This session aims at bringing together researchers using observational and/or modeling approaches (at various scales) to improve our understanding of polar tropospheric clouds, precipitation, and related mechanisms and impacts. Contributions are invited on various relevant processes including (but not limited to):
- Drivers of cloud/precipitation microphysics at high latitudes,
- Sources of cloud nuclei both at local and long range,
- Linkages of polar clouds/precipitation to the moisture sources and transport, including extreme transport events (e.g., atmospheric rivers, moisture intrusions),
- Relationship of moisture/cloud/precipitation processes to the atmospheric dynamics, ranging from synoptic and meso-scale processes to teleconnections and climate indices,
- Interactions between clouds and radiation, including impacts on the surface energy balance,
- Impacts that the clouds/precipitation in the Polar Regions have on the polar and global climate system, surface mass and energy balance, sea ice and ecosystems.
Papers including new methodologies specific to polar regions are encouraged, such as (i) improving polar cloud/precipitation parameterizations in atmospheric models, moisture transport events detection and attribution methods specifically in the high latitudes, and (ii) advancing observations of polar clouds and precipitation.
Mesoscale cellular convection (MCC), which can be found in- and outside marine cold air outbreaks (MCAOs) over the Southern Ocean (SO), has been shown to influence the cloud radiative effect and potentially shortwave cloud feedbacks. While MCC morphology and cell-size scaling have been studied extensively in the subtropics and North Atlantic MCAOs, far less is known about how these relationships behave in the SO, where mixed-phase clouds dominate. In this study, we investigate the physical controls on MCC cell size and its variability during SO MCAOs based on collocated active and passive remote sensing products and reanalysis fields.
Specifically we combine MODIS retrievals of liquid water path and 0.86 μm reflectance for MCC classification and cell identification, ERA5 reanalysis for dynamical and thermodynamic fields, and DARDAR-v2 radar–lidar profiles to determine cloud-top height, cloud-top temperature, and cloud phase. Image segmentation applied to 200 × 200 km² scenes along DARDAR overpasses yields a catalogue of 19,500 MCC cells, 86% of which are supercooled—a clear reflection of the high prevalence of mixed-phase clouds in the SO.
Contrary to established behaviour in shallow NH boundary layers, we find no evidence of a constant aspect-ratio regime and no systematic deepening of the BL during MCAO evolution. Open and closed cells exhibit similar median diameters (~36–37 km), although open cells display a longer tail toward larger sizes. Thermodynamic and dynamic conditions—including stability parameter M, BL depth, and surface forcing—show minimal influence on cell-size variability. Approximately half of all mixed-phase open cells occur within MCAO regimes defined by M > –5 K, yet cell diameter remains largely insensitive to the strength of the outbreak.
Backward trajectory analysis indicates that time since cold air mass formation may play a more decisive role: larger cells tend to reside in older, more mature MCAO air masses. Our findings suggest that, in the SO, MCC cell growth is primarily constrained by air-mass age rather than boundary-layer deepening or thermodynamic forcing.
How to cite: Possner, A., Danker, J., McCoy, I., and Sourdeval, O.: Constraints on Southern Ocean Mesoscale Cellular Convective Cell Growth, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7721, https://doi.org/10.5194/egusphere-egu26-7721, 2026.
The clouds associated with Marine Cold Air Outbreaks (MCAOs) exhibit characteristic structures, initially forming as roll clouds or cloud streets parallel to the wind direction, and eventually breaking up into a cellular cloud field.
Here, a novel correlation-based metric, the Correlation clOud Street Index (COSI) is introduced. It is defined as the Pearson correlation coefficient between an image and an optimally oriented and scaled Gabor kernel, providing a quantitative measure of cloud street presence and distinctness. The calculation of this index also extracts cloud street spacing (wavelength) and orientation as structural properties.
Applied to satellite observations with extensive spatial and temporal coverage, we utilise the COSI to get novel insights into the spatio-temporal evolution of cloud street structures in marine cold air outbreaks. By analysing sequences of consecutive satellite images for individual events, we capture the cloud evolution for both the overall MCAO and along quasi-Lagrangian trajectories. We quantify the systematic increase in cloud street wavelength with increasing distance from the ice edge and assess the aspect ratio (wavelength divided by cloud top height) across a larger dataset. The dependence on the MCAO strength is also evaluated. The cases analysed correspond to periods with (AC)3 aircraft campaigns, allowing the aircraft observations to be placed in a broader context and providing more detailed observations of meteorological conditions along flight trajectories.
This work was supported by the DFG funded Transregio-project TRR 172 “Arctic Amplification (AC)3“.
How to cite: Sundermann, H., Klingebiel, M., Ehrlich, A., and Deneke, H.: Quantifying the Evolution of Cloud Street Structures During Arctic Marine Cold Air Outbreaks Using Satellite Observations, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18004, https://doi.org/10.5194/egusphere-egu26-18004, 2026.
