Extreme precipitation represents a major hazard in Europe, particularly in regions with complex terrain and strong land-sea contrasts such as the Alps and the Mediterranean. Here, we investigate synoptic-scale circulation patterns associated with extreme precipitation using simulations from the nextGEMS (Next Generation Earth Modelling Systems) high-resolution climate experiments at different horizontal resolutions.Synoptic regimes associated with extreme precipitation events over Italy and surrounding regions are identified using Gaussian Mixture Model clustering applied to daily standardised anomalies of mean sea-level pressure and 500 hPa geopotential height. The resulting classification of days with extreme precipitation is used to analyse the occurrence and characteristics of precipitation extremes under different large-scale flow situations and to assess how these relationships depend on model resolution and the representation of deep convection.The analysis reveals that dominant weather regimes are consistently represented across simulations with horizontal grid spacings between 4 and 9 km, indicating a robust representation of synoptic-scale variability. However, substantial differences emerge in the representation of regime-conditioned precipitation extremes. Higher-resolution simulations more realistically capture the intensity and spatial structure of extreme precipitation, particularly over complex Alpine terrain and along Mediterranean coastlines. These improvements are primarily associated with a limited number of circulation regimes characterised by strong moisture transport and favourable flow configurations for orographic lifting. Consequently, resolution-dependent differences in extreme precipitation are not uniform across all synoptic situations but are confined to specific large-scale regimes.These findings highlight the value of combining circulation-regime diagnostics with kilometre-scale climate simulations to better understand the multi-scale processes controlling regional precipitation extremes and their sensitivity to model resolution and convective parameterizations.

The presence of Arctic clouds plays a crucial role in the evolution of the surface temperature of Arctic sea ice. However, large biases in cloud representation remain in state-of-the-art weather and climate models. In this study, we use observational data from the one-year Arctic ship campaign Multi-disciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) to evaluate the Integrated Forecasting System (IFS), the global weather prediction model of the European Centre for Medium-range Weather Forecasts (ECMWF). We find seasonal biases in the cloud liquid water path, which is underestimated in winter and overestimated in summer. We show that the occurrence of supercooled liquid clouds with strong supercooling (below ) is underestimated, while the occurrence of liquid-containing clouds close to freezing temperature is overestimated. Focusing on winter, we investigate the sensitivity of supercooled liquid clouds to different model uncertainties in a single-column model setup. We find the strongest sensitivity is to uncertainties in cloud microphysics and show that reducing the assumed ice particle number concentration (within the bounds of uncertainty) reduces the ice deposition rate and improves the underestimation of supercooled liquid clouds significantly. As a result, the long-wave downward radiation at the surface improves. Positive effects on the boundary-layer structure are shown in a case study. Furthermore, we document the sensitivity of clouds to ice-particle fall speed and to small fractions of open ocean in the sea ice, which are often present in the model when satellite observations show full sea-ice cover. Both sensitivities are minor compared with the sensitivity to uncertain assumptions that affect the ice deposition rate directly. Our results can guide future model development to reduce Arctic cloud biases.

The Atacama at the west coast of South America is one of the driest regions on earth. Any atmospheric transport of water vapor into this desert which may form fog or dew is accordingly important for its supply with freshwater. Within the CRC 'Earth Evolution at the dry Limit' a network of climate stations has been installed in the core of the Atacama (Schween et al 2020). This network shows a very regular circulation with strong winds from the west during day time and weaker winds from the east during night. These winds are part of a circulation pattern between the coast and the slopes of the Andes known as Rutllant cell. The daytime westerly winds in the desert are moister than the night-time easterlies but this day-night difference in moisture vanishes at the slope of the Andes. Accordingly there is a net transport of water vapor into the desert. But from these surface measurements it remains unclear whether this moisture remains in the surface layer or leaves the region at higher levels, To get better insight in the circulation we performed simulations with the ICON-LEM model in a 300x300km domain centered around 20.75degS and 69.75W with a resolution of 624m. It covers the ocean as well the high Andes including the coastal mountain range and the central depression. A simulation of a typical winter day showed that the circulation is rather a complex movement of airmasses than a closed circulation. The moist air from the ocean reaches only partly up the slopes of the Andes before it switches to the night time pattern and flows back into the central depression of the desert. There the moist air collects as shallow pools in the basins and valleys where it eventually forms fog. When the following morning the breeze propagates into the desert, convergence at its head leads to injection of moist air into the free troposphere. We use the model data to identify corridors in which moist air from the ocean enters the desert. In the regions where fog forms we calculate the horizontal transport of liquid (fog) water which can be used to estimate fog water deposition to the surface. We calculate a moisture budget for different layers of the atmosphere to identify where and when water vapor enters and leaves the desert. Reference:Schween, J. H., D. Hoffmeister, and U. Löhnert, 2020: Filling the Observational Gap in the Atacama Desert with a new Network of Climate Stations, Global and Planetary Change, 184, https://doi.org/10.1016/j.gloplacha.2019.103034

