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Observations collected during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) provide a detailed description of the impact of thermodynamic and kinematic forcings on atmospheric boundary layer (ABL) stability in the central Arctic. This study reveals that the Arctic ABL is stable and near-neutral with similar frequencies, and strong stability is the most persistent of all stability regimes. MOSAiC radiosonde observations, in conjunction with observations from additional measurement platforms including a 10 m meteorological tower, ceilometer, microwave radiometer, and radiation station, provide insight into the relationships between atmospheric stability and various atmospheric thermodynamic and kinematic forcings of ABL turbulence, and how these relationships differ by season. We found that stronger stability largely occurs in low wind (i.e., wind speeds are slow), low radiation (i.e., surface radiative fluxes are minimal) environments, a very shallow mixed ABL forms in low wind, high radiation environments, weak stability occurs in high wind, moderate radiation environments, and a near-neutral ABL forms in high wind, high radiation environments. Surface pressure (a proxy for synoptic staging) partially explains the observed wind speeds for different stability regimes. Cloud frequency and atmospheric moisture contribute to the observed surface radiation budget. Unique to summer, stronger stability may also form when moist air is advected from over the warmer open ocean to over the colder sea ice surface, which decouples the colder near-surface atmosphere from the advected layer, and is identifiable through observations of fog and atmospheric moisture.

Precipitation is a key variable in the hydrological cycle. However, observations of precipitation are quite challenging and even more so in remote locations such as the Arctic. The Arctic is experiencing a rapidly changing climate with a strong increase in near-surface air temperature, known as Arctic Amplification. In particular, the Svalbard archipelago is located in the warmest region of the Arctic and reveals the highest temperature increase (Dahlke and Maturilli, 2017). Such changes also affect the hydrological cycle. For example, climate models reveal a strong increase in precipitation in the Arctic (McCrystall et al., 2021) with rain becoming the most dominant precipitation type (Bitanja and Andry, 2017). Continuous detailed observations, which can also be set in context to satellite products and reanalyses data, are necessary to better understand precipitation and precipitation related processes in the Arctic.In this study, we make use of the complementary precipitation observations performed as part of the Transregional Collaborative Research Centre on Arctic Amplification TR172 (http://www.ac3-tr.de; Wendisch et al., 2017) at the Arctic research station AWIPEV at Ny-Ålesund, Svalbard, to analyze precipitation characteristics in detail. The observations include an OTT Pluvio2 weighing gauge, an OTT Parsivel2 distrometer and a METEK MRR-2 micro rain radar (MRR). While the Pluvio and the Parsivel provide information on surface precipitation amount and type, the MRR provides information on the vertical structure of precipitation up to a height of 1 km. Measurements are available since spring/summer 2017 allowing for an analysis of more than 4 years of data.First results show that the yearly precipitation amount based on Pluvio ranges from 306 mm to 552 mm (values are uncorrected for undercatch). Using the one-minute resolved data of Parsivel, precipitation frequency is highly variable within the different months ranging from 0.4 % to 18.8 % with solid precipitation being the most dominant type typically from September to March and liquid precipitation in the months May to August. In addition to monthly and yearly statistics, we will also characterize and analyze in detail the individual precipitation events. One question to be addressed is how much of the precipitation is related to atmospheric rivers (ARs). ARs are long, narrow, and transient corridors of strong horizontal water vapor transport which account for 80-90 % of the poleward moisture transport. Although their occurrence in the Arctic is limited, they are a significant source of rain and snow in the Arctic. Understanding linkages between precipitation and weather events and using observational data to evaluate models and reanalysis in the current climate will aid developing more accurate future predictions.

Comparing the output of general circulation models to observations is essential for assessing and improving the quality of models. While numerical weather prediction models are routinely assessed against a large array of observations, comparing climate models and observations usually requires long time series to build robust statistics. Here, we show that by nudging the large-scale atmospheric circulation in coupled climate models, model output can be compared to local observations for individual days. We illustrate this for three climate models during a period in April 2020 when a warm air intrusion reached the MOSAiC expedition in the central Arctic. Radiosondes, cloud remote sensing and surface flux observations from the MOSAiC expedition serve as reference observations. The climate models AWI-CM1/ECHAM and AWI-CM3/IFS miss the diurnal cycle of surface temperature in spring, likely because both models assume the snow pack on ice to have a uniform temperature. CAM6, a model that uses three layers to represent snow temperature, represents the diurnal cycle more realistically. During a cold and dry period with pervasive thin mixed-phase clouds, AWI-CM1/ECHAM only produces partial cloud cover and overestimates downwelling shortwave radiation at the surface. AWI-CM3/IFS produces a closed cloud cover but misses cloud liquid water. All models overestimate downward turbulent heat fluxes under stable stratification, a long-standing issue in weather and climate models. Our results show that nudging the large-scale circulation to the observed state allows a meaningful comparison of climate model output even to short-term observational campaigns. We suggest that nudging can simplify and accelerate the pathway from observations to climate model improvements and substantially extends the range of observations suitable for model evaluation.

Variability in the components of the Arctic surface energy budget and the atmospheric boundary layer (ABL) structure are to a large extent controlled by synoptic-scale changes and associated air mass properties. The transition of air masses between the radiatively clear and cloudy states, along with their characteristic surface impacts in radiation and ABL structure, can occur in either direction and on short time scales. In both states as well as during the transition, insufficient model representation of radiative processes and cloud microphysical properties cause biases in numerical weather prediction- and climate models. We employ observations from radiosondes, MET tower, and the ShupeTurner cloud microphysics product, which itself synthesizes a wealth of instruments, for the classification of an event of transition between low-level mixed phase cloud and clear conditions. The observed air mass properties and transition process are compared to ERA5 reanalysis data and output from a simulation of the coupled regional climate model HIRHAM-NAOSIM which applied non-spectral nudging to ERA5 in order to reproduce the observed synoptic-scale changes. The approach highlights the potential of event-based analysis of transformations of cloudy Arctic air masses by confronting models with observations.

