With the Arctic rapidly changing, the needs to observe, understand, and model the changes are essential. To support these needs, an annual cycle of observations of atmospheric properties, processes, and interactions were made while drifting with the sea ice across the central Arctic during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition from October 2019 to September 2020. An international team designed and implemented the comprehensive program to document and characterize all aspects of the Arctic atmospheric system in unprecedented detail, using a variety of approaches, and across multiple scales. These measurements were coordinated with other observational teams to explore cross-cutting and coupled interactions with the Arctic Ocean, sea ice, and ecosystem through a variety of physical and biogeochemical processes. This overview outlines the breadth and complexity of the atmospheric research program, which was organized into 4 subgroups: atmospheric state, clouds and precipitation, gases and aerosols, and energy budgets. Atmospheric variability over the annual cycle revealed important influences from a persistent large-scale winter circulation pattern, leading to some storms with pressure and winds that were outside the interquartile range of past conditions suggested by long-term reanalysis. Similarly, the MOSAiC location was warmer and wetter in summer than the reanalysis climatology, in part due to its close proximity to the sea ice edge. The comprehensiveness of the observational program for characterizing and analyzing atmospheric phenomena is demonstrated via a winter case study examining air mass transitions and a summer case study examining vertical atmospheric evolution. Overall, the MOSAiC atmospheric program successfully met its objectives and was the most comprehensive atmospheric measurement program to date conducted over the Arctic sea ice. The obtained data will support a broad range of coupled-system scientific research and provide an important foundation for advancing multiscale modeling capabilities in the Arctic.

Year-round observations of the physical snow and ice properties and processes that govern the ice pack evolution and its interaction with the atmosphere and the ocean were conducted during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition of the research vessel Polarstern in the Arctic Ocean from October 2019 to September 2020. This work was embedded into the interdisciplinary design of the 5 MOSAiC teams, studying the atmosphere, the sea ice, the ocean, the ecosystem, and biogeochemical processes. The overall aim of the snow and sea ice observations during MOSAiC was to characterize the physical properties of the snow and ice cover comprehensively in the central Arctic over an entire annual cycle. This objective was achieved by detailed observations of physical properties and of energy and mass balance of snow and ice. By studying snow and sea ice dynamics over nested spatial scales from centimeters to tens of kilometers, the variability across scales can be considered. On-ice observations of in situ and remote sensing properties of the different surface types over all seasons will help to improve numerical process and climate models and to establish and validate novel satellite remote sensing methods; the linkages to accompanying airborne measurements, satellite observations, and results of numerical models are discussed. We found large spatial variabilities of snow metamorphism and thermal regimes impacting sea ice growth. We conclude that the highly variable snow cover needs to be considered in more detail (in observations, remote sensing, and models) to better understand snow-related feedback processes. The ice pack revealed rapid transformations and motions along the drift in all seasons. The number of coupled ice–ocean interface processes observed in detail are expected to guide upcoming research with respect to the changing Arctic sea ice.

Wind farms affect local weather and microclimates; hence, parameterizations of their effects have been developed for numerical weather prediction models. While most wind farm parameterizations (WFPs) include drag effects of wind farms, models differ on whether or not an additional turbulent kinetic energy (TKE) source should be included in these parameterizations to simulate the impact of wind farms on the boundary layer. Therefore, we use aircraft measurements above large offshore wind farms in stable conditions to evaluate WFP choices. Of the three case studies we examine, we find the simulated ambient background flow to agree with observations of temperature stratification and winds. This agreement allows us to explore the sensitivity of simulated wind farm effects with respect to modeling choices such as whether or not to include a TKE source, horizontal resolution, vertical resolution and advection of TKE. For a stably stratified marine atmospheric boundary layer (MABL), a TKE source and a horizontal resolution on the order of 5 km or finer are necessary to represent the impact of offshore wind farms on the MABL. Additionally, TKE advection results in excessively reduced TKE over the wind farms, which in turn causes an underestimation of the wind speed deficit above the wind farm. Furthermore, using fine vertical resolution increases the agreement of the simulated wind speed with satellite observations of surface wind speed.

