Assessing the vertical structure of Arctic aerosols using tethered- balloon-borne measurements

The rapidly-warming Arctic is sensitive to perturbations in the surface energy budget, which can be caused by clouds and aerosols. However, the interactions between clouds and aerosols are poorly quantified in the Arctic, in part due to: (1) limited observations of vertical structure of aerosols relative to clouds and (2) ground-based observations often being 15 inadequate for assessing aerosol impacts on cloud formation in the characteristically stratified Arctic atmosphere. Here, we present a novel evaluation of Arctic aerosol vertical distributions using almost 3 years’ worth of tethered balloon system (TBS) measurements spanning multiple seasons. The TBS was deployed at the U.S. Department of Energy Atmospheric Radiation Measurement Program’s facility at Oliktok Point, Alaska. Aerosols were examined in tandem with atmospheric stability and ground-based remote sensing of cloud macrophysical properties to specifically address the representativeness of near-surface 20 aerosols to those at cloud base. Based on a statistical analysis of the TBS profiles, ground-based aerosol number concentrations were unequal to those at cloud base 86% of the time. Intermittent aerosol layers were observed 63% of the time due to poorly mixed below-cloud environments, mostly in the spring, causing a decoupling of the surface from the cloud layer. A uniform distribution of aerosol below cloud was observed only 14% of the time due to a well-mixed below-cloud environment, mostly during the fall. The equivalent potential temperature profiles of the below-cloud environment reflected the aerosol profile 89% 25 of the time whereby a mixed or stratified below-cloud environment was observed during a uniform or layered aerosol profile, respectively. In general, a combination of aerosol sources, thermodynamic structure, and wet removal processes from clouds and precipitation likely played a key role in establishing observed aerosol vertical structure. Results such as these could be used to improve future parameterizations of aerosols and their impacts on Arctic cloud formation and radiative properties.

The presence of atmospheric aerosols has been established as an important modulator of environmental change in the Arctic Law and Stohl, 2007;Quinn et al., 2008), yet the magnitude of their effects-especially on clouds through nucleation of droplets and ice-is not well understood and thus contributes significantly to uncertainty in climate model simulations (Fridlind and Ackerman, 2018;Klein et al., 2009;Taylor et al., 2019;Zelinka et al., 2020). Aerosol properties 40 have been measured at surface observatories around the Arctic for several decades (e.g., Barrie and Barrie, 1990;Bodhaine, 1983;Freud et al., 2017;Maenhaut et al., 1989;Pacyna et al., 1984;Quinn et al., 2000;Quinn et al., 2009;Quinn et al., 2002;Schmeisser et al., 2018;Sharma et al., 2019;Uttal et al., 2016). From these observatories, we have learned that there is a strong seasonal evolution in the abundance and sources of aerosols-with significantly higher mass concentrations under the winter/spring "Arctic haze" phenomenon, as compared to the relatively pristine summer influenced by local biogenic emissions 45 and intermittent transport of aerosols from lower latitude wildfires (Croft et al., 2016;Garrett et al., 2010;Lange et al., 2018;Quinn et al., 2008;Quinn et al., 2009;Shaw, 1995;Udisti et al., 2016;Willis et al., 2018;Winiger et al., 2019). From the perspective of aerosol-cloud interactions, the concentration, size, and composition of aerosols have been shown to play a significant role in augmenting the radiative effects of Arctic clouds with respect to both solar and infrared radiation (Garrett and Zhao, 2006;Lubin and Vogelmann, 2006, 2007Maahn et al., 2017;Mauritsen et al., 2011). Numerous studies have 50 demonstrated that the Arctic atmosphere is often highly stratified (Graversen et al., 2008;Persson et al., 2002) and that turbulent coupling between the surface and clouds is sporadic (Brooks et al., 2017). This stratification results in layering of aerosols that are not captured by surface observations Fisher et al., 2010;Jacob et al., 2010;Matsui et al., 2011a;Matsui et al., 2011b;McNaughton et al., 2011). Although less common, unstable conditions occasionally exist whereby a well-mixed boundary layer can couple the surface to the cloud-mixed layer or the clouds are low enough for cloud-driven 55 turbulence to couple the cloud mixed-layer and surface layer (Curry et al., 1988;Shupe et al., 2013;Sotiropoulou et al., 2014;Vüllers et al., 2020), with aerosol near the surface representative of those at cloud base due to vertical mixing. The contrasting and dynamic characteristics of the lower Arctic atmosphere, and the fact that most of preceding information on aerosols are gleaned from ground-based observations, motivate the need for profiling measurements to directly explore the vertical distributions of aerosols and their interactions with clouds. 