We present a comprehensive balloon-borne measurement dataset collected during a dedicated Arctic observation campaign conducted from 19 March to 18 April 2024 in the transition from polar night to polar day at the Villum Research Station (VRS) at Station Nord in Greenland. The objective of the observations was to characterise the temporal evolution of the Arctic atmospheric boundary layer (ABL), focusing on key transition periods, including cloud development, low-level jet evolution, and day to night shifts. Data were collected by the Balloon-bornE moduLar Utility for profilinG the lower Atmosphere (BELUGA) tethered-balloon system performing in-situ measurements of temperature, relative humidity, wind speed, turbulence, and thermal infrared irradiance from the surface to several hundred meters altitude, with frequent profiling in high vertical resolution. Twenty-eight research flights delivered more than 300 profiles, with up to 8 profiles per hour, complemented by daily radiosonde launches. This paper specifies the BELUGA instrumentation at VRS, data processing procedures, and the publicly available Level-2 data (BELUGA and radiosonde), provided in instrument-separated data subsets listed in a data collection (10.1594/PANGAEA.986431, ). One possible major application of the data is to evaluate different model types (such as numerical weather prediction, single-column, large-eddy simulations) in representing processes controlling the Arctic ABL. To prepare such evaluations, we give an overview of the observations, environmental conditions during the campaign, and highlight specific events that are valuable for model comparison. We introduce an event in which temporal temperature changes influence the ABL inversion, radiative heating-rate profiles associated with transitions between cloudy and cloud-free conditions, and an observed Arctic low-level jet compared with reanalysis, offering insights into the Arctic ABL evolution.

Arctic low-level clouds play an important, albeit uncertain, role in the Arctic climate system. Consequently, their effect on the radiative energy budget (REB) is subject to considerable uncertainty as well. To reduce this uncertainty and to assess the importance of processes driving the cloud radiative effect (CRE), it is crucial to quantitatively disentangle the impact of essential parameters that non-linearly affect the CRE. Therefore, this study uses a CRE parameterization and low-level airborne REB observations in combination with an approach similarly applied in climate dynamics to quantify the contributions of the concurrently observed solar zenith angle (SZA), cloud optical thickness, and surface albedo on the solar CRE at the surface. Based on a case study characterized by inhomogeneous cloud and surface conditions in the marginal sea ice zone, it is shown that the surface albedo contributed more than 95 % to the solar CRE difference between open ocean and sea ice. Using the same approach, the analysis is extended to observations from a series of aircraft campaigns and indicates that the variability in the non-cloud properties SZA and surface albedo between seasons and surface types, respectively, has a larger impact on the resulting difference in the solar CRE than the variability in cloud properties.

This case study explores the evolution of clouds during an Arctic cold-air outbreak in the Fram Strait region observed during the HALO-(AC)3 aircraft campaign. Our research provides information about the formation, structure, microphysical and macrophysical properties, and radiative effects and investigates the role of vertical wind shear and buoyancy forces in the transition from regular cloud streets to rather isotropic cloud patterns. Our findings show that lower horizontal boundary layer wind speeds (<12 ms-1) disrupt the formation of cloud streets, leading to more isotropic cloud patterns, characterized by increasing cloud fraction (from 0.73 to 0.84) and cloud top height (from 330 to 390 m), and quantify the increase in liquid water path as well. In addition, we observe an increase in the number concentration of ice crystals in a size range between 100-1000 m and notable riming processes within organized cloud streets. Concurrent radiation measurements in our case study reveal that isotropic cloud patterns can exhibit either low or high albedo as well as low or high Fnet,TIR, suggesting that these patterns represent different developing stages.

