Search

One dimensional atmospheric boundary layer (ABL) model coupled with detailed atmospheric chemistry and aerosol dynamical model, the model SOSAA, was used to predict the ABL and detailed aerosol population (characterized by the number size distribution) time evolution. The model was applied over a period of ten days in May 2013 for a pine forest site in southern Finland. The period was characterized by frequent new particle formation events and simultaneous intensive aerosol transformation. Throughout this study we refer to nucleation, condensational growth and coagulation as aerosol dynamical processes, i.e. the processes that govern the particle size distribution evolution. The aim of the study was to analyze and quantify the role of aerosol and ABL dynamics in vertical transport of aerosols. It was of particular interest to what extent the fluxes above canopy deviate due to above mentioned processes from the particle dry deposition on the canopy foliage. The model simulations revealed that the particle concentration change due to aerosol dynamics can frequently exceed the effect of particle deposition even an order of magnitude or more. The impact is however strongly dependent on particle size and time. In spite of the fact that the time scale of turbulent transfer inside canopy is much smaller than the time scales of aerosol dynamics and dry deposition, letting to assume well mixed properties of air, the fluxes at the canopy top frequently deviate from deposition inside forest. This is due to transformation of aerosol concentration throughout the ABL and resulting complicated pattern of vertical transport. Therefore we argue that the comparison of time scales of aerosol dynamics and deposition defined for the processes below the flux measurement level do not unambiguously describe the importance of aerosol dynamics for vertical transport within canopy. We conclude that under dynamical conditions the micrometeorological particle flux measurements such as performed by the eddy covariance technique do not generally represent the dry deposition. The deviation can be systematic for certain size ranges so that the conclusion applies also to time averaged particle fluxes. [ABSTRACT FROM AUTHOR]

Using the 1-D atmospheric chemistry transport model SOSAA, we have investigated the atmospheric reactivity of a boreal forest ecosystem during the HUMPPACOPEC- 10 campaign (summer 2010, at SMEAR II in southern Finland). For the very first time, we present vertically resolved model simulations of the NO3 and O3 reactivity (R) together with the modelled and measured reactivity of OH. We find that OH is the most reactive oxidant (R ~3 s-1) followed by NO3 (R ~0:07 s-1) and O3 (R ~2✕10-5 s-1). The missing OH reactivity was found to be large in accordance with measurements (~65%) as would be expected from the chemical subset described in the model. The accounted OH radical sinks were inorganic compounds (~ 41%, mainly due to reaction with CO), emitted monoterpenes (~14%) and oxidised biogenic volatile organic compounds (~44%). The missing reactivity is expected to be due to unknown biogenic volatile organic compounds and their photoproducts, indicating that the true main sink of OH is not expected to be inorganic compounds. The NO3 radical was found to react mainly with primary emitted monoterpenes (~60%) and inorganic compounds (~37%, including NO2). NO2 is, however, only a temporary sink of NO3 under the conditions of the campaign (with typical temperatures of 20-25 °C) and does not affect the NO3 concentration. We discuss the difference between instantaneous and steadystate reactivity and present the first boreal forest steady-state lifetime of NO3 (113 s). O3 almost exclusively reacts with inorganic compounds (~91%, mainly NO, but also NO2 during night) and less with primary emitted sesquiterpenes (~6%) and monoterpenes (~ 3%). When considering the concentration of the oxidants investigated, we find that OH is the oxidant that is capable of removing organic compounds at a faster rate during daytime, whereas NO3 can remove organic molecules at a faster rate during night-time. O3 competes with OH and NO3 during a short period of time in the early morning (around 5 a.m. local time) and in the evening (around 7-8 p.m.). As part of this study, we developed a simple empirical parameterisation for conversion of measured spectral irradiance into actinic flux. Further, the meteorological conditions were evaluated using radiosonde observations and ground-based measurements. The overall vertical structure of the boundary layer is discussed, together with validation of the surface energy balance and turbulent fluxes. The sensible heat and momentum fluxes above the canopy were on average overestimated, while the latent heat flux was underestimated. [ABSTRACT FROM AUTHOR]

