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In the framework of the Multidisciplinary drifting Observatory for the Study of Arctic Climate Polarstern expedition, the Leibniz Institute for Tropospheric Research, Leipzig, Germany, operated the shipborne OCEANET-Atmosphere facility for cloud and aerosol observations throughout the whole year. OCEANET-Atmosphere comprises, amongst others, a multiwavelength Raman lidar, a microwave radiometer, and an optical disdrometer. A cloud radar was operated aboard Polarstern by the US Atmospheric Radiation Measurement program. These measurements were processed by applying the so-called Cloudnet methodology to derive cloud properties. To gain a comprehensive view of the clouds, lidar and cloud radar capabilities for low- and high-altitude observations were combined. Cloudnet offers a variety of products with a spatiotemporal resolution of 30 s and 30 m, such as the target classification, and liquid and ice microphysical properties. Additionally, a lidar-based low-level stratus retrieval was applied for cloud detection below the lowest range gate of the cloud radar. Based on the presented dataset, e.g., studies on cloud formation processes and their radiative impact, and model evaluation studies can be conducted., (© 2024. The Author(s).)

Mechanisms behind the phenomenon of Arctic amplification are widely discussed. To contribute to this debate, the (AC)3 project was established in 2016 (www.ac3-tr.de/). It comprises modeling and data analysis efforts as well as observational elements. The project has assembled a wealth of ground-based, airborne, shipborne, and satellite data of physical, chemical, and meteorological properties of the Arctic atmosphere, cryosphere, and upper ocean that are available for the Arctic climate research community. Short-term changes and indications of long-term trends in Arctic climate parameters have been detected using existing and new data. For example, a distinct atmospheric moistening, an increase of regional storm activities, an amplified winter warming in the Svalbard and North Pole regions, and a decrease of sea ice thickness in the Fram Strait and of snow depth on sea ice have been identified. A positive trend of tropospheric bromine monoxide (BrO) column densities during polar spring was verified. Local marine/biogenic sources for cloud condensation nuclei and ice nucleating particles were found. Atmospheric–ocean and radiative transfer models were advanced by applying new parameterizations of surface albedo, cloud droplet activation, convective plumes and related processes over leads, and turbulent transfer coefficients for stable surface layers. Four modes of the surface radiative energy budget were explored and reproduced by simulations. To advance the future synthesis of the results, cross-cutting activities are being developed aiming to answer key questions in four focus areas: lapse rate feedback, surface processes, Arctic mixed-phase clouds, and airmass transport and transformation. [ABSTRACT FROM AUTHOR]

In the Arctic, new particle formation (NPF) and subsequent growth processes are the keys to produce Aitken-mode particles, which under certain conditions can act as cloud condensation nuclei (CCNs). The activation of Aitken-mode particles increases the CCN budget of Arctic low-level clouds and, accordingly, affects Arctic climate forcing. However, the growth mechanism of Aitken-mode particles from NPF into CCN range in the summertime Arctic boundary layer remains a subject of current research. In this combined Arctic cruise field and modeling study, we investigated Aitken-mode particle growth to sizes above 80 nm. A mechanism is suggested that explains how Aitken-mode particles can become CCN without requiring high water vapor supersaturation. Model simulations suggest the formation of semivolatile compounds, such as methanesulfonic acid (MSA) in fog droplets. When the fog droplets evaporate, these compounds repartition from CCNs into the gas phase and into the condensed phase of nonactivated Aitken-mode particles. For MSA, a mass increase factor of 18 is modeled. The postfog redistribution mechanism of semivolatile acidic and basic compounds could explain the observed growth of >20 nm h -1 for 60-nm particles to sizes above 100 nm. Overall, this study implies that the increasing frequency of NPF and fog-related particle processing can affect Arctic cloud properties in the summertime boundary layer., (© The Author(s) 2023. Published by Oxford University Press on behalf of National Academy of Sciences.)

Aerosols play a critical role in the Arctic's radiative balance, influencing solar radiation and cloud formation. Limited observations in the central Arctic leave gaps in understanding aerosol dynamics year-round, affecting model predictions of climate-relevant aerosol properties. Here, we present the first annual high-time-resolution observations of submicron aerosol chemical composition in the central Arctic during the Arctic Ocean 2018 (AO2018) and the 2019–2020 Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expeditions. Seasonal variations in the aerosol mass concentrations and chemical composition in the central Arctic were found to be driven by typical Arctic seasonal regimes and resemble those of pan-Arctic land-based stations. Organic aerosols dominated the pristine summer, while anthropogenic sulfate prevailed in autumn and spring under haze conditions. Ammonium, which impacts aerosol acidity, was consistently less abundant, relative to sulfate, in the central Arctic compared to lower latitudes of the Arctic. Cyclonic (storm) activity was found to have a significant influence on aerosol variability by enhancing emissions from local sources and the transport of remote aerosol. Local wind-generated particles contributed up to 80 % (20 %) of the cloud condensation nuclei population in autumn (spring). While the analysis presented herein provides the current central Arctic aerosol baseline, which will serve to improve climate model predictions in the region, it also underscores the importance of integrating short-timescale processes, such as seasonal wind-driven aerosol sources from blowing snow and open leads/ocean in model simulations. This is particularly important, given the decline in mid-latitude anthropogenic emissions and the increase in local ones. [ABSTRACT FROM AUTHOR]

Melt ponds on Arctic sea ice affect the radiative balance of the region as they introduce darkening of the sea ice during the Arctic summer. The temporal extent and spatial extent of the ponding, as well as its amplitude, reflect the state of Arctic sea ice and are important for our understanding of Arctic sea ice change. Remote sensing retrievals of melt pond fraction (MPF) provide information on both the present state of the melt pond development and its change throughout the years, which is valuable information in the context of climate change and Arctic amplification. In this work, we transfer the earlier published Melt Pond Detector (MPD) remote sensing retrieval to the Ocean and Land Colour Instrument (OLCI) data on board the Sentinel-3 satellite and so complement the existing Medium Resolution Imaging Spectrometer (MERIS) MPF dataset (2002–2011) from Environmental Satellite (ENVISAT) with recent data (2017–present). To evaluate the bias of the MPF product, comparisons to Sentinel-2 MultiSpectral Instrument (MSI) high-resolution satellite imagery are presented, in addition to earlier published validation studies. Both MERIS and OLCI MPD tend to overestimate the small MPFs (ranging from 0 to 0.2), which can be attributed to the presence of water-saturated snow and sea ice before onset of ponding. Good agreement for the middle-range MPF (0.2–0.8) is observed, and the areas of exceptionally high MPF = 100 % are recognized as well. The earlier published MERIS MPFs (2002–2011) were reprocessed using an improved cloud clearing routine and together with recent Sentinel-3 data provide an internally consistent dataset, which allows the MPF development in the past 20 years to be analyzed. Although the total summer hemispheric MPF trend is moderate, at + 0.75 % per decade, the regional weekly MPF trends display a pronounced dynamic and range from - 10 % to as high as + 20 % per decade, depending on the region. We conclude the following effects: The global Arctic melt onset shifted towards spring by at least 2 weeks, with the melt onset happening in late May in recent years as compared to early June to mid-June in the beginning of the dataset. There has been a change in the pond onset regime in recent years, with the East Siberian and Laptev Sea dominating the melt onset and not the Beaufort Gyre region as before. The central Arctic, north Greenland and the Canadian Arctic Archipelago (CAA) have shown signs of increasing first-year ice (FYI) fraction in recent years. The daily gridded MPF averages are available on the web page of the Institute of Environmental Physics, University of Bremen, as a historic dataset for the ENVISAT data and as ongoing operational processing for the Sentinel-3 data. [ABSTRACT FROM AUTHOR]

The aim of this study is to highlight the issue of missed supercooled liquid water (SLW) detection in the current radar/lidar derived products and to investigate the potential of the combined use of the EarthCARE mission and the Arctic Weather Satellite (AWS)—Microwave Radiometer (MWR) observations to fill this observational gap and to improve snowfall retrieval capabilities. The presence of SLW layers, which is typical of snowing clouds at high latitudes, represents a significant challenge for snowfall retrieval based on passive microwave (PMW) observations. The strong emission effect of SLW has the potential to mask the snowflake scattering signal in the high-frequency channels (>90 GHz) exploited for snowfall retrieval, while the detection capability of the combined radar/lidar SLW product—which is currently used as reference for the PMW-based snowfall retrieval algorithm—is limited to the cloud top due to SLW signal attenuation. In this context, EarthCARE, which is equipped with both a radar and a lidar, and the AWS-MWR, whose channels cover a range from 50 GHz to 325.15 GHz, offer a unique opportunity to improve both SLW detection and snowfall retrieval. In the current study, a case study is analyzed by comparing available PMW observations with AWS-MWR simulated signals for different scenarios of SLW layers, and an extensive comparison of the CloudSat brightness temperature (TB) product with the corresponding simulated signal is carried out. Simulated TBs are obtained from a radiative transfer model applied to cloud and precipitation profiles derived from the algorithm developed for the EarthCARE mission (CAPTIVATE). Different single scattering models are considered. This analysis highlights the missed detection of SLW layers embedded by the radar/lidar product and the sensitivity of AWS-MWR channels to SLW. Moreover, the new AWS 325.15 GHz channels are very sensitive to snowflakes in the atmosphere, and unaffected by SLW. Therefore, their combination with EarthCARE radar/lidar measurements can be exploited to both improve snowfall retrieval capabilities and to constrain snowfall microphysical properties. [ABSTRACT FROM AUTHOR]

