates. Meteomatics created a bespoke solution for CLOUDLAB, providing two MM-670 ML Meteodrones adapted to their specific needs. One drone was equipped with flares for cloud seeding, and the other with an optical particle counter for measuring aerosol particles in-flight. The drone software was also adjusted to make it easier for the CLOUDLAB team to configure their flight missions.
Operational Impact
Quantitative Benefit
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