New particle formation (NPF) is an important atmospheric phenomenon. During a NPF event, molecular clusters first form by nucleation and then grow further by condensation of vapors. The growth step is crucial because it controls the number of particles that can become cloud condensation nuclei. In order to better understand the influence of biogenic emissions on particle growth, we carried out modeling studies of NPF events during the BEACHON-ROCS campaign at Manitou Experimental Forest Observatory in Colorado, USA. The site is representative of the semi-arid Western US. The implemented chemistry scheme with the latest Criegee intermediates reaction rates under estimates sulfuric acid concentration by 50%, suggesting missing atmospheric sulfuric acid sources. The results emphasize the contribution from biogenic volatile organic compound emissions to particle growth by demonstrating the effects of the oxidation products of monoterpenes and 2-Methyl-3-buten-2-ol (MBO). Monoterpene oxidation products are shown to influence the nighttime particle loadings significantly while their concentrations are insufficient to grow the particles during the day. The growth of ultrafine particles in daytime appears to be closely related to the OH oxidation products of MBO. [ABSTRACT FROM AUTHOR]

Using the 1D atmospheric chemistry-transport model SOSAA, we have investigated the atmospheric reactivity of a boreal forest ecosystem during the HUMPPA-COPEC-10 campaign (summer 2010, at SMEAR II in Southern Finland). For the very first time, we present vertically resolved model simulations of the NO3- and O3-reactivity (R) together with the modelled and measured reactivity of OH. We find that OH is the most reactive oxidant (R ~ 3 s-1) followed by NO3 (R ~ 0.07s-1) and O3 (R ~ 2 x10-5 s-1). The missing OH-reactivity was found to be large in accordance with measurements (~ 65%) as would be expected from the chemical subset described in the model. The accounted OH radical sinks were inorganic compounds (~ 41%, mainly due to reaction with CO), emitted monoterpenes (~ 14%) and oxidised biogenic volatile organic compounds (~ 44%). The missing reactivity is expected to be due to unknown biogenic volatile organic compounds and their photoproducts, indicating that the true main sink of OH is not expected to be inorganic compounds. The NO3 radical was found to react mainly with primary emitted monoterpenes (~ 60%) and inorganic compounds (~ 37%, including NO2). NO2 is, however, only a temporary sink of NO3 under the conditions of the campaign and does not affect the NO3 concentration. We discuss the difference between instantaneous and steady state reactivity and present the first boreal forest steady state lifetime of NO3 (113 s). O3 almost exclusively reacts with inorganic compounds (~ 91%, mainly NO, but also NO2 during night) and less with primary emitted sesquiterpenes (~ 6%) and monoterpenes (~ 3%). When considering the concentration of the oxidants investigated, we find that O3 is the oxidant that is capable of removing pollutants fastest. As part of this study, we developed a simple empirical parameterisation for conversion of measured spectral irradiance into actinic flux. Further, the meteorological conditions were evaluated using radiosonde observations and ground based measurements. The overall vertical structure of the boundary layer is discussed, together with validation of the surface energy balance and turbulent [ABSTRACT FROM AUTHOR]

The shape of ice crystals affects their radiative properties, growth rate, fall speed, and collision efficiency; thus, it plays a significant role in cloud optical properties and precipitation formation. Ambient conditions, like temperature and humidity, determine the basic habit of ice crystals, while microphysical processes, such as riming and aggregation, further shape them, resulting in a diverse set of ice crystal shapes and effective densities. Current classification algorithms face two major challenges: (1) ice crystals are often classified as a whole (at the image scale), necessitating identification of the dominant component of aggregated ice crystals, and (2) single-label classifications lead to information loss because of the compromise between basic habit and microphysical process information. To address these limitations, we present a two-pronged solution here: (1) a rotated object detection algorithm (IceDetectNet) that classifies each component of an aggregated ice crystal individually and (2) a multi-label classification scheme that considers both basic habits and physical processes simultaneously. IceDetectNet was trained and tested on two independent datasets obtained by a holographic imager during the NASCENT campaign in Ny-Ålesund, Svalbard, in November 2019 and April 2020. The algorithm correctly classified 92 % of the ice crystals as either aggregate or non-aggregate and achieved an overall accuracy of 86 % for basic habits and 82 % for microphysical process classification. At the component scale, IceDetectNet demonstrated high detection and classification accuracy across all sizes, indicating its ability to effectively classify individual components of aggregated ice crystals. Furthermore, the algorithm demonstrated a good generalization ability by classifying ice crystals from an independent generalization dataset with overall accuracies above 70 %. IceDetectNet can provide a deeper understanding of ice crystal shapes, leading to better estimates of ice crystal mass, fall velocity, and radiative properties; therefore, it has the potential to improve precipitation forecasts and climate projections. [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]