Observations collected during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) provide an annual cycle of the vertical thermodynamic and kinematic structure of the atmospheric boundary layer (ABL) in the central Arctic. A self-organizing map (SOM) analysis conducted using radiosonde observations shows a range in the Arctic ABL vertical structure from very shallow and stable, with a strong surface-based virtual potential temperature (θv) inversion, to deep and near-neutral, with a weak elevated θv inversion. Profile observations from the DataHawk2 uncrewed aircraft system between 23 March and 26 July 2020 largely sampled the same profile structures, which can be further analyzed to provide unique insight into the turbulent characteristics of the ABL. The patterns identified by the SOM allowed for the derivation of criteria to categorize stability within and just above the ABL, which reveals that the Arctic ABL is stable and near-neutral with similar frequencies. In conjunction with observations from additional measurement platforms, including a 10 m meteorological tower, ceilometer, and microwave radiometer, the radiosonde observations provide insight into the relationships between atmospheric stability and a variety of atmospheric thermodynamic and kinematic features. The average ABL height was found to be 150 m, and ABL height increases with decreasing stability. A low-level jet was observed in 76 % of the radiosondes, with an average height of 401 m and an average speed of 11.5 m s−1. At least one temperature inversion below 5 km was observed in 99.7 % of the radiosondes, with an average base height of 260 m and an average intensity of 4.8 °C. The only cases without a temperature inversion were those with weak stability aloft. Clouds were observed within the 30 minutes preceding radiosonde launch 64 % of the time. These were typically low clouds, and high clouds largely coincide with a stable ABL. The amount of atmospheric moisture present increases with decreasing stability.

This study analyzes turbulent properties in, and the thermodynamic structure of the Arctic atmospheric boundary layer (ABL) during winter and the transition to spring. These processes influence the evolution and longevity of clouds, and impact the surface radiative energy budget in the Arctic. For the measurements we have used an instrumental payload carried by a helium filled tethered balloon. This system was deployed between December 2019 and May 2020 during the yearlong Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. Vertically highly resolved in situ measurements of profiles of turbulent parameters were obtained reaching from the sea ice up to several hundred meters height. The two typical states of the Arctic ABL were identified: cloudless situations with a shallow and stable ABL, and cloudy conditions maintaining a mixed ABL. We have used profile data to estimate the height of the surface mixing layer. For this purpose, a bulk Richardson number criterion approach was introduced. By deriving a critical bulk Richardson number for wintertime in high latitudes, we have extended the analysis to radiosonde data. Furthermore, we have tested the applicability of the Monin-Obukhov similarity theory to derive surface mixing layer heights based on measured surface fluxes.

Comparing the output of general circulation models to observations is essential for assessing and improving the quality of models. While numerical weather prediction models are routinely assessed against a large array of observations, comparing climate models and observations usually requires long time series to build robust statistics. Here, we show that by nudging the large-scale atmospheric circulation in coupled climate models, model output can be compared to local observations for individual days. We illustrate this for three climate models during a period in April 2020 when a warm air intrusion reached the MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) expedition in the central Arctic. Radiosondes, cloud remote sensing and surface flux observations from the MOSAiC expedition serve as reference observations. The climate models AWI-CM1/ECHAM and AWI-CM3/IFS miss the diurnal cycle of surface temperature in spring, likely because both models assume the snowpack on ice to have a uniform temperature. CAM6, a model that uses three layers to represent snow temperature, represents the diurnal cycle more realistically. During a cold and dry period with pervasive thin mixed-phase clouds, AWI-CM1/ECHAM only produces partial cloud cover and overestimates downwelling shortwave radiation at the surface. AWI-CM3/IFS produces a closed cloud cover but misses cloud liquid water. Our results show that nudging the large-scale circulation to the observed state allows a meaningful comparison of climate model output even to short-term observational campaigns. We suggest that nudging can simplify and accelerate the pathway from observations to climate model improvements and substantially extends the range of observations suitable for model evaluation.

Marine Cold Air Outbreaks (MCAOs) have a profound influence on atmospheric conditions and the surface-atmosphere heat exchange in Fram Strait and Svalbard. Comparing the global reanalysis ERA5 to its novel Arctic counterpart CARRA for November-March 1991-2020, we investigate the surface turbulent heat fluxes and the spatial characteristics of MCAOs throughout the troposphere. We find that the sensible heat flux from the surface to the atmosphere is substantially higher in CARRA, while the latent heat flux is higher in ERA5. For sensible heat flux, the differences scale with the magnitude, leading to maximum disagreement over the ice-free ocean where the flux is high. Accounting for the varying magnitude over different surface types, we find the largest relative disagreement over sea ice. During MCAOs, negative anomalies in temperature and specific humidity are present throughout the entire troposphere in both reanalyses. Meanwhile, positive heat flux anomalies are found in northwestern Fram Strait, where the sensible heat flux from the ocean to the atmosphere is roughly doubled during MCAOs. Around much of Svalbard, sea ice decline has caused positive trends in the surface-atmosphere potential temperature difference forming the basis of the MCAO index, leading to higher heat fluxes. In Fram Strait however, both reanalyses show negative trends in the MCAO index and the heat fluxes in January, when the increase in potential temperature is larger at 850 hPa than at the surface.