Marine cold-air outbreaks (MCAOs) strongly affect the Arctic water cycle and, thus, climate through large-scale air mass transformations. The description of air mass transformations is still challenging, partly because previous observations do not resolve fine scales, particularly for the initial development of an MCAO, and due to a lack of information about the thermodynamical evolution starting over sea ice and continuing over open ocean and associated cloud microphysical properties. Therefore, we focus on the crucial initial development within the first 200 km over open water for two case studies in April 2022 during the HALO-(AC)3 campaign (named after the High Altitude and Long Range Research Aircraft and Transregional Collaborative Research Centre ArctiC Amplification: Climate Relevant Atmospheric and SurfaCe Processes and Feedback Mechanisms (AC)3). The two events, just 3 d apart, belong to a particularly long-lasting MCAO and occurred under relatively similar thermodynamic conditions. Even though both events were stronger than the climatological 75th percentile of that period, the first event was characterized by colder air masses from the central Arctic which led to an MCAO index twice as high compared to that of the second event. The evolution and structure were assessed by flight legs crossing the Fram Strait multiple times at the same location, sampling perpendicularly to the cloud streets. Airborne remote sensing and in situ measurements were used to build statistical descriptions of the boundary layer, dynamics, clouds, and precipitation. For this purpose, we established a novel approach based solely on radar reflectivity measurements to detect roll circulation that forms cloud streets. The two cases exhibit different properties of clouds, riming, and roll circulations, though the width of the roll circulation is similar. For the stronger event, cloud tops are higher; more liquid-topped clouds exist; the liquid water path, mean radar reflectivity, precipitation rate, and precipitation occurrence have increased; and riming is active. The variability in rime mass has the same horizontal scale as the roll circulation, implying the importance of roll circulation on cloud microphysics and precipitation. Boundary layer and cloud properties evolve with distance over open water, as seen by, e.g., cloud top height rising. In general, cloud streets form after traveling 15 km over open water. After 20 km, this formation enhances cloud cover to just below 100 %. After around 30 km, precipitation forms, though for the weaker event, the development of precipitation is shifted to larger distances. Within our analysis, we developed statistical descriptions of various parameters (i) within the roll circulation and (ii) as a function of distance over open water. These detailed cloud metrics are particularly well suited for the evaluation of cloud-resolving models close to the sea ice edge to evaluate their representation of dynamics and microphysics. [ABSTRACT FROM AUTHOR]

Cloud radar Doppler spectra are of particular interest for investigating cloud microphysical processes, such as ice formation, riming and ice multiplication. When hydrometeor types within a cloud radar observation volume have different terminal fall velocities, they can produce individual Doppler spectrum peaks. The peaks of different particle types can overlap and be further broadened and blended by turbulence and other dynamical effects. If these (sub-)peaks can be separated, properties of the underlying hydrometeor populations can potentially be estimated, such as their fall velocity, number, size and to some extent their shape. However, this task is complex and dependent on the operation settings of the specific cloud radar, as well as atmospheric dynamics and hydrometeor characteristics. As a consequence, there is a need for adjustable tools that are able to detect peaks in cloud radar Doppler spectra to extract the valuable information contained in them. This paper presents the synergistic use of two algorithms used for analyzing the peaks in Doppler spectra: PEAKO and peakTree. PEAKO is a supervised machine learning tool that can be trained to obtain the optimal parameters for detecting peaks in Doppler spectra for specific cloud radar instrument settings. The learned parameters can then be applied by peakTree, which is used to detect, organize and interpret Doppler spectrum peaks. The application of the improved PEAKO–peakTree toolkit is demonstrated in two case studies. The interpretation is supported by forward-simulated cloud radar Doppler spectra by the Passive and Active Microwave TRAnsfer tool (PAMTRA), which are also used to explore the limitations of the algorithm toolkit posed by turbulence and the number of spectral averages chosen in the radar settings. From the PAMTRA simulations, we can conclude that a minimum number of n = 20–40 spectral averages is desirable for Doppler spectrum peak discrimination. Furthermore, small liquid peaks can only be reliably separated for eddy dissipation rate values up to approximately 0.0002 m2s-3 in the simulation setup which we tested here. The first case study demonstrates that the methods work for different radar systems and settings by comparing the results for two cloud radar systems which were operated simultaneously at a site in Punta Arenas, Chile. Detected peaks which can be attributed to liquid droplets agree well between the two systems, as well as with an independent liquid-predicting neural network. The second case study compares PEAKO–peakTree-detected cloud radar Doppler spectrum peaks to in situ observations collected by a balloon-based holographic imager during a campaign in Ny-Ålesund, Svalbard. This case demonstrates the algorithm toolkit's ability to identify different hydrometeor types but also reveals its limitations posed by strong turbulence and a low n. Despite these challenges, the algorithm toolkit offers a powerful means of extracting comprehensive information from cloud radar observations. In the future, we envision PEAKO–peakTree applications on the one hand for interpreting cloud microphysics in case studies. The identification of liquid cloud peaks emerges as a valuable asset, e.g., in studies on cloud radiative effects, in seeder–feeder processes, or for tracing vertical air motions. Furthermore, the computation of the moments for each subpeak enables the tracking of hydrometeor populations and the observation of growth processes along fallstreaks. On the other hand, PEAKO–peakTree applications could be extended to statistical evaluations of longer data sets. Both algorithms are openly available on GitHub, offering accessibility for the scientific community. [ABSTRACT FROM AUTHOR]

In the central Arctic, high-quality water vapour observations are sparse due to the low density of meteorological stations and uncertainties in satellite remote sensing. Different reanalyses also disagree on the amount of water vapour in the central Arctic. The Multidisciplinary drifting Observatory for the Study of the Arctic Climate (MOSAiC) expedition provides comprehensive observations that are suitable for evaluating satellite products and reanalyses. Radiosonde observations provide high-quality water vapour estimates with a high vertical but a low temporal resolution. Observations from the microwave radiometers (MWRs) on board the research vessel Polarstern complement these observations through high temporal resolution. In this study, we demonstrate the high accuracy of the combination of the two MWRs HATPRO (Humidity and Temperature Profiler) and MiRAC-P (Microwave Radiometer for Arctic Clouds – Passive). For this purpose, we developed new retrievals of integrated water vapour (IWV) and profiles of specific humidity and temperature using a neural network approach, including observations from both HATPRO and MiRAC-P to utilize their different water vapour sensitivity. The retrievals were trained with the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis version 5 (ERA5) and synthetic MWR observations simulated with the Passive and Active Microwave radiative TRAnsfer tool (PAMTRA). We applied the retrievals to synthetic and real observations and evaluated them with ERA5 and radiosondes launched during MOSAiC, respectively. To assess the benefit of the combination of HATPRO and MiRAC-P compared to single MWR retrievals, we compared the errors with respect to MOSAiC radiosondes and computed the vertical information content of the specific humidity profiles. The root mean squared error (RMSE) of IWV was reduced by up to 15 %. Specific humidity biases and RMSE were reduced by up to 75 % and 50 %, respectively. The vertical information content of specific humidity could be increased from 1.7 to 2.4 degrees of freedom. We also computed relative humidity from the retrieved temperature and specific humidity profiles and found that RMSE was reduced from 45 % to 15 %. Finally, we show a case study demonstrating the enhanced humidity profiling capabilities compared to the standard HATPRO-based retrievals. The vertical resolution of the retrieved specific humidity profiles is still low compared to radiosondes, but the case study revealed the potential to resolve major humidity inversions. To what degree the MWR combination detects humidity inversions, also compared to satellites and reanalyses, will be part of future work. [ABSTRACT FROM AUTHOR]

Accurate and detailed retrieval of global horizontal irradiance (GHI) has many benefits, for instance, in support of the energy transition towards an energy supply with a high share of renewable energy sources and for validating high-resolution weather and climate models. In this study, we apply a downscaling algorithm that combines the high-resolution visible and standard-resolution channels on board the Meteosat Spinning Enhanced Visible and Infrared Imager (SEVIRI) to obtain cloud physical properties and GHI at an increased nadir spatial resolution of 1 km × 1 km instead of 3 km × 3 km. We validate the change in accuracy of the high-resolution GHI in comparison to the standard-resolution product against ground-based observations from a unique network of 99 pyranometers deployed during the HOPE field campaign in Jülich, Germany, from 18 April to 22 July 2013. Over the entire duration of the field campaign, a small but statistically significant reduction in root mean square error (RMSE) of 2.8 Wm-2 is found for the high-resolution GHI at a 5 min scale. The added value of the increased spatial resolution is largest on days when GHI fluctuates strongly: for the 10 most variable days a significant reduction in the RMSE of 7.9 Wm-2 is obtained with high- versus standard-resolution retrievals. In contrast, we do not find significant differences between both resolutions for clear-sky and fully overcast days. The sensitivity of these results to temporal- and spatial-averaging scales is studied in detail. Our findings highlight the benefits of spatially dense network observations as well as a cloud-regime-resolved approach for the validation of GHI retrievals. We also conclude that more research is needed to optimally exploit the instrumental capabilities of current advanced geostationary satellites in terms of spatial resolution for GHI retrieval. [ABSTRACT FROM AUTHOR]