The aerosol particles serving as cloud condensation and ice nuclei contribute to key cloud processes associated with cold-air outbreak (CAO) events but are poorly constrained in climate models due to sparse observations. Here we retrieve aerosol number size distribution modes from measurements at Andenes, Norway, during the Cold-Air Outbreaks in the Marine Boundary Layer Experiment (COMBLE) and at Zeppelin Observatory, approximately 1000 km upwind from Andenes at Svalbard. During CAO events at Andenes, the sea-spray-mode number concentration is correlated with strong over-ocean winds with a mean of 8±4 cm−3 that is 71 % higher than during non-CAO conditions. Additionally, during CAO events at Andenes, the mean Hoppel minimum diameter is 6 nm smaller than during non-CAO conditions, though the estimated supersaturation is lower, and the mean number concentration of particles that likely activated in-cloud is 109±61 cm−3 with no statistically significant difference from the non-CAO mean of 99±66 cm−3. For CAO trajectories between Zeppelin Observatory and Andenes, the upwind-to-downwind change in number concentration is the largest for the accumulation mode with a mean decrease of 93±95 cm−3, likely attributable primarily to precipitation scavenging. These characteristic properties of aerosol number size distributions during CAO events provide guidance for evaluating CAO aerosol–cloud interaction processes in models. [ABSTRACT FROM AUTHOR]

The budget of reactive nitrogen species, which play a central role in atmospheric chemistry (e.g. in photochemical O3 production), is poorly understood in forested regions. In this study, through observations of NO, NO2 , NOy , and O3 in the Rambouillet Forest near Paris, France, we have examined nighttime processes controlling NOx in an anthropogenically impacted forest environment. The O3 mixing ratios displayed a strong diel profile at the site that was driven by a variable but generally rapid deposition to soil and foliar surfaces. The O3 diel profile was strongly influenced by relative humidity and temperature inversion. Only when the O3 mixing ratio was sufficiently low (and thus the NO lifetime sufficiently long) were sustained NO peaks observed above the instrumental detection limit, enabling the derivation of average NO emission rates of ∼1.4 ppbvh-1 from the soil. Observations of the lack of increase in NO2 at night, despite a significant production rate from the reaction of NO with O3 , enabled an effective lifetime of NO2 of ∼0.5 –3 h to be derived. As the loss of NO2 was not compensated for by the formation of gas- or particle-phase reactive nitrogen species, it was presumably either driven by deposition to soil and foliar surfaces or any products formed were themselves short-lived with respect to deposition. By comparison, the daytime lifetime of NO2 with respect to loss by reaction with OH is about 1 d. Our results indicate that the nighttime deposition of NO2 is a major sink of boundary layer NOx in this temperate forest environment. [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]

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 climate impact of Arctic aerosols, like the Arctic Haze, and their origin are not fully understood. Therefore, long-term aerosol observations in the Arctic are performed. In this study, we present a homogenised data set from a sun and star photometer operated in the European Arctic, in Ny-Ålesund, Svalbard, of the 20 years from 2004–2023. Due to polar day and polar night, it is crucial to use observations of both instruments. Their data is evaluated in the same way and follows the cloud-screening procedure of AERONET. Additionally, an improved method for the calibration of the star photometer is presented. We found out, that autumn and winter are generally more polluted and have larger particles than summer. While the monthly median Aerosol Optical Depth (AOD) decreases in spring, the AOD increases significantly in autumn. A clear signal of large particles during the Arctic Haze can not be distinguished from large aerosols in winter. With autocorrelation analysis, we found that AOD events usually occur with a duration of several hours. We also compared AOD events with large-scale processes, like large-scale oscillation patterns, sea ice, weather conditions, or wildfires in the Northern Hemisphere but did not find one single cause that clearly determines the Arctic AOD. Therefore the observed optical depth is a superposition of different aerosol sources. [ABSTRACT FROM AUTHOR]