Continuous height-resolved observations of aerosol profiles over the central Arctic throughout a full year were performed for the first time. Such measurements covering aerosol layering features are required for an adequate modeling of Arctic climate conditions, especially with respect to a realistic consideration of cloud formation and here, in particular, of ice nucleation processes. MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) offered this favorable opportunity to monitor aerosol and clouds over the central Arctic over all four seasons, from October 2019 to September 2020. In this article, a summary of MOSAiC lidar observations aboard the icebreaker Polarstern of tropospheric aerosol products is presented. Particle optical properties, i.e., light-extinction profiles and aerosol optical thickness (AOT), and estimates of cloud-relevant aerosol properties (cloud condensation nucleus, CCN, and ice-nucleating particle concentrations, INPs) are discussed, separately for the lowest part of the troposphere (near the surface at 250 m height), within the lower free troposphere (2000 m height), and regarding INPs also near the tropopause (cirrus level, 8–10 km height). In situ observations of the particle number concentration and INPs aboard Polarstern are included in the study. Strong differences between summer and winter aerosol conditions were found. During the winter months (Arctic haze period) a strong decrease of the aerosol light extinction coefficient (532 nm) with height up to about 4–5 km height was found with values of 20–100 Mm-1 close to the surface and an order of magnitude less at 1500–2000 m height. Lofted aged wildfire smoke layers caused a re-increase of the aerosol concentration from the middle troposphere up to stratospheric heights and were continuously observable from October 2019 to May 2020. In summer (June to August 2020), much lower particle extinction coefficients, frequently as low as 1–5 Mm-1, were observed. Aerosol removal, controlled by cloud scavenging processes (widely suppressed in winter, very efficient in summer) in the lowermost 1–2 km of the atmosphere, seem to be the main reason for the strong differences between winter and summer aerosol conditions. In line with this pronounced annual cycle in the aerosol optical properties, CCN concentrations (0.2 % supersaturation level) ranged from 50–500 cm-3 in the atmospheric boundary layer (ABL) in winter and 1–40 cm-3 in summer. In the lower free troposphere, however, the CCN level was roughly constant throughout the year with values mostly from 30–100 cm-3. A strong contrast between winter to summer was also given in terms of ABL INPs which control ice production in low-level clouds. INP concentration of 0.01–0.2 L-1 prevailed in the ABL in winter at typical ice-nucleating cloud temperatures of -25 °C and assuming soil dust as the main INP type, and were roughly 2 orders of magnitude lower in the ABL in summer at typical cloud top temperatures of -10 °C. In the summer ABL, marine aerosol (biogenic components) is most probably the main INP type, continental INP contributions (e.g., soil dust INPs) are suppressed by efficient wet removal during long-range transport. A strong reduction in the INP population was also found in the lower free troposphere at 2000 m height from winter to summer (2 orders of magnitude), mostly due to the change in the prevailing ice-nucleation temperatures. Estimated INP concentration accumulated from 0.004–0.02 L-1 during the winter months. The highlight of the MOSAiC lidar studies was the detection of a persistent wildfire smoke layer in the upper troposphere and lower stratosphere from October 2019 to May 2020. The smoke particles (organic aerosol) triggered continuously cirrus formation at INP concentrations mostly from 1–20 L-1 close to the tropopause during the entire winter period.

The rapidly transforming Svalbard and Fram Strait region is characterised by strong air-sea exchanges and represents a major gateway of oceanic and atmospheric transport between the Arctic and lower latitudes. In winter, Marine Cold Air Outbreaks (MCAOs) extract large amounts of energy from the ocean in the form of surface sensible and latent heat fluxes. We investigate how the spatiotemporal variability in Fram Strait MCAOs affects the heat fluxes in ERA5 and the novel Arctic reanalysis CARRA over ocean, sea-ice and land during November-March 1991-2020. We find that the daily mean heat fluxes are strongly correlated with the MCAO index and that wind speed only plays a large role for the heat fluxes when the MCAO index is positive. The sensible heat flux from the surface to the atmosphere reaches greater values in CARRA than in ERA5 while the opposite is true for the latent heat flux. The difference between the reanalyses scale with the magnitude of the heat fluxes, leading to large disagreement over ice-free ocean, where the fluxes have their highest values. When accounting for the differences in magnitude, we find the largest disagreement between the reanalyses over sea ice. In addition, we find that although sea ice loss drives positive ocean-to-atmosphere heat flux trends around much of Svalbard, negative trends in the monthly mean heat fluxes are seen in Fram Strait during the winter, especially in January. These negative trends reflect the decline in the surface-atmosphere potential temperature difference which forms the basis for the MCAO index. Finally, we examine the vertical structure of the atmosphere during MCAOs and find anomalously northerly winds, low temperature and low specific humidity throughout the troposphere. The specific humidity anomalies are strongest at low altitudes over the ice-free ocean in southern Fram Strait, while the temperature anomalies reach their maximum in the vicinity of the ice edge. Over the ice-free ocean, where the heat fluxes warm the air from below, the strongest temperature anomalies are found around the altitude of the 800 hPa level.