Mountain-wave-induced temperature perturbations can locally enable the formation of polar stratospheric clouds (PSCs). We examine a decade-long (2002–2012) record of ice PSCs derived from MIPAS/Envisat measurements. The points with the smallest temperature difference (ΔTice_min) between the frost point temperature (Tice) and the environmental temperature along the line of sight have been proposed and shown to provide a better estimate of the location of ice PSC observation from MIPAS. The temperature for the ice PSC observations is analyzed based on ERA5. Following this, we investigated the temperature history of the ice PSCs detected above Tice at the observation points along 24 h backward trajectories.
We find that 52 % of Arctic and 26 % of Antarctic ice PSCs are detected above Tice, with pronounced clustering over mountainous terrain and in downstream regions. The backward trajectories were calculated by using the MPTRAC model, initialized at the ΔTice_min locations. Analysis of the temperature evolution along these trajectories shows that the fraction of ice PSCs at a temperature above Tice along the trajectory decreases, with the strongest decrease within the 6 h before observation. Accounting for temperature fluctuations along the air-mass histories, reduces the fractions of too warm ice PSCs at observation to 33 % in the Arctic and 9 % in the Antarctic.
These results demonstrate the substantial role of orographic waves in ice PSC formation and provide observational constraints for chemistry–climate model evaluation. This contribution is based on the published analysis of Zou et al. (2024, Atmos. Chem. Phys., 24, 11759–11774, https://doi.org/10.5194/acp-24-11759-2024) .
How to cite: Zou, L., Spang, R., Griessbach, S., Hoffmann, L., Khosrawi, F., Müller, R., and Tritscher, I.: Mountain-wave influence on polar stratospheric ice clouds: evidence from MIPAS–ERA5 analysis, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2998, https://doi.org/10.5194/egusphere-egu26-2998, 2026.
The role of Water Vapor (WV) in Arctic amplification remains uncertain and is under investigation (Wendisch and coauthors, 2023). Understanding its role in the mechanisms driving Arctic amplification requires detailed information on its spatio-temporal variability. However, WV variability in the Arctic has rarely been examined. Temporally highly resolved integrated water vapor (IWV) data from ground-based MWR observations are ideally suited for the analysis of WV temporal variability. In this study, we make use of 13 years of measurements of the Humidity and Temperature PROfiler (HATPRO) at the AWIPEV atmospheric observatory (Ny-Ålesund, Svalbard). Extreme events of atmospheric moistening and drying are identified, characterized, and further related to the prevailing circulation weather systems. Since WV transport into the Arctic is episodic and primarily occurs through brief, intense events typically associated with cyclones (Henderson et al., 2021), it is essential to analyze these events in further detail. To analyze these events, we identify minima and maxima in the IWV time series. We define “extreme” using a threshold in IWV amplitudes within a respective time interval. An event can either consist of only one maximum (moistening) or minimum (drying) or of multiple maxima/minima.
When focusing on extreme atmospheric moistening and drying events, we find that absolute IWV amplitudes are highest in summer and lowest in winter. The events last between 2 and 142 hours. By contrast, winter shows a greater relative variability (with respect to the monthly mean) than summer, with IWV changes exceeding 250% within a few hours in some cases. Events with only one maximum (moistening) or one minimum (drying) are short-lived (75% last less than 24 hours), while those with multiple maxima/minima last longer, with a mean of 48 hours. We find that extreme atmospheric moistening and drying at Ny-Ålesund proceed differently: drying happens more rapidly but with smaller amplitudes than moistening. Also, the synoptic regimes favoring moistening and drying differ. For moistening the weather types ASW, AW, AS, and CSE account for half of the extreme moistening events, with the anticyclonic types transporting moisture over the North Atlantic. In contrast, CSE is associated with moisture transport over Scandinavia and West Russia, spanning the Barents and Kara Seas. For drying, significantly different weather systems can be responsible. Other studies found a positive trend in cyclone activity over the Barents Sea (e.g., Wickström et al., 2019), which could favor greater moisture transport driven by CSE.
We gratefully acknowledge the funding by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Project Number 268020496 – TRR 172, within the framework of the Transregional Collaborative Research Center “ArctiC Amplification: Climate Relevant Atmospheric and SurfaCe Processes, and Feedback Mechanisms (AC)³”. We thank the AWIPEV team for their support in operating our instruments at AWIPEV within the project AWIPEV_0016.
How to cite: Buhren, C., Crewell, S., Pettersen, C., Eisenhuth, P., Ritter, C., and Ebell, K.: Quantifying the temporal variability of water vapor in Ny-Ålesund and its relation to weather systems, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12546, https://doi.org/10.5194/egusphere-egu26-12546, 2026.