Background: The post-pandemic period, military conflicts, and geopolitical instability have all contributed to concerns regarding the world's sustainable and stable development, and small national economies are particularly vulnerable to these challenges. The five countries of the Western Balkan region (Republic of Serbia, Republic of North Macedonia, Bosnia and Herzegovina, Montenegro, and Albania) have established their national interests and formulated security policies in line with their strategic commitment to the green transition and integration into the European Union. The region has been grappling with a multitude of challenges for several decades, and further instability may be expected beyond 2022. This paper aims to analyze the impact of sustainable development politicization on the security policies of Western Balkan countries and identify critical challenges to the region's sustainable development. Main text: The main research findings suggest that the security strategy of the Western Balkan countries was distinct from their economic and energy development until the beginning of the twenty-first century. Sustainable development is a strategic commitment of the Western Balkan countries, but it necessitates intricate changes, particularly in energy and economy. However, the Western Balkan countries have been confronted with new challenges due to the intricate geopolitical developments that emerged after 2022. The following are particularly noteworthy: frequently conflicting regional initiatives, the usage of energy resources and essential minerals, and significant impacts on how individuals form their opinion on these matters. The factors mentioned above are distinct security threats that require the Western Balkan countries to pursue solutions. Conclusions: A politicized approach to sustainable development is a novel phenomenon that has to be incorporated into current security policy. Specifically, the present approach, which prioritizes the state's security, often conflicts with the emerging concept of individual security (which focuses on the stability of the economy and the environment). This situation adds a layer of complexity to the position of the Western Balkan countries. They have a limited capacity to impact geopolitical developments, and in order to make progress, maintain stability, and foster social peace, they must make concessions and cooperate with influential economies that frequently have conflicting geopolitical interests. [ABSTRACT FROM AUTHOR]

Aerosol–cloud interactions in mixed-phase clouds (MPCs) are one of the most uncertain drivers of the hydrological cycle and climate change. A synergy of in situ, remote-sensing and modelling experiments were used to determine the source of ice-nucleating particles (INPs) for MPCs at Mount Helmos in the eastern Mediterranean. The influences of boundary layer turbulence, vertical aerosol distributions and meteorological conditions were also examined. When the observation site is in the free troposphere (FT), approximately 1 in ×106 aerosol particles serve as INPs around -25 °C. The INP abundance spans 3 orders of magnitude and increases in the following order: marine aerosols; continental aerosols; and, finally, dust plumes. Biological particles are important INPs observed in continental and marine aerosols, whereas they play a secondary, although important, role during Saharan dust events. Air masses in the planetary boundary layer (PBL) show both enriched INP concentrations and a higher proportion of INPs to total aerosol particles, compared with cases in the FT. The presence of precipitation/clouds enriches INPs in the FT but decreases INPs in the PBL. Additionally, new INP parameterizations are developed that incorporate the ratio of fluorescent-to-nonfluorescent or coarse-to-fine particles and predict >90 % of the observed INPs within an uncertainty range of a factor of 10; these new parameterizations exhibit better performance than current widely used parameterizations and allow ice formation in models to respond to variations in dust and biological particles. The improved parameterizations can help MPC formation simulations in regions with various INP sources or different regions with prevailing INP sources. [ABSTRACT FROM AUTHOR]

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 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]