Heterogeneous radiative forcing in mid-latitudes, such as that exerted by aerosols, has been found to affect the Arctic climate, though the mechanisms remain debated. In this study, we leverage deep learning (DL) techniques to explore the complex response of the Arctic climate system to local radiative forcing over Europe. We conducted sensitivity experiments using the Max Planck Institute Earth System Model (MPI-ESM1.2) coupled with atmosphere–ocean–land-surface components. Large-scale circulation patterns can mediate the impact of the forcing on Arctic climate dynamics. We employed a DL-based clustering approach to classify large-scale atmospheric circulation patterns. To enhance the analysis of how these patterns impact the Arctic climate, the poleward moist static energy transport (PMSET) associated with the atmospheric circulation patterns was incorporated as an additional similarity metric in the clustering process. Furthermore, we developed a novel method to analyze the circulation patterns' contributions to various climatic parameter anomalies. Our findings indicate that the negative radiative forcing over Europe alters existing circulation patterns and their occurrence frequency without introducing new ones. Specifically, our analysis revealed that while the regional radiative forcing alters the occurrence frequencies of the circulation patterns, these changes are not the primary drivers of the forcing's impact on the Arctic parameters. Instead, it is the shifts in the mean spatial characteristics of the atmospheric circulation patterns, induced by the forcing, that predominantly determine the effects on the Arctic climate. Our methodology facilitates the uncovering of complex, nonlinear interactions within the climate system, capturing nuances that are often obscured in broader seasonal anomaly analyses. This approach enables a deeper understanding of the dynamics driving observed climatic anomalies and their links to specific atmospheric circulation patterns. [ABSTRACT FROM AUTHOR]

The use of depolarization lidar to measure atmospheric volume depolarization ratio (VDR) is a common technique to classify cloud phase (liquid or ice). Previous work using a machine learning framework, applied to peak properties derived from co-polarized attenuated backscatter data, has been demonstrated to effectively detect supercooled-liquid-water-containing clouds (SLCCs). However, the training data from Davis Station, Antarctica, include no warm liquid water clouds (WLWCs), potentially limiting the model's accuracy in regions where WLWCs are present. In this work, we apply the same framework used on the Davis data to a 9-month micro-pulse lidar dataset collected in Ōtautahi / Christchurch, Aotearoa / New Zealand, a location which includes WLWC. We then evaluate the results relative to a reference VDR cloud-phase mask. We found that the Davis model performed relatively poorly at detecting SLCC with a recall score of 0.18, often misclassifying WLWC as SLCC. The performance of our new model, trained using data from Ōtautahi / Christchurch, displays recall scores as high as 0.88 for identification of SLCC, although it generally underestimates SLCC occurrence. The overall performance of the new model highlights the effectiveness of the machine learning technique when appropriate training data relevant to the location are used. [ABSTRACT FROM AUTHOR]

Upcoming submillimeter wave satellite missions require an improved understanding of sea ice emissivity to separate atmospheric and surface microwave signals under dry polar conditions. This work investigates hectometer-scale observations of airborne sea ice emissivity between 89 and 340 GHz , combined with high-resolution visual imagery from two Arctic airborne field campaigns that took place in summer 2017 and spring 2019 northwest of Svalbard, Norway. Using k -means clustering, we identify four distinct sea ice emissivity spectra that occur predominantly across multiyear ice, first-year ice, young ice, and nilas. Nilas features the highest emissivity, and multiyear ice features the lowest emissivity among the clusters. Each cluster exhibits similar nadir emissivity distributions from 183 to 340 GHz. To relate hectometer-scale airborne measurements to kilometer-scale satellite footprints, we quantify the reduction in the variability of airborne emissivity as footprint size increases. At 340 GHz , the emissivity interquartile range decreases by almost half when moving from the hectometer scale to a footprint of 16 km , typical of satellite instruments. Furthermore, we collocate the airborne observations with polar-orbiting satellite observations. After resampling, the absolute relative bias between airborne and satellite emissivities at similar channels lies below 3 %. Additionally, spectral variations in emissivity at nadir on the satellite scale are low, with slightly decreasing emissivity from 183 to 243 GHz , which occurs for all hectometer-scale clusters except those predominantly composed of multiyear ice. Our results will enable the development of microwave retrievals and assimilation over sea ice in current and future satellite missions, such as the Ice Cloud Imager (ICI) and EUMETSAT Polar System – Sterna (EPS–Sterna). [ABSTRACT FROM AUTHOR]

Here, we compared the concentrations of cloud condensation nuclei (CCN) and particle number size distributions (PNSDs) measured during the transient period from the winter to the summer East Asian monsoon in 2021 with those in 2014 to explore possible responses to how CCN responds to upwind continental air pollutant mitigation and marine traffic fuel sulfur content (FSC) regulation over the northwest Pacific Ocean (NWPO). We also employed the Positive Matrix Factorization (PMF) analysis to apportion concentrations of CCN (Nccn) to different sources in order to quantify its source-specified responses to mitigation of air pollution during the transient period. Our results showed that (1) upwind continental mitigation likely reduced Nccn by approximately 200 cm−3 and 400 cm−3 at 0.2% and 0.4% supersaturation (SS), respectively, in the marine background atmosphere over the NWPO; (2) FSC regulation resulted in a decrease in Nccn at 0.4% SS by about 50 cm−3 and was nearly negligible at 0.2% SS over the NWPO. Additionally, a PMF-resolved factor, characterized by a dominant nucleation mode, was present only in 2014 and disappeared in 2021, likely due to the reduction. This estimation, however, suffered from uncertainties since seasonal changes were hard to be deducted accurately. PMF-resolved factors accurately represented Nccn in 80–90% of cases, but this accuracy was not observed in the remaining cases. Finally, an integrated analysis of satellite-derived cloud parameters and ship-based measurements indicated that the reduced Nccn over the NWPO might be co-limited with meteorological factors in forming cloud droplets during the transient period. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

This study emulates dropsondes to elucidate the extent to which sporadic airborne sondes adequately represent divergence of moisture transport in Arctic atmospheric rivers (ARs). The convergence of vertically integrated moisture transport (IVT) plays a crucial role as it favours precipitation that significantly affects Arctic sea ice properties. Long-range research aircraft can transect ARs and drop sondes to determine their IVT divergence. In order to assess the representativeness of future sonde-based IVT divergence in Arctic ARs, we disentangle the sonde-based deviations from an ideal instantaneous IVT divergence, which result from undersampling by a limited number of sondes and from the flight duration. Our synthetic study uses C3S Arctic Regional Reanalysis (CARRA) reanalyses to set up an idealised scenario for airborne AR observations. For nine Arctic spring ARs, we mimic flights transecting each AR in CARRA and emulate sonde-based IVT representation by picking single vertical profiles. The emulation quantifies IVT divergence observability by two approaches. First, sonde-based IVT and its divergence are compared to the continuous IVT interpolated onto the flight cross-section. The comparison specifies uncertainties of discrete sonde-based IVT variability and divergence. Second, we determine how temporal AR evolution affects IVT divergence values by contrasting time-propagating sonde-based values with the divergence based on instantaneous snapshots. For our Arctic AR cross-sections, we find that coherent wind and moisture variabilities contribute less than 10 % to the total transport. Both quantities are uncorrelated to a great extent. Moisture turns out to be the more variable quantity. We show that sounding spacing greater than 100 km results in errors greater than 10 % of the total IVT along AR cross-sections. For IVT divergence, the Arctic ARs exhibit similar differences in moisture advection and mass convergence across the embedded front as mid-latitude ARs, but we identify moisture advection as being dominant. Overall, we confirm the observability of IVT divergence with an uncertainty of around 25 %–50 % using a sequence of at least seven sondes per cross-section. Rather than sonde undersampling, it is the temporal AR evolution over the flight duration that leads to high deviations in divergence components. In order to realise the estimation of IVT divergence from dropsondes, flight planning should consider not only the sonde positioning, but also the minimisation of the flight duration. Our benchmarks quantify sonde-based uncertainties as essential preparatory work for the upcoming airborne closure of the moisture budget in Arctic ARs. [ABSTRACT FROM AUTHOR]

How air masses transform during meridional transport into and out of the Arctic is not well represented by numerical models. The airborne field campaign HALO- (AC)3 applied the High Altitude and Long-range Research Aircraft (HALO) within the framework of the collaborative research project on Arctic amplification (AC)3 to address this question by providing a comprehensive observational basis. The campaign took place from 7 March to 12 April 2022 in the North Atlantic sector of the Arctic, a main gateway of atmospheric transport into and out of the Arctic. Here, we investigate to which degree the meteorological and sea ice conditions during the campaign align with the long-term climatology (1979–2022). For this purpose, we use the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis v5 (ERA5), satellite data, and measurements at Ny-Ålesund, including atmospheric soundings. The observations and reanalysis data revealed two distinct periods with different weather conditions during HALO- (AC)3 : the campaign started with a warm period (11–20 March 2022) where strong southerly winds prevailed that caused poleward transport of warm and moist air masses, so-called moist and warm air intrusions (WAIs). Two WAI events were identified as atmospheric rivers (ARs), which are narrow bands of strong moisture transport. These warm and moist air masses caused the highest measured 2 m temperatures (5.5 °C) and daily precipitation rates (42 mm d -1) at Ny-Ålesund for March since the beginning of the record (1993). Over the sea ice northwest of Svalbard, ERA5 indicated record-breaking rainfall. After the passage of a strong cyclone on 21 March 2022, a cold period followed. Northerly winds advected cold air into the Fram Strait, causing marine cold air outbreaks (MCAOs) until the end of the campaign. This second phase included one of the longest MCAO events found in the ERA5 record (19 d). On average, the entire campaign period was warmer than the climatological mean due to the strong influence of the ARs. In the Fram Strait, the sea ice concentration was well within the climatological variability over the entire campaign duration. However, during the warm period, a large polynya opened northeast of Svalbard, untypical for this season. Compared to previous airborne field campaigns focusing on the evolution of (mixed-phase) clouds, a larger variety of MCAO conditions was observed during HALO- (AC)3. In summary, air mass transport into and out of the Arctic was more pronounced than usual, providing exciting prospects for studying air mass transformation using HALO- (AC)3. [ABSTRACT FROM AUTHOR]