The ERC Synergy funded project AWACA aims to understand the atmospheric branch of the water cycle over Antarctica. It relies on innovative observations of the tropospheric meteorological conditions and the isotopic composition of water vapor and hydrometeors along a 1100-km transect between Dumont d’Urville station at the coast and Concordia station on the high inner Antarctic plateau. The deployment of instruments was completed in the austral summer season from November 2024 to February 2025. The instruments will remain in place for three years. At four locations along the transect, temporary container-stations were deployed. Each container includes, among other instruments, a Metek MIRA 35 GHz cloud radar, an MRR-PRO 24 GHz precipitation radar, and a BASTA 95 GHz cloud radar. Adjacent to each container is a comprehensive surface weather station.
This contribution will present a case study of a coastal cyclone and resulting moist air intrusion in February 2025, focusing on the radar data. Trajectory analysis confirmed that air parcels within the same intrusion traveled inland over multiple sites of the observational transect. However, the mechanisms by which the moisture of the intrusion is converted into precipitation differ between the coast and the high plateau. Taking advantage of the multi-frequency, spectral, polarimetric radar dataset, differences in the microphysics of snowfall along the transect have been investigated. On the coastal slope of the ice sheet, uplift, turbulence and the presence of liquid water lead to riming and aggregation of snowflakes. On the high plateau, dry and cold conditions lead to smaller snow particles, for which the variation in the radar signal appears to arise from variations in primary production and ice crystal habit.
How to cite: Corden, H., Delanoë, J., Toledo Bittner, F., and Berne, A.: Precipitation processes in an Antarctic moist air intrusion: insights from multi-frequency radar observations over a 1100-km transect, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19611, https://doi.org/10.5194/egusphere-egu26-19611, 2026.
Clouds play an important role in Greenland’s surface mass balance, as they govern accumulation through precipitation and influence surface melt by altering the radiative balance. Therefore, correctly representing clouds in polar regional climate models is crucial for obtaining reliable surface mass balance estimates and projections. However, the complex, small-scale cloud microphysical processes involved in cloud formation, dissipation, and phase changes are often poorly represented in models. As in-situ observations of polar clouds are sparse, satellite observations can be an effective tool for evaluating and improving climate models. The new EarthCARE satellite, launched in May 2024, provides high-resolution co-located observations of the vertical structure of clouds and aerosols, and top-of-atmosphere radiation. Here, we show how these observations can be used to evaluate cloud representation in climate models by comparing them with output of the polar regional climate model RACMO (version 2.4p1).
We will present a comparison of over one year of multi-instrument EarthCARE observations of clouds and radiation for the Greenland region with model output that is co-located in time and space. We find that for clouds in all phases (solid, liquid, and mixed), RACMO tends to miss clouds at higher altitudes and underestimates water content for most locations and vertical levels. As a result, in RACMO, snowfall is less often generated at higher altitudes but more often at lower altitudes. However, the simulated snowfall rates are underestimated. Rainfall shows similar patterns, with rainfall modeled more frequently, but with lower rainfall rates. We will use these comparisons, along with EarthCARE’s radiation observations and retrieved cloud microphysical properties, to work towards improved cloud representation, surface radiation, and surface mass balance estimates in RACMO.
How to cite: Feenstra, T., van den Berg, W. J., van Zadelhoff, G.-J., Donovan, D. P., van Dalum, C. T., and van den Broeke, M. R.: How can EarthCARE satellite observations help improve Greenland’s clouds in the regional climate model RACMO?, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10742, https://doi.org/10.5194/egusphere-egu26-10742, 2026.
Arctic surface warming is driven by a changing surface energy budget. However, sparse observations in the Arctic limit our ability to identify drivers of surface energy budget change. Here, we leverage detailed long-term observations at the Atmospheric Radiation Measurement (ARM) program's North Slope of Alaska (NSA) facility to constrain and attribute drivers of surface radiation change 2001-2023. We combine cloud and atmospheric observations with radiative transfer calculations, allowing us to quantify the relative impact of clouds, temperature, and water vapor on surface radiation trends and variability. At the ARM NSA facility, downwelling longwave radiation is increasing year-round and downwelling shortwave radiation is decreasing during summer. We find that cloud changes intensify the downwelling longwave radiation trend, which is largely due to warming. We also find that cloud changes drive decreasing downwelling shortwave radiation during summer. These results reveal the important role of clouds in driving surface radiation trends along the North Slope of Alaska.
How to cite: Bertrand, L., Kay, J., and de Boer, G.: Observed cloud and atmospheric drivers of surface radiation change 2001-2023 on the North Slope of Alaska, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15936, https://doi.org/10.5194/egusphere-egu26-15936, 2026.