This paper presents the unmanned research aircraft Carolo P360 "ALADINA" (Application of Light-weight Aircraft for Detecting IN situ Aerosol) for investigating the horizontal and vertical distribution of ultrafine particles in the atmospheric boundary layer (ABL). It has a wingspan of 3.6 m, a maximum take-off weight of 25 kg and is equipped with aerosol instrumentation and meteorological sensors. A first application of the system, together with the unmanned research aircraft MASC (Multi-Purpose Airborne Carrier) of the Eberhard Karls University of Tübingen (EKUT), is described. As small payload for ALADINA, two condensation particle counters (CPC) and one optical particle counter (OPC) were miniaturised by re-arranging the vital parts and composing them in a space-saving way in the front compartment of the airframe. The CPCs are improved concerning the lower detection threshold and the response time to less than 1.3 s. Each system was characterised in the laboratory and calibrated with test aerosols. The CPCs are operated in this study with two different lower detection threshold diameters of 11 and 18 nm. The amount of ultrafine particles, which is an indicator for new particle formation, is derived from the difference in number concentrations of the two CPCs (ΔN). Turbulence and thermodynamic structure of the boundary layer are described by measurements of fast meteorological sensors that are mounted at the aircraft nose. A first demonstration of ALADINA and a feasibility study were conducted in Melpitz near Leipzig, Germany, at the Global Atmosphere Watch (GAW) station of the Leibniz Institute for Tropospheric Research (TROPOS) on 2 days in October 2013. There, various ground-based instruments are installed for long-term atmospheric monitoring. The ground-based infrastructure provides valuable additional background information to embed the flights in the continuous atmospheric context and is used for validation of the airborne results. The development of the boundary layer, derived from backscatter signals of a portable Raman lidar POLLYXT, allows a quick overview of the current vertical structure of atmospheric particles. Ground-based aerosol number concentrations are consistent with the results from flights in heights of a few metres. In addition, a direct comparison of ALADINA aerosol data and ground-based aerosol data, sampling the air at the same location for more than 1 h, shows comparable values within the range of ± 20 %. MASC was operated simultaneously with complementary flight patterns. It is equipped with the same meteorological instruments that offer the possibility to determine turbulent fluxes. Therefore, additional information about meteorological conditions was collected in the lowest part of the atmosphere. Vertical profiles up to 1000 m in altitude indicate a high variability with distinct layers of aerosol, especially for the small particles of a few nanometres in diameter on 1 particular day. The stratification was almost neutral and two significant aerosol layers were detected with total aerosol number concentrations up to 17 000 ± 3400 cm−3 between 180 and 220 m altitude and 14 000 ± 2800 cm−3 between 550 and 650 m. Apart from those layers, the aerosol distribution was well mixed and reached the total number concentration of less than 8000 ± 1600 cm−3. During another day, the distribution of the small particles in the lowermost ABL was related to the stratification, with continuously decreasing number concentrations from 16 000 ± 3200 cm−3 to a minimum of 4000 ± 800 cm−3 at the top of the inversion at 320 m. Above this, the total number concentration was rather constant. In the region of 500 to 600 m altitude, a significant difference of both CPCs was observed. This event occurred during the boundary layer development in the morning and represents a particle burst within the ABL.

As part of the ongoing X-Wakes research project, a 5-month wake-measurement campaign was conducted using a scanning lidar installed amongst a cluster of offshore wind farms in the German Bight. The main objectives of this study are (1) to demonstrate the performance of such a system and thus quantify cluster wake effects reliably and (2) to obtain experimental data to validate the cluster wake effect simulated by the flow models involved in the project. Due to the lack of free wind flow for the wake flow directions, wind speeds obtained from a mesoscale model (without any wind farm parameterization) for the same time period were used as a reference to estimate the wind speed deficit caused by the wind farm wakes under different wind directions and atmospheric stabilities. For wind farm waked wind directions, the lidar data show that the wind speed is reduced up to 30 % at a wind speed of about 10 m s⁻¹, depending on atmospheric stability and distance to the wind farm. For illustrating the spatial extent of cluster wakes, an airborne dataset obtained during the scanning wind lidar campaign is used and compared with the mesoscale model with wind farm parameterization and the scanning lidar. A comparison with the results of the model with a wind farm parameterization and the scanning lidar data reveals a relatively good agreement in neutral and unstable conditions (within about 2 % for the wind speed), whereas in stable conditions the largest discrepancies between the model and measurements are found. The comparative multi-sensor and model approach proves to be an efficient way to analyze the complex flow situation in a modern offshore wind cluster, where phenomena at different length scales and timescales need to be addressed.

The unmanned research aircraft ALADINA (Application of Light-weight Aircraft for Detecting in situ Aerosols) has been established as an important tool for boundary layer research. For simplified integration of additional sensor payload, a flexible and reliable data acquisition system was developed at the Institute of Flight Guidance, Technische Universität (TU) Braunschweig. The instrumentation consists of sensors for temperature, humidity, three-dimensional wind vector, position, black carbon, irradiance and atmospheric particles in the diameter range of ultra-fine particles up to the accumulation mode. The modular concept allows for straightforward integration and exchange of sensors. So far, more than 200 measurement flights have been performed with the robustly-engineered system ALADINA at different locations. The obtained datasets are unique in the field of atmospheric boundary layer research. In this study, a new data processing method for deriving parameters with fast resolution and to provide reliable accuracies is presented. Based on tests in the field and in the laboratory, the limitations and verifiability of integrated sensors are discussed.