Within this timeframe, the CLOUDLAB project has achieved several key milestones in its efforts to advance the understanding of cloud physics. The main work performed and results achieved so far are as follows:
1. Demonstrated that a multi-rotor Uncrewed Aerial Vehicle (UAV) can be used for targeted glaciogenic cloud seeding, which opens up new possibilities for cloud seeding research and applications in weather modification and climate intervention.
2. Integration of optical particle counters (OPCs) on the measurement UAV and HoloBalloon Tethered Balloon System (TBS) to provide accurate aerosol measurements to detect the seeding plume.
3. Set-up of the CLOUDLAB main site including a large set of ground-based remote sensing instrumentation (e.g. cloud radars, microwave radiometers), aerosol instrumentation and the TBS HoloBalloon. Established different UAV launching sites in the surrounding of the main site and obtained flight permissions for the UAVs, including the horizontal seeding pattern, which has ensured smooth operations and efficient execution of the experiments.
4. Developed a quick-look feature for data review after each scan and developed a webpage to display data from all remote sensing sources. This information is essential for adapting experimental parameters to environmental conditions, particularly the wind direction.
5. Conducted 42 out-of-cloud seeding experiments to characterize the dispersion and particle size distribution of the seeding plume, utilizing the measurement UAV equipped with a OPC. This has provided valuable data on the dispersion of seeding plumes and their interactions with the environment.
6. Conducted 74 successful in-cloud seeding experiments at varying temperatures, growth times, and INP concentrations, providing valuable insights into cloud microphysics (e.g. ice crystal growth rates, Wegener-Bergeron-Findeisen process) and the conditions necessary for effective cloud seeding.
7. Analysis of remote sensing and in-situ measurements to quantify the influence of the seeding on the number and size of aerosol particles, cloud droplets and ice crystals.
8. Derive ice crystal growth rate from seeding at different locations in the cloud.
9. Implemented seeding particle tracers in the ICON-LES model, which enables the simulation of the conducted seeding experiments. The large-eddy simulations of seeding experiments were able to reproduce the observed ice crystal number concentrations most of the time, but not the observed fast reductions in cloud droplet number concentrations.
10. An overview of CLOUDLAB project with some first results was published in BAMS and the development of two UAVs was published in AMT.