The Arctic has warmed much more than the global mean during past decades. The lapse-rate feedback (LRF) has been identified as large contributor to the Arctic amplification (AA) of climate change. This particular feedback arises from the vertically non-uniform warming of the troposphere, which in the Arctic emerges as strong near-surface, and muted free-tropospheric warming. Stable stratification and meridional energy transport are two characteristic processes that are evoked as causes for this vertical warming structure. Our aim is to constrain these governing processes by making use of detailed observations in combination with the large climate model ensemble of the 6th Coupled Model Intercomparison Project (CMIP6). We build on the result that CMIP6 models show a large scatter in Arctic LRF and AA, which are positively correlated for the historical period 1951–2014. Thereby, we present process-oriented constraints by linking characteristics of the current climate to historical climate simulations. In particular, we compare a large consortium of present-day observations to co-located model data from subsets with weak and strong simulated AA and Arctic LRF in the past. Our results firstly suggest that local Arctic processes mediating the lower thermodynamic structure of the atmosphere are more realistically depicted in climate models with weak Arctic LRF and AA (CMIP6/w) in the past. In particular, CMIP6/w models show stronger inversions at the end of the simulation period (2014) for boreal fall and winter, which is more consistent with the observations. This result is based on radiosonde observations from the year-long MOSAiC expedition in the central Arctic, together with long-term radio soundings at the Utqiaǵvik site in Alaska, USA, and dropsonde measurements from aircraft campaigns in the Fram Strait. Secondly, remote influences that can further mediate the warming structure in the free troposphere are more realistically represented by models with strong simulated Arctic LRF and AA (CMIP6/s) in the past. In particular, CMIP6/s models systemically simulate a stronger Arctic energy transport convergence in the present climate for boreal fall and winter, which is more consistent with reanalysis results. Locally, we find links between changes in transport pathways and vertical warming structures that favor a positive LRF in the CMIP6/s simulations. This hints to the mediating influence of advection on the Arctic LRF. We emphasise that one major attempt of this work is to give insights in different perspectives on the Arctic LRF. We present a variety of contributions from a large collaborative research consortium to ultimately find synergy among them in support of advancing our understanding of the Arctic LRF.

Near-surface mercury and ozone depletion events occur in the lowest part of the atmosphere during Arctic spring. Mercury depletion is the first step in a process that transforms long-lived elemental mercury to more reactive forms within the Arctic that are deposited to the cryosphere, ocean, and other surfaces, which can ultimately get integrated into the Arctic food web. Depletion of both mercury and ozone occur due to the presence of reactive halogen radicals that are released from snow, ice, and aerosols. In this work, we added a detailed description of the Arctic atmospheric mercury cycle to our recently published version of the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem 4.3.3) that includes Arctic bromine and chlorine chemistry and activation/recycling on snow and aerosols. The major advantage of our modelling approach is the online calculation of bromine concentrations and emission/recycling that is required to simulate the hourly and daily variability of Arctic mercury depletion. We used this model to study coupling between reactive cycling of mercury, ozone, and bromine during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) spring season in 2020 and evaluated results compared to land-based, ship-based, and remote sensing observations. The model predicts that elemental mercury oxidation is driven largely by bromine chemistry and that particulate mercury is the major form of oxidized mercury. The model predicts that the majority (74%) of oxidized mercury deposited to land-based snow is re-emitted to the atmosphere as gaseous elemental mercury, while a minor fraction (4%) of oxidized mercury that is deposited to sea ice is re-emitted during spring. Our work demonstrates that hourly differences in bromine/ozone chemistry in the atmosphere must be considered to capture the springtime Arctic mercury cycle, including its integration into the cryosphere and ocean.

An advanced multiwavelength polarization Raman lidar was operated aboard the icebreaker Polarstern during the MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) expedition to continuously monitor aerosol and cloud layers in the central Arctic up to 30 km height. The expedition lasted from September 2019 to October 2020 and measurements were mostly taken between 85 and 88.5∘ N. The lidar was integrated into a complex remote-sensing infrastructure aboard the Polarstern. In this article, novel lidar techniques, innovative concepts to study aerosol–cloud interaction in the Arctic, and unique MOSAiC findings will be presented. The highlight of the lidar measurements was the detection of a 10 km deep wildfire smoke layer over the North Pole region between 7–8 km and 17–18 km height with an aerosol optical thickness (AOT) at 532 nm of around 0.1 (in October–November 2019) and 0.05 from December to March. The dual-wavelength Raman lidar technique allowed us to unambiguously identify smoke as the dominating aerosol type in the aerosol layer in the upper troposphere and lower stratosphere (UTLS). An additional contribution to the 532 nm AOT by volcanic sulfate aerosol (Raikoke eruption) was estimated to always be lower than 15 %. The optical and microphysical properties of the UTLS smoke layer are presented in an accompanying paper (Ohneiser et al., 2021). This smoke event offered the unique opportunity to study the influence of organic aerosol particles (serving as ice-nucleating particles, INPs) on cirrus formation in the upper troposphere. An example of a closure study is presented to explain our concept of investigating aerosol–cloud interaction in this field. The smoke particles were obviously able to control the evolution of the cirrus system and caused low ice crystal number concentration. After the discussion of two typical Arctic haze events, we present a case study of the evolution of a long-lasting mixed-phase cloud layer embedded in Arctic haze in the free troposphere. The recently introduced dual-field-of-view polarization lidar technique was applied, for the first time, to mixed-phase cloud observations in order to determine the microphysical properties of the water droplets. The mixed-phase cloud closure experiment (based on combined lidar and radar observations) indicated that the observed aerosol levels controlled the number concentrations of nucleated droplets and ice crystals.

