Abstract. Ice nucleating particles (INPs) are rare aerosols essential for cloud ice formation in the mixed-phase temperature range between -38 °C and 0 °C. Due to measurement challenges and limitations in instrument capabilities, the availability of atmospheric observations of INPs remains scarce in time and space. Consequently, no observation-based global distribution of INPs exists so far. This study applies a machine learning (gradient boosting) algorithm to predict the INP concentration over the mixed-phase temperature range across the globe using aerosol mass concentration reanalysis and observed immersion-mode INPs. This proof-of-concept exercise demonstrates that even with limited measurements, the occurrence of INPs can be estimated, following the spatial pattern of key aerosol species. Point-based evaluation metrics, R2 and log-based RMSE, reach 0.83 and 0.71 for the gradient boosting model, compared to 0.75 and 0.86 for the linear regression benchmark. Regional INP spectra with temperature extracted from the machine learning model agree within one order of magnitude with observations, except over Antarctica (mean bias factor of 150). INPs in continental (oceanic) regions are well predicted within a mean bias of 2.4 (overestimated within a mean bias of 4) by the machine learning model. The prediction is driven by the strong temperature dependence followed by mid-sized dust particles. This approach can resolve a long-standing source of INP prediction uncertainty in regional weather and climate models.

Particle nucleation from trace atmospheric vapours is important for climate since it gives rise to more than half of global cloud condensation nuclei. Sulfuric acid (H2SO4) has long been recognised to drive particle nucleation in the atmosphere and, more recently, highly oxygenated products of biogenic vapours-in particular monoterpenes such as α-pinene (C10H16)-have also been shown to nucleate under atmospheric conditions, without requiring additional vapours. This raises the question of whether a nucleation synergy exists between α-pinene oxygenated organic molecules (AP-OOM) and H2SO4, as has been suggested by early studies. Here we report new particle formation from AP-OOM and H2SO4 in the absence of base vapours such as ammonia (NH3), measured in experiments performed with the CERN CLOUD (Cosmics Leaving Outdoor Droplets) chamber at cool boundary layer temperatures of -10 °C and +5 °C. We find that AP-OOM nucleation rates increase strongly when H2SO4 concentrations exceed around 106 cm-3. The enhancement is synergistic and cannot be explained as a simple linear addition of independent chemical systems. Above this threshold, the nucleation rate depends approximately linearly on H2SO4 concentration, in contrast with the strong sensitivity to H2SO4 for H2SO4-NH3 nucleation. Nucleation rates are 10-100-fold higher in the presence of ions from galactic cosmic rays or from the CERN pion beam. Based on these measurements, we have parameterised a temperature-dependent H2SO4-AP-OOM nucleation rate in the absence of base vapours and implemented it in the EMAC (ECHAM/MESSy Atmospheric Chemistry) Earth system model. In comparison with a parameterisation developed in an earlier study [Riccobono et al., Science, 2014, 344, 717-721.], the new parameterisation indicates sharply reduced nucleation rates in the boundary layer over warm regions, and increased rates over northern boreal forests.

Mineral dust particles emitted from dry, uncovered soil can be transported over vast distances, thereby influencing climate and environment. Its impacts are highly size-dependent, yet large particles with diameters d(p)>10 mu m remain understudied due to their low number concentrations and instrumental limitations. Accurately characterizing the particle size distribution (PSD) at emission is crucial for understanding dust transport and climate interactions. Here we characterize the dust PSD at an emission source during the Jordan Wind Erosion and Dust Investigation (J-WADI) campaign, conducted in Wadi Rum, Jordan, in September 2022, focusing on super-coarse (10 < d(p )<= 62.5 m) and giant (d(p)>62.5 mu m) particles. This study is the first to continuously cover the full range of diameters from d(p)=0.4 to 200 mu m at an emission source by using a suite of aerosol spectrometers with overlapping size ranges. This overlap enabled a systematic intercomparison and validation across instruments, improving PSD reliability. Results show significant PSD variability over the course of the campaign. During periods with friction velocities (u(*)) above 0.22 m s(-1) (or similar to 3.3 m s(-1) threshold 4 m wind speed), the approximate threshold for local dust emission by saltation, both dust concentrations and the contributions of super-coarse and giant particles typically increased with increasing u(*), especially under neutral to unstable atmospheric stability conditions. These large particles accounted for about 90 % of the total mass concentration during the campaign. A prominent mass concentration peak was observed near d(p)=60 mu m in geometric diameter. While particle concentrations for d(p)<10 m showed good agreement among most instruments, discrepancies appeared for larger d(p) due to reduced instrument sensitivity at the size range boundaries and sampling inefficiencies. Despite these challenges, physical samples collected using a flat-plate sampler largely confirmed the PSDs derived from the aerosol spectrometers. These findings help to advance our understanding of the dust PSD and the abundance of super-coarse and giant particle at emission sources.