Fog holes were reported over cities of the Indo‐Gangetic plains of India, which were attributed to the urban heat island (UHI) effect. The present study reports the observational evidence of fog holes over rural area using satellite and ground observations. Delayed onset and early dissipation of fog is observed over the holes. Numerical simulations demonstrate that aerosol‐radiation interaction (ARI) leads to fog holes over both urban and rural regions. The anthropogenic aerosols and associated ARI dominate the UHI effect over the urban fog holes, while the aerosol absorption due to ARI mainly controls the rural fog holes. Turning off aerosol absorption causes ∼ 2 hours delay in the fog dissipation over urban area, whereas it yields persistent fog over rural area under saturated environment. An enhancement of soluble Aitken black carbon over the fog holes indicates the importance of aging process during fog dissipation. Plain Language Summary: This study reports the occurrence of fog holes over rural and urban regions and investigates the mechanism behind the formation of fog holes using DM‐Chem. The main reason behind the fog hole formation over Indo‐Gangetic plains is the absorption of radiation by the total black carbon aerosols. The absence of the absorbing component of aerosol‐radiation interaction leads to the occurrence of fog over both the urban and rural hole areas. The fog hole areas are correlated with an enhanced formation of small sized soluble black carbon aerosols. These findings suggest the need for detailed aging processes of carbonaceous particles in atmospheric models. Key Points: Fog holes over the rural regions reported for the first timeDelayed onset and early dissipation of fog over the hole regionsAerosol radiation effect (absorption) dominates over the urban heat island effect [ABSTRACT FROM AUTHOR]

Warm-air intrusions (WAIs) are responsible for the transportation of warm and moist air masses from the mid-latitudes into the high Arctic (> 70° N). In this work, we study cirrus clouds that form during WAI events (WAI cirrus) and during undisturbed Arctic conditions (AC cirrus) and investigate possible differences between the two cloud types based on their macrophysical and optical properties with a focus on relative humidity over ice (RHi). We use airborne measurements from the combined high-spectral-resolution and differential-absorption lidar, WALES, performed during the HALO-(AC) 3 campaign. We classify each research flight and the measured clouds as either AC or WAI, based on the ambient conditions, and study the macrophysical, geometrical and optical characteristics for each cirrus group. As our main parameter we choose the relative humidity over ice (RHi), which we calculate RHi by combining the lidar water vapor measurements with model temperatures. Ice formation occurs at certain RHi values depending on the dominant nucleation process taking place. RHi can thus be used as an indication of the nucleation process and the structure of cirrus clouds. We find that during WAI events the Arctic is warmer and moister and WAI cirrus clouds are both geometrically and optically thicker compared to AC cirrus. WAI cirrus clouds and the layer directly surrounding them are more frequently supersaturated, also at high supersaturations over the threshold for homogeneous ice nucleation (HOM). AC cirrus clouds have a supersaturation-dominated cloud top and a subsaturated cloud base. WAI cirrus clouds also have high supersaturations at cloud top but also at cloud base. [ABSTRACT FROM AUTHOR]

Mixed-phase clouds (MPCs) are key players in the Arctic climate system due to their role in modulating solar and terrestrial radiation. Such radiative interactions rely, among other factors, on the ice content of MPCs, which is regulated by the availability of ice-nucleating particles (INPs). While it appears that INPs are associated with the presence of primary biological aerosol particles (PBAPs) in the Arctic, the nuances of the processes and patterns of INPs and their association with clouds and moisture sources have not been resolved. Here, we investigated for a full year the abundance of and variability in fluorescent PBAPs (fPBAPs) within cloud residuals, directly sampled by a multiparameter bioaerosol spectrometer coupled to a ground-based counterflow virtual impactor inlet at the Zeppelin Observatory (475 m a.s.l.) in Ny-Ålesund, Svalbard. fPBAP concentrations (10 -3 –10 -2 L -1) and contributions to coarse-mode cloud residuals (0.1 to 1 in every 10 3 particles) were found to be close to those expected for high-temperature INPs. Transmission electron microscopy confirmed the presence of PBAPs, most likely bacteria, within one cloud residual sample. Seasonally, our results reveal an elevated presence of fPBAPs within cloud residuals in summer. Parallel water vapor isotope measurements point towards a link between summer clouds and regionally sourced air masses. Low-level MPCs were predominantly observed at the beginning and end of summer, and one explanation for their presence is the existence of high-temperature INPs. In this study, we present direct observational evidence that fPBAPs may play an important role in determining the phase of low-level Arctic clouds. These findings have potential implications for the future description of sources of ice nuclei given ongoing changes in the hydrological and biogeochemical cycles that will influence the PBAP flux in and towards the Arctic. [ABSTRACT FROM AUTHOR]

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 Wm-2. Above open ocean, the agreement is closer, with an overestimation of 28 Wm-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 Wm-2 above sea ice and a larger bias of 48 Wm-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. [ABSTRACT FROM AUTHOR]

Temperature and water vapor profiles are essential to climate change studies and weather forecasting. Hyperspectral instruments are of great value for retrieving temperature and water vapor profiles, enabling accurate monitoring of their changes. Successful retrievals of temperature and water vapor profiles require accuracy of hyperspectral radiometer measurements. In this study, the radiometric accuracy of an airborne hyperspectral microwave radiometer, the High Spectral Resolution Airborne Microwave Sounder (HiSRAMS), and a ground-based hyperspectral infrared radiometer, the Atmospheric Emitted Radiance Interferometer (AERI), is simultaneously assessed by performing radiative closure tests under clear-sky conditions in Ottawa, Canada. As an airborne instrument, HiSRAMS has two radiometers measuring radiance in the oxygen band (49.6–58.3 GHz) and water vapor band (175.9–184.6 GHz) for zenith-pointing and nadir-pointing observations. AERI provides ground-based, zenith-pointing radiance measurements between 520 and 1800 cm -1. A systematic warm radiance bias is present in AERI observations in the window band. Upon removal of this bias, improved radiative closure was attained in the window band. The brightness temperature (BT) bias in nadir-pointing HiSRAMS observations is smaller than at the zenith. A novel but straightforward method is developed to diagnose the radiometric accuracy of the two instruments in comparison based on the relationship between radiometric bias and optical depth. Compared to AERI, HiSRAMS demonstrates similar radiometric accuracy for nadir-pointing measurements but exhibits relatively poor accuracy for zenith-pointing measurements, which requires further characterization. Future work on temperature and water vapor concentration retrievals using HiSRAMS and AERI is warranted. [ABSTRACT FROM AUTHOR]

Turbulence in clouds is known to enhance particle collision rates, as widely demonstrated for warm rain formation. A similar impact on ice growth processes is expected but a solid observational basis is missing. A statistical analysis of a 15‐month data set of cloud radar observations allows for the first time to quantify the impact of turbulence on ice aggregation and riming in Arctic low‐level mixed‐phase clouds. Increasing eddy dissipation rate (EDR), from below 10−4 to above 10−3 m2 s−3, yields larger ice aggregates, and higher particle concentration, likely caused by increasing fragmentation. In conditions more favorable to riming, higher EDR is associated with dramatically higher particle fall velocities (by up to 125%), under similar liquid water paths, indicative of markedly higher degrees of riming. Our findings thus reveal the key role of turbulence for cold precipitation formation, and highlight the need for an improved understanding of turbulence‐hydrometeor interactions in cold clouds. Plain Language Summary: Liquid and frozen precipitation mainly forms by collision and subsequent aggregation of small particles. Collisions between cloud particles, such as droplets and ice crystals, are thought to be increased by turbulence. While this effect has been intensively studied for liquid‐only clouds, the impact of turbulence on ice‐ice collisional growth (aggregation) and ice‐liquid collisional growth (riming) is expected but has so far been poorly quantified. We study the effect of turbulence on aggregation and riming based on a long‐term remote‐sensing data set of low‐level clouds containing both ice and liquid particles, recorded at the Arctic site of Ny‐Ålesund, Svalbard. Cloud radar observations are used to retrieve the dissipation rate of turbulent kinetic energy (i.e., the eddy dissipation rate; EDR), which is the relevant quantity driving increases in collision rates, and to characterize ice particle properties. We find evidence that higher EDR regimes enhance the aggregation of particles, and are associated with signatures of increased ice particle concentration, possibly caused by the production of particle fragments upon collision. In temperature regimes more favorable to riming, turbulence dramatically enhances the particles' fall velocity, denoting higher degrees of riming. Our findings thus highlight a key role of turbulence for the formation of precipitable ice. Key Points: Relation between turbulence and ice growth investigated based on long‐term remote sensing data set of Arctic low‐level mixed‐phase cloudsHigher eddy dissipation rate (EDR) correlates with larger ice aggregates, and possibly higher degrees of fragmentationHigh EDR is an essential component needed for the formation of rimed particles [ABSTRACT FROM AUTHOR]