Fram Strait in the northern North Atlantic is a key region for marine cold air outbreaks (MCAOs), southward discharges of polar air under northerly air flow, which have a strong impact on air-sea heat fluxes, boundary layer processes and severe weather. This study investigates climatologies and decadal trends of Fram Strait MCAOs of different intensity classes based on the ERA5 reanalysis product for 1979–2020. Among striking interannual variability, it is shown that the main MCAO season is December through March, when MCAOs occur around 2/3 of the time. We report on significant decadal MCAO decreases in December and January, and a significant increase in March. While the mid-winter decrease is mainly related to the different paces of warming between the surface and the lower atmosphere, the increase in March can be related to changes in synoptic circulation patterns. As an explanation for the latter, a possible feedback between retreating Barents Sea sea ice, enhanced cyclonic activity and Fram Strait MCAOs is postulated. Exemplifying the trend toward stronger MCAOs during March, the study details the recordbreaking MCAO season in early 2020, and an observational case study of an extreme MCAO event in March 2020 is conducted. Thereby, radiosonde observations are combined with kinematic air back-trajectories to provide rare observational evidence for the diabatic cooling and drying during the MCAO preconditioning phase.

During the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition, meteorological conditions over the lowest 1 km of the atmosphere were sampled with the DataHawk2 (DH2) fixed-wing uncrewed aircraft system (UAS). These in situ observations of the central Arctic atmosphere are some of the most extensive to date and provide unique insight into the atmospheric boundary layer (ABL) structure. The ABL is an important component of the Arctic climate, as it can be closely coupled to cloud properties, surface fluxes, and the atmospheric radiation budget. The high temporal resolution of the UAS observations allows us to manually identify the ABL height (ZABL) for 65 out of the total 89 flights conducted over the central Arctic Ocean between 23 March and 26 July 2020 by visually analyzing profiles of virtual potential temperature, humidity, and bulk Richardson number. Comparing this subjective ZABL with ZABL identified by various previously published automated objective methods allows us to determine which objective methods are most successful at accurately identifying ZABL in the central Arctic environment and how the success of the methods differs based on stability regime. The objective methods we use are the Liu–Liang, Heffter, virtual potential temperature gradient maximum, and bulk Richardson number methods. In the process of testing these objective methods on the DH2 data, numerical thresholds were adapted to work best for the UAS-based sampling. To determine if conclusions are robust across different measurement platforms, the subjective and objective ZABL determination processes were repeated using the radiosonde profile closest in time to each DH2 flight. For both the DH2 and radiosonde data, it is determined that the bulk Richardson number method is the most successful at identifying ZABL, while the Liu–Liang method is least successful. The results of this study are expected to be beneficial for upcoming observational and modeling efforts regarding the central Arctic ABL.

The tethered balloon-borne measurement system BELUGA (Balloon-bornE moduLar Utility for profilinG the lower Atmosphere) was deployed over the Arctic sea ice for 4 weeks in summer 2020 as part of the Multidisciplinary drifting Observatory for the Study of Arctic Climate expedition. Using BELUGA, vertical profiles of dynamic, thermodynamic, aerosol particle, cloud, radiation, and turbulence properties were measured from the ground up to a height of 1,500 m. BELUGA was operated during an anomalously warm period with frequent liquid water clouds and variable sea ice conditions. Three case studies of liquid water phase, single-layer clouds observed on 3 days (July 13, 23, and 24, 2020) are discussed to show the potential of the collected data set to comprehensively investigate cloud properties determining cloud evolution in the inner Arctic over sea ice. Simulated back-trajectories show that the observed clouds have evolved within 3 different air masses (“aged Arctic,” “advected over sea ice,” and “advected over open ocean”), which left distinct fingerprints in the cloud properties. Strong cloud top radiative cooling rates agree with simulated results of previous studies. The weak warming at cloud base is mostly driven by the vertical temperature profile between the surface and cloud base. In-cloud turbulence induced by the cloud top cooling was similar in strength compared to former studies. From the extent of the mixing layer, it is speculated that the overall cloud cooling is stronger and thus faster in the warm oceanic air mass. Larger aerosol particle number concentrations and larger sizes were observed in the air mass advected over the sea ice and in the air mass advected over the open ocean.

International audience; 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.

Wasserdampf trägt als Treibhausgas zum Strahlungsbudget der Atmosphäre bei und ist im atmosphärischen Energietransport, bei Wolkenprozessen und der Niederschlagsbildung von Bedeutung. Die Kenntnis der vertikalen Wasserdampfprofile in der Arktis ist ein wichtiger Beitrag zum Verständnis des arktischen Klimasystems und seines Wandels. Im Rahmen der MOSAiC-Kampagne wurden vom Oktober 2019 bis Oktober 2020 über ein Jahr verschiedenste klimarelevante Parameter gemessen. Mit dem Raman-Lidar PollyXT konnten erstmals nördlich von 85°N vertikal hochaufgelöste Profile des atmosphärischen Wasserdampfes aufgenommen werden. Die Dunkelheit der Polarnacht und niedrige Sonnenstände ermöglichten kontinuierliche Messungen des Wasserdampfes von Oktober 2019 bis März 2020. Die Kalibrierung der Raman-Lidar-Daten erfolgt mit Radiosondenprofilen oder dem integrierten Wasserdampf eines Mikrowellenradiometers.Die gemessenen Absolutwerte des Wasserdampfmischungsverhältnisses in der Arktis sind sehr gering, die vertikale Verteilung ist jedoch hoch variabel und die relative Feuchte erreicht aufgrund der tiefen Temperaturen bodennah häufig Werte nahe 100%. Die vertikale Struktur des Wasserdampfes und der verschiedenen in unterschiedlichen Höhen gemessenen Feuchteschichten lässt auf unterschiedliche Quellen des Wasserdampfes schließen. Zum einen gibt es lokale Quellen wie Verdunstung und Kondensation, die vor allem bodennah auftreten und zum anderen wird im Bereich der freien Troposphäre Wasserdampf aus entfernteren Regionen herantransportiert. Die Stärke des Transports wird dabei hauptsächlich von der allgemeinen Zirkulation in der Atmosphäre bestimmt, welche in der Arktis durch die Arktische Oszillation (AO) beschrieben werden kann. Mit Hilfe des AO Indexes lassen sich positive Phasen (AO>0) mit einem starken Polar Vortex und wenig meridionalem Transport und negative Phasen (AOdeutliche Unterschiede in der Vertikalstruktur und der Gesamtmenge des Wasserdampfes für die beiden Phasen. Während der negativen Phase der arktischen Oszillation werden mehrere zeitlich sehr variable Wasserdampfschichten beobachtet. Bei positivem AO Index ist dagegen nur eine homogene Schicht erkennbar und die Werte des Wasserdampfmischungsverhältnisses sind deutlich geringer. Zudem lassen sich in beiden Phasen Zusammenhänge zwischen Wasserdampf- und Temperaturprofilen erkennen. In der Höhe von Feuchteinversionen treten zum Beispiel häufig auch Temperaturinversionen auf. Mit der Untersuchung weiterer Fallbeispiele soll die vertikale Struktur des Wasserdampfes in der Atmosphäre, deren zeitliche Veränderung und der Zusammenhang zur Arktischen Oszillation weiter analysiert werden.