60 Remote sensing can be of value by filling in spatial gaps of vertical aerosol observations. While polar orbiting sensors offer valuable information on aerosol class and optical properties within the troposphere, they can be limited in that: (1) no data are available north of 82 ˚N; (2) signals become attenuated under optically thick clouds, casting a "shadow"; (3) they have issues with surface brightness when masking clouds, especially over the high albedo frozen surfaces (Mei et al., 2013); (4) they may https://doi.org/10.5194/acp-2020-989 Preprint. Discussion started: 7 October 2020 c Author(s) 2020. CC BY 4.0 License. clouds (AMPCs) in the spring (Curry et al., 2000;Fridlind et al., 2007) and fall (McFarquhar et al., 2007). The fourth International Polar Year (IPY; 2008)-a collaborative, international effort with intensive foci on the polar regions-involved several aircraft campaigns to characterize regional and transported aerosols and their impacts on clouds in the spring and summer in the North America Arctic Lathem et al., 2013;McFarquhar et al., 2011;Wang et al., 2011;Zamora et al., 2016), European Arctic (Ancellet et al., 2014), and Greenland (Quennehen et al., 2011;Thomas et al., 2013). 85 More recent spring and summertime aircraft campaigns in the North American (Creamean et al., 2018c;Maahn et al., 2017), European (Eirund et al., 2019;Liu et al., 2015;Wendisch et al., 2019;Young et al., 2017;Young et al., 2016a;Young et al., 2016b), and Canadian Arctic sectors Burkart et al., 2017;Leaitch et al., 2016;Schulz et al., 2019;Willis et al., 2019) involved a more comprehensive set of observations to assess spatiotemporal distributions of aerosols, their sources, and their impacts on cloud microphysics. While such Arctic airborne missions have yielded crucial information on aerosol 90 sources and their impacts on clouds over the course of the last three decades, they are logistically and financially demanding, focus on relatively short intensive periods, and can be affected by fast-flying flow-induced issues (Spanu et al., 2020).
Additionally, traditional manned aircraft are often not able to fly within hundreds of meters of the ground, therefore preventing them from providing critical information on near-surface aerosol properties and the surface-cloud interface.
To bridge the gap between aerosols at the surface and at altitudes attainable by manned aircraft, smaller platforms such at 95 unmanned aerial and tethered balloon systems (UASs and TBSs, respectively) can be employed, and on a more routine basis https://doi.org/10.5194/acp-2020-989 Preprint. Discussion started: 7 October 2020 c Author(s) 2020. CC BY 4.0 License. than traditional manned aircraft. Aerosol size distributions, composition, biology, and/or cloud-relevant properties have been measured via UAS and TBS in several locations globally (Ardon-Dryer et al., 2011;Bryan et al., 2014;Creamean et al., 2018d;de Boer et al., 2016;Greenberg et al., 2009;Maletto et al., 2003;Marinou et al., 2019;Porter et al., 2020;Renard et al., 2016;Schrod et al., 2017;Siebert et al., 2004;Techy et al., 2010;Telg et al., 2017;Wehner et al., 2007), however, such observations 100 are relatively sparse in the Arctic compared to lower latitudes. Balloon-borne observations of aerosols date back to the 1980s and 90s Khattatov et al., 1994;Kondo et al., 1990;Suortti et al., 2001), yet these were focused on stratospheric aerosol. Recent technological and instrumentational advancements have afforded information on vertical distribution, size, and type of aerosol present in the Arctic boundary layer (Atkinson et al., 2013;Dagsson-Waldhauserova et al., 2019;Ferrero et al., 2019). Both TBSs and UASs have their advantages and disadvantages in terms of flight ceiling, 105 profiling, retrievability, cost, operational logistics, and payload restrictions, but some major advantages of TBSs are their flexibility to profile and hover at desired altitudes and flight duration can be several hours depending on power availability for instrumentation.