Atmospheric rivers (ARs) are essential for the Arctic water cycle, but observations quantifying the moisture processes of individual Arctic ARs are sparse. This study quantified the evolution of the moisture budget components of an Arctic AR derived from airborne observations from two research flights on consecutive days. We investigated how poleward transport of warm and moist air masses by ARs generates precipitation near the sea ice edge and how advection and evaporation affect the local moisture amount during the dissipation of the AR. Using observations from the High-Altitude and LOng-Range Research Aircraft (HALO), we derived the atmospheric moisture budget components (local tendency of moisture, evaporation, moisture transport divergence, and precipitation) within an Arctic AR during the HALO-(𝒜𝒞)3 aircraft campaign. The budget components were quantified in sectors ahead of the AR-embedded cold front using airborne observations from dropsondes, radiometers, and a radar device and compared with values derived from reanalyses and numerical weather prediction simulations. We found that the observed moisture budget components in the pre-cold frontal sectors contribute up to ±1mmh-1 to the local moisture amount. The moisture transport divergence primarily controls the local moisture amount within the AR, while surface interactions are of minor importance. Precipitation is heterogeneous but overall weak (<0.1mmh-1), and evaporation is small. As the AR dissipated, the budget components changed from drying to moistening, mainly due to moisture advection. We demonstrated the feasibility of closing the moisture budget using single aircraft measurements, even though we found significant residuals that model-based comparisons attribute to subscale variability.

Mixed-phase clouds are common in the Arctic atmospheric boundary layer and their representation is challenging for models. Recent studies suggest that the ECMWF Integrated Forecast System (IFS) shows too many cloudy periods in the Arctic in summer and generally misses the periods with clear skies, while in winter the cloudy state is underrepresented.We use ground-based remote sensing data from the MOSAiC campaign to assess systematic errors in modelled liquid cloud water over the whole MOSAiC period and combine this with more detailed analyses of selected cases.In addition, we perform sensitivity tests to identify ways to improve the parametrization for Arctic mixed-phase clouds in the IFS.We run cases in the Single Column Model (SCM) version of the IFS and investigate the representativity of model sensitivities in the SCM for the 3D model.

Profiles of thermodynamic and cloud properties and their transformations during Arctic Warm Air Intrusions (WAIs) and Cold Air Outbreaks (CAOs) were observed during an aircraft campaign, and simulated using the ICON weather prediction model. The data were collected along flight patterns aimed at sampling the same air parcels multiple times, enabling Eulerian and quasi-Lagrangian measurement-model comparisons and model process studies. Within the Eulerian framework, the temperature profiles agreed well with the ICON output although a small model bias of −0.9 K was detected over sea ice during CAOs. Also, the air parcels did not adjust to the changing surface skin temperature quickly enough. The specific humidity profiles were reproduced by ICON with mean deviations of 6.0 % and 19.5 % for WAIs and CAOs, respectively. Radar reflectivities based on ICON output captured the vertical cloud distributions during the airmass transformations. The simulated process rates of temperature and humidity along the trajectories showed that adiabatic processes dominated the heating and cooling of the air parcels over diabatic effects during both WAIs and CAOs. Of the diabatic processes, latent heating and turbulence had a stronger impact on the temperature process rates than terrestrial radiative effects, especially over the warm ocean surface during CAOs. Finally, a quasi-Lagrangian observation-model comparison was performed. For WAIs, the observed change rates of temperature and humidity were not perfectly captured in the simulations. For the CAOs, the calculated heating and moistening change rates of the airmasses were well represented by ICON with remaining deviations close to the surface.

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.

