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Using clouds as a natural laboratory to improve precipitation forecast skills

Project description

Using drones for cloud seeding to understand ice and precipitation formation in clouds

Despite attempts to use chemicals to modify weather by seeding clouds in past decades, scientists still lack a deeper understanding of the fundamental processes in clouds that lead to precipitation. To fill this knowledge gap, the EU-funded CLOUDLAB project will apply a pioneering methodology of using drones for cloud seeding (injection of different ice-nucleating particle concentrations) to investigate microphysical changes related to ice formation and cloud evolution. It will be part of a multidimensional approach of targeted cloud seeding (including ground-based remote sensing and a tethered balloon system), focusing on wintertime stratus clouds in Switzerland, in conditions allowing the repetition of field experiments under comparable conditions. Expected results include an improved precipitation forecast and knowledge transfer to climate intervention methods.


Clouds have been seeded since the 1940s. Aimed at inducing weather modification, the method uses chemicals to alter the microphysical processes within a cloud to enhance precipitation, suppress hail, or dissipate fog. While the concept of cloud seeding is not new, detailed knowledge about the underlying microphysical processes in clouds is still sparse. CLOUDLAB will tackle this gap by injecting different ice nucleating particle concentrations into supercooled stratus clouds to investigate related microphysical changes, including fundamental aspects of ice formation and growth. To achieve this, the project combines a multi-dimensional approach of targeted cloud seeding with a focus on wintertime stratus clouds in Switzerland, the least dynamic cloud type which best mimics laboratory conditions and allows repetition of field experiments under similar initial conditions. We will inject ice nucleating particles from a seeding drone and perform measurements with ground-based remote sensing, a tethered balloon system equipped with a holographic imager and a measurement drone. Combined with measured meteorological parameters, we aim to understand the impact of cloud inhomogeneities for precipitation initiation via the ice phase. The analysis of our cloud seeding events will be used to validate and improve cloud microphysics schemes in the Swiss weather forecast model in large eddy simulations mode. By coarsening the horizontal resolution to weather forecast mode, the simulations will be extended to include all cloud types where the same microphysical processes are at work to improve precipitation forecast skills in Switzerland. Hence, CLOUDLAB will further the understanding of ice microphysics and precipitation initiation which will also improve climate projections. In addition to pioneering of a new methodology of using drones for cloud seeding, our results will be of particular interest to the weather modification and climate intervention communities.


Net EU contribution
€ 3 499 926,00
Raemistrasse 101
8092 Zuerich

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Schweiz/Suisse/Svizzera Zürich Zürich
Activity type
Higher or Secondary Education Establishments
Other funding
€ 0,00

Beneficiaries (1)