Uncertainties in model representations of aerosol-cloud interactions, especially in the Arctic, are exacerbated when models attempt to simulate cloud-radiative interactions and the surface energy budget (Sedlar et al., 2020). This is in part due to the 110 unique behaviour of AMPCs, which can persist for days within 1 km of the ground (Gierens et al., 2020;Morrison et al., 2012;Shupe, 2011;Shupe et al., 2011) and have been shown to increase surface temperature by almost 20 ˚C (Dimitrelos et al., 2020). Additionally, Arctic clouds are particularly sensitive to modulations from aerosols (de Boer et al., 2013;Eirund et al., 2019;Morrison et al., 2008;Norgren et al., 2018;Solomon et al., 2018). Therefore, both near-surface profiling and groundbased measurements equate to an ideal combination for investigating relationships between aerosols, clouds, and atmospheric 115 state to address these issues and improve representation of aerosol impacts on Arctic cloud microphysics and radiative properties.
In this paper, we provide some unique perspectives on the distribution of aerosol properties in the lower Arctic atmosphere collected using TBS at Oliktok Point, Alaska between spring 2016 and summer 2019 de Boer et al., 2015;Dexheimer et al., 2019). These flights generally occurred between the months of May and October under various field 120 campaigns, including the Inaugural Campaigns for ARM Research using Unmanned Systems (ICARUS; , Aerosol Vertical Profiling at Oliktok Point (AVPOP; Creamean et al., 2018a) and Profiling at Oliktok Point to Enhance Year of Polar Prediction (YOPP) Experiments (POPEYE; de Boer et al., 2019a;de Boer et al., 2019b). Using aerosol and atmospheric state measurements from these systems, we attempt to answer the following question: Are ground based aerosol measurements representative of those at cloud level? We also address under which atmospheric conditions such links exist 125 (i.e., cloud coupled or decoupled from the surface). Section 2 provides an overview of the platforms and sensors deployed as part of these campaigns. Section 3 includes information on aerosol vertical distribution, comparison with surface-based https://doi.org/10.5194/acp-2020-989 Preprint. Discussion started: 7 October 2020 c Author(s) 2020. CC BY 4.0 License. observations, and relationships between aerosol stratification and thermodynamic stratification. Finally, section 4 offers discussion on the impact of these measurements, as well as a summary of our findings. Oliktok Point includes a restricted airspace area (R-2204) to enable TBS flights at AMF3 (for details, see de Boer et al., 2015;Figure 1b). The dates, times, and flight hours for all TBS flights used from ICARUS, AVPOP, and 135 POPEYE are provided in Table 1. Flights occurred to altitudes up to 1.5 km a.m.s.l. and with durations from 1 to 9 h in various atmospheric conditions including clear sky, broken to overcast clouds, rain, sleet, and snow (Dexheimer et al., 2019). Typical profiles included: (1) a gradual ascent, hovering at a desired altitude, then a gradual descent, (2) if already airborne, a gradual descent, hovering at a desired altitude, then gradual ascent, (3) quick ascent and descent, (4) quick ascent followed by hovering at a desired altitude, then quick descent, and (5) a stepwise path up or down. A flight consisted of one or a combination of 140 these profiles, especially when a cloud was present and variable in terms of location throughout the flight (section 3.1).

Tethered balloon system (TBS) platform
The TBS platform consisted of a helium-filled balloon, tether, and winch (see Dexheimer, 2018 for complete details). Two different balloons were used, including a 34 m 3 helikite (Allsopp Helikites Ltd.) and a 79 m 3 aerostat (SkyDoc™ and Drone 145 Aviation Corp.). The helikite ( Figure 1c) uses lighter-than-air principles to obtain its initial lift and a kite-like structure to achieve stability and dynamic lift, while the larger aerostat uses a skirt instead of a kite to achieve stability in flight Dexheimer, 2018;Dexheimer et al., 2019). The helikite was typically used for flights with desired altitudes up to 700 m above the ground, had a maximum payload of < 10 kg, and could be operated in wind speeds < 11 m s -1 . The aerostat was used when desired altitudes were > 600 m above ground, a heavier payload was needed (10 -25 kg), but when surface 150 wind speeds were < 8 m s -1 (Dexheimer, 2018). Several winches were employed, including: (1) a commercial, off-the-shelf electric winch (SkyDoc™) that has been modified at Sandia National Laboratories and integrated into a dedicated balloon trailer for both the aerostat and helikite (Figure 1c), (2) a hydraulic winch and pump that have been integrated into a dedicated balloon trailer (Carolina Unmanned Vehicles, Inc.) for the helikite, or (3) a small electric winch (My-te) attached to a receiver on a truck for the helikite. The most used winch deployed > 2 km of Plasma® 12-strand synthetic rope, which has a minimum 155 breaking strength of 2494 kg (Cortland Company, Inc.). https://doi.org/10.5194/acp-2020-989 Preprint. Discussion started: 7 October 2020 c Author(s) 2020. CC BY 4.0 License.