Ice nucleating particles (INPs) exert a substantial impact on radiative properties and lifetimes of mixed-phase clouds and can modulate their precipitation efficiency. Advancing our understanding of the abundance and properties of INPs is essential to elucidate how clouds change in a warming climate. We conducted INP measurements at the Storm Peak Laboratory (3200 m a.s.l.), in the Rocky Mountains (CO, USA) during two field campaigns in 2021/2022 and in 2025. INP concentrations were continuously measured with the Portable Ice Nucleation Experiment between-22 and-32 degrees C. INP concentrations were remarkably similar during the two campaigns and followed a seasonal pattern. Lowest concentrations were observed during winter, with median January values falling below 10 INP stdL(-1) at T >-26 degrees C. In spring, median INP concentrations increased by approximately one order of magnitude. Springtime is associated with increased dust concentrations in the Western United States, and back trajectories revealed regional and local dust regions as INP sources. As climate change is expected to intensify the influence of dust sources from deserts and semi-arid regions, this might impact INP concentrations. Moreover, INP sizes were investigated by ranked correlation coefficient analysis of parallel measurements of super-micrometer particles, and alternated INP measurements behind a 1 & micro;m impactor. In addition, for the first time, PINE was coupled to a pumped counterflow virtual impactor to analyze the sizes of ice residuals. Overall, super-micrometer particles were found to contribute significantly to the INP population throughout the entire campaign, with a reduced importance during winter.

Abstract. Mixed-phase clouds, which are dominant in mid- and high-latitude regions, strongly influence Earth’s radiative balance and precipitation processes. Their formation depends critically on the presence of ice-nucleating particles (INPs), which are rare relative to cloud condensation nuclei. The HyICE-2018 measurement campaign took place at the SMEAR II station in the high-latitude boreal forest of Hyytiälä, Finland, between February and June 2018. Two continuous-flow diffusion chambers Portable Ice Nucleation Chamber I and II (PINC and PINCii) with high-frequency sampling were deployed to measure INP concentrations. We applied machine-learning techniques to explore predictors of INP variability using more than 500 high-resolution atmospheric, aerosol, and ecosystem variables measured continuously at Station for Measuring Ecosystem-Atmosphere Relations (SMEAR) II. We identify distinct differences between winter and spring/summer measurements. The winter measurements conducted with PINC appear to be nearly independent of any monitored variable. In contrast, the spring/summer measurements conducted with PINCii appear to be more closely linked to and responsive to ambient aerosol properties. Furthermore, we find that classical parameterizations based on particle concentration overestimate observed INP concentrations in the boreal environment. However, similar empirical fits based on local proxies, such as a marker of biogenic aerosol or nitrate, yield improved agreement during spring and summer, while no improvement occurs during winter. These results underscore the need for site-specific parameterizations to capture INP variability in the complex boreal environments.

The Southern Ocean (SO) is one of the cloudiest regions on Earth. However, cloud radiative effects are not well represented over the SO in atmospheric models, which is mainly due to an underestimation of aerosols. To address this and other fundamental and pressing open questions on the interaction of atmospheric radiation, aerosol nucleation and growth, cloud formation and impacts over the SOI, the HALO-South aircraft mission was conducted in September and October 2025 based in Christchurch, Aotearoa New Zealand. HALO stands for High Altitude and Long Range Research Aircraft. HALO-South covered the full cycle of processes from aerosol formation, cloud evolution, and radiative interaction with a special focus on the characteristics and effects of mixed-phase clouds. The instrumental payload of HALO included a unique and comprehensive in-situ and remote sensing suite of instruments. It was designed to collect data to improve our understanding of fundamental atmospheric processes and to extrapolate and upscale the results using satellite data and global climate models in order to resolve long-standing measurement-modelling discrepancies. In addition, the ground-based stations in Tāwhaki and Invercargill with remote sensing and in-situ long term measurements will extend the data to a larger scale in time. The first analysis of the campaign shows promising insights into cloud and aerosol processes over the SO, which will be presented and discussed.Acknowledgments: This work was supported by the DFG (Deutsche Forschungsgemeinschaft, German Research Foundation) Priority Program SPP 1294, the Max Planck Society, Priority Program SPP 1294, the German Aerospace Center (DLR)

