ALBERT

Description: The heterogeneous freezing temperatures of supercooled drops were measured by using an acoustic levitator. This technique allows to freely suspending single drops in air without electrical charges thereby avoiding any electrical influences which may affect the freezing process. Heterogeneous nucleation caused by several mineral dust particles (montmorillonite, two types of illite) was investigated in the immersion mode. Drops of 1 unit{mm} in radius were monitored by a~video camera during cooling down to −28 °C to simulate the tropospheric temperature range. The surface temperature of the drops was remotely determined with an infra-red thermometer so that the onset of freezing was indicated. For comparisons, measurements with one particle type were additionally performed in the Mainz vertical wind tunnel with drops of 340 unit{{mu}m} radius freely suspended. The data were interpreted regarding the particle surfaces immersed in the drops. Immersion freezing was observed in a~temperature range between −13 and −26 °C in dependence of particle type and surface area per drop. The results were evaluated by applying two descriptions of heterogeneous freezing, the stochastic and the singular model.

Description: The heterogeneous freezing temperatures of supercooled drops were measured using an acoustic levitator. This technique allows one to freely suspend single drops in the air without any wall contact. Heterogeneous nucleation by two types of illite (illite IMt1 and illite NX) and a montmorillonite sample was investigated in the immersion mode. Drops of 1 mm in radius were monitored by a video camera while cooled down to −28 °C to simulate freezing within the tropospheric temperature range. The surface temperature of the drops was contact-free, determined with an infrared thermometer; the onset of freezing was indicated by a sudden increase of the drop surface temperature. For comparison, measurements with one particle type (illite NX) were additionally performed in the Mainz vertical wind tunnel with drops of 340 μm radius freely suspended. Immersion freezing was observed in a temperature range between −13 and −26 °C as a function of particle type and particle surface area immersed in the drops. Isothermal experiments in the wind tunnel indicated that after the cooling stage freezing still proceeds, at least during the investigated time period of 30 s. The results were evaluated by applying two descriptions of heterogeneous freezing, the stochastic and the singular model. Although the wind tunnel results do not support the time-independence of the freezing process both models are applicable for comparing the results from the two experimental techniques.

Description: The interaction of aerosol particles with radiation, clouds, and precipitation is a critical issue in understanding the atmosphere in the mid- and high latitudes of the southern hemisphere. The high abundance of supercooled liquid water in clouds above the Southern Ocean and coastal Antarctica is still puzzling. Atmospheric scientists cannot explain yet to which extent vertical dynamics or pristine aerosol conditions control the persistence of liquid layers. Furthermore, virtually nothing is known about how the abundant supercooled-liquid water influences precipitation formation and the radiative budget. This is especially true in the remote region of Antarctica, where detailed vertically resolved observations of aerosol, cloud, and precipitation are scarce and prevent one to capture the complex cloud processes. We will present a unique observation campaign that will help to address the open questions by contributing a one-year remote-sensing dataset for a coastal ice shelf in Dronning Maud Land in the Atlantic sector of Antarctica. The mobile ground-based remote-sensing supersite OCEANET-Atmosphere is deployed at Neumayer Station III (70.67°S, 8.27°W) in 2023. The synergistic combination of a multi-wavelength polarization Raman lidar, a 35-Ghz polarimetric cloud radar, a microwave radiometer, and a Doppler lidar provides valuable profile information of cloud and aerosol properties as well as their interaction. The remote-sensing data is augmented by the stations long-term records of meteorological parameters and aerosol physics and chemistry. Through case studies, we will demonstrate the supersites’ capabilities to relate cloud-relevant aerosol properties with cloud-microphysics and discuss the potential to address the science questions based on the dataset.

Description: Reliable in situ surface mass balance (SMB) estimates in polar regions are scarce due to limited spatial and temporal data availability. This study aims at deriving automated and continuous specific SMB time series for fast-moving parts of ice sheets and shelves (flow velocity 〉 10 m a−1) by developing a combined global navigation satellite system (GNSS) reflectometry and refractometry (GNSS-RR) method. In situ snow density, snow water equivalent (SWE), and snow deposition or erosion are estimated simultaneously as an average over an area of several square meters and independently on weather conditions. The combined GNSS-RR method is validated and investigated regarding its applicability to a moving, high-latitude ice shelf. A combined GNSS-RR system was therefore installed in November 2021 on the Ekström ice shelf (flow velocity ≈ 150 m a−1) in Dronning Maud Land, Antarctica. The reflected and refracted GNSS observations from the site are post-processed to obtain snow accumulation (deposition and erosion), SWE, and snow density estimates with a 15 min temporal resolution. The results of the first 16 months of data show a high level of agreement with manual and automated reference observations from the same site. Snow accumulation, SWE, and density are derived with uncertainties of around 9 cm, 40 kg m−2 a−1, and 72 kg m−3, respectively. This pilot study forms the basis for extending observational networks with GNSS-RR capabilities, particularly in polar regions. Regional climate models, local snow modeling, and extensive remote sensing data products will profit from calibration and validation based on such in situ time series, especially if many such sensors will be deployed over larger regional scales.