Balloon-borne instrumentation
The commercial sensors integrated into the ARM TBS platform and presented here included a Portable Optical Particle Spectrometer (POPS; Gao et al., 2016;Telg et al., 2017) (Handix Scientific LLC) for particle size distributions and a standard iMet-1-RSB radiosonde (International Met Systems, Inc.) for pressure, temperature, relative humidity, and GPS altitude and 160 position. When GPS altitude data were not recorded or suspect, altitude was derived from the iMet pressure-based altitude retrievals. Total payload weight for the flight-ready POPS enclosure and radiosonde was approximately 6.3 kg. A condensation particle counter (CPC 3007; TSI, Inc.) was also commonly deployed with the POPS and iMet sensors for total particle concentrations (10 -1000 nm), but data are not presented here as the objective is to focus on the size range relevant to aerosolcloud interactions. Up to two POPSs were suspended along the tether at different altitudes. One POPS was operated just below 165 the balloon in order to reach the maximum possible altitude (Figure 1d). If a second POPS was deployed, it was generally located up to 100 meters lower than the top POPS to sample near the cloud base. The POPS measures particle size distributions from 140 nm to 3 μm with a 405-nm wavelength laser, has a maximum particle concentration of 1250 cm -3 (±10% accuracy), and a sample flow rate of 0.18 L min -1 . It can function down to -40 ˚C with an additional heat sources for the laser and within the enclosure, thus operation is possible in the cold Arctic temperatures at Oliktok Point and in AMPCs. Optical particle 170 counters (OPCs) similar to the POPS have been operated successfully via balloon in several previous studies all over the world (Creamean et al., 2018d;Greenberg et al., 2009;Hofmann, 1993;Hofmann et al., 1989;Iwasaka et al., 2003;Kim et al., 2003;Maletto et al., 2003;Renard et al., 2016;Siebert et al., 2004;Tobo et al., 2007;Wehner et al., 2007).

Ground-based measurements
The AMF3-which was installed at Oliktok Point in 2013 and will be relocated to the southeast U.S. in 2021 175 (https://www.arm.gov/capabilities/observatories/amf)-includes a comprehensive collection of instrumentation for gases, aerosols, clouds, precipitation, atmospheric state, and thermodynamic structure. For the current work, we exploited continuous ground-based measurements of: (1) total aerosol concentrations in the ultrafine (3 nm -10 μm) and fine (10 nm -10 μm) modes using an ultrafine and fine condensation particle counter (CPCu and CPCf, respectively; TSI, Inc.); (2)  GHz) microwave radiometer system (MWR; Radiometrics, Inc.; Cadeddu, 2012); (6) precipitation data from a NASA groundbased precipitation imaging package (PIP; https://wallops-prf.gsfc.nasa.gov/Disdrometer/PIP/index.html); and (6) basic surface meteorology including wind speed and direction from the aerosol observing system (AOSMET; Kyrouac, 2016). The 185 UHSAS measures aerosol size distributions from 60 to 1000 nm, which has a 140 to 1000 nm overlap with the POPS. When directly comparing data between the UHSAS and POPS, only number concentrations within this overlap region were used.