The global warming is amplified in the Arctic. To collect data that help to constrain weather and climate models, which often do not realistically represent the enhanced Arctic warming, the HALO-(AC)³ aircraft campaign was conducted in March and April 2022 over the Norwegian and Greenland Seas, the Fram Strait, and the central Arctic Ocean. 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 have been employed. Whenever possible, the three aircraft were flown in collocated formation. The campaign focused on one specific challenge posed by the models: The reasonable representation of transformations of air masses during their meridional transport into (northward by moist and warm air intrusions, WAIs) and out of (southward via marine cold air outbreaks, CAOs) the Arctic. To observe the air mass transformations, a quasi-Lagrangian flight strategy using trajectory calculations was realized enabling to sample the moving air mass parcels twice along their trajectories. Eight distinct WAI and 12 CAO cases were probed extensively. From the quasi-Lagrangian measurements, we have derived the diabatic heating and moistening of the moving air masses during CAOs and WAIs, the development of cloud macrophysical and microphysical properties along the southward pathways of the air masses during CAOs, and the moisture budget of WAIs. As an example result, we have obtained typical values of the surface-driven diabatic heating between 1–3 K h-1 and of the near-surface moistening between 0.05–0.3 g kg-1 h-1 within the lowest about 0.5 km. From the observations of WAIs, a weak diabatic cooling 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 km altitude were derived. In addition, we discuss the frequency of occurrence of the different thermodynamic phases of Arctic low-level clouds, the interaction of Arctic cirrus with sea ice, water vapor, and aerosol particles, and the characteristic microphysical and chemical properties of Arctic aerosol particles. Finally, we provide proof of a concept to measure mesoscale divergence and subsidence in the Arctic using data from dropsondes released during circular flight patterns. [ABSTRACT FROM AUTHOR]

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 Kh-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 gkg-1 versus 0.069 gkg-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 FROM AUTHOR]

Upcoming submillimeter wave satellite missions require an improved understanding of the sea ice emissivity to separate atmospheric and surface microwave signals under dry polar conditions. This work investigates hectometer-scale airborne sea ice emissivity observations between 89 and 340 GHz combined with high-resolution visual imagery from two Arctic airborne field campaigns in summer 2017 and spring 2019 northwest of Svalbard, Norway. We identify four distinct sea ice emissivity spectra through K-Means clustering, which occur predominantly over multiyear ice, first-year ice, young ice, and nilas. Nilas features the highest, and multiyear ice features the lowest emissivity among the clusters. Each cluster exhibits similar nadir emissivity distributions from 183 to 340 GHz. To relate hectometer-scale airborne to kilometer-scale satellite footprints, we quantify the reduction of airborne emissivity variability with increasing footprint size. At 340 GHz, the emissivity interquartile range decreases by almost half from the hectometer scale to a footprint of 16 km, typical for satellite instruments. Furthermore, we collocate the airborne observations with polar-orbiting satellite observations. After resampling, the absolute relative bias between airborne and satellite emissivities at similar channels lies below 3 %. Additionally, spectral nadir emissivity variations on the satellite scale are low, with slightly decreasing emissivity from 183 to 243 GHz, which occurs for all hectometer-scale clusters except for predominantly multiyear ice. Our results will enable the development of microwave retrievals and assimilation over sea ice from current and future satellite missions such as Ice Cloud Imager (ICI) and European Polar System (EPS) Sterna. [ABSTRACT FROM AUTHOR]

An accurate representation of the annual evolution of surface albedo of the Arctic Ocean, especially during the melting period, is crucial to obtain reliable climate model predictions in the Arctic. Therefore, the output of the surface albedo scheme of a coupled regional climate model (HIRHAM–NAOSIM) was evaluated against airborne and ground-based measurements. The observations were conducted during five aircraft campaigns in the European Arctic at different times of the year between 2017 and 2022; one of them was part of the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition in 2020. We applied two approaches for the evaluation: (a) relying on measured input parameters of surface type fraction and surface skin temperature (offline) and (b) using HIRHAM–NAOSIM simulations independently of observational data (online). From the offline method we found a seasonally dependent bias between measured and modeled surface albedo. In spring, the cloud effect on surface broadband albedo was overestimated by the surface albedo parametrization (mean albedo bias of 0.06), while the surface albedo scheme for cloudless cases reproduced the measured surface albedo distributions for all seasons. The online evaluation revealed an overestimation of the modeled surface albedo resulting from an overestimation of the modeled cloud cover. Furthermore, it was shown that the surface type parametrization contributes significantly to the bias in albedo, especially in summer (after the drainage of melt ponds) and autumn (onset of refreezing). The lack of an adequate model representation of the surface scattering layer, which usually forms on bare ice in summer, contributed to the underestimation of surface albedo during that period. The difference between modeled and measured net irradiances for selected flights during the five airborne campaigns was derived to estimate the impact of the model bias for the solar radiative energy budget at the surface. We revealed a negative bias between modeled and measured net irradiances (median: -6.4 W m -2) for optically thin clouds, while the median value of only 0.1 W m -2 was determined for optically thicker clouds. [ABSTRACT FROM AUTHOR]

The Arctic experiences remarkable changes in environmental parameters that affect fluctuations in the surface energy budget, including radiation and sensible and latent heat fluxes. Cold air masses and cloud transformations during marine cold air outbreaks (MCAOs) substantially influence the radiative fluxes, thereby shaping the link between large-scale dynamics, sea ice conditions, and the surface energy budget. In this study, we investigate various cloud characteristics during intense MCAOs over the Barents Sea from 2000 to 2018 using satellite data. We identify 72 intense MCAO events that propagated southward using reanalysis data of the surface temperature and potential temperature at the 800 hPa level. We investigate the macro- and microphysical parameters and radiative properties of clouds within selected MCAOs, their dependence on sea ice concentration, and their initial air mass properties using satellite data. A significant increase in low-level clouds near the ice edge (up to +25% anomalies) and a smooth transition to upper-level clouds is revealed. The total cloud top height during intense MCAOs is generally 500–700 m lower than under neutral conditions. MCAOs induce a positive net cloud radiative effect, which peaks at +20 W m−2 (100 km from the ice edge) and gradually decreases towards the continent (−2.3 W m−2 per 100 km). Our study provides evidence for the importance of changes in the cloud radiative effect within MCAOs, which should be accurately simulated in regional and global climate models. [ABSTRACT FROM AUTHOR]

Riming is a key precipitation formation process in mixed-phase clouds which efficiently converts cloud liquid to ice water. Here, we present two methods to quantify riming of ice particles from airborne observations with the normalized rime mass, which is the ratio of rime mass to the mass of a size-equivalent spherical graupel particle. We use data obtained during the HALO-(AC) 3 aircraft campaign, where two aircraft collected radar and in situ measurements that were closely spatially and temporally collocated over the Fram Strait west of Svalbard in spring 2022. The first method is based on an inverse optimal estimation algorithm for the retrieval of the normalized rime mass from a closure between cloud radar and in situ measurements during these collocated flight segments (combined method). The second method relies on in situ observations only, relating the normalized rime mass to optical particle shape measurements (in situ method). We find good agreement between both methods during collocated flight segments with median normalized rime masses of 0.024 and 0.021 (mean values of 0.035 and 0.033) for the combined and in situ method, respectively. Assuming that particles with a normalized rime mass smaller than 0.01 are unrimed, we obtain average rimed fractions of 88 % and 87 % over all collocated flight segments. Although in situ measurement volumes are in the range of a few cubic centimeters and are therefore much smaller than the radar volume (about 45 m footprint diameter at an altitude of 500 m above ground, with a vertical resolution of 5 m), we assume they are representative of the radar volume. When this assumption is not met due to less homogeneous conditions, discrepancies between the two methods result. We show the performance of the methods in a case study of a collocated segment of cold-air outbreak conditions and compare normalized rime mass results with meteorological and cloud parameters. We find that higher normalized rime masses correlate with streaks of higher radar reflectivity. The methods presented improve our ability to quantify riming from aircraft observations. [ABSTRACT FROM AUTHOR]

Clouds play an important role in controlling the radiative energy budget of the Arctic atmospheric boundary layer. To quantify the impact of clouds on the radiative heating or cooling of the lower atmosphere and of the surface, vertical profile observations of thermal-infrared irradiances were collected using a radiation measurement system carried by a tethered balloon. We present 70 profiles of thermal-infrared radiative quantities measured in summer 2020 during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition and in autumn 2021 and spring 2022 in Ny-Ålesund, Svalbard. Measurements are classified into four groups: cloudless, low-level liquid-bearing cloud, elevated liquid-bearing cloud, and elevated ice cloud. Cloudless cases display an average radiative cooling rate of about - 2 K d -1 throughout the atmospheric boundary layer. Instead, low-level liquid-bearing clouds are characterized by a radiative cooling up to - 80 K d -1 within a shallow layer at cloud top, while no temperature tendencies are identified underneath the cloud layer. Radiative transfer simulations are performed to quantify the sensitivity of radiative cooling rates to cloud microphysical properties. In particular, cloud top cooling is strongly driven by the liquid water path, especially in optically thin clouds, while for optically thick clouds the cloud droplet number concentration has an increased influence. Additional radiative transfer simulations are used to demonstrate the enhanced radiative importance of the liquid relative to ice clouds. To analyze the temporal evolution of thermal-infrared radiation profiles during the transitions from a cloudy to a cloudless atmosphere, a respective case study is investigated. [ABSTRACT FROM AUTHOR]