The simulations of upward and downward irradiances by the Integrated Forecasting System (IFS) of the European Centre for Medium-Range Weather Forecasts are compared with broadband solar irradiance measurements from the Arctic CLoud Observations Using airborne measurements during polar Day (ACLOUD) campaign. For this purpose, offline radiative transfer simulations were performed with the ecRad radiation scheme using the operational IFS output. The simulations of the downward solar irradiance agree within the measurement uncertainty. However, the IFS underestimates the reflected solar irradiances above sea ice significantly by −35 W m−2. Above open ocean, the agreement is closer, with an overestimation of 28 W m−2. A sensitivity study using measured surface and cloud properties is performed with ecRad to quantify the contributions of the surface albedo, cloud fraction, ice and liquid water path and cloud droplet number concentration to the observed bias. It shows that the IFS sea ice albedo climatology underestimates the observed sea ice albedo, causing more than 50 % of the bias. Considering the higher variability of in situ observations in the parameterization of the cloud droplet number concentration leads to a smaller bias of −27 W m−2 above sea ice and a larger bias of 48 W m−2 above open ocean by increasing the range from 36–69 to 36–200 cm−3. Above sea ice, realistic surface albedos, cloud droplet number concentrations and liquid water paths contribute most to the bias improvement. Above open ocean, realistic cloud fractions and liquid water paths are most important for reducing the model–observation differences.

Global warming is amplified in the Arctic. However, numerical models struggle to represent key processes that determine Arctic weather and climate. To collect data that help to constrain the models, the HALO–(𝒜𝒞)3 aircraft campaign was conducted over the Norwegian and Greenland seas, the Fram Strait, and the central Arctic Ocean in March and April 2022. The campaign focused on one specific challenge posed by the models, namely the reasonable representation of transformations of air masses during their meridional transport into and out of the Arctic via northward moist- and warm-air intrusions (WAIs) and southward marine cold-air outbreaks (CAOs). Observations were made over areas of open ocean, the marginal sea ice zone, and the central Arctic sea ice. Two low-flying and one long-range, high-altitude research aircraft were flown in colocated formation whenever possible. To follow the air mass transformations, a quasi-Lagrangian flight strategy using trajectory calculations was realized, enabling us to sample the same moving-air parcels twice along their trajectories. Seven distinct WAI and 12 CAO cases were probed. From the quasi-Lagrangian measurements, we have quantified the diabatic heating/cooling and moistening/drying of the transported air masses. During CAOs, maximum values of 3 K h−1 warming and 0.3 g kg−1 h−1 moistening were obtained below 1 km altitude. From the observations of WAIs, diabatic cooling rates of up to 0.4 K h−1 and a moisture loss of up to 0.1 g kg−1 h−1 from the ground to about 5.5 km altitude were derived. Furthermore, the development of cloud macrophysical (cloud-top height and horizontal cloud cover) and microphysical (liquid water path, precipitation, and ice index) properties along the southward pathways of the air masses were documented during CAOs, and the moisture budget during a specific WAI event was estimated. In addition, we discuss the statistical frequency of occurrence of the different thermodynamic phases of Arctic low-level clouds, the interaction of Arctic cirrus clouds with sea ice and water vapor, and the characteristics of microphysical and chemical properties of Arctic aerosol particles. Finally, we provide a proof of concept to measure mesoscale divergence and subsidence in the Arctic using data from dropsondes released during the flights.

Arctic air masses undergo intense transformations when moving southward from closed sea ice to warmer open waters in marine cold-air outbreaks (CAOs). Due to the lack of measurements of diabatic heating and moisture uptake rates along CAO flows, studies often depend on atmospheric reanalysis output. However, the uncertainties connected to those datasets remain unclear. Here, we present height-resolved airborne observations of diabatic heating, moisture uptake, and cloud evolution measured in a quasi-Lagrangian manner. The investigated CAO was observed on 1 April 2022 during the HALO-(AC)3 campaign. Shortly after passing the sea-ice edge, maximum diabatic heating rates over 6 K h−1 and moisture uptake over 0.3 gkg-1h-1 were measured near the surface. Clouds started forming and vertical mixing within the deepening boundary layer intensified. The quasi-Lagrangian observations are compared with the fifth-generation global reanalysis (ERA5) and the Copernicus Arctic Regional Reanalysis (CARRA). Compared to these observations, the mean absolute errors of ERA5 versus CARRA data are 14 % higher for air temperature over sea ice (1.14 K versus 1.00 K) and 62 % higher for specific humidity over ice-free ocean (0.112 g kg−1 versus 0.069 g kg−1). We relate these differences to issues with the representation of the marginal ice zone and corresponding surface fluxes in ERA5, as well as the cloud scheme producing excess liquid-bearing, precipitating clouds, which causes a too-dry marine boundary layer. CARRA's high spatial resolution and demonstrated higher fidelity towards observations make it a promising candidate for further studies on Arctic air mass transformations.