Low-level clouds and fog play a crucial role in the surface energy balance of polar regions, where even small perturbations in radiative fluxes can trigger amplified climatic responses. In these environments, the frequent presence of fog and stratiform low clouds strongly modulates both shortwave and longwave radiation, exerting a dominant control on near-surface temperature. The radiative effect of these clouds is highly sensitive to their thermodynamic phase: liquid-containing clouds generally enhance downwelling longwave radiation, promoting surface warming, whereas ice-dominated clouds are more transparent in the infrared and can contribute to surface cooling, particularly during polar night. As both the Arctic and Antarctic undergo rapid warming accompanied by shifts in cloud phase partitioning, understanding the occurrence and temporal variability of liquid and ice fog and low clouds is essential for accurately representing polar climate feedbacks and their role in ongoing climate change.
Using 11 years of cloud observations from the active satellite sensor CALIPSO, we characterize the spatial and temporal patterns of fog and low clouds (FLCs) across the polar regions, stratified by season and light conditions. Our results show a pronounced reduction in ice FLCs over Antarctica (~1% per year), while the Southern Ocean exhibits a decrease in liquid FLCs during winter under both daytime and nighttime conditions. In the Arctic, both liquid and ice FLCs decrease over land and sea-ice-covered regions from fall to spring. Over the Arctic Ocean, however, we find an increase in liquid FLCs during these seasons regardless of solar angle, whereas ice FLCs increase only under conditions of available solar radiation.
Overall, the observed trends in fog and low-level clouds suggest a potentially important role in modulating polar surface energy budgets.
How to cite: Bruno, O. and Cermak, J.: Spatial and temporal patterns of fog and low clouds in the Polar regions, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6771, https://doi.org/10.5194/egusphere-egu26-6771, 2026.
Fog is a common feature of the lower atmosphere in the Arctic, yet its long-term variability, seasonal changes, and sensitivity to rapid climate warming remain poorly known. Using meteorological data from five Svalbard stations from 1970 to 2020, we analyse seasonal fog occurrence, fog type (advection versus radiation), temperature, wind patterns. We also use sulphate aerosol data from one Svalbard station to investigate aerosol conditions.
High fog frequencies (7-15 %) are seen at the stations located on smaller islands in the vicinity of Svalbard (Janmayen, Bjørnøya, Hopen). The other two sites, located at Spitsbergen (Svalbard Airport, Ny-Ålesund), show substantially lower fog frequencies (0-4%). During summer, the fog frequency is highest for all stations, with radiation fog dominating at Spitsbergen sites while on the island stations, both advection fog and radiation fog is types are common. During winter, advection fog is predominant from cold, northerly to northeasterly marine airflows at most sites. The temperature during advection fog in winter is colder than during the formation of radiation fog. Spring and autumn seasonal represent transitional periods, with both fog types occurring but at lower overall frequencies. The wind direction during fog change seasonally, shifting from northerly/easterly in winter to southerly/westerly in summer.
Fog occurrence has decreased at most sites between 1970 and 2020. The drop is especially noticeable at Janmayen and Bjørnøya. The fog frequency at the Spitsbergen sites is also declining but with a weaker decreasing trend. The analysis shows that it is advection fog that is decreasing and not radiation fog. Regional warming, reduced sea-ice extent, and lower Arctic aerosol loading could be responsible for this decreasing trends. These results indicate that fog is sensitive to climate change in the Arctic. It changes visibility, the local radiation budget, and the way air and sea interact in an environment that is changing quickly.
How to cite: singh, S. and Sporre, M. K.: Climatology and trends of fog in the Svalbard region, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3966, https://doi.org/10.5194/egusphere-egu26-3966, 2026.
The overall gain and loss of snow and ice on the surface of the Antarctic ice sheet is strongly driven by rare extreme events, some of which result from atmospheric rivers transporting both moisture and heat from the tropics towards the south pole. Moisture transport is strongly driven by large-scale patterns, e.g. the El Niño Southern Oscillation, the Southern Annular Mode, PSA1 and PSA2 patterns. Additionally, in recent years, the Southern Ocean region has witnessed major changes, including sequential record lows for sea ice extent and warming oceans, with direct impacts on the Antarctic ice sheet and Southern Ocean. Previous research has highlighted the strong sensitivity of precipitation in West Antarctica to large-scale patterns, and especially the importance of atmospheric rivers. However, atmospheric rivers are only one mechanism of transport, and estimates are subject to the reliability of detection algorithms. Additionally, the ability to fully-capture drivers and impacts of extreme events are limited by spatiotemporal resolution in Earth Systems Models.
Here, we employ a variable-resolution version of the global Community Earth Systems Model (VR-CESM2) with enhanced resolution over Antarctica over the historical period (1990-2020), run at a high time-resolution capable of capturing extremes and calculating atmospheric rivers. We additionally employ moisture-tagging (linking precipitation to a moisture source region), which can quantify links between sources and sinks of extreme precipitation directly and identify mechanisms which drive transport. Here, we will focus on drivers of extremes in West Antarctica, comparing mechanisms identified via direct moisture tagging with those concurrent with atmospheric rivers.