The AOS inlet is positioned at a height of approximately 10 m above the ground. We employed a combination of the ceilometer https://doi.org/10.5194/acp-2020-989 Preprint. Discussion started: 7 October 2020 c Author(s) 2020. CC BY 4.0 License. and KAZR to establish cloud presence, base, and depth in order to classify when the POPS was measuring aerosol concentrations below, in, and above cloud. 190

Data mining and availability
All data from the POPS, iMet, CPCs, UHSAS, ceilometer, KAZR, MWR, PIP, and AOSMET were compiled into single data files per flight and are available on the DOE ARM Data Archive as an intensive operating period (IOP) product (https://adc.arm.gov/discovery/#/results/primary_meas_type_code::aerosconc/iopShortName::amf2018avpop/instrument_cat egory_code::atmprof). To simplify data analysis, we identified parameters that are most relevant to addressing the question of 195 whether ground based aerosol measurements are representative of those at cloud level, and merged them into a single product, where we aligned and, if needed, resampled timestamps indices. This product includes retrievals from in situ measurements on the tether (instrument payload altitude, relative humidity, temperature, potential temperature, equivalent potential temperature, particle number concentration, and particle mean diameter), in situ ground observations (precipitation rate and particle number concentration), ground-based remote sensing (cloud base and cloud top altitudes and liquid water path), and 200 hybrid retrievals (particle number concentrations in the overlapping size range from the UHSAS and POPS). The data presented here have been re-processed from the POPS raw data retrieved from the instrument after each flight session. This step was necessary to improve the signal-to-noise ratio, which is particularly important in low-particle-number conditions encountered frequently in the Arctic, and to match detection limits of POPS and the UHSAS instruments. Data from one of the POPS (SN18) during May 2017 flights were omitted due to an instrument pump failure. These discrepancies were remedied 205 after the May flights and observations from this sensor were re-integrated into the analysis. Lower atmospheric stability was determined using the thermodynamic measurements provided by the iMet sensors. Specifically, the equivalent potential temperature ( E ) was calculated using the Python MetPy package (May et al., 2020). With E profiles available from the TBS, the variance in E between the surface and cloud base was analysed to evaluate mixing in the lower atmosphere. Since wellmixed atmospheres should have a constant E profile, increased variance would indicate some form of stratification within the 210 column. Based on a statistical evaluation of this variance, a threshold of 0.25 was selected as a cut-off for distinguishing between well-mixed and stratified profiles. Unless otherwise indicated, data herein are presented in a.m.s.l. and universal coordinated time (UTC).
Here, we describe definitions for key terms used throughout this paper. A "flight" corresponds to the entire duration of a TBS deployment, while a "profile" represents a segment of ascent or descent during the flights-there can be multiple profiles per 215 flight (see example of how a flight is dissected into profiles in Figure 2). Specifically, a profile is defined by the measurements in between the minimum and maximum altitude attained during each ascent/descent. We also compare aerosol concentrations at various vertical levels relative to the ground and to cloud height. "Ground" aerosol concentrations are defined as the POPS number concentrations averaged between 20 and 40 m of each profile-data below 20 m were removed due to aerosol contamination from the winch generator (i.e. spikes in POPS number concentration were typically observed below this 220 altitude). POPS data quality at the "ground" was cross-checked with the UHSAS number concentrations in the overlapping size region (see section 3.1). "Cloud-base" aerosol concentrations are defined as POPS number concentrations averaged between the average cloud base height for each profile and 40 m below that altitude. "Below-cloud", "in-cloud", and "abovecloud" aerosol is defined as the average number concentration of aerosol from the POPS from 20 m to the average cloud base height, the average cloud base height to average cloud top height, and average cloud top height to the maximum height of each 225 profile, respectively.