Abstract. This paper investigates the influence of clouds on vegetation albedo. For this purpose, we use coupled atmosphere-vegetation radiative transfer (RT) simulations combining the library for Radiative transfer (libRadtran) and the vegetation Soil Canopy Observation of Photosynthesis and Energy fluxes (SCOPE2.0) model. Both models are iteratively linked to more realistically simulate cloud–vegetation-radiation interactions above three types of canopies represented by the spherical, erectophile, and planophile leaf angle distributions. The coupled models are applied to simulate solar, spectral and broadband irradiances under cloud-free and cloudy conditions, with the focus on the visible to near-infrared wavelength range from 0.4 to 2.4 µm wavelengths. The simulated irradiances are used to investigate the spectral and broadband effect of clouds on the vegetation albedo. It is found that changes in solar zenith angle and cloud optical thickness are equally important for variations in the vegetation albedo. For solar zenith angles less than 50° –60°, the vegetation albedo is increased by clouds by up to 0.1. The greatest increase in albedo was observed during the transition from cloud-free to cloud conditions with a cloud optical thickness (τ ) of about 6. For larger values of τ the vegetation albedo saturates and increases only slightly. The increase of the vegetation albedo is a result of three effects: (i) dependence of the canopy reflectivity on the direct and diffuse fraction of downward irradiance, (ii) the shift in the spectral weighting of downward irradiance due to scattering and absorption by clouds, and (iii) multiple scattering between the top of canopy and the cloud base. The observed change in vegetation albedo due to cloudiness is parameterized by a polynomial function, representing a potential method to include cloud–vegetation-radiation interactions in numerical weather prediction and global climate models.

A melting snow layer on Arctic sea ice, as a composition of ice, liquid water, and air, supplies meltwater that may trigger the formation of melt ponds. As a result, surface reflection properties are altered during the melting season and thereby may change the surface energy budget. To study these processes, sea ice surface reflection properties were derived from airborne measurements using imaging spectrometers. The data were collected over the closed and marginal Arctic sea ice zone north of Svalbard in May-June 2017. A retrieval approach based on different absorption indices of pure ice and liquid water in the near-infrared spectral range was applied to the campaign data. The technique enabled us to retrieve the spatial distribution of the liquid water fraction of a snow layer and the effective radius of snow grains. For observations from three research flights, liquid water fractions between 6.5 % and 17.3 % and snow grain sizes between 129 and 414 mu m were derived. In addition, the melt pond depth was retrieved based on an existing approach that isolates the dependence of a melt pond reflection spectrum on the pond depth by eliminating the reflection contribution of the pond ice bottom. The application of the approach to several case studies revealed a high variability of melt pond depth, with maximum depths of 0.33 m. The results were discussed considering uncertainties arising from the airborne reflection measurements, the setup of radiative transfer simulations, and the retrieval method itself. Overall, the presented retrieval methods show the potential and the limitations of airborne measurements with imaging spectrometers to map the transition phase of the Arctic sea ice surface, examining the snow layer composition and melt pond depth.