Ice nucleation activity (INA) in the mixed-phase cloud (MPC) regime has been extensively studied. Nevertheless, most research has focused on particles smaller than a few micrometers, leaving the INA dependence on mineralogical composition and size poorly characterized for particles larger than ten micrometers in diameter. This gap is important because: (1) large mineral dust particles (LMDPs) can undergo long-range atmospheric transport and reach altitudes where MPCs form; (2) their mineralogical composition may differ from that of smaller particles, affecting the density of ice-active sites; and (3) larger particles are more susceptible to atmospheric aging through coatings by chemical and organic compounds, which can further modify their INA. Here, we used natural soil dust samples collected during field campaigns in Morocco and Iceland, covering particle sizes from fine to super-coarse dust and characterized in terms of mineralogical composition and size. The samples' INA was measured in the AIDA and AIDAm cloud chambers and the INSEKT and IR-DROFA freezing assays in more than 300 experiments. Moroccan samples exhibited INA comparable to that reported for K-feldspar in previous studies, with no dependence on particle size, consistent with the nearly constant K-feldspar fraction across all size bins. In contrast, Icelandic samples showed lower INA than in other studies using samples of similar composition, along with a subtle size dependence linked to the size-varying pyroxene content, which decreased with increasing particle size. Our findings elucidate the role of LMDPs in immersion freezing and their relationship with mineralogy and size for low- and high-latitude dust sources.

Atmospheric simulation chambers are one of the best available tools to study atmospheric processes, as they enable experiments under conditions that are both reproducible and well-controlled. 16 unique simulation chamber facilities are part of the distributed pan-European Aerosol, Clouds and Trace Gases Research Infrastructure (ACTRIS). Their research focuses on fundamental gas-phase reaction kinetics, complex reaction mechanisms, aerosol formation and cloud chemistry, as well as other aspects of atmospheric processes. They use both simplified and complex air mixtures in their research. Results of chamber experiments enable the discovery of unknown chemical mechanisms and the determination of physicochemical parameters of atmospheric constituents. Simulation chambers are ideal for testing instruments and quality assurance of their data. The variability of their research capability is reflected in differences in the size (ranging from approximately 1-270 m3), the wall material, and the type of instrumentation used to measure physical parameters, gas-phase species, physicochemical properties of aerosol particles as well as cloud droplets and ice crystals. Most chambers in ACTRIS are indoors and use artificial light sources to initiate photochemical reactions while some chambers are located outside so that natural sunlight can be used. During experiments, steady state conditions may be achieved, the evolution of initial conditions may be observed, or expansion and mixing techniques may induce cloud formation. In this paper, the ACTRIS simulation chambers are described along with the quality control measures for carrying out experiments and reporting data. An overview of how users from the research community and industry can gain access to the ACTRIS simulation chambers and associated data centre is presented. Recent developments in the application of ACTRIS simulation chambers for answering current and future atmospheric research questions are discussed.

The presence of ice-nucleating particles (INPs) in the atmosphere plays a crucial role in shaping cloud radiative properties, influencing their lifespan, and affecting precipitation and storm dynamics. To enable continuous and high-resolution monitoring of INP concentrations, the Portable Ice Nucleation Experiment (PINE) was developed. Complementing this, the PINE INP Analysis (PIA) software was created to ensure a standardised and reproducible data processing workflow. This work presents the setup of software version 3.0.0 and the structure of the processed data. The two main components of the software – the automated quality control of the data and the algorithm to distinguish between aerosols and droplets versus ice crystals based on their optical size – are described in detail. The second part of this study provides recommendations for quality assurance of PINE measurements. It outlines procedures for conducting background checks to detect potential contamination within the chamber, evaluates the consistency between adjacent temperature sensors, and discusses how large aerosol particles can impact measurement uncertainty.