Quantifying the role of clouds in the earth's radiation budget is essential for improving our understanding of the drivers and feedback mechanisms of climate change. This holds in particular for the Arctic, the region currently undergoing the most rapid changes. This region, however, also poses significant challenges to remote-sensing retrievals of clouds and radiative fluxes, introducing large uncertainties in current climate data records. In particular, low-level stratiform clouds are common in the Arctic but are, due to their low altitude, challenging to observe and characterize with remote-sensing techniques. The availability of reliable ground-based observations as reference is thus of high importance. In the present study, radiative transfer simulations using state-of-the-art ground-based remote sensing of clouds are contrasted with surface radiative flux measurements to assess their ability to constrain the cloud radiative effect. Cloud radar, lidar, and microwave radiometer observations from the PS106 cruise in the Arctic marginal sea ice zone in summer 2017 were used to derive cloud micro- and macrophysical properties by means of the instrument synergy approach of Cloudnet. Closure of surface radiative fluxes can only be achieved by a realistic representation of the low-level liquid-containing clouds in the radiative transfer simulations. The original, most likely erroneous, representation of these low-level clouds in the radiative transfer simulations led to errors in the cloud radiative effect of 54 W m -2. In total, the proposed method could be applied to 11 % of the observations. For the data, where the proposed method was utilized, the average relative error decreased from 109 % to 37 % for the simulated solar and from 18 % to 2.5 % for the simulated terrestrial downward radiative fluxes at the surface. The present study highlights the importance of jointly improving retrievals for low-level liquid-containing clouds which are frequently encountered in the high Arctic, together with observational capabilities both in terms of cloud remote sensing and radiative flux observations. Concrete suggestions for achieving these goals are provided. [ABSTRACT FROM AUTHOR]

Intense air mass transformations take place when cold, dry Arctic air masses move southward from the closed sea ice onto the much warmer ice-free Arctic ocean during marine cold air outbreaks (MCAOs). In spite of intensive research on MCAOs during recent years, the temporal rates of diabatic heating and moisture uptake relevant also for cloud formation/dissipation have not been measured along MCAO flows. Instead, reanalyses have typically been used for climatological investigations of MCAOs or to supply higher-resolution models with lateral boundary conditions and time-dependent forcings. Meanwhile, the uncertainties connected to those datasets remain unclear. Here, we present height-resolved observations of diabatic heating rates, moisture uptake, and cloud evolution measured in a quasi-Lagrangian manner. The investigated specific MCAO was observed on 01 April 2022 during the HALO-(AC)3 airborne campaign that was conducted in spring 2022. Shortly after passing the ice edge, maximum diabatic heating rates larger than 6 K h−1 and moisture uptake of more than 0.3 g kg−1 h−1 were measured close above the ocean surface. As the air mass continued its drift southwards, clouds started to form and vertical mixing within the steadily deepening boundary layer was intensified. The quasi-Lagrange observations are compared with reanalysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF) latest global reanalysis ERA5 and the Copernicus Arctic Regional Reanalysis (CARRA). It was found that the mean absolute errors (MAEs) of ERA5 versus CARRA data are 60 % higher for air temperature over sea ice (1.4 K versus 0.9 K), and 70 % higher for specific humidity over ice-free ocean (0.12 g kg−1 versus 0.07 g kg−1). We relate these differences not only to issues with representations of the marginal ice zone and corresponding surface fluxes in ERA5, but also to the cloud scheme producing excess liquid-bearing clouds and precipitation, causing a too-dry marine boundary layer. Overall, the combination of CARRA's high spatial resolution, an improved handling of cold surfaces, and the demonstrated higher fidelity towards the observations, make it a well-suited candidate for further investigations of Arctic air mass transformations. [ABSTRACT FROM AUTHOR]

Carbohydrates, originating from marine microorganisms, enter the atmosphere as part of sea spray aerosol (SSA) and can influence fog and cloud microphysics as cloud condensation nuclei (CCN) or ice-nucleating particles (INP). Particularly in the remote Arctic region, significant knowledge gaps persist about the sources, the sea-to-air transfer mechanisms, atmospheric concentrations, and processing of this substantial organic group. In this ship-based field study conducted from May to July 2017 in the Fram Strait, Barents Sea, and central Arctic Ocean, we investigated the sea-to-air transfer of marine combined carbohydrates (CCHO) from concerted measurements of the bulk seawater, the sea surface microlayer (SML), aerosol particles and fog. Our results reveal a wide range of CCHO concentrations in seawater (22–1070 µ g L -1), with notable variations among different sea-ice-related sea surface compartments. Enrichment factors in the sea surface microlayer (SML) relative to bulk water exhibited variability in both dissolved (0.4–16) and particulate (0.4–49) phases, with the highest values in the marginal ice zone (MIZ) and aged melt ponds. In the atmosphere, CCHO was detected in super- and submicron aerosol particles (CCHO aer,super : 0.07–2.1 ng m -3 ; CCHO aer,sub : 0.26–4.4 ng m -3) and fog water (CCHO fog,liquid : 18–22 000 µ g L -1 ; CCHO fog,atmos : 3–4300 ng m -3). Enrichment factors for sea–air transfer varied based on assumed oceanic emission sources. Furthermore, we observed rapid atmospheric aging of CCHO, indicating both biological/enzymatic processes and abiotic degradation. This study highlights the diverse marine emission sources in the Arctic Ocean and the atmospheric processes shaping the chemical composition of aerosol particles and fog. [ABSTRACT FROM AUTHOR]

This study evaluates methods to derive the surface mixing layer (SML) height of the Arctic atmospheric boundary layer (ABL) using in situ measurements inside the Arctic ABL during winter and the transition period to spring. An instrumental payload carried by a tethered balloon was used for the measurements between December 2019 and May 2020 during the year-long Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. Vertically highly resolved (centimeter scale) in situ profile measurements of mean and turbulent parameters were obtained, reaching from the sea ice to several hundred meters above ground. Two typical conditions of the Arctic ABL over sea ice were identified: cloudless situations with a shallow surface-based inversion and cloudy conditions with an elevated inversion. Both conditions are associated with significantly different SML heights whose determination as accurately as possible is of great importance for many applications. We used the measured turbulence profile data to define a reference of the SML height. With this reference, a more precise critical bulk Richardson number of 0.12 was derived, which allows an extension of the SML height determination to regular radiosoundings. Furthermore, we have tested the applicability of the Monin–Obukhov similarity theory to derive SML heights based on measured turbulent surface fluxes. The application of the different approaches and their advantages and disadvantages are discussed. [ABSTRACT FROM AUTHOR]

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 µ m), optical thickness (11.8) and effective liquid water path (72.3 g m -2) compared to spring conditions (8.7 µ m, 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. [ABSTRACT FROM AUTHOR]

Intense air mass transformations take place when cold, dry Arctic air masses move southward from the closed sea ice onto the much warmer ice-free Arctic ocean during marine cold air outbreaks (MCAOs). In spite of intensive research on MCAOs during recent years, the temporal rates of diabatic heating and moisture uptake relevant also for cloud formation/dissipation have not been measured along MCAO flows. Instead, reanalyses have typically been used for climatological investigations of MCAOs or to supply higher resolution models with lateral boundary conditions and time-dependent forcings. Meanwhile, the uncertainties connected to those datasets remain unclear. Here, we present height-resolved observations of diabatic heating rates, moisture uptake, and cloud evolution measured in a quasi-Lagrangian manner. The investigated specific MCAO was observed on 01 April 2022 during the HALO-(AC) airborne campaign that was conducted in spring 2022. Shortly after passing the ice edge, maximum diabatic heating rates larger than 6Kh-1and moisture uptake of more than 0.3 g kg-1 h-1were measured close above the ocean surface. As the air mass continued its drift southwards, clouds started to form and vertical mixing within the steadily deepening boundary layer was intensified. The quasi-Lagrange observations are compared with reanalysis data from the European Centre for Medium-RangeWeather Forecasts (ECMWF) latest global reanalysis ERA5 and the Copernicus Arctic Regional Reanalysis (CARRA). It was found that the mean absolute errors (MAEs) of ERA5 versus CARRA data are 60% higher for air temperature over sea ice (1.4K versus 0.9K), and 70% higher for specific humidity over ice-free ocean (0.12 g kg-1versus 0.07 g kg-1). We relate these differences not only to issues with representations of the marginal ice zone and corresponding surface fluxes in ERA5, but also to the cloud scheme producing excess liquid-bearing clouds and precipitation, causing a too-dry marine boundary layer. Overall, the combination of CARRA's high spatial resolution, an improved handling of cold surfaces, and the demonstrated higher fidelity towards the observations, make it a well-suited candidate for further investigations of Arctic air mass transformations. [ABSTRACT FROM AUTHOR]