How to cite: Datta, R., Herrington, A., Nusbaumer, J., and Trusel, L.: Unpacking Global Drivers of Extreme Precipitation over West Antarctica, using a Variable-Resolution Earth Systems Model with Explicit Moisture Tagging, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14927, https://doi.org/10.5194/egusphere-egu26-14927, 2026.
The strong warming of the Arctic has profound implications for the atmospheric energy budget. Recent studies indicate that the Arctic energy balance is transitioning from a predominantly radiative-advective equilibrium towards a radiative-advective convective regime.
Using monthly CMIP6 model output from an idealized CO2-forcing scenario, we analyze changes in the occurrence of convective precipitation relative to total precipitation. Our results show a pronounced seasonal and surface-dependent signal. This pattern is also reflected in the associated trend estimates. However, the inter-model spread across the CMIP6 models is substantial, with individual models even exhibiting opposing trend signs. This large spread is consistent with pronounced differences in simulated sea ice extent among the models, suggesting potential linkages to other key variables.
How to cite: Vliegen, S. and Quaas, J.: Model analysis of convective precipitation in the Arctic, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16990, https://doi.org/10.5194/egusphere-egu26-16990, 2026.
The precise simulation of in-cloud icing is essential for various atmospheric and aviation-related applications. This study aims to investigate the sensitivity of different microphysics schemes within the Weather Research and Forecasting model (WRF) V 4.4 in simulating in-cloud ground icing events during the period from May 2023 to April 2024 over Fagernes Mountain, a complex terrain site in northern Norway. Specifically, we will investigate the Thompson, Thompson-Eidhammer, WDM7, and P3 schemes. Microphysics schemes are critical in representing the formation, growth, and fallout of hydrometeors, within clouds, thereby significantly impacting the accuracy of cloud and precipitation forecasts in numerical weather prediction models.
Preliminary insights suggest that there may be significant variations in the simulation of in-cloud icing among the different microphysics schemes. For instance, one of our case studies has indicated that the Thompson scheme might excel at low icing rates, while the Morrison scheme could perform better at high icing rates. The Thompson-Eidhammer and P3 schemes are sophisticated and may provide more nuanced predictions of cloud liquid water and icing severity across various conditions. In contrast, simplerschemes might underestimate or overestimate icing conditions due to their less comprehensive treatment of microphysical processes. This study will highlight the importance of selecting an appropriate microphysics scheme based on specific meteorological conditions and the desired level of detail in the simulation. The results will underscore the need for continued refinement of microphysics parameterizations in numerical weather prediction models to improve the accuracy of in-cloud ground icing forecasts and other related applications.
How to cite: Punde, P., Birkelund, Y., and Eidhammer, T.: Assessing the Influence of Microphysics Parameterizations on In-Cloud Ground Icing Using WRF V 4.4 , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-22022, https://doi.org/10.5194/egusphere-egu26-22022, 2026.
Arctic Amplification is not well understood. It is the result of a complicated interplay between remote and local forcing and feedback processes. Therefore, it is crucial to enhance our understanding of the transport of energy and moisture from lower latitudes. The amount of aerosol in the Arctic is also an important quantity as their role in Arctic Amplification, via direct radiative forcing and aerosol-cloud interactions, remain poorly quantified.
In this work, we aim to better quantify how aerosols, energy, and moisture are transported to and distributed within the Arctic. We investigate observations at Arctic stations, including, Villum and Zeppelin, and perform backward-in-time simulations with the Lagrangian atmospheric transport model FLEXPART (Pisso et al., 2019; Bakels et al., 2024) to derive so-called emission sensitivities and use these sensitivities to better quantify source regions of aerosols, energy, and moisture.
In general, we aim to better describe the spatial and temporal atmospheric transport characteristics into the Arctic and how these characteristics have changed in recent years. We focus on the transport during warm-air intrusions, since almost 30% of the total poleward transport of moisture (during winter) occurs during such events (Woods et al., 2013). Warm-air intrusions are often associated with large-scale atmospheric blocking patterns forcing a change in transport direction from east to more poleward, bringing warm, moist, and cloudy air into the Arctic. Warm-air intrusions can also be favourable for an enhanced transport of aerosols (e.g., Dada et al., 2022).
Since climate models show large biases in moisture flux during these events (Woods et al., 2017), there is clearly a need to better quantify the transport of moisture, energy, and aerosols during these events. This will also help to provide better forcing for climate simulations.
