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Clouds and blue sky.

Remote sensing observations provide novel information on atmospheric aerosols

Atmospheric aerosols are vastly heterogeneous in size, type and concentrations, and they also vary in both time and space. Currently, their role in cloud formation compiles one of the greatest sources of uncertainty in radiative forcing calculations and projections of future climate. Remote sensing techniques provide a powerful tool for the observation of aerosol particles and clouds. Lidars along with cloud radars are the two fundamental instruments in atmospheric research for the profiling of the atmosphere. To link aerosol properties and cloud formation, a lidar-radar synergy was used in this thesis. Moreover, certain aerosol types are not well defined and frequently are misclassified in aerosol classification algorithms. In this thesis we have addressed the optical properties of pollen and Arabian dust; two aerosol types which affect both climate and human health.

Low‑level mixed‑phase clouds are very common in the Arctic. Here, we correlated the amount of aerosols with the occurrence of the cloud phase and we found that mixed-phase clouds were more abundant under the higher aerosol loading, supporting the extended lifetime of these clouds in the Arctic. Moreover, depending on the aerosol load, the temperature at which a cloud completely glaciated varied by up to 6–10 °C, regardless the type of the aerosol. In comparison, the different aerosol types resulted to less than 4 °C discrepancies in the glaciation temperature. Thus, moderate association was found with varying the aerosol type as opposed to aerosol load.

The properties of pollen and Arabian dust are currently poorly known and therefore their effect on clouds and their health/allergy potential is not accurately represented in models. We argue that different pollen types can be classified with a lidar setup. Furthermore, we found that the properties of Arabian dust differ from dust particles originating from the Saharan region, and these differences should be taken into account in lidar-related applications and models.

The doctoral dissertation of MSc Maria Filioglou, entitled Atmospheric profiling using the lidar technique will be examined at the Faculty of Science and Forestry 17.6. (online). The opponent in the public examination will be Manager, PhD Franco Marenco, Met Office, Satellite Imagery Applications Group (SIAG), UK, and the custos will be Head of Group, Docent Mika Komppula, Finnish Meteorological InstituteThe public examination will be held in English.

Link to the event

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Link to the dissertation