In total, 282 profiles were obtained. The TBS flew and collected POPS data at the ground and at cloud base for 63 of those 282 profiles. Remaining profiles either did not reach cloud base or were profiles in or above cloud during the middle of the flight and did not descend to the ground. The 63 profiles were categorized into cases, including: (1) cases where the ground POPS concentrations = cloud-base POPS concentrations, (2) cases featuring decreasing or increasing POPS concentrations 230 with height to cloud base height (called "gradients"), and (3) cases with intermittent layers of aerosol between the ground and cloud base height. Cases where "ground = cloud-base" were defined programmatically as when "cloud-base" POPS concentrations were within 10% of the "ground" POPS concentrations. This metric was used to determine whether groundbased aerosol is representative of aerosol at cloud base. For cases where aerosol number concentrations at the ground did not equal those at cloud base, gradients and intermittent layers were identified visually. Ground = cloud-base cases were also 235 visually checked to assure they belonged to the correct case category and that intermittent layers were not present. Some visual intervention was necessary for placement of profiles in their correct case categories. E profiles were compared in tandem to the POPS profiles to identify if the boundary layer was thermodynamically well-mixed or stratified. A mixed or stratified boundary layer corresponded to E within or outside of this variance threshold, respectively. Profiles with missing or insufficient POPS or E data were removed from statistical analyses (section 3.3). 240

General atmospheric and ground-based aerosol conditions during TBS flights in Arctic Alaska
TBS flights spanning the campaigns in Table 1  good agreement between the two separate instruments during TBS flights. The POPS appeared to have slightly higher concentrations when greater than approximately 100 to 150 cm -3 (Figure 4b), however, both methods were still in good agreement even when including all the data measured by POPS between ground and cloud base (Figure 4c). Possible sources of disagreement could be due to: (1) the inlets (i.e., the UHSAS is on a stack inlet in which the air is humidity-controlled to 40% versus the POPS, which has a small inlet directly exposed to ambient conditions), (2) concentrations were not corrected 260 for aerosol loss in either instrument, and/or (3) proximity to very localized sources (e.g., the AMF3 generators or operations vehicle exhaust). Figure 5 demonstrates the transitions in number concentration and mean particle diameter during all TBS deployments. In general, high (low) concentrations corresponded to smaller (larger) sizes of particles (e.g., profiles 260 -280). The highest 265 concentrations were observed when the TBS flew well below cloud base in the summer (e.g., profiles 81 -100, 180 -200, and 230 -240), which is likely due to a combination of more prominent surface sources and separation of those sources from cloud base where scavenging of the aerosol could occur (Browse et al., 2012;Huang et al., 2010;Limbeck and Puxbaum, 2000;Yum and Hudson, 2001). In general, the highest number concentrations of the smallest particles observed by the POPS were likely primary combustion particles from Prudhoe Bay oilfield emissions, which have been previously observed as a 270 prominent source on the North Slope (Creamean et al., 2018c;Gunsch et al., 2017;Kirpes et al., 2020), and possibly to a lesser extent, growth of aerosols from new particle formation events (Kolesar et al., 2017). The TBS data agreed with the groundbased UHSAS data whereby relatively high concentrations of particles within the size range (i.e., 60 nm -1 μm) that would be expected from oilfield plumes (Gunsch et al., 2020) were observed, specifically when strong winds originated from the southeast (Figure 6) from where a high density of oil wells exists (Creamean et al., 2018c). The North Slope is also subject to 275 local marine biological emissions that increase particle numbers starting in May and peak during the summer (specifically July) when sunlight hours and open water sources are at their maxima (Creamean et al., 2018b;Polissar et al., 2001;Quinn et al., 2009;Quinn et al., 2002). This biological source could have contributed to the particles measured at Oliktok Point, but given the dominant wind direction, this was likely a minor influence during the summer months of the current study. However, the low concentrations of aerosol associated with easterly winds was likely a result of an influence from marine biological 280 aerosol as demonstrated by Creamean et al. (2018b) in May 2017. Some of the largest particles were observed in low concentrations during the summer and relatively high concentrations in the fall (e.g., profiles 45 -60, 120 -140, 260 -270; Figure 5), presumably due to influences from supermicron sea salt aerosol when open water is present off the coast (May et al., 2016;Quinn et al., 2002). September was particularly influenced by marine sources given the low particle counts and easterly winds from over open ocean directly off the coast of Oliktok Point (Figure 1b), while October was likely influenced 285 by a combination of supermicron sea salt and oilfield activities as the winds transitioned to predominantly originating from the Prudhoe Bay oil wells ( Figure 6). Emissions from a local lead were visible during early July 2018 (e.g., profiles 81 -100; The seasonal dependencies of aerosol number concentrations measured by TBS are summarized in Figure 7, with spring, summer, and fall corresponding to 