Bakels et al. (2024): 10.5194/gmd-17-7595-2024; Dada et al. (2022): 10.1038/s41467-022-32872-2; Lapere et al. (2024): 10.1029/2023JD039606; Pisso et al. (2019): 10.5194/gmd-12-4955-2019; Woods et al. (2013): 10.1002/grl.50912; Woods et al. (2017): 10.1175/JCLI-D-16-0710.1
How to cite: Plach, A., Eckhardt, S., Evangeliou, N., and Ekman, A. M. L.: Atmospheric transport characteristics during warm-air intrusions – focusing on aerosol, energy, and moisture transport, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12413, https://doi.org/10.5194/egusphere-egu26-12413, 2026.
Low-level Arctic clouds, especially mixed-phase clouds, are key drivers of regional climate and Arctic amplification, yet their microphysical and dynamical properties remain difficult to observe in data-sparse regions. EarthCARE offers new opportunities to address this observational gap; however, its measurements require validation using independent reference data. As a contribution to these validation activities, the Polar 5 research aircraft of the Alfred Wegener Institute has been equipped with an EarthCARE-like instrument suite and operated during the COMPEX-EC (Clouds over cOMPlEX environment – EarthCARE) in April 2025 from Kiruna, Sweden. During seven research flights, we collected more than 5 hours of along-track airborne radar measurements collocated with EarthCARE overpasses, covering diverse Arctic conditions from marine cold-air outbreaks (CAO) over the Norwegian Sea to cloud fields over northern Scandinavia. For moving platforms, such as aircraft, corrections addressing horizontal and vertical motion, as well as attitude, need to be applied to some of the measurements. Hereby, the Doppler velocity is especially challenging, and this is further complicated by the installation of the W-band Microwave Radar/radiometer for Arctic Clouds (MiRAC) on Polar 5 in a belly pod with a 25° inclination under the aircraft, which enhances the complexity. MiRAC is complemented by a microwave radiometer, an Airborne Mobile Aerosol Lidar for Arctic research (AMALi), spectral and broadband radiative sensors, and dropsondes. The collected data provide a unique basis for evaluating EarthCARE cloud products, with a particular focus on cloud geometric properties and vertical cloud structure. Cloud-top heights are derived from AMALi and MiRAC and compared to spaceborne retrievals from EarthCARE ATLID and CPR across different Arctic cloud regimes. We exploit the complementary sensitivities of lidar and radar to assess the detectability of thin liquid-topped clouds and mixed-phase cloud layers. Dropsondes released during EarthCARE overpasses provide thermodynamic and wind profiles that support the interpretation of observed cloud structures and precipitation occurrence. Beyond EarthCARE validation, the dataset contributes to an enhanced understanding of Arctic cloud vertical structure and its relevance to precipitation development under different synoptic conditions. Ongoing work aims to extend the analysis towards Doppler-based interpretations of cloud dynamics.
This work was supported by the DFG funded Transregio-project TRR 172 "Arctic Amplification (AC)³".
How to cite: van Gelder, L., Kollias, P., Mech, M., Pfitzenmaier, L., and Crewell, S.: New insights into Arctic mixed-phase clouds from airborne and EarthCARE observations, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14343, https://doi.org/10.5194/egusphere-egu26-14343, 2026.
Clouds containing supercooled liquid are common over the Southern Ocean and coastal Antarctica. The liquid phase not only has strong influence on the surface energy budget, but also cloud microphysics and precipitation formation. Often, the droplets occur in thin layers stacked on top of each other and/or coexisting with ice particles. Both of these aspects pose a significant challenge for observations. Cloud radar Doppler spectra can contain this information in the form of individual peaks for different particle populations, but extracting useful data is challenging for automated retrievals.
Combining advanced Doppler spectra analysis techniques with established retrieval methods, such as ACTRIS-Cloudnet, can provide cloud microphysical properties even under complex conditions. This approach has been applied to observations from Neumayer Station III, Antarctica (70.67°S, 8.27°W), where synergistic remote sensing instruments are operated since 2023. During the 2024/25 austral summer, tethered-balloon in-situ observations provided complementary information on cloud droplet properties.
Two aspects will be presented: Firstly, properties of liquid layers in geometrically thick snowfall clouds. Spatiotemporal coinciding balloon-borne observations provide independent verification. Secondly, observations of seeder-feeder situations, in which ice crystals sediment into a supercooled – potentially drizzling – layer. It is envisaged that the Doppler spectral analysis will be implemented as a new method in ACTRIS-Cloudnet in the future.
How to cite: Radenz, M., Lonardi, M., Temel, Y., Vogl, T., Engelmann, R., Schmale, J., and Seifert, P.: Toward enhanced retrievals of supercooled droplet properties in Antarctic clouds , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14797, https://doi.org/10.5194/egusphere-egu26-14797, 2026.
Marine cold air outbreaks (CAOs) represent an important meridional transport mechanism out of the Arctic towards lower latitudes. The cloud field properties change with the air mass transformation, and the thermal-infrared all-sky cloud radiative effect (CRE) is increasing in the downstream direction during the initial stages of a CAO. These evolution processes are important to understand current and future CAOs in a warming Arctic, which will favor weaker events.