Flower clouds are trade-wind shallow cumuli, with tops reaching 3 km altitude, organised into 100-km wide clusters. They are widespread over the subtropics and associated with the strongest cloud radiative effect among trade-wind cumuli mesoscale organisations. In the context of large uncertainty in climate projections due to the representation of shallow clouds, major knowledge gaps remain about the global impact of mesoscale organisations and the local processes driving them. Here, the processes governing the flower organisation are investigated based on the case study of February 2, 2020 from the Elucidate the Couplings Between Clouds, Convection, and Circulation (EUREC4A) campaign, east of Barbados. One flower cloud is simulated with a large-eddy simulation (LES), using the Meso-NH model at 100-m horizontal grid spacing, and validated extensively with high-resolution observations from the High Altitude and Long-range Research Aircraft (HALO), dropsondes, and satellite measurements. The cloud-top altitudes exhibit a trimodal distribution. The processes shaping flower clouds are wide cold pools and cloudy updrafts organised in one large arc at the western edge. These updrafts are responsible for the highest cloud tops and drive most of the vertical turbulent fluxes of sensible heat, humidity, and momentum. A mesoscale circulation takes place at the scale of the flower clouds and makes them very similar to deep mesoscale convective systems.

Due to their potential to either warm or cool the surface, liquid-phase clouds and their interaction with the ice-free and sea-ice-covered ocean largely determine the energy budget and surface temperature in the Arctic. Here, we use airborne measurements of solar spectral cloud reflectivity obtained during the Arctic CLoud Observations Using airborne measurements during polar Day (ACLOUD) campaign in summer 2017 and the Arctic Amplification: FLUXes in the Cloudy Atmospheric Boundary Layer (AFLUX) campaign in spring 2019 in the vicinity of Svalbard to retrieve microphysical properties of liquid-phase clouds. The retrieval was tailored to provide consistent results over sea-ice and open-ocean surfaces. Clouds including ice crystals that significantly bias the retrieval results were filtered from the analysis. A comparison with in situ measurements shows good agreement with the retrieved effective radii and an overestimation of the liquid water path and reduced agreement for boundary-layer clouds with varying fractions of ice water content. Considering these limitations, retrieved microphysical properties of clouds observed over the ice-free ocean and sea ice in spring and early summer in the Arctic are compared. In early summer, the liquid-phase clouds have a larger median effective radius (9.5 µm), optical thickness (11.8) and effective liquid water path (72.3 g m−2) compared to spring conditions (8.7 µm, 8.3 and 51.8 g m−2, respectively). The results show larger cloud droplets over the ice-free Arctic Ocean compared to sea ice in spring and early summer caused mainly by the temperature differences in the surfaces and related convection processes. Due to their larger droplet sizes, the liquid clouds over the ice-free ocean have slightly reduced optical thicknesses and lower liquid water contents compared to the sea-ice surface conditions. The comprehensive dataset on microphysical properties of Arctic liquid-phase clouds is publicly available and could, e.g., help to constrain models or be used to investigate effects of liquid-phase clouds on the radiation budget.

This study analyses the cloud radiative effect (CRE) obtained from near-surface observations of three airborne campaigns in the Arctic north-west of Svalbard: Airborne measurements of radiative and turbulent FLUXes of energy and momentum in the Arctic boundary layer (AFLUX, March/April 2019), Arctic CLoud Observations Using airborne measurements during polar Day (ACLOUD, May/June 2017), and Multidisciplinary drifting Observatory for the Study of Arctic Climate - Airborne observations in the Central Arctic (MOSAiC-ACA, August/September 2020). The surface CRE quantifies the potential of clouds to modify the radiative energy budget at the surface and is calculated by combining broadband radiation measurements during low-level flight sections in mostly cloudy conditions with radiative transfer simulations of cloud-free conditions. The significance of surface albedo changes due to the presence of clouds is demonstrated, and this effect is considered in the cloud-free simulations. The observations are discussed with respect to differences of the CRE between sea ice and open-ocean surfaces and between the seasonally different campaigns. The results indicate that the CRE depends on cloud, illumination, surface, and thermodynamic properties. The solar and thermal-infrared (TIR) components of the CRE, CRE(sol )and CRETIR, are analysed separately, as well as combined for the study of the total CRE (CREtot). The inter-campaign differences of CREsol are dominated by the seasonal cycle of the solar zenith angle, with the strongest cooling effect in summer. The lower surface albedo causes a stronger solar cooling effect over open ocean than over sea ice, which amounts to -259 Wm(-2) (-108 Wm(-2)) and -65 Wm(-2) (-17 Wm(-2)), respectively, during summer (spring). Independent of campaign and surface type, CRETIR is only weakly variable and shows values around 75 Wm(-2). In total, clouds show a negative CREtot over open ocean during all campaigns. In contrast, over sea ice, the positive CREtot suggests a warming effect of clouds at the surface, which neutralizes during mid-summer. Given the seasonal cycle of the sea ice distribution, these results imply that clouds in the Fram Strait region cool the surface during the sea ice minimum in late summer, while they warm the surface during the sea ice maximum in spring.

