This paper discusses the radiation budget and its temporal variability over Poland. The data analysis is based on the MERRA-2 reanalysis for the years 1980–2020. During the last four decades, the enhancement of climate warming has been observed, which coincides with the changes in the radiation budget. Positive and statistically significant trends at the top of the atmosphere (TOA; 0.7 ± 0.2 W/m 2 /10 year) and on the Earth’s surface (1.5 ± 0.2 W/m 2 /10 year) radiation budget (net downward flux) are mainly a consequence of changes in the amount of aerosol and greenhouse gases (GHG). According to MERRA-2, the AOD during this period decreased by − 0.19 (at 550 nm), which is 87% of the long-term (1980–2021) mean value (0.22). The reduction of AOD is due mainly to the decline of non-absorbing sulfate particles, which leads to a reduction of single-scattering albedo (SSA) by − 0.008 per decade and Angstrom exponent (AE) by − 0.06 per decade (both trends statistically significant). On the other hand, the GHG concentration increased by 4.9%/10 year and 3%/10 year, respectively, for CO 2 and CH 4 . The total column of water vapor increased (1.3%/10 year), while ozone decreased (− 1%/10 year). Despite the fact that cloud cover and cloud optical depth (COD) decreased (− 1.8%/10 year and − 1.0%/10 year), the impact of cloud on temporal variability radiation budget is small. It can be explained by nearly compensated shortwave (SW) cooling and longwave (LW) heating effects. During the analysis period, near-surface air temperature increased by 2.0 °C. The estimated increase in SW net surface radiation (7.9 W/m 2 ) leads to climate warming by 0.8 °C, which is a consequence mainly of the reduction of aerosol (0.4 °C) and cloud cover (0.2 °C). The impact of the change of SW radiation on air temperature is more pronounced during the warm season, while during the cold, air temperature change is controlled mainly by the variability of air mass advection.

Abstract. Low-cost devices for particulate matter measurements are characterised by small dimensions and a light weight. This advantage makes them ideal for UAV measurements, where those parameters are crucial. However, they also have some issues. The values of particulate matter from low-cost optical particle counters can be biased by high ambient humidity. In this article, we evaluate the low-cost Alphasense OPC-N3 optical particle counter for measuring the microphysical properties of fog. This study aimed to show that OPC-N3 not only registers aerosols or humidified aerosols but also registers fog droplets. The study was carried out on the rooftop of the Institute of Geophysics, University of Warsaw, Poland, during autumn–winter 2021. To validate the results, the data from OPC-N3 were compared with the data obtained from the reference instrument, the Oxford Lasers VisiSize D30. VisiSize D30 is a shadowgraph device able to register photos of individual droplets. Considering the effective radius of droplets, it is possible to differentiate low-visibility situations between fog conditions (which are not hazardous for people) from haze events, when highly polluted air can cause health risks to people. The compared microphysical properties were liquid water content (LWC), number concentration (Nc), effective radius reff and statistical moments of radius. The Pearson correlation coefficient between both devices for LWC was 0.92, Nc was 0.95 and reff was 0.63. Overall, these results suggest good compliance between instruments. However, the OPC-N3 has to be corrected regarding professional equipment.

We present the first estimations of single hygroscopic parameter κ for Polish urban area. The results were obtained using an inexpensive OPC-N3 optical particulate matter counter and the ASC 1000 Acoem Aerosol Conditioning System. Our studies were carried out during the winter and spring seasons, between 2020 and 2022 in Warsaw, Poland. We study the difference of κ between these two seasons, as the aerosol has different origins. The mean value of the hygroscopicity parameter for spring (April–June) was 0.13±0.13 and for winter (December-March) it was 0.04±0.04 (obtained using PM1). The mean value of the growth factor for spring (April–June) was 1.52±0.23 and for winter (December–March) it was 1.16±0.13 (obtained using PM1). The values for winter period suggest that during the cold season the aerosol mixture in the atmosphere is dominated by non-hygroscopic particles. However events of higher κ > 0.5 where occurring (mostly for big aerosol particles 1–10 μm in size), when the air mass was coming from North Atlantic carrying sea salt particles. Furthermore, based on κ we propose a method to remove the dependence of PM values on relative humidity on the OPC-N3 optical particulate counter.