Water vapor profiles with high vertical and temporal resolution were determined by use of the Raman lidar PollyXT within the MOSAiC campaign in the Arctic during the winter time 2019 – 2020. These measurements need a calibration. Usually, radiosonde data are utilized to calibrate the lidar data by the profile or the linear fit method, respectively. The radiosonde is drifting with the wind; thus, it is often measuring different atmospheric volumes compared to the lidar observations. The period 5-7 February 2020 is used to demonstrate the results. The correlation coefficient of the linear fit between the radiosonde and the lidar data varies with the different atmospheric conditions. The calibration results from the profile method coincide with those of the linear fit method, but the selection of the appropriate calibration setup is not straightforward. The varying correlation of the calibration results is attributed to the partly too low data-variability of the water vapor mixing ratio in the respective heights. Moreover, the drift of the radiosondes with the wind and hence measurements of atmospheric volumes with lateral distances will have decreased the correlation between the lidar and the radiosonde measurements. During MOSAiC a microwave radiometer was collocated close to the lidar. This system was measuring the same atmospheric vertical column. Its product, the integrated water vapor, might be useful for the calibration of the lidar. Hence, the contribution will analyze the error of the lidar retrieved water vapor mixing ratio that includes the calibration with the radiosonde data and the microwave radiometer product.

During the 1-year MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) expedition, the German icebreaker Polarstern drifted through Arctic Ocean ice from October 2019 to May 2020, mainly at latitudes between 85 and 88.5∘ N. A multiwavelength polarization Raman lidar was operated on board the research vessel and continuously monitored aerosol and cloud layers up to a height of 30 km. During our mission, we expected to observe a thin residual volcanic aerosol layer in the stratosphere, originating from the Raikoke volcanic eruption in June 2019, with an aerosol optical thickness (AOT) of 0.005–0.01 at 500 nm over the North Pole area during the winter season. However, the highlight of our measurements was the detection of a persistent, 10 km deep aerosol layer in the upper troposphere and lower stratosphere (UTLS), from about 7–8 to 17–18 km height, with clear and unambiguous wildfire smoke signatures up to 12 km and an order of magnitude higher AOT of around 0.1 in the autumn of 2019. Case studies are presented to explain the specific optical fingerprints of aged wildfire smoke in detail. The pronounced aerosol layer was present throughout the winter half-year until the strong polar vortex began to collapse in late April 2020. We hypothesize that the detected smoke originated from extraordinarily intense and long-lasting wildfires in central and eastern Siberia in July and August 2019 and may have reached the tropopause layer by the self-lifting process. In this article, we summarize the main findings of our 7-month smoke observations and characterize the aerosol in terms of geometrical, optical, and microphysical properties. The UTLS AOT at 532 nm ranged from 0.05–0.12 in October–November 2019 and 0.03–0.06 during the main winter season. The Raikoke aerosol fraction was estimated to always be lower than 15 %. We assume that the volcanic aerosol was above the smoke layer (above 13 km height). As an unambiguous sign of the dominance of smoke in the main aerosol layer from 7–13 km height, the particle extinction-to-backscatter ratio (lidar ratio) at 355 nm was found to be much lower than at 532 nm, with mean values of 55 and 85 sr, respectively. The 355–532 nm Ångström exponent of around 0.65 also clearly indicated the presence of smoke aerosol. For the first time, we show a distinct view of the aerosol layering features in the High Arctic from the surface up to 30 km height during the winter half-year. Finally, we provide a vertically resolved view on the late winter and early spring conditions regarding ozone depletion, smoke occurrence, and polar stratospheric cloud formation. The latter will largely stimulate research on a potential impact of the unexpected stratospheric aerosol perturbation on the record-breaking ozone depletion in the Arctic in spring 2020.

