Influence of air mass origin on microphysical properties of low-level clouds in a subarctic environment .

: In this work, an analysis was performed to investigate how different long-range transport air masses can affect the occurrence and the microphysical properties of low-level clouds in a clean subarctic environment. The cloud measurements comprised in-situ and ground-based and were 15 conducted during eight Pallas Cloud Experiments (PaCE) held in the autumn between 2004 and 2019. Each PaCE was carried out at the Pallas Atmosphere – Ecosystem Supersite, located in the Finnish subarctic region. Two cloud spectrometer ground setups were installed on the roof of the station to measure cloud microphysical properties: the Cloud, Aerosol and Precipitation Spectrometer probe (CAPS) and the Forward Scattering Spectrometer Probe (FSSP). Air mass histories were analyzed using 20 the Lagrangian particle dispersion model FLEXPART in order to investigate the differences between five distinct source regions (Arctic, Eastern, Southern, Western and Local). The results showed that there was a connection between the microphysical properties of the clouds we sampled during PaCEs and the air mass source region. The occurrence of clouds at the measuring station was mainly connected with air masses coming from the continental regions. Higher values of cloud droplet number 25 concentrations ( N c ) were related to air masses coming from the Southern and Eastern regions (continental), whereas the lowest We in cloud measurements two ground-based spectrometers obtain the cloud droplet size distribution. The FLEXible PARTicle (Flexpart) dispersion model was used to analyze the air mass history. A description of the measurement site and the instrumentation, as it was installed, of the we how the backward trajectories were calculated. the optimal threshold of travelling air masses within a region to represent an air mass type is and a detailed analysis is made to find out to what the air mass type influences the microphysical properties of the low-level clouds. we summarize our main conclusions. Emeis et al., 2004), except in 2019 when it was replaced by a model CL31, Vaisala Oyj. The meteorological variables were monitored by an automatic weather station (model Milos 500, Vaisala Oyj). All the weather sensors that were used in this work were described in Hatakka et al. (2003). The temperature was measured at 570 m ASL by a PT100 sensor, the horizontal visibility by a weather sensor (model FDP12P, Vaisala Oyj), the relative humidity by a HUMICAP (Vaisala Oyj), the 155 barometric pressure by a BAROCAP (Vaisala Oyj) sensors, the wind direction by a heated wind vane and the wind speed by a heated cup (Vaisala Oyj).