Current general circulation models struggle to capture the phase-partitioning of clouds accurately, both overestimating and underestimating the supercooled liquid substantially. This impacts the radiative properties of clouds. Therefore, it is of interest to understand which processes determine the phase-partitioning. In this study, microphysical-process rates are analysed to study what role each phase-changing process plays in low-level Arctic clouds. Several months of cloud-resolving ICON simulations using a two-moment cloud microphysics scheme are evaluated. The microphysical-process rates are extracted using a diagnostic tool introduced here, which runs only the microphysical parameterization using previously simulated days. It was found that the processes impacting ice are more efficient during polar night than polar day. For the mixed-phase clouds (MPCs), it became clear that phase changes involving the vapour phase dominated in contrast to processes between liquid and ice. Computing the rate of the Wegener–Bergeron–Findeisen process further indicated that the MPCs frequently (42 % of the time) seemed to be glaciating. Additionally, the dependence of each process on the temperature, vertical wind, and saturation was evaluated. This showed that, in particular, the temperature influences the occurrence and interactions of different processes. This study helps to better understand how microphysical processes act in different regimes. It additionally shows which processes play an important role in contributing to the phase-partitioning in Arctic low-level mixed-phase clouds. Therefore, these processes could potentially be better targeted for improvements in the ICON model that aim to more accurately represent the phase-partitioning of Arctic low-level mixed-phase clouds.

Abstract. This study quantifies the evolution of the moisture budget components of an Arctic atmospheric river (AR) derived from airborne observations from two research flights on consecutive days. We investigate how poleward transport of warm and moist air masses by AR generates precipitation near the sea ice edge, and how advection and evaporation additionally affect the local moisture amount during the dissipation phase of the AR. Using the High Altitude and LOng Range Research Aircraft (HALO), we derive the atmospheric moisture budget components (local tendency of moisture, evaporation, moisture transport divergence and precipitation) within an intense Arctic AR event during the HALO-(𝒜𝒞)3 aircraft campaign. The components are quantified in sectors ahead of the AR-embedded cold front by airborne observations from dropsondes, radiometers and a radar. They are compared with model-based values from reanalyses and numerical weather prediction simulations. The observational moisture budget components in the pre-cold frontal sectors contribute up to ± 1 mm h-1 to local moisture amount. The moisture transport divergence primarily controls the local moisture amount within the AR, while surface interactions are of minor importance. Precipitation is heterogenous but overall weak (<0.1 mm h-1) and evaporation is small. Although the AR decreases in strength, the budget components change from drying to significant moistening, mainly due to moisture advection. For this AR, we demonstrate the feasibility of the budget closure using single aircraft measurements, although we find significant residuals. Model-based comparisons suggest that these residuals stem from grid sub-scale variability within the AR corridor.

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.

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Among arctic moist air intrusions, atmospheric rivers (ARs) provide substantial moisture transport over long distances poleward. Along their corridors, warm and moist air masses undergo various transformation processes and can cause regional sea ice decline, especially when they induce precipitation as rain. Quantifying the components of the atmospheric moisture budget in arctic ARs is key to elucidate their precipitation efficiency. We close the AR moisture budget by measurements of the High Altitude LOng range research aircraft (HALO) during the recent HALO-(AC)³ campaign (Spring, 2022) in the vicinity of the Fram Start and Arctic ocean.Our analysis is based on a strong AR event that HALO observed on two consecutive days during the occurrence of a sequence of moist air intrusions mid of March 2022. Dropsondes detect the vertical atmospheric profile and therefrom quantify the integrated water vapour transport (IVT) along AR cross sections. Applying regression methods then allows calculating the divergence of IVT. Since the limited number of dropsondes may deteriorate such calculations, we estimate the arising uncertainties using the ICOsahedral Nonhydrostatic model (ICON) in a storm-resolving configuration. Retrieved moisture profiles from the microwave radiometer (HAMP) further complement the sporadic sonde-based moisture profiles. We use the nadir cloud and precipitation radar mounted aboard HALO to derive precipitation rates along the flight curtains.As the comparison with ICON suggests, the set of dropsondes to derive the IVT divergence within a reasonable range. The advection of moisture is roughly twice as strong as mass convergence. Both components act on different heights, with convergence dominating in the boundary layer (0-1 km) near the low-level jet, whereas moisture advection is more elevated (1-4 km). The strongest moisture convergence arises in the warm prefrontal AR sector while precipitation dominates slightly westwards in the AR centre. The investigated AR event caused rain over sea-ice with a melting layer up to 1.5 km. While there was less IVT on the second observation day, mean precipitation increased from the first day. Model simulations show that evaporation makes only a small contribution to the budget. Within the ICON simulations, the comparison of precipitation purely based on the along-track radar curtain against that over the entire AR corridor indicates that the along-track curtain captures the mean precipitation intensity of the AR corridor, but misrepresents its spatial variability. However, the HALO devices outperform the ICON simulations in terms of the vertical variability of moisture conversion processes.