Methanesulfonic acid (MSA; CH3SO3H), produced by oxidation of dimethylsulfide (DMS; CH3SCH3), is a key precursor for aerosols in the marine boundary layer and free troposphere. Laboratory experiments show that MSA contributes to both particle nucleation and subsequent growth, often together with sulfuric acid (H2SO4) and base vapours such as ammonia (NH3). However, the influence of relative humidity (RH) on MSA condensation to particles remains uncertain. Here, in experiments conducted under low NH3 conditions (<4 parts per trillion by volume, pptv) at the CERN Cosmics Leaving OUtdoor Droplets (CLOUD) chamber, we find that RH critically regulates the participation of MSA in the initial growth of newly formed particles. Between +10 °C and -10 °C, MSA drives rapid particle growth at high RH (>50%), whereas its contribution at low RH (<16%) is negligible. When comparing with aerosol process models such as the Model for Acid-Base Chemistry in Nanoparticle Growth (MABNAG), we find that the model fails to match our laboratory results. In particular, our measurements show that MSA drives rapid particle growth at substantially warmer temperatures and lower relative humidities than predicted by the Extended Aerosol Inorganic Model (E-AIM). This highlights the importance of further experiments to fully quantify the effect of RH on MSA particle growth and evaporation, and incorporating these measurements in aerosol models. This will be essential for accurately representing the important role of MSA in marine aerosols in global models, particularly in cold, low-NH3 environments like polar regions and the free troposphere.

Abstract. Volatile methylated sulfur compounds (VMS), particularly dimethyl sulfide (DMS) and methanethiol (MeSH), are important natural sources of atmospheric sulfur. Their oxidation pathways and contribution to aerosols and cloud condensation nuclei (CCN) remain uncertain. Here, we investigate four gas-phase chemical mechanisms of increasing complexity for VMS oxidation using the global chemistry-climate model EMAC, and evaluate the results against shipborne and ground-based observations of DMS, sulfuric acid (SA), and methanesulfonic acid (MSA) between 2016 and 2019. In the marine boundary layer, DMS mixing ratios are largely insensitive to the choice of mechanism and agree well with observations, whereas simulated SA and MSA differ markedly between mechanisms. Notably, oxidation by bromine monoxide (BrO) is the dominant process controlling the DMS loss rates and concentrations in the Southern Ocean. We also evaluate the contribution of MSA to global new particle formation in the marine boundary layer, based on recent measurements of (SA+MSA)-NH3 -H2O nucleation at the CERN CLOUD chamber. Our simulations show that, under the cold and humid conditions of the Southern Ocean and Antarctic, MSA-induced nucleation rates become comparable to those of SA, with MSA accounting for around 25 % of CCN0.4 over the Southern Ocean and up to 40 % over the Antarctic. MSA is therefore a key trace gas in the sulfur budget of these regions and a substantial source of CCN. This is particularly relevant for the Southern Ocean, where climate models exhibit a large positive shortwave radiation bias that has been linked to underestimated CCN concentrations.

This work deals with the analysis of different filter sampling methods to obtain INP concentration spectra using the GRAnada Ice Nuclei Spectrometer (GRAINS), a droplet freezing array based on the design of the Colorado State University Ice Spectrometer (CSU-IS) but with droplet volumes of 100 & micro;L. GRAINS was first validated with NX Illite, showing spectra consistent with literature, and also compared with FrESH (Freezing Experiment Setup Helsinki), INSEKT (Ice Nucleation Spectrometer of the Karlsruhe Institute of Technology), and PINE (Portable Ice Nucleation Experiment) for aerosol standards as well as ambient samples, with results generally within confidence intervals or a factor of 5. To assess the filter sampling methods, we simultaneously sampled ambient aerosol on polycarbonate filters (commonly used for INP analysis) and microfiber quartz filters (used for chemical analysis) over three months, with 27 filters of each type. Three analysis approaches were tested: washing the polycarbonate filters (Polycarbonate method), randomly punching the quartz filters (Quartz 96-punch method), and washing a larger punch of the quartz filter (Quartz punch washed method). Our results showed a good performance of the three methods, obtaining similar results for the INP concentrations, with approximately 89 % of the data within a factor of 5. Differences between methods become more evident at lower temperatures, with higher INP concentrations detected with both Quartz methods compared to the Polycarbonate method, which could be related to the particle extraction efficiency of this method. Differences between the three methods varied depending on the sample, with general good agreement for polluted and background conditions and different levels of agreement for dust particles. Still, there is a clear correlation between the three methods, with Spearman's coefficients of around 0.9 (p<0.05). The Quartz punch washed method allows to perform sample dilutions similar to the Polycarbonate method, making it a potential alternative to the Quartz 96-punch method for analyzing INP concentrations using quartz filters.