Though wind power predictions have been consistently improved in the last decade, persistent reasons for remaining uncertainties are sudden large changes in wind speed, so-called ramps. Here, we analyse the occurrence of ramp events in a wind farm in Eastern Germany and the performance of a wind power prediction tool in forecasting these events for forecasting horizons of 15 and 30 min. Results on the seasonality of ramp events and their diurnal cycle are presented for multiple ramp definition thresholds. Ramps were found to be most frequent in March and April and least frequent in November and December. For the analysis, the wind power prediction tool is fed by different wind velocity forecast products, for example, numerical weather prediction (NWP) model and measurement data. It is shown that including observational wind speed data for very short-term wind power forecasts improves the performance of the power prediction tool compared to the NWP reference, both in terms of ramp detection and in decreasing the mean absolute error between predicted and generated wind power. This improvement is enhanced during ramp events, highlighting the importance of wind observations for very short-term wind power prediction.

During marine cold air outbreaks (MCAOs), cold and dry Arctic air masses are transported from the central Arctic southward across the closed sea ice and much warmer open oceans. They experience significant transformations including a rapid heating and moistening, often leading to cloud formation. While intense wintertime MCAOs have been analyzed widely, the air mass transformations during other seasons have been studied sparsely. We address this gap by investigating an MCAO case observed in September 2020. To study the transformation processes, we combine the fifth generation of atmospheric reanalyses of the global climate (ERA5), trajectory calculations, as well as shipborne and airborne measurements. In the central Arctic, observations acquired from aboard the research vessel (RV) Polarstern during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition characterized the initial state of the air mass over closed sea ice. Trajectories indicated the pathway the air mass took from RV Polarstern southward to the Fram Strait. For the first 24 h of the southbound drift, the air masses remained quasi-stationary. Then, still 15 h ahead of the marginal sea ice zone, differential advection across the boundary layer flow introduced humidity and clouds at higher altitudes between 1.5 and 2.5 km. ERA5-derived temperature and humidity tendencies indicated complex vertical interactions. Radiative cloud-top cooling, entrainment, and turbulence were significantly reduced in the lower and enhanced in the upper advected cloud layer. Eventually, the lower cloud deck dissipated. After this confluence of 2 different air masses, observations gathered by Polar 5 in Fram Strait as part of the MOSAiC Airborne observations in the Central Arctic campaign revealed cloudy, moist layers throughout the lowest 3.5 km and an increasing boundary layer height. Comparing the initial with the final state 48 h later, the largest net heating of +8 K was found close to the surface, yet the largest net moistening of +2.5 g kg−1 at an altitude of 1 km, as the initial profile was exceptionally dry here. We conclude that the observed air mass transformations were driven by the surface changes from sea ice to open ocean but additionally strongly impacted by the differential advection of clouds and moisture across the near-surface MCAO flow.

The new airborne thermal infrared imager VELOX (Video airbornE Longwave Observations within siX channels) is introduced. It covers six spectral bands in the thermal infrared wavelength range from 7.7 μm to 12 μm and is operated on board of the German High Altitude and Long Range Research Aircraft (HALO) of the German Aerospace Center (Deutsches Luft und Raumfahrtzentrum, DLR). The imager measures two-dimensional (2D) fields of the upward terrestrial radiance within a field of view of 35.5° by 28.7° with 640 by 512 spatial pixels. These 2D radiance fields can be converted into 2D fields of brightness temperature. With a horizontal resolution of better than 10 m VELOX extends the HALO remote sensing instrument suite to observe clouds and surface properties. The calibration and correction procedures for VELOX are presented. First measurements, collected during the ElUcidating the RolE of Cloud-Circulation Coupling in ClimAte (EUREC4A) campaign are shown, including analysis of the cloud top brightness temperature, cloud mask/fraction calculations, cloud top altitude estimates, and Sea Surface Temperature (SST) analysis. The investigations reveal that the cloud top temperature can be resolved with a resolution of about 0.1 K, which translates into a vertical resolution of about 10 m with respect to cloud top altitude.