Here, we aim to identify the driving factors of this downstream increase for different CAO events of varying intensity, which were observed during the HALO-(AC)3 campaign in spring 2022. The High Altitude and LOng range research aircraft (HALO) sampled CAOs in a quasi-Lagrangian way with a remote sensing payload. The thermal-infrared imager VELOX (Video airbornE Longwave Observations within siX channels) provided 2D broadband (7.7 µm to 12.0 µm) brightness temperature fields of cloud tops and the surface with a spatial resolution of 10 m for a 10 km target distance. First, a cloud mask is applied to those brightness temperature fields to determine cloud fractions. In a next step, two types of CRE are calculated. A cloud-only CRE is derived for all identified cloud pixels while an all-sky CRE is calculated for cloud-free as well as cloud pixels. The comparison of the cloud-only and all-sky VELOX CREs enables a determination of the all-sky CRE driver, i.e., cloud top temperature or cloud fraction. In addition, lidar cloud top heights and a large-scale all-sky CRE, based on measurements by a broadband radiometer and radiative transfer simulations, are analyzed to provide further context for the analyzed cases. The results imply that the strength of the all-sky CRE increase depends on the CAO intensity and is in general driven by increasing cloud fraction. Thus, this analysis provides a TOA-like perspective on the thermal-infrared radiative impact of a low-level cloud field, which is (trans-)forming during the initial stages of a CAO.
How to cite: Rosenburg, S., Schäfer, M., Ehrlich, A., Luebke, A., Klingebiel, M., Müller, J., and Wendisch, M.: Quantifying drivers of the thermal-infrared radiative effect of Arctic low-level clouds in cold air outbreaks, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11006, https://doi.org/10.5194/egusphere-egu26-11006, 2026.
Climate change signals are especially strong in the Arctic, where warming from 1979 to 2021 proceeded at nearly four times the global average rate (Rantanen et al., 2022). The magnitude of this warming varies across the region, and the Svalbard archipelago, located in the warmest part of the Arctic, has experienced particularly intense temperature increases (Dahlke and Maturilli, 2017).
The influence of clouds on the rapidly evolving Arctic climate system, as well as the processes governing their behavior, remains a key research challenge. Although detailed cloud observations are essential, only a limited number of Arctic sites provide continuous, high-resolution vertical measurements of cloud properties. One such site is the German-French Arctic Research Base AWIPEV at the Ny-Ålesund Research Station on Svalbard. Since 2016, a 94 GHz cloud radar has been operating at this location as part of the Transregional Collaborative Research Centre TR172 on Arctic Amplification (AC)³ (http://www.ac3-tr.de; Wendisch et al., 2023). In combination with complementary remote-sensing instruments, including ceilometers and microwave radiometers, this observational setup allows for continuous cloud monitoring with high temporal and vertical resolution. This presentation highlights key results derived from a decade of cloud radar observations.
Clouds are present at Ny-Ålesund during roughly 78% of the time, most frequently at low levels between 0.5 and 1.5 km. While pure liquid clouds show a distinct seasonal variability, mixed-phase clouds occur year-round and account for about 42% of all cloud observations. These liquid-containing clouds have a significant influence on the Arctic surface energy budget, leading to an overall warming at Ny-Ålesund due to the enhanced longwave downward radiation flux.
Based on the 10-year-long dataset, we will examine the interannual variability of clouds and precipitation at Ny-Ålesund, as well as their impact on surface radiation.
Acknowledgment: We gratefully acknowledge the funding by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Project Number 268020496 – TRR 172, within the framework of the Transregional Collaborative Research Center “ArctiC Amplification: Climate Relevant Atmospheric and SurfaCe Processes, and Feedback Mechanisms (AC)³”. We also acknowledge the support of AWIPEV for the project AWIPEV_0016.
How to cite: Ebell, K., Mech, M., Walbröl, A., Buhren, C., Krobot, P., Ritter, C., and Maturilli, M.: A decade beneath Arctic clouds: Continuous radar observations at Ny-Ålesund, Svalbard, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17911, https://doi.org/10.5194/egusphere-egu26-17911, 2026.
Clouds are still a major source of uncertainty in projections of the future climate because of complex feedback mechanisms and their interplay with other atmospheric and surface properties (i.e., through solar and thermal-infrared radiation and precipitation). In the Arctic, where the climate is projected to warm the strongest, clouds pose a particular challenge to current climate and weather forecast models because of the difficulties in simulating the frequently occurring mixed-phase clouds and the sparsity of observational data.
In this study, we aim to improve our understanding of Arctic clouds on multi-annual time scales by performing statistical analyses of cloud states and their transitions using cloud radar data from the research site Ny-Ålesund, Svalbard. We have gathered nine years of comprehensive cloud and precipitation observations with the 94-GHz cloud radars, which were operated at the German-French Arctic Research Base AWIPEV observatory in synthesis with other in-situ and remote sensing instruments (i.e., microwave radiometers, lidar, disdrometers, ...). The additional meteorological measurements also allow us to study how atmospheric conditions affect the cloud states and transitions.