In this study the OPC-N3 low-cost particle matter counter was used to determine the hygroscopic properties of the aerosol. The work shows the first results of aerosol hygroscopicity conducted in Poland. The study was performed during Spring 2020 (lock-down period) and Winter 2020/2021. The research was conducted in the Geophysics Institute at the University of Warsaw, close to the city center. Two OPC-N3 sensors were connected to the outlet from two legs of the Aerosol Conditioning System ACS1000. In one of them, low relative humidity was kept at the level of 20%, and in the other, the relative humidity was changed in the range of 50-90% in cycles. The calculation of growth factor was done by dividing the PM1 measured from wet pipe by PM1 measured in the dry channel. The hygroscopicity parameter κ was calculated from κ-Köhler theory, showing a fluctuation of the κ parameter which depends on aerosol type. The variability of κ during Spring was ranging from values of 0.075 up to 0.437 (growth factor range 1.294 – 2.625). The observed κ for Winter oscillates between 0.018 - 0.077 (growth factor range 1.057 – 1.246). The values of hygroscopicity of aerosol in winter are smaller than the ones corresponding to Spring, in line with respect to previous literature reports. The study shows possibility to use OPC-N3 for calculation of the hygroscopic properties of the aerosol, however it means that the measurements of PM done by OPC-N3 can be biased by high relative humidity.

Turbulence observed during the Physics of Stratocumulus Top (POST) research campaign is analyzed. Using in-flight measurements of dynamic and thermodynamic variables at the interface between the stratocumulus cloud top and free troposphere, the cloud top region is classified into sublayers, and the thicknesses of these sublayers are estimated. The data are used to calculate turbulence characteristics, including the bulk Richardson number, mean-square velocity fluctuations, turbulence kinetic energy (TKE), TKE dissipation rate, and Corrsin, Ozmidov and Kolmogorov scales. A comparison of these properties among different sublayers indicates that the entrainment interfacial layer consists of two significantly different sublayers: the turbulent inversion sublayer (TISL) and the moist, yet hydrostatically stable, cloud top mixing sublayer (CTMSL). Both sublayers are marginally turbulent, i.e., the bulk Richardson number across the layers is critical. This means that turbulence is produced by shear and damped by buoyancy such that the sublayer thicknesses adapt to temperature and wind variations across them. Turbulence in both sublayers is anisotropic, with Corrsin and Ozmidov scales as small as ∼ 0.3 and ∼ 3 m in the TISL and CTMSL, respectively. These values are ∼ 60 and ∼ 15 times smaller than typical layer depths, indicating flattened large eddies and suggesting no direct mixing of cloud top and free-tropospheric air. Also, small scales of turbulence are different in sublayers as indicated by the corresponding values of Kolmogorov scales and buoyant and shear Reynolds numbers.

High spatial resolution measurements of temperature and liquid water content, accompanied by moderate-resolution measurements of humidity and turbulence, collected during the Physics of Stratocumulus Top experiment are analyzed. Two thermodynamically, meteorologically and even optically different cases are investigated. An algorithmic division of the cloud-top region into layers is proposed. Analysis of dynamic stability across these layers leads to the conclusion that the inversion capping the cloud and the cloud-top region is turbulent due to the wind shear, which is strong enough to overcome the high static stability of the inversion. The thickness of this mixing layer adapts to wind and temperature jumps such that the gradient Richardson number stays close to its critical value. Turbulent mixing governs transport across the inversion, but the consequences of this mixing depend on the thermodynamic properties of cloud top and free troposphere. The effects of buoyancy sorting of the mixed parcels in the cloud-top region are different in conditions that permit or prevent cloud-top entrainment instability. Removal of negatively buoyant air from the cloud top is observed in the first case, while buildup of the diluted cloud-top layer is observed in the second one.