Anthropogenic ammonia (NH3) emissions have significantly increased in recent decades due to enhanced agricultural activities, contributing to global air pollution. While the effects of NH3 on surface air quality are well documented, its influence on particle dynamics in the upper troposphere-lower stratosphere (UTLS) and related aerosol impacts remain unquantified. NH3 reaches the UTLS through convective transport and can enhance new particle formation (NPF). This modeling study evaluates the global impact of anthropogenic NH3 on UTLS particle formation and quantifies its effects on aerosol loading and cloud condensation nuclei (CCN) abundance. We use the EMAC Earth system model, incorporating multicomponent NPF parameterizations from the CERN CLOUD experiment. Our simulations reveal that convective transport increases NH3-driven NPF in the UTLS by one to three orders of magnitude compared to a baseline scenario without anthropogenic NH3, causing a doubling of aerosol numbers over high-emission regions. These aerosol changes induce a 2.5-fold increase in upper tropospheric CCN concentrations. Anthropogenic NH3 emissions increase the relative contribution of water-soluble inorganic ions to the UTLS aerosol optical depth (AOD) by 20% and increase total column AOD by up to 80%. In simulations without anthropogenic NH3, UTLS aerosol composition is dominated by sulfate and organic species, with a marked reduction in ammonium nitrate and aerosol water content. This results in a decline of aerosol mass concentration by up to 50%. These findings underscore the profound global influence of anthropogenic NH3 emissions on UTLS particle formation, AOD, and CCN production, with important implications for cloud formation and climate.

Gaining a precise understanding of the particle size distribution (PSD) of mineral dust at emission is critical to assess its climate impacts. Despite its importance, comprehensive measurements at dust sources remain scarce and usually neglect part of the super-coarse (particle diameter d between 10 and 62.5 μm) and the entire giant (d > 62.5 μm) particle size ranges. Measurements in those size ranges are particularly challenging due to expected relatively low number concentrations and low sampling efficiencies of instrument inlets. This study aims to better constrain the abundance of super-coarse and giant dust at emission as part of the Jordan Wind erosion And Dust Investigation (J-WADI, https://www.imk-tro.kit.edu/11800.php) field campaign conducted north of Wadi Rum in Jordan in September 2022. The goal of J-WADI is to improve our fundamental understanding of the emission of desert dust, in particular its full-range size distribution and mineralogical composition. To capture the dust PSD across the entire size spectrum, we deployed multiple aerosol spectrometers, including active, passive, and open-path devices, such that in combination, a size range from approximately 0.4 to 200 μm was covered. Here we investigate the variability of the PSD in the super-coarse and giant ranges from observed dust events, address instrumental uncertainties and the impact of different inlets on the resulting PSDs. Our preliminary results reveal a mass concentration peak at around 30 μm, potentially limited toward larger sizes by substantially reduced inlet efficiencies. Giant dust particles were generally detected during active dust emission starting from friction velocities larger than around 0.2 m s-1. Based on our results, we will investigate the mechanisms facilitating super-coarse and giant dust particle emission and transport. Quantifying the conditions for and the amount of super-coarse and giant dust at emission will lay the foundation to incorporate its impacts in weather and climate models.

Isoprene (C5H8) is the non-methane hydrocarbon with the highest emissions to the atmosphere. It is mainly produced by vegetation, especially broad-leaved trees, and efficiently transported to the upper troposphere in deep convective clouds, where it is mixed with lightning NOx. Isoprene oxidation products drive rapid formation and growth of new particles in the tropical upper troposphere. However, isoprene oxidation pathways at low temperatures are not well understood. Here, in experiments at the CERN CLOUD chamber at 223 K and 243 K, we find that isoprene oxygenated organic molecules (IP-OOM) all involve two successive OH ∙ oxidations. However, depending on the ambient concentrations of the termination radicals ( HO 2 ∙ , NO ∙ , and NO 2 ∙ ), vastly-different IP-OOM emerge, comprising compounds with zero, one or two nitrogen atoms. Our findings indicate high IP-OOM production rates for the tropical upper troposphere, mainly resulting in nitrate IP-OOM but with an increasing non-nitrate fraction around midday, in close agreement with aircraft observations.