Two airborne field campaigns focusing on observations of Arctic mixed-phase clouds and boundary layer processes and their role with respect to Arctic amplification have been carried out in spring 2019 and late summer 2020 over the Fram Strait northwest of Svalbard. The latter campaign was closely connected to the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. Comprehensive datasets of the cloudy Arctic atmosphere have been collected by operating remote sensing instruments, in-situ probes, instruments for the measurement of turbulent fluxes of energy and momentum, and dropsondes on board the AWI research aircraft Polar 5. In total, 24 flights with 111 flight hours have been performed over open ocean, the marginal sea ice zone, and sea ice. The datasets follow documented methods and quality assurance and are suited for studies on Arctic mixed-phase clouds and their transformation processes, for studies with a focus on Arctic boundary layer processes, and for satellite validation applications. All datasets are freely available via the world data center PANGAEA.

Abstract. The directional reflection of solar radiation by the Arctic Ocean is dominated by two main surface types: sea ice (often snow-covered) and ice-free (open) ocean. However, in the transitional marginal sea ice zone (MIZ), the reflection properties of both surface types are mixed, which might cause uncertainties in the results of retrieval methods of atmospheric parameters over the MIZ using airborne and satellite measurements. To quantify these uncertainties, respective measurements of reflection properties of the MIZ are needed. Therefore, in this study, an averaged hemispherical-directional reflectance factor (HDRF) of the inhomogeneous surface (mixture of sea ice and open ocean surfaces) in the MIZ is derived using airborne measurements collected with a digital fish-eye camera. For this purpose, a sea ice mask was constructed to separate the reflectivity measurements from sea ice and open ocean pixels. The separated data sets were accumulated and averaged to provide separate HDRFs for sea ice and open ocean surfaces. The respective results were compared with simulations and independent measurements available from the literature. Using the sea ice fraction derived in parallel from the digital camera images, the mixed HDRF describing the directional reflectivity of the inhomogeneous surface of the MIZ was reconstructed by a linear weighting procedure. The result was compared with the original measurements of directional reflectivity over the MIZ. It is concluded that the HDRF of the MIZ can be well reconstructed by linear combination of the HDRFs of homogeneous sea ice and open ocean surfaces, accounting for the special conditions present in the MIZ compared to homogeneous surfaces.

The clouds in the Atlantic trade-wind region are known to have an important impact on the global climate system. Acquiring a comprehensive characterization of these clouds based on observations is a challenge, but it is necessary for the evaluation of their representation in models. An exploration of how the macrophysical and microphysical cloud properties and organization of the cloud field impact the large-scale cloud radiative forcing is presented here. In situ measurements of the cloud radiative effects based on the Broadband AirCrAft RaDiometer Instrumentation (BACARDI) on board the High Altitude and LOng Range Research Aircraft (HALO) and cloud observations from the GOES-16 satellite collected during the ElUcidating the RolE of Cloud-Circulation Coupling in ClimAte (EUREC(4)A) campaign demonstrate what drives the cloud radiative effects in shallow trade-wind clouds. We find that the solar and terrestrial radiative effects of these clouds are largely driven by their macrophysical properties (cloud fraction and a scene-averaged liquid water path). We also conclude that the microphysical properties, cloud top height and organization of the cloud field increasingly determine the cloud radiative effects as the cloud fraction increases.