We present direct measurements of biogenic volatile organic compound (BVOC)-induced nitrate radical (NO3) reactivity (kVOC) through the diel cycle in the suburban, temperate forest of Rambouillet near Paris (France). The data were obtained in a 6-week summer period in 2022 as part of the Atmospheric ChemistRy Of the Suburban foreSt (ACROSS) campaign. kVOC was measured in a small (700 m2) clearing mainly at a height of 5.5 m above ground level but also at 40 m (for 5 d and nights). At nighttime, mean values (and 25th–75th percentile ranges) of knightVOC(5.5m) = (0.24-0.06+0.32) s-1 and knightVOC(40m) = (0.016-0.007+0.018) s-1 indicate a significant vertical gradient and low NO3 reactivity above the canopy, whereas knightVOC (5.5 m) showed peak values of up to 2 s-1 close to the ground. The strong vertical gradient in NO3 reactivity could be confirmed by measurements between 0 and 24 m on one particular night characterized by a strong temperature inversion and is a result of the decoupling of air masses aloft from the ground- and canopy-level sources of BVOCs (and nitric oxide, NO). No strong vertical gradient was observed in the mean daytime NO3 reactivity, with kdayVOC(5.5m) = (0.12±0.04) s-1 for the entire campaign and kdayVOC(40m) = (0.07±0.02) s-1 during the 5 d period. Within the clearing, the fractional contribution of VOCs to the total NO3 loss rate coefficient (ktot , determined by photolysis, reaction with NO and VOCs) was 80 %–90 % during the night and ∼ 50 % during the day. In terms of chemical losses of α -pinene below canopy height in the clearing, we find that at nighttime hydroxyl radicals (OH) and ozone (O3) dominate, with NO3 contributing "only" 17 %, which decreases further to 8.5 % during the day. Based on measured OH, measured O3 , and calculated NO3 concentrations, the chemical lifetime of BVOCs at noon is about 1 h and is likely to be longer than timescales of transport out of the canopy (typically of the order of minutes), thus significantly reducing the importance of daytime in-canopy processing. Clearly, in forested regions where sufficient nitric oxide and nitrogen dioxide (NOx) is available, the role of NO3 and OH as initiators of BVOC oxidation is not strictly limited to nighttime and daytime, respectively, as often implied in e.g. atmospheric chemistry textbooks. [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]

In recent years, with the continuous progress of Internet of things technology, the typical application of Internet of things has been gradually launched. The virtual reality platform of the Internet of things technology provides an effective means for the multi-path development of technology, and provides an important reference for the refinement of management mode. Virtual reality technology is the extension of network information. It sets up a virtual scene for people and realizes the integration between people and machines. As the most advanced information technology in the current situation, cloud computing technology and ubiquitous network contain innovative ideas. In the current era, CG image has entered into many fields, such as film, game, network, medical treatment, industry and so on, and quickly become the new focus of cultural industry. As an art form of art technology integration, CG image brings unprecedented development prospects for film and television art with its outstanding plasticity and simulacrity. In this paper, we use the ubiquitous Internet of things technology to build a CG virtual reality framework. The proposed model is validated under different database and the performance is tested with different information sources. [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]

The thermodynamic phase of clouds in low and middle levels over the Southern Ocean and the Arctic marine regions is poorly known, leading to uncertainties in the radiation budget in weather and climate models. To improve the knowledge of the cloud phase, we analyse 2 years of the raDAR-liDAR (DARDAR) dataset based on active satellite instruments. We classify clouds according to their base and top height and focus on low-, mid-, and mid- to low-level clouds as they are the most frequent in the mixed-phase temperature regime. Low-level single-layer clouds occur in 8 % –15 % of all profiles, but single-layer clouds spanning the mid-level also amount to approx. 15 %. Liquid clouds show mainly a smaller vertical extent but a horizontally larger extent compared to ice clouds. The results show the highest liquid fractions for low-level and mid-level clouds. Two local minima in the liquid fraction are observed around cloud top temperatures of -15 and -5 ° C. Mid-level and mid- to low-level clouds over the Southern Ocean and low-level clouds in both polar regions show higher liquid fractions if they occur over sea ice compared to the open ocean. Low-level clouds and mid- to low-level clouds with high sea salt concentrations, used as a proxy for sea spray, show reduced liquid fractions. In mid-level clouds, dust shows the largest correlations with liquid fraction, with a lower liquid fraction for a higher dust aerosol concentration. Low-level clouds clearly show the largest contribution to the shortwave cloud radiative effect in both polar regions, followed by mid- to low-level clouds. [ABSTRACT FROM AUTHOR]