Warm Air Intrusions (WAI) are responsible for the transportation of warm and moist airmasses from the mid-latitudes into the high arctic (>70° N). In this work, we study cirrus clouds that form during WAI events (WAI cirrus) and during undisturbed arctic conditions (AC cirrus) and investigate possible differences between the two cloud types based on their macrophysical and optical properties with a focus on Relative Humidity over ice (RHi). We use airborne measurements from the combined high spectral resolution and differential absorption lidar, WALES, performed during the HALO-(AC)3 campaign. We classify each research flight and the measured clouds as either AC or WAI, based on the ambient conditions and study the macrophysical, geometrical and optical characteristics for each cirrus group. As our main parameter we choose the Relative Humidity over ice (RHi) which we calculate RHi by combining the lidar water vapor measurements with model temperatures. RHi is affected by and can be used as an indication of the nucleation process and the structure of cirrus clouds. We find that during WAI events the arctic is warmer and moister and WAI cirrus are both geometrically and optically thicker compared to AC cirrus. WAI cirrus and the layer directly surrounding them, are more frequently supersaturated, also at high supersaturations over the threshold for homogeneous ice nucleation (HOM). AC cirrus have a supersaturation dominated cloud top and a subsaturated cloud base. WAI cirrus also have high supersaturations at cloud top, but also at cloud base. [ABSTRACT FROM AUTHOR]

Mixed-phase clouds (MPC) are key players in the Arctic climate system due to their role in modulating solar and terrestrial radiation. Such radiative interactions critically rely on the ice content of MPC which, in turn, also depend on the availability of ice nucleating particles (INP). INP sources and concentrations are poorly understood in the Arctic. Recently, INP active at high temperatures were associated with the presence of primary biological aerosol particles (PBAP). Here, we investigated for a full year the abundance and variability of fluorescent PBAP (fPBAP) within cloud residuals, directly sampled by a multiparameter bioaerosol spectrometer coupled to a ground-based counterflow virtual impactor inlet at the Zeppelin Observatory (475 m asl), Ny-Ålesund, Svalbard. fPBAP concentrations (10-3–10-2 L-1) and contributions to coarse-mode aerosol (0.1 to 1 in every 103 particles) within cloud residuals were found to be close to those expected for concentrations of high-temperature INP. Transmission electron microscopy also confirmed the presence of fPBAP, most likely bacteria, within the cloud residual samples. Seasonally, our results reveal an elevated presence of fPBAP within cloud residuals in summer. Parallel water vapor isotope measurements point towards a link between summer clouds and regionally sourced air masses. Low-level MPC were predominantly observed at the beginning and end of summer, and one explanation for their presence is the existence of high-temperature INP. In this study, we present observational evidence that fPBAP may play an important role in determining the phase of low-level Arctic clouds. These findings have potential implications for the future description of sources of cloud condensation nuclei given ongoing changes in the hydrological and biogeochemical cycles that will influence the PBAP flux in and towards the Arctic. [ABSTRACT FROM AUTHOR]

We present a comprehensive quality-controlled 15-month dataset of remote sensing observations of low-level mixed-phase clouds (LLMPCs) taken at the high Arctic site of Ny-Ålesund, Svalbard, Norway. LLMPCs occur frequently in the Arctic region and extensively affect the energy budget. However, our understanding of the ice microphysical processes taking place in these clouds is incomplete. The dual-wavelength and polarimetric Doppler cloud radar observations, which are the cornerstones of the dataset, provide valuable fingerprints of ice microphysical processes, and the high number of cases included allows for the compiling of robust statistics for process studies. The radar data are complemented with thermodynamic retrievals from a microwave radiometer, liquid base height from a ceilometer, and wind fields from large-eddy simulations. All data are quality controlled, especially the cloud radar data, which are accurately calibrated, matched, and corrected for gas and liquid-hydrometeor attenuation, ground clutter, and range folding. We finally present an analysis of the temperature dependence of Doppler, dual-wavelength, and polarimetric radar variables, to illustrate how the dataset can be used for cloud microphysical studies. The dataset has been published in and is freely available at: 10.5281/zenodo.7803064. [ABSTRACT FROM AUTHOR]

The Earth Cloud, Aerosol and Radiation Explorer (EarthCARE) is a combination of multiple active and passive instruments on a single platform. The Atmospheric Lidar (ATLID) provides vertical information of clouds and aerosol particles along the satellite track. In addition, the Multi-Spectral Imager (MSI) collects multi-spectral information from the visible to the infrared wavelengths over a swath width of 150 km across the track. The ATLID–MSI Column Products processor (AM-COL) described in this paper combines the high vertical resolution of the lidar along track and the horizontal resolution of the imager across track to better characterize a three-dimensional scene. ATLID Level 2a (L2a) data from the ATLID Layer Products processor (A-LAY), MSI L2a data from the MSI Cloud Products processor (M-CLD) and the MSI Aerosol Optical Thickness processor (M-AOT), and MSI Level 1c (L1c) data are used as input to produce the synergistic columnar products: the ATLID–MSI Cloud Top Height (AM-CTH) and the ATLID–MSI Aerosol Column Descriptor (AM-ACD). The coupling of ATLID (measuring at 355 nm) and MSI (at ≥670 nm) provides multi-spectral observations of the aerosol properties. In particular, the Ångström exponent from the spectral aerosol optical thickness (AOT 355/670 nm) adds valuable information for aerosol typing. The AOT across track, the Ångström exponent and the dominant aerosol type are stored in the AM-ACD product. The accurate detection of the cloud top height (CTH) with lidar is limited to the ATLID track. The difference in the CTH detected by ATLID and retrieved by MSI is calculated along track. The similarity of MSI pixels across track with those along track is used to transfer the calculated CTH difference to the entire MSI swath. In this way, the accuracy of the CTH is increased to achieve the EarthCARE mission's goal of deriving the radiative flux at the top of the atmosphere with an accuracy of 10 W m -2 for a 100 km 2 snapshot view of the atmosphere. The synergistic CTH difference is stored in the AM-CTH product. The quality status is provided with the products. It depends, e.g., on day/night conditions and the presence of multiple cloud layers. The algorithm was successfully tested using the common EarthCARE test scenes. Two definitions of the CTH from the model truth cloud extinction fields are compared: an extinction-based threshold of 20 Mm -1 provides the geometric CTH, and a cloud optical thickness threshold of 0.25 describes the radiative CTH. The first CTH definition was detected with ATLID and the second one with MSI. The geometric CTH is always higher than or equal to the radiative CTH. [ABSTRACT FROM AUTHOR]

To investigate the influence of sea ice openings like leads on wintertime Arctic clouds, the air mass transport is exploited as a heat and humidity feeding mechanism which can modify Arctic cloud properties. Cloud microphysical properties in the central Arctic are analysed as a function of sea ice conditions during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition in 2019–2020. The Cloudnet classification algorithm is used to characterize the clouds based on remote sensing observations and the atmospheric thermodynamic state from the observatory on board the research vessel (RV) Polarstern. To link the sea ice conditions around the observational site with the cloud observations, the water vapour transport (WVT) being conveyed towards RV Polarstern has been utilized as a mechanism to associate upwind sea ice conditions with the measured cloud properties. This novel methodology is used to classify the observed clouds as coupled or decoupled to the WVT based on the location of the maximum vertical gradient of WVT height relative to the cloud-driven mixing layer. Only a conical sub-sector of sea ice concentration (SIC) and the lead fraction (LF) centred on the RV Polarstern location and extending up to 50 km in radius and with an azimuth angle governed by the time-dependent wind direction measured at the maximum WVT is related to the observed clouds. We found significant asymmetries for cases when the clouds are coupled or decoupled to the WVT and selected by LF regimes. Liquid water path of low-level clouds is found to increase as a function of LF, while the ice water path does so only for deep precipitating systems. Clouds coupled to WVT are found to generally have a lower cloud base and larger thickness than decoupled clouds. Thermodynamically, for coupled cases the cloud-top temperature is warmer and accompanied by a temperature inversion at the cloud top, whereas the decoupled cases are found to be closely compliant with the moist adiabatic temperature lapse rate. The ice water fraction within the cloud layer has been found to present a noticeable asymmetry when comparing coupled versus decoupled cases. This novel approach of coupling sea ice to cloud properties via the WVT mechanism unfolds a new tool to study Arctic surface–atmosphere processes. With this formulation, long-term observations can be analysed to enforce the statistical significance of the asymmetries. Furthermore, our results serve as an opportunity to better understand the dynamic linkage between clouds and sea ice and to evaluate its representation in numerical climate models for the Arctic system. [ABSTRACT FROM AUTHOR]

The simulations of upward and downward irradiances by the Integrated Forecasting System (IFS) of the European Centre for Medium-Range Weather Forecasts are compared to broadband solar irradiance measurements from the Arctic CLoud Observations Using airborne measurements during polar Day (ACLOUD) campaign. For this purpose, offline radiative transfer simulations with the ecRad radiation scheme using the operational IFS output were performed. 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 Wm−2. Above open ocean, the agreement is closer with an overestimation of 29 Wm−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 Wm−2 above sea ice and a larger bias of 48 Wm−2 above open ocean by increasing the range from 36–69 cm−3 to 36–200 cm−3. Above sea ice, realistic surface albedos, cloud droplet number concentrations and liquid water paths contribute most to a bias improvement. Above open ocean, realistic cloud fractions and liquid water paths are most important to reduce the model-observation differences. [ABSTRACT FROM AUTHOR]