In the context of the Transregional Collaborative Research Center on "Arctic Amplification: Climate Relevant Atmospheric and Surface Processes, and Feedback Mechanisms”, we challenge the ICOsahedral Non-hydrostatic modelling framework ICON by performing simulations in a complex Arctic environment. Our study aims at adding a significant reference for how well ICON can perform in the Arctic and give ideas on how to improve the performance related to the microphysical parameterizations. With the ambition to resolve the clouds directly, we used ICON in the large-eddy mode (ICON-LEM), which enables the use of a 3D Smagorinsky turbulence scheme. We further applied a two-moment microphysics scheme. The setup consists of a circular domain with 600 m resolution centred around Ny-Ålesund (Svalbard) with approx. 100 km diameter. As forcing, hourly data from a 2.4 km ICON-NWP simulation covering a limited area around the archipelago of Svalbard was used. These NWP simulations were forced with the operational global ICON forecasts. Ny-Ålesund was chosen because of its intricate topography, heterogenic surfaces and availability of observational data for comparisons. The setup was run semi-operationally for 24 h on a daily basis for several months and therefore we were able to create statistics based on an outstandingly large data set. Using the columnar output of Ny-Ålesund we compared it to a large variety of observations (e.g. liquid water path, wind and relative humidity). This evaluation showed an astonishingly high agreement between the measurements and the simulations. For instance, the orographically influenced flow, as well as seasonal and short-range changes in humidity, are captured. Certain aspects, such as the formation of liquid vs ice in clouds, need improvement. On the whole, we could show that ICON-LEM is a useful tool to study the Arctic atmosphere and its changing climate. Further, we can continue to get a better picture of possibilities to understand the microphysical processes and improve their representation in the model. This work was supported by the DFG funded Transregio-project TR 172 “Arctic Amplification (AC)3“.

This data contains the simulation data as meteogram from ICON-LEM simulations with ca. 600 m resolution. The output location is Ny-Ålesund. The data is for the months Aug and Oct 2021. This data was used in the PhD thesis of Theresa Kiszler. Thesis title: "Improving our understanding of cloud phase-partitioning using long-term cloud-resolving simulations of Svalbard". The original simulation setup is is described in the method section of the paper "A Performance Baseline for the Representation of Clouds and Humidity in Cloud-Resolving ICON-LEM Simulations in the Arctic" by Kiszler et al. (2023). https://doi.org/10.1029/2022MS003299 The following adaptation has been made to the simulation settings: The CCN activation is based on a version by Segal and Khain (2006) using the lowest possible number concentration, i.e. maritime aerosols. The INP nucleation follows the paper by Phillips et al. (2008) only using dust as aerosol. The implementation of the mentioned schemes was not done by us, only the settings were changed to use these schemes instead of the default version.

Mechanisms behind the phenomenon of Arctic amplification are widely discussed. To contribute to this debate, the (AC)3 project has been established in 2016 (http://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, ship-borne, 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 air mass transport and transformation.

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 Chellini et al. (2023) and is freely available at: https://doi.org/10.5281/zenodo.7803064.

The Arctic is warming faster than the global average and any other region of a similar size. One important factor in this is the poleward atmospheric transport of heat and moisture, which contributes directly to the surface and air warming. In this case study, the atmospheric circulation and spatio-temporal structure of a moisture intrusion event is assessed, which occurred from 5 to 7 June 2017 over the Nordic seas during an intensive measurement campaign over Svalbard. This analysis focuses on high-spatial-resolution simulations with the ICON (ICOsahedral Non-hydrostatic) model which is put in context with coarser-resolution runs as well the ERA5 reanalysis. A variety of observations including passive microwave satellite measurements is used for evaluation. The global operational ICON forecasts from the Deutscher Wetterdienst (DWD) at 13 km horizontal resolution are used to drive high-resolution Limited-Area Mode (LAM) ICON simulations over the Arctic with 6 and 3 km horizontal resolutions. The results show the skilful capacity of the ICON-LAM model to represent the observed spatio-temporal structure of the selected moisture intrusion event and its signature in the temperature, humidity and wind profiles, and surface radiation. In several aspects, the high-resolution simulations offer a higher accuracy than the global simulations and the ERA5 reanalysis when evaluated against observations. One feature where the high-resolution simulations demonstrated an advanced skill is the representation of the changing vertical structure of specific humidity and wind associated with the moisture intrusion passing Ny-Ålesund (western Svalbard); the humidity increase at 1–2 km height topped by a dry layer and the development of a low-level wind jet are best represented by the 3 km simulation. The study also demonstrates that such moisture intrusions can have a strong impact on the radiative and turbulent heat fluxes at the surface. A drastic decrease in downward shortwave radiation by ca. 500 W m−2 as well as an increase in downward longwave radiation by ca. 100 W m−2 within 3 h have been determined. These results highlight the importance of both moisture and clouds associated with this event for the surface energy budget.