The representation of Arctic clouds and their phase distributions, i.e., the amount of ice and supercooled water, influences predictions of future Arctic warming. Therefore, it is essential that cloud phase is correctly captured by models in order to accurately predict the future Arctic climate. Ice crystal formation in clouds happens through ice nucleation (primary ice production) and ice multiplication (secondary ice production). In common weather and climate models, rime splintering is the only secondary ice production process included. In addition, prescribed number concentrations of cloud condensation nuclei or cloud droplets and ice-nucleating particles are often overestimated in Arctic environments by standard model configurations. This can lead to a misrepresentation of the phase distribution and precipitation formation in Arctic mixed-phase clouds, with important implications for the Arctic surface energy budget. During the Ny-Ålesund Aerosol Cloud Experiment (NASCENT), a holographic probe mounted on a tethered balloon took in situ measurements of number and mass concentrations of ice crystals and cloud droplets in Svalbard, Norway, during fall 2019 and spring 2020. In this study, we choose one case study from this campaign that shows evidence of strong secondary ice production and use the Weather Research and Forecasting (WRF) model to simulate it at a high vertical and spatial resolution. We test the performance of different microphysical parametrizations and apply a new state-of-the-art secondary ice parametrization. We find that agreement with observations highly depends on the prescribed cloud condensation nuclei/cloud droplet and ice-nucleating particle concentrations and requires an enhancement of secondary ice production processes. Lowering mass mixing ratio thresholds for rime splintering inside the Morrison microphysics scheme is crucial to enable secondary ice production and thereby match observations for the right reasons. In our case, rime splintering is required to initiate collisional breakup. The simulated contribution from collisional breakup is larger than that from droplet shattering. Simulating ice production correctly for the right reasons is a prerequisite for reliable simulations of Arctic mixed-phase cloud responses to future temperature or aerosol perturbations. [ABSTRACT FROM AUTHOR]

Accurately representing mixed‐phase clouds (MPCs) in global climate models (GCMs) is critical for capturing climate sensitivity and Arctic amplification. Secondary ice production (SIP), can significantly increase ice crystal number concentration (ICNC) in MPCs, affecting cloud properties and processes. Here, we introduce a machine‐learning (ML) approach, called Random Forest SIP (RaFSIP), to parameterize SIP in stratiform MPCs. RaFSIP is trained on 16 grid points with 10‐km horizontal spacing derived from a 2‐year simulation with the Weather Research and Forecasting (WRF) model, including explicit SIP microphysics. Designed for a temperature range of 0 to −25°C, RaFSIP simplifies the description of rime splintering, ice‐ice collisional break‐up, and droplet‐shattering using only a limited set of inputs. RaFSIP was evaluated offline before being integrated into WRF, demonstrating its stable online performance in a 1‐year simulation keeping the same model setup as during training. Even when coupled with the 50‐km grid spacing domain of WRF, RaFSIP reproduces ICNC predictions within a factor of 3 when compared to simulations with explicit SIP microphysics. The coupled WRF‐RaFSIP scheme replicates regions of enhanced SIP and accurately maps ICNCs and liquid water content, particularly at temperatures above −10°C. Uncertainties in RaFSIP minimally impact surface cloud radiative forcing in the Arctic, resulting in radiative biases under 3 Wm−2 compared to simulations with detailed microphysics. Although the performance of RaFSIP in convective clouds remains untested, its adaptable nature allows for data set augmentation to address this aspect. This framework opens possibilities for GCM simplification and process description through physics‐guided ML algorithms. Plain Language Summary: Being able to correctly simulate the amount of ice and liquid in clouds is essential for accurate predictions of the cloud radiative forcing in the climatologically sensitive polar regions. A number of collisional processes between ice and liquid particles in clouds, known as secondary ice production, can significantly enhance the ice crystal number concentrations contained in them. This enhancement is often accompanied by a decrease in the cloud liquid water content, resulting in less opaque clouds to incoming solar radiation, which, in turn, can cause a cloud‐induced warming at the surface. Currently most global climate models are missing the description of the most important secondary ice production processes, which can lead to a biased radiative impact of clouds at the surface. To address this, we propose using a machine learning algorithm trained on high‐resolution model outputs to include the effect of ice multiplication in large‐scale climate models. The machine learning framework effectively captures the physical processes underlying secondary ice production in stratiform clouds using only a few inputs readily available in model frameworks. This approach has the potential to improve model predictions bringing them closer to the observed cloud phase partitioning. Key Points: A random‐forest parameterization for secondary ice production is developed using outputs from a 10‐km horizontal grid spacing simulationCloud phase partitioning agrees within a factor of 3, with radiative biases below 3 Wm−2 compared to the detailed microphysics simulationThe scheme can be adjusted to coarser resolutions typical of climate models without losing computational efficiency and numerical stability [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]