Aerosol source apportionment improves the understanding of aerosol-cloud interaction processes and benefits the parameterization of ice nucleating particles (INPs), which also contributes to the predictability of climate models for quantifying the impacts of aerosols on the changing climate. This study, which took place in the frame of the Cloud-Aerosol InteractionS in the Helmos background TropOsphere (CALISHTO) campaign, investigates the interactions between mixed-phased clouds and aerosol particles at Helmos Mt. in Peloponnese, Greece (north-eastern Mediterranean). The source apportionment of INPs originating from different aerosol sources is achieved by identifying exclusive characteristics of relevant air masses. A synergy of measurement techniques was employed, including in-situ measurements for INP number concentration and aerosol property characterization, remote sensing techniques for atmospheric condition observations, as well as modelling simulations for calculating aerosol particle footprints.The number concentration of INPs was observed in the mixed-phase cloud regime (>−27°C) in both the planetary boundary layer (PBL) and the free troposphere (FT). The results show that one in a million of aerosol particles can serve as INPs under the background condition in FT. The presence of precipitation/clouds may enrich INPs by suspending biological particles from near ground sources or releasing cloud-processed particles when the observation site is above PBL. The intrusion of remotely transported air masses leads to increased INPs for conditions above PBL, suggesting the observed INPs are of both local and remote origins. In addition, the INP abundance of different sources spans a range of three orders of magnitude and increases following the order of marine aerosols, continental aerosols, and then dust plumes. Biological particles are approximate to INPs observed in continental and marine aerosols, whereas mineral dust particles dominate the observed INPs when dust plumes are present. Furthermore, a case study on a calendar day was performed to investigate the effects of precipitation/clouds on INP abundance in the PBL. In contrast observations above the PBL, the presence of precipitation/clouds may lead to wet removal of aerosol particles and thus, decreased INPs.Statistical analysis suggests that INP concentration in the mixed-phase cloud regime is significantly correlated with fluorescent particles, including biological and non-biological particles such as dust particles associated with fluorescent materials. The ratio of fluorescent to nonfluorescent particles and the ratio of coarse (>1.0 μm) to fine (90% INP observations within an uncertainty range of a factor of 10. The improved predictabilities of the adapted INP parameterizations are demonstrated by comparisons to parameterizations reported in the literature, and the improvement will reduce the uncertainties in cloud physics simulations.

We report the drivers of spatiotemporal variability of ice nucleating particles (INPs) for mixed-phase orographic clouds (~−25 °C) in the Eastern Mediterranean. In the planetary boundary layer, pronounced INP diurnal periodicity is observed, which is mainly driven by biological (and to a lesser extent, dust) particles but not aerosols from biomass burning. The comparison of size-resolved and fluorescence-discriminated aerosol particle properties with INPs reveals the primary role of fluorescent bioaerosol. The presence of Saharan dust increases INPs during nighttime more than daytime, because of lower boundary layer height during nighttime which decreases the contribution of aerosols (including bioaerosols) from the boundary layer. INP diurnal periodicity is absent in the free troposphere, although levels are driven by the availability of bioaerosol and dust particles. Given the effective ice nucleation ability of bioaerosols and subsequent effects from ice multiplication at warm temperatures, the lack of such cycles in models points to important and overlooked drivers of cloud formation and precipitation in mountainous regions.

A novel filter-based sampler was deployed during the Pallas Cloud Experiment (PaCE) 2022 for a one-month period in September and October 2022 in Finnish Lapland around 5 km north of the Sammaltunturi station. This area frequently features low-level clouds during autumn. The sampler was deployed on-board of an uncrewed aerial vehicle (UAV) and on the ground. Two filters were deployed simultaneously on the ground and on the UAV to enable a comparison between the two vertical levels. The dataset contains 9 ice-nucleating particle (INP) concentration spectra that feature a temporal overlap at both altitudes, a handling blank filter to assess possible contamination during handling and additional samples from both setups without the temporal overlap. The dataset is the first of its kind, providing altitude-based INP concentrations in Finnish Lapland, and is available at the Zenodo Open Science data archive (https://doi.org/10.5281/zenodo.13911633, Böhmländer et al., 2024). There is no clear systematic difference between INP concentrations measured at the different altitudes. The INP concentration is variable over the period measured and also does show some differences on the vertical level. The INP concentration at 253 K varies between 0.15 and 3.06 Lstd-1 on the ground, and between 0.48 and 1.69 Lstd-1 at higher altitudes. The connection to synoptic conditions and ambient measurements might provide a better understanding of the origin, lifetime, and distribution of INPs in Finnish Lapland.