Modern machine learning algorithms are well suited to analyse big data sets and reveal features imperceptible to the human eye because of the complexity of the problem. We train a Vision Transformer [1-3] with height-resolved cloud radar reflectivities, Doppler velocities, ceilometer data and liquid water path-sensitive brightness temperatures at 89 GHz in a self-supervised framework. The Vision Transformer learns to identify distinct features in the training data and therefore find different cloud states without direct human intervention.
Here, we present our first steps focussing on the interpretation of the machine learning model output and fine tune the settings to better discern the cloud states. Different cloud macro- and microphysical properties are tested to understand the nature of each cluster the machine learning algorithm produced.
Later, we will apply the trained machine learning algorithm to synthetic radar data simulated with the Passive and Active Microwave radiative TRAnsfer (PAMTRA, [4]) model based on the output of the ICOsahedral Non-hydrostatic (ICON, [5]) model in large-eddy configuration. By comparing the observation-based analysis with the one performed on the simulated radar data we aim to further shed light on the strengths and weaknesses of ICON regarding cloud states and transitions.
We gratefully acknowledge the funding by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - Project Number 268020496 - TRR 172, within the framework of the Transregional Collaborative Research Center "ArctiC Amplification: Climate Relevant Atmospheric and Surface Processes, and Feedback Mechanisms (AC)³". We also acknowledge the support of AWIPEV for the project AWIPEV_0016.
[1]: Vaswani, A., et al., 2017, Inc. arXiv, 1706.03762, https://arxiv.org/abs/1706.03762.
[2]: Caron, M., et al., 2021, arXiv, 2104.14294, https://arxiv.org/abs/2104.14294.
[3]: Chatterjee, D., et al., 2024, Geophys. Res. Lett., 51, 12, e2024GL108889, doi: 10.1029/2024GL108889.
[4]: Mech, M. et al., 2020, Geosci. Model Dev., 13, 4229-4251, doi: 10.5194/gmd-13-4229-2020.
[5]: Zängl, G. et al., 2015, Q. J. R. Meteorolog. Soc., 141, 563-579, doi: 10.1002/qj.2378.
How to cite: Walbröl, A., Risse, N., Chatterjee, D., Crewell, S., and Ebell, K.: Cloud state transitions at Ny-Ålesund: A machine learning supported statistical analysis, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17535, https://doi.org/10.5194/egusphere-egu26-17535, 2026.
The contribution of Arctic mixed-phase clouds (MPCs) to the accelerated climate warming in the Arctic, known as Arctic amplification, remains uncertain due to complex microphysical and environmental interactions. Cloud condensation nuclei (CCN) concentrations influence MPC properties; however, current models often prescribe CCN levels much higher than Arctic observations suggest. To address this, we investigate the sensitivity of MPC properties to CCN concentrations using 600-m ICON-LEM simulations around Ny-Ålesund. The CCN sensitivity studies are based on typical CCN concentrations observed at the Zeppelin Observatory, serving as a benchmark for Ny-Ålesund conditions. We select simulation days by analyzing aerosol optical depth (AOD) measurements in Ny-Ålesund to represent high and low aerosol loading regimes, which are confirmed by Micro-Pulse Lidar (MPL) observations. Our initial studies, spanning mimicked Arctic, maritime, and polluted CCN regimes, reveal clear CCN effects: lower CCN concentrations reduce liquid water path (LWP) and increase radar reflectivity (Ze), mainly due to enhanced rain and graupel formation. However, the model underestimates the observed Ze, indicating shortcomings in the representation of phase partitioning. The results suggest that microphysical sensitivity varies with cloud height, with low-level MPCs responding more strongly than higher layers. We further explore this by separating cloud layers relative to the melting layer and analyzing their CCN sensitivity. To increase robustness, additional summer and winter low-level MPC cases are included. Complementing CCN sensitivity, ice nucleating particle (INP) sensitivity studies constrained by observed INP concentrations from the Gruvebadet observatory assess INP influence on phase-partitioning and precipitation in low-level MPCs. Identifying suitable CCN–INP combinations may improve MPC representation in ICON-LEM and deepen understanding of the aerosol-cloud interactions driving Arctic amplification.
This work was supported by the DFG-funded Transregio-project TRR 172 ”Arctic Amplification (AC)³”.
How to cite: Bruder, L., Ritter, C., Hiranuma, N., Kang, H., and Schemann, V.: Exploring Aerosol-Cloud Interactions in Arctic Mixed-Phase Clouds Using ICON-LEM, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18430, https://doi.org/10.5194/egusphere-egu26-18430, 2026.