Despite their proven importance for the atmospheric radiative energy budget, the effect of cirrus on climate and the magnitude of their modification by human activity is not well quantified. Besides anthropogenic pollution sources on the ground, aviation has a large local effect on cirrus microphysical and radiative properties via the formation of contrails and their transition to contrail cirrus. To investigate the anthropogenic influence on natural cirrus, we compare the microphysical properties of cirrus measured at mid-latitude (ML) regions (<60 ∘ N) that are often affected by aviation and pollution with cirrus measured in the same season in comparatively pristine high latitudes (HLs; ≥60 ∘ N). The number concentration, effective diameter, and ice water content of the observed cirrus are derived from in situ measurements covering ice crystal sizes between 2 and 6400 µm collected during the CIRRUS-HL campaign (Cirrus in High Latitudes) in June and July 2021. We analyse the dependence of cirrus microphysical properties on altitude and latitude and demonstrate that the median ice number concentration is an order of magnitude larger in the measured mid-latitude cirrus, with 0.0086 cm-3 , compared to the high-latitude cirrus, with 0.001 cm-3. Ice crystals in mid-latitude cirrus are on average smaller than in high-latitude cirrus, with a median effective diameter of 165 µm compared to 210 µm , and the median ice water content in mid-latitude cirrus is higher (0.0033 gm-3) than in high-latitude cirrus (0.0019 gm-3). In order to investigate the cirrus properties in relation to the region of formation, we combine the airborne observations with 10 d backward trajectories to identify the location of cirrus formation and the cirrus type, i.e. in situ or liquid origin cirrus, depending on whether there is only ice or also liquid water present in the cirrus history, respectively. The cirrus formed and measured at mid-latitudes (M–M) have a particularly high ice number concentration and low effective diameter. This is very likely a signature of contrails and contrail cirrus, which is often observed in the in situ origin cirrus type. In contrast, the largest effective diameter and lowest number concentration were found in the cirrus formed and measured at high latitudes (H–H) along with the highest relative humidity over ice (RHi). On average, in-cloud RHi was above saturation in all cirrus. While most of the H–H cirrus were of an in situ origin, the cirrus formed at mid-latitudes and measured at high latitudes (M–H) were mainly of liquid origin. A pristine Arctic background atmosphere with relatively low ice nuclei availability and the extended growth of few nucleated ice crystals may explain the observed RHi and size distributions. The M–H cirrus are a mixture of the properties of M–M and H–H cirrus (preserving some of the initial properties acquired at mid-latitudes and transforming under Arctic atmospheric conditions). Our analyses indicate that part of the cirrus found at high latitudes is actually formed at mid-latitudes and therefore affected by mid-latitude air masses, which have a greater anthropogenic influence. [ABSTRACT FROM AUTHOR]

The MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) expedition was the largest Arctic field campaign ever conducted. MOSAiC offered the unique opportunity to monitor and characterize aerosols and clouds with high vertical resolution up to 30 km height at latitudes from 80 to 90 ∘ N over an entire year (October 2019 to September 2020). Without a clear knowledge of the complex aerosol layering, vertical structures, and dominant aerosol types and their impact on cloud formation, a full understanding of the meteorological processes in the Arctic, and thus advanced climate change research, is impossible. Widespread ground-based in situ observations in the Arctic are insufficient to provide these required aerosol and cloud data. In this article, a summary of our MOSAiC observations of tropospheric aerosol profiles with a state-of-the-art multiwavelength polarization Raman lidar aboard the icebreaker Polarstern is presented. Particle optical properties, i.e., light-extinction profiles and aerosol optical thickness (AOT), and estimates of cloud-relevant aerosol properties such as the number concentration of cloud condensation nuclei (CCN) and ice-nucleating particles (INPs) are discussed, separately for the lowest part of the troposphere (atmospheric boundary layer, ABL), within the lower free troposphere (around 2000 m height), and at the cirrus level close to the tropopause. In situ observations of the particle number concentration and INPs aboard Polarstern are included in the study. A strong decrease in the aerosol amount with height in winter and moderate vertical variations in summer were observed in terms of the particle extinction coefficient. The 532 nm light-extinction values dropped from >50 Mm -1 close to the surface to <5 Mm -1 at 4–6 km height in the winter months. Lofted, aged wildfire smoke layers caused a re-increase in the aerosol concentration towards the tropopause. In summer (June to August 2020), much lower particle extinction coefficients, frequently as low as 1–5 Mm -1 , were observed in the ABL. Aerosol removal, controlled by in-cloud and below-cloud scavenging processes (widely suppressed in winter and very efficient in summer) in the lowermost 1–2 km of the atmosphere, seems to be the main reason for the strong differences between winter and summer aerosol conditions. A complete annual cycle of the AOT in the central Arctic could be measured. This is a valuable addition to the summertime observations with the sun photometers of the Arctic Aerosol Robotic Network (AERONET). In line with the pronounced annual cycle in the aerosol optical properties, typical CCN number concentrations (0.2 % supersaturation level) ranged from 50–500 cm -3 in winter to 10–100 cm -3 in summer in the ABL. In the lower free troposphere (at 2000 m), however, the CCN level was roughly constant throughout the year, with values mostly from 30 to 100 cm -3. A strong contrast between winter and summer was also given in terms of ABL INPs which control ice production in low-level clouds. While soil dust (from surrounding continents) is probably the main INP type during the autumn, winter, and spring months, local sea spray aerosol (with a biogenic aerosol component) seems to dominate the ice nucleation in the ABL during the summer months (June–August). The strong winter vs. summer contrast in the INP number concentration by roughly 2–3 orders of magnitude in the lower troposphere is, however, mainly caused by the strong cloud temperature contrast. A unique event of the MOSAiC expedition was the occurrence of a long-lasting wildfire smoke layer in the upper troposphere and lower stratosphere. Our observations suggest that the smoke particles frequently triggered cirrus formation close to the tropopause from October 2019 to May 2020. [ABSTRACT FROM AUTHOR]

Riming is a key precipitation formation process in mixed-phase clouds by efficiently converting cloud liquid to ice water. Here, we present two methods to quantify riming of ice particles from airborne observations with the normalized rime mass, which is the ratio of rime mass to the mass of a size-equivalent spherical graupel particle. We use data obtained during the HALO-(AC)3 aircraft campaign, where two aircraft were collecting spatially and temporally closely collocated radar and in situ measurements over the Fram Strait west of Svalbard in spring 2022. The first method is based on an inverse Optimal Estimation algorithm to retrieve the normalized rime mass from a closure between cloud radar and in situ measurements during these collocated flight segments ('combined method'). The second method relies on in situ observations only, by relating the normalized rime mass to optical particle shape measurements ('in situ method'). We find good agreement between both methods during collocated flight segments with median normalized rime masses of 0.018 and 0.016 (mean values of 0.027 and 0.028) for combined and in situ method, respectively. Assuming particles with a normalized rime mass smaller 0.01 to be unrimed, we obtain average rimed fractions of 77 % and 75 %. Although in situ measurement volumes are in the range of a few cm3 and therefore much smaller than the radar volume (about 45 m footprint diameter), we assume they are representative of the radar volume. When this assumption is not met due to less homogeneous conditions, discrepancies between the two methods result. We compare normalized rime mass results with meteorological and cloud parameters and show the performance of the methods in two case studies, 1) a collocated segment in cold air outbreak conditions and 2) an in situ only flight close to a polar low. We find that higher normalized rime masses correlate with streaks of higher radar reflectivity. We also observe rimed particles in regions without liquid water, suggesting that particles were rimed in a liquid layer above and precipitated. The methods presented improve our ability to quantify riming from aircraft observations. [ABSTRACT FROM AUTHOR]

The Arctic has warmed more rapidly than the global mean during the past few decades. The lapse rate feedback (LRF) has been identified as being a 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 sixth Coupled Model Intercomparison Project (CMIP6). We build on the result that CMIP6 models show a large spread in AA and Arctic LRF, which are positively correlated for the historical period of 1951–2014. Thus, 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 that show a weak and strong simulated AA and Arctic LRF in the past. Our analyses suggest that the vertical temperature structure of the Arctic boundary layer is more realistically depicted in climate models with weak (w) AA and Arctic LRF (CMIP6/w) in the past. In particular, CMIP6/w models show stronger inversions in the present climate for boreal autumn and winter and over sea ice, which is more consistent with the observations. These results are based on observations from the year-long Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition in the central Arctic, long-term measurements at the Utqiaġvik site in Alaska, USA, and dropsonde temperature profiling from aircraft campaigns in the Fram Strait. In addition, the atmospheric energy transport from lower latitudes that can further mediate the warming structure in the free troposphere is more realistically represented by CMIP6/w models. In particular, CMIP6/w models systemically simulate a weaker Arctic atmospheric energy transport convergence in the present climate for boreal autumn and winter, which is more consistent with fifth generation reanalysis of the European Centre for Medium-Range Weather Forecasts (ERA5). We further show a positive relationship between the magnitude of the present-day transport convergence and the strength of past AA. With respect to the Arctic LRF, we find links between the changes in transport pathways that drive vertical warming structures and local differences in the LRF. This highlights the mediating influence of advection on the Arctic LRF and motivates deeper studies to explicitly link spatial patterns of Arctic feedbacks to changes in the large-scale circulation. [ABSTRACT FROM AUTHOR]