In satellite-based and airborne imagery, the observed radiances reflected by a certain pixel at the surface are additionally influenced by reflections from the neighboring surface pixels and multiple scatterings due to atmospheric components (mainly cloud and aerosol particles) into the observational solid angle of the imaging camera. This phenomenon is commonly referred to as the atmospheric adjacency effect. This three-dimensional (3D) radiative transfer effect is caused by spatial inhomogeneities of the surface reflectivity and the atmospheric properties. Based on the recently published 3D radiative transfer code LEIPSIC (Light Estimator Including Polarization, Surface Inhomogeneities, and Clouds), a new atmospheric correction (AC) algorithm is proposed to consider for the atmospheric adjacency effect when estimating the surface reflectivity from satellite or airborne imagery. The effectiveness of the new AC algorithm is quantified and compared to the results based on the independent pixel approximation (IPA) radiative transfer approach. It is shown that the image blurring caused by the atmospheric adjacency effect and the error of reflectivity retrievals are reduced by 80% using the new AC algorithm. Furthermore, the simulations demonstrate that the vertical profile of the atmospheric properties is crucial in determining the quality of the AC.

The size and shape of snow grains directly impacts the reflection by a snowpack. In this article, different approaches to retrieve the optical-equivalent snow grain size (ropt) or, alternatively, the specific surface area (SSA) using satellite, airborne, and ground-based observations are compared and used to evaluate ICON-ART (ICOsahedral Nonhydrostatic—Aerosols and Reactive Trace gases) simulations. The retrieval methods are based on optical measurements and rely on the ropt-dependent absorption of solar radiation in snow. The measurement data were taken during a three-week campaign that was conducted in the North of Greenland in March/April 2018, such that the retrieval methods and radiation measurements are affected by enhanced uncertainties under these low-Sun conditions. An adjusted airborne retrieval method is applied which uses the albedo at 1700 nm wavelength and combines an atmospheric and snow radiative transfer model to account for the direct-to-global fraction of the solar radiation incident on the snow. From this approach, we achieved a significantly improved uncertainty (<25%) and a reduced effect of atmospheric masking compared to the previous method. Ground-based in situ measurements indicated an increase of ropt of 15 µm within a five-day period after a snowfall event which is small compared to previous observations under similar temperature regimes. ICON-ART captured the observed change of ropt during snowfall events, but systematically overestimated the subsequent snow grain growth by about 100%. Adjusting the growth rate factor to 0.012 µm2 s−1 minimized the difference between model and observations. Satellite-based and airborne retrieval methods showed higher ropt over sea ice (<300 µm) than over land surfaces (<100 µm) which was reduced by data filtering of surface roughness features. Moderate-Resolution Imaging Spectroradiometer (MODIS) retrievals revealed a large spread within a series of subsequent individual overpasses, indicating their limitations in observing the snow grain size evolution in early spring conditions with low Sun.

Large-scale air mass exchanges between lower latitudes and the inner Arctic are one key aspect in understanding Arctic climate change. Of particular interest are Warm and Moist Air Intrusions (WMAI). These events, albeit covering only 10 % of the time, drive >60 % of the overall moisture flux into the Arctic. Conveyed by surging downward longwave radiation, WMAI can trigger pronounced sea-ice melt and alter local atmospheric conditions for weeks. However, many models struggle with a correct representation of air mass transformations during these events. Thus, a Lagrangian approach is suggested to perform airborne measurement campaigns and to analyze numerical weather forecast and reanalysis data. Here, we present a combination of the Lagrangian analysis tool Lagranto with ECMWF forecast datasets and the atmospheric flight planning tool MSS. This approach was applied during the September 2020 MOSAiC airborne campaign. Additionally, five-day forward and backward trajectories were calculated to identify air masses linking the airborne observations with ground-based observations at the MOSAiC camp. A first analysis of the air mass characteristics and their change along the trajectories is presented. Due to vertical wind shear, such an air mass analysis is not trivial. It requires a detailed flight planning in order to sample the temporal and spatial (horizontal and vertical) development of the air masses. As an outlook for the upcoming spring 2022 HALO-(AC)3 campaign, the potential of combining Lagranto with MSS in predicting the most effective flight track is therefore demonstrated.