Marine Cold Air Outbreaks (MCAOs) are common features above the open water surfaces of the Nordic Seas. They are characterized by marked vertical temperature gradients, which typically persist over several days, and strongly shape air-sea heat exchanges, convection, weather and boundary layer characteristics in the affected region. Based on the novel ERA-5 reanalysis product, we are analyzing climatological and recent aspects of MCAOs in the Fram Strait region of the North Atlantic, which is a “hot spot” particularly during winter and early spring. MCAOs in Fram Strait occur preferably when persistent low pressure systems occupy Northern Scandinavia and the Barents/Kara Sea, which exerts strong zonal pressure gradients across Fram Strait. Based on the vertical gradients of potential temperature, occurrence frequencies of MCAOs of different strengths are investigated. It is found that MCAOs of moderate strength occur at an average of 7-9 days per month between December and March, while especially strong MCAOs occur at an average of 1-3 days in that time. Regarding the former, March is the only month for which a significant trend of +1.7 days/month/decade was found over the 1979-2020 period. While regional MCAO expression is dependent on both the relative location of the ice edge and on the atmospheric circulation, MCAO increase in Fram Strait in March can be explained mainly with the latter and the associated zonal pressure gradient.February and March 2020 serve as examples of particularly strong and persistent MCAOs in Fram Strait. The record-breaking strong polar vortex at that time, which had received global attention in the media and literature, had left its associated footprint in near surface and tropospheric circulation fields, hence providing anomalous northerly flow across the ice edge in Fram Strait. While this clearly shaped MCAOs in Fram Strait, associated anomalies were also observed in the North Atlantic Sea Ice edge, and were even detected in upper air profiles and sea ice conditions on Svalbard.For the detailed study of such northerly advection events, atmospheric data gathered during the year-long MOSAiC expedition 2019/2020 in the central Arctic are expected to provide valuable information in the upstream direction of the anomalies in Fram Strait.

During the one-year MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) expedition the German icebreaker Polarstern drifted through the Arctic Ocean ice from October 2019 to May 2020, mainly at latitudes between 85° N and 88.5° N. A multiwavelength polarization Raman lidar was operated aboard the research vessel and continuously monitored aerosol and cloud layers up to 30 km height. The highlight of the lidar measurements was the detection of a persistent, 10 km deep wildfire smoke layer in the upper troposphere and lower stratosphere (UTLS) from about 7–8 km to 17–18 km height. The smoke layer was present throughout the winter half year until the polar vortex, the strongest of the last 40 years, collapsed in late April 2020. The smoke originated from major fire events, especially from extraordinarily intense and long-lasting Siberian fires in July and August 2019. In this article, we summarize the main findings of our seven-month smoke observations and characterize the aerosol properties and decay of the stratospheric perturbation in terms of geometrical, optical, and microphysical properties. The UTLS aerosol optical thickness (AOT) at 532 nm ranged from 0.05–0.12 in October–November 2019 and was of the order of 0.03–0.06 during the central winter months (December–February). As an unambiguous sign of the dominance of smoke, the particle extinction-to-backscatter ratio (lidar ratio) at 355 nm was found to be much lower than the respective 532 nm lidar ratio. Mean values were 55 sr (355 nm) and 85 sr (532 nm). We further present a review of previous height resolved Arctic aerosol observations (remote sensing) in our study. For the first time, a coherent and representative view on the aerosol layering features in the Central Arctic from the surface up to 27 km height during the winter half year is presented. Finally, a potential impact of the wildfire smoke aerosol on the record-breaking ozone depletion over the Arctic in the spring of 2020 is discussed based on smoke, ozone, and polar stratospheric cloud observations.

An advanced multiwavelength polarization Raman lidar was operated aboard the icebreaker Polarstern during the MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) expedition, lasting from September 2019 to October 2020, to contiuously monitor aerosol and cloud layers in the Central Arctic up to 30 km height at latitudes mostly between 85° N and 88.5° N. The lidar was integrated in a complex remote sensing infrastructure aboard Polarstern. Modern aerosol lidar methods and new lidar techniques and concepts to explore aerosol-cloud interaction were applied for the first time in the Central Arctic. Aim of the introductory article is to provide an overview of the observational spectrum of the lidar products for representative measurement cases. Highlight of the lidar measurements was the detection of a 10 km deep wildfire smoke layer over the North Pole area from, on average, 7 km to 17 km height with an aerosol optical thickness (AOT) at 532 nm around 0.1 (in October–November 2019) and 0.05 from December to mid of March 2020. The wildfire smoke was trapped within the extraordinarily strong polar vortex and remained detectable until the beginning of May 2020. Arctic haze was also monitored and characterized in terms of backscatter, extinction, and extinction-to-backscatter ratio at 355 and 532 nm. High lidar ratios from 60–100 sr in lofted mixed haze and smoke plumes are indicative for the presence of strongly light-absorbing fine-mode particles. The AOT at 532 nm was of the order of 0.025 for the tropospheric haze layers. In addition, so-called cloud closure experiments were applied to Arctic mixed-phase cloud and cirrus observations. The good match between cloud condensation nucleus concentration (CCNC) and cloud droplet number concentration (CDNC) and, on the other hand, between ice-nucleating particle concentration (INPC) and ice crystal number concentration (ICNC) indicated a clear influence of aerosol particles on the evolution of the cloud systems. CDNC was mostly between 20 and 100 cm−3 in the liquid-water dominated cloud top layer. ICNC was of the order of 0.1–1 L−1. The study of the impact of wildfire smoke particles on cirrus formation revealed that heterogeneous ice formation with smoke particles (organic aerosol particles) as INPs may have prevailed. ICNC values of 10–40 L−1 were clearly below ICNC levels that would indicate homogeneous freezing.