Low-level mixed-phase clouds (MPCs) occur widely and frequently in the Arctic, and on average introduce a strong positive radiative forcing. While precipitation is expected to affect radiative characteristics of Arctic MPCs, the relevancy of precipitation-formation processes, such as aggregation and riming, has been widely overlooked. An incomplete understanding of precipitation-formation processes in Arctic MPCs is likely to impact our ability to accurately simulate their evolution, macrophysical characteristics, and radiative effects. We employ a 3-year dataset of remote sensing observations from Ny-Ålesund, Svalbard, including two vertically-pointing Doppler radar systems, measuring at K- and W-band, to statistically assess the relevancy of aggregation and riming in Arctic low-level MPCs. We use the ratio of radar reflectivities measured at the two frequencies as a proxy for particle size, and match it with Doppler velocity information and temperature retrievals, to identify situations when the ice-particle growth is dominated by either aggregation or riming. We find observational evidence that large ice particles (mass median diameter > 1mm) mostly form when the mixed-phase layer of the low-level MPC is at temperatures compatible with dendritic growth (-15 to -10°C). Fall speeds of these larger particles are incompatible with significant riming. While mixed-phase layer temperatures between -15 and -10°C seem to be essential for the formation of large aggregates, these larger hydrometeors are not uniformly distributed across the cloud field. They are in fact observed in small pockets, suggesting that further dynamical processes might be needed to fully explain these signatures. Surprisingly, we find no evidence of enhanced aggregation at temperatures above -5°C in Arctic low-level MPCs. This is typically observed in mid-latitude clouds, and in deeper cloud systems in Ny-Ålesund as well. We hypothesize that ice particles sedimenting from higher levels might be an essential component needed to trigger enhanced aggregation above -5°C. We will discuss potential reasons for the absence of this feature, which are likely connected to the specific ice habits growing at these temperatures, as well as enhanced riming.

State-of-the-art high resolution, convection resolving NWP models and reanalysis typically operate on a horizontal resolution of 1-5 km. These models require specific data assimilation schemes with frequent analysis (every 1-6 h) and corresponding dense and frequent observations to define the detailed initial conditions. Key variables needed for convection-resolving data assimilation are, among others, the 3-dimensional fields of temperature and humidity. Both variables are not adequately (vertically, horizontally and temporally) measured by current observing systems. The vertical resolution of atmospheric profiles provided by satellite sensors is poor, especially in the atmospheric boundary layer, where convection resolving models have many layers close to the surface to better describe the surface-atmosphere exchange processes. To the necessary information, a new generation of observations through the lowest few kilometers of the atmosphere is required. A network of ground-based remote sensing sensors (e.g., microwave radiometer, MWR, or water vapor DIAL) has the potential to provide real time profile observations to forecasting centers. Maintaining an operational observing network is a difficult and expensive task. Therefore, it is essential to evaluate the impact of different components of the current observing system and to assess the potential contribution of a new observing components to the analysis of the atmospheric state. In our study we perform an Observing System Simulation Experiment (OSSE) to show the potential benefit of ground-based MWR for improving the initial thermodynamic state of the atmosphere. The Nature Run (NR), representing the “true” atmosphere, is performed using the ICON-LES model for a 150x150 km domain in the western part of Germany with 500 m horizontal resolution for summer convective cases. The MWR observations, dependent on cloudiness, temperature and humidity profiles, are simulated with the radiative transfer model RTTOV-gb and assimilated into the convection resolving ICON model (2km horizontal resolution). In this contribution, we will present first impact studies of assimilating synthetic observations of single MWR instruments on the initial temperature and humidity fields and extend the approach for evaluating the effect of a network of instruments with respect to other variables relevant for solar power applications, such as precipitation and solar radiation.