We present the design and validation of an unmanned aerial vehicle (UAV) equipped with a bespoke optical particle counter (OPC). This is used to monitor atmospheric particles, which have significant effects on our weather and climate. These effects are hard to characterise properly, partly because they occur in regions that are not commonly accessible to traditional instrumentation. Our new platform gives us the capability to access these regions.

We intercompared three cloud spectrometers ground setups in conditions with frequently occurring supercooled clouds. The measurements were conducted during the Pallas Cloud Experiment (PaCE) in 2013, in the Finnish sub-Arctic region at Sammaltunturi station. The main meteorological parameters influencing the spectrometers' performance was the wind direction. Final recommendations and our view on the main limitations of each spectrometer ground setup are presented.

Due to the complex spatiotemporal and physical properties of clouds, their quantitative depictions in different atmospheric reanalysis datasets are still highly uncertain. A radiance-based evaluation approach is developed to evaluate the quality of cloud properties by directly comparing them with satellite radiance observations. ERA5 and CRA are found to have great capability in representing the cloudy atmosphere over East Asia, and MERRA-2 tends to slightly overestimate clouds over the region.

Measurements of ice cloud particle populations are needed to improve climate and weather prediction. This paper makes a comparison between ice cloud particle populations measured using two different airborne cloud particle probes. It is concluded that measurements of particle populations from older probes are similar to those from newer probes, except in total numbers of particles counted. Therefore, more airborne studies of ice clouds need to be made using newer cloud particle probes.