The Svalbard archipelago in the Arctic North Atlantic is experiencing rapid changes in the surface climate and sea ice distribution, with impacts for the coupled climate system and the local society. Using observational data of surface air temperature (SAT) from 1980–2016 across the whole Svalbard archipelago, and sea ice extent (SIE) from operational sea ice charts, a systematic assessment of climatologies, long-term changes and regional differences is conducted. The proximity to the warm water mass of the West Spitsbergen Current (WSC) drives a markedly warmer climate in the western coastal regions compared to northern and eastern Svalbard. This imprints on the SIE climatology in southern and western Svalbard, where the annual maxima of 50–60% area ice coverage are substantially less than 80–90% in the northern and eastern fjords. Owing to winter-amplified warming, the local climate is shifting towards more maritime conditions, and SIE reductions of between 5% to 20% per decade in particular regions are found, such that a number of fjords in the west have been virtually ice-free in recent winters. The strongest decline comes along with SAT forcing and occurs over the most recent 1–2 decades in all regions. In the 1980s and 1990s, enhanced northerly winds and sea ice drift can explain 30–50% of SIE variability around northern Svalbard, where they had correspondingly lead to a SIE increase. At the same time, interannual temperature fluctuations within the WSC waters can explain 20-37% of SIE variability in a number of fjords on the west coast. With an ongoing warming it is suggested that both the meteorological and cryospheric conditions in eastern Svalbard will become increasingly similar to what is already observed in the western fjords, namely suppressed typical Arctic climate conditions.

The two concerted field campaigns Arctic CLoud Observations Using airborne measurements during polar Day (ACLOUD) and the Physical feedbacks of Arctic planetary boundary level Sea ice, Cloud and AerosoL (PASCAL) took place near Svalbard from 23 May to 26 June 2017. They were focused on studying Arctic mixed-phase clouds and involved observations from two airplanes (ACLOUD), an icebreaker (PASCAL), as well as surface-based stations, a tethered balloon, and satellites. Here, we present the synoptic development during the 35 day period of the campaigns, using classical near-surface and upper-air meteorological observations, as well as operational satellite and model data. Over the campaign period, short-term synoptic variability was substantial, dominating over the long-term background effect of Arctic amplification. During the first campaign week, cold and dry Arctic air from the north persisted, with a distinct but seasonally unusual cold air outbreak. Cloudy conditions with mostly low-level clouds prevailed. The subsequent two weeks were characterized by warm and moist maritime air from the south and east, which included two warm air advections. These synoptical disturbances caused lower cloud cover fractions and higher-reaching cloud systems. In the final two weeks, adiabatically warmed westerly air dominated, with a strongly varying cloud distribution in between the two other periods. Results presented here provide synoptic information needed to analyze and interpret data of upcoming studies from ACLOUD/PASCAL, while also offering unprecedented measurements in a sparsely observed region.

The two concerted field campaigns, Arctic CLoud Observations Using airborne measurements during polar Day (ACLOUD) and the Physical feedbacks of Arctic planetary boundary level Sea ice, Cloud and AerosoL (PASCAL), took place near Svalbard from 23 May to 26 June 2017. They were focused on studying Arctic mixed-phase clouds and involved observations from two airplanes (ACLOUD), an icebreaker (PASCAL) and a tethered balloon, as well as ground-based stations. Here, we present the synoptic development during the 35-day period of the campaigns, using near-surface and upper-air meteorological observations, as well as operational satellite, analysis, and reanalysis data. Over the campaign period, short-term synoptic variability was substantial, dominating over the seasonal cycle. During the first campaign week, cold and dry Arctic air from the north persisted, with a distinct but seasonally unusual cold air outbreak. Cloudy conditions with mostly low-level clouds prevailed. The subsequent 2 weeks were characterized by warm and moist maritime air from the south and east, which included two events of warm air advection. These synoptical disturbances caused lower cloud cover fractions and higher-reaching cloud systems. In the final 2 weeks, adiabatically warmed air from the west dominated, with cloud properties strongly varying within the range of the two other periods. Results presented here provide synoptic information needed to analyze and interpret data of upcoming studies from ACLOUD/PASCAL, while also offering unprecedented measurements in a sparsely observed region.

Arctic amplification of climate warming is caused by various feedback processes in the atmosphere-ocean-ice system, and yields the strongest temperature increase during winter in the Arctic North Atlantic region. Located in this key region, Svalbard is affected by increasing winter cyclone activity associated with warm and moist air advection from lower latitudes. In our study, we attempt to quantify the advective contribution to the recent observed atmospheric winter warming in the Svalbard area (1996 - 2016). Based on Ny-Ålesund radiosonde measurements during winter, a strong dependence of the tropospheric temperature on the synoptic flow direction is identified. Using FLEXTRA air backward trajectories, an increase in occurrence frequency of air with origin in the lower latitude Atlantic region is found, that is attributed to a change in atmospheric circulation patterns involving an intensified Icelandic low and a pronounced Ural blocking high. Both the Scandinavian blocking and the Ural blocking high seem to play an important role in the context of advecting air from lower latitudes towards the Svalbard region, therefore our study is of particular relevance for aerosol and trace gas transport, and according measurements on Svalbard . Beyond that, the enhanced occurrence of the Ural blocking in the recent decade has been linked to sea ice retreat in the Barents/Kara Seas. Given that this link is robust, it would directly feed back on additional sea ice retreat in the region due both to anomalous advection of warm air masses from the south and mechanically pushing pack ice more northward, leaving more open water surfaces along the Svalbard coast. Regarding the circulation changes, we find that about one quarter (0.45 K per decade) of the observed tropospheric winter warming trend in the North Atlantic region of the Arctic (2 K per decade) is due to increased advection of warm and moist air from the lower latitude Atlantic region. Furthermore, the Ny-Ålesund radiosonde data evidence that the corresponding warming footprint extends significantly from the surface throughout the entire troposphere, with a vertically constant relative contribution to the overall warming. Essentially, the climate of the Svalbard region as center of the strongest recent winter warming is found to be particularly sensitive to changes in the atmospheric circulation compared to other regions of the Arctic.