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. [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 aerosol particles that provide cloud condensation and ice nuclei contribute to key cloud processes associated with cold-air outbreak (CAO) events but are poorly constrained in climate models due to sparse observations. Here we retrieve aerosol size distribution modes from measurements at Andenes, Norway during the Cold-Air Outbreaks in the Marine Boundary Layer Experiment (COMBLE) and at Zeppelin Observatory, approximately 1000 km upwind in Svalbard. During CAO events at Andenes, the sea spray mode number concentration is correlated to strong over-ocean winds with a mean of 8±4 cm-3 that is 71 % higher than during non-CAO conditions. Additionally during CAO events at Andenes, the mean Hoppel minimum diameter is 6 nm smaller than during non-CAO conditions though the estimated supersaturation is lower and the number concentration of particles that likely activated in-cloud is 109±61 cm-3 (similar to non-CAO conditions). For CAO trajectories between Zeppelin Observatory and Andenes, the upwind-to-downwind change in number concentration is largest for the accumulation mode with a mean decrease of 93±95 cm-3, likely attributable primarily to precipitation scavenging. These characteristic properties of aerosol size distributions during CAO events provide guidance for evaluating CAO aerosol-cloud interaction processes in models. [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]

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]

Active vegetation fires in south‐eastern (SE) Europe resulted in a notable increase in the number concentration of aerosols and cloud condensation nuclei (CCN) particles at two high latitude locations—the SMEAR IV station in Kuopio, Finland, and the Zeppelin Observatory in Svalbard, high Arctic. During the fire episode aerosol hygroscopicity κ slightly increased at SMEAR IV and at the Zeppelin Observatory κ decreased. Despite increased κ in high CCN conditions at SMEAR IV, the aerosol activation diameter increased due to the decreased supersaturation with an increase in aerosol loading. In addition, at SMEAR IV during the fire episode, in situ measured cloud droplet number concentration (CDNC) increased by a factor of ∼7 as compared to non‐fire periods which was in good agreement with the satellite observations (MODIS, Terra). Results from this study show the importance of SE European fires for cloud properties and radiative forcing in high latitudes. Plain Language Summary: Wildfires are large sources of aerosol particles and affect human health and climate. Aerosols from fires are transported long distances in the atmosphere and affect the aerosol and cloud properties at places far from the actual sources. In this study, we measured the long‐range transported (LRT) fire air masses from south‐eastern (SE) Europe at a northern European and a high Arctic site. LRT fire emissions from SE Europe increase the aerosol number and mass loading in Finland and even in the high Arctic. Results show that the effect of fire emissions on aerosol hygroscopicity depends on the properties of both the LRT fires and the background aerosols at a given location. The cloud properties analysis in eastern Finland shows that despite high hygroscopicity and increased CCN activity, the aerosol activation diameter for clouds increased during the fire episode. This is due to the depletion of available water vapor in clouds due to the increased aerosol loading. Satellite observations show an increase in cloud droplet number concentration during the fire episode confirming the effect of LRT fires on cloud properties in eastern Finland. This study can improve the understanding of the effect of LRT fires on aerosol and cloud properties at remote locations. Key Points: Vegetation fires from southern Europe enhance aerosol and cloud condensation nuclei concentrations in northern Europe and the high ArcticA contrary trend in aerosol hygroscopicity is observed at these two locations during a strong fire episode as compared to non‐fire periodsCloud droplet number concentrations in liquid clouds show strong response to fire aerosol both in in situ and satellite observations [ABSTRACT FROM AUTHOR]