9 (38), 27 (176), and 10 (68) flights (profiles), respectively. Specifically, we compare between aerosol concentrations at the ground, below-cloud, at cloud base, in-cloud, and above the cloud. In addition, we show 295 average values for cloud base height and depth and the percentage of profiles during precipitation. Average number concentrations were highest in the summer at almost all vertical levels, particularly for below-cloud aerosol, which could be caused by: (1) a combination of sources including local oilfield emissions, local/regional biogenic aerosol production, and episodic regionally-transported aerosol from Siberian and Alaskan wildfires (Creamean et al., 2018c;Maahn et al., 2017;Stohl, 2006), (2) inefficient below-cloud scavenging, and (3) insufficient wet removal via precipitation. The highest and deepest 300 clouds were observed in the summer, in agreement with previous work on the North Slope . Additionally, precipitation was much less prominent in the summer than spring or fall (11% of profiles had precipitation versus 24% and 26% in spring and fall, respectively). In concert, these observations indicate there was likely less efficient scavenging of aerosol by clouds and precipitation in the summer as compared to other seasons. The spring did not have as high of concentrations of aerosol at all levels below cloud top as the summer, which could be a result of more efficient wet scavenging from clouds (i.e., 305 they were lowest during the spring profiles) and precipitation. Another explanation could be that our "spring" flights occurred in May during the tail end of the Arctic haze, weakening of the polar vortex, and the very start of the transition into peak summertime biological productivity from marine and terrestrial sources (Creamean et al., 2018b). The only exception is the above-cloud aerosol, which was highest during the spring compared to summer and fall-characteristic of long-range transported Arctic haze that typically resides in elevated layers in the free troposphere  and to a lesser 310 degree, transported closer to the surface (Quinn et al., 2007). Capturing this below-cloud region further demonstrates the utility for TBS measurements in the lowest levels of the Arctic atmosphere. The lowest aerosol concentrations were measured during fall, probably due to: (1) limited influences from long-range transport, (2) less impact from regional fires, (3) reduction of sunlight yielding less biological productivity, and (4) wet scavenging by precipitation (26% of profiles occurred during precipitation). 315

Relationships between aerosols, thermodynamics, and cloud structure
While variability in emissions, transport, and wet removal mechanisms control absolute aerosol number concentrations, the stability of the atmosphere governs the vertical distribution of the aerosol population resulting from the major sources and sinks. Here, we mainly focus on the below-cloud environment to assess relationships between aerosol concentrations at the surface, in the boundary layer, and at cloud base. Profiles were classified into four separate cases based on the structure of 320 POPS number concentration with height and atmospheric mixing (i.e., E ) below-cloud: (1) profiles with a well-mixed belowcloud environment (i.e., approximately constant E ) and consistent aerosol concentrations with height up to cloud base, (2) profiles with a stratified below-cloud environment and increasing or decreasing gradient in below-cloud aerosol, (3) profiles with a stratified below-cloud environment and intermittent aerosol layers between the ground and cloud base, and (4) outliers whereby no relationship between below-cloud thermodynamic structure and number concentrations existed. Only profiles with 325 E and POPS data are classified into the different cases (63 profiles total). These data are illustrated in Figure 8 as ratios of E and POPS number concentrations at all altitudes within the below-cloud region as compared to their respective values at the ground. The cases where the ground aerosol was equivalent to the cloud-base aerosol concentrations under a well-mixed belowcloud environment (case 1) all fall at the 1:1 nexus of both parameters (i.e., E and POPS number concentrations were both consistent in their below-cloud profiles from their ground values). There were very few profiles that fit the constraints of case 330 1 (8 profiles) when a cloud-driven mixed layer existed in the below-cloud environment as shown by the very consistent E with height. For cases whereby below-cloud stratification existed (46 profiles total), E caused a gradient (increasing or decreasing aerosol number concentrations with height) or intermittent layers (1 or more layers or "spikes" with elevated number concentrations; aerosol layers existed at levels approximately equivalent to the locations of temperature inversions).
Data from these cases fall along the "cross" evident in Figure 8. Interestingly, the outlier profiles (7 total) appeared to occur 335 during well-mixed conditions (i.e., consistent E with height) but had aerosol profiles with decreasing gradients (6 profiles with E ratio ~ 1 and POPS ratio < 1) or decreasing gradients with an intermittent layer (1 profiles with E ratio ~ 1 and POPS ratio < 1 but with "spikes"). The outliers spanned all seasons (1, 2, and 4 profiles for spring, summer, and fall, respectively), but typically occurred during conditions that had: (1) highly variable cloud base (i.e., large standard deviations with the minimum reaching down to near the surface, (2) a very low average cloud base (< 200 m), (3) high relative humidity at the 340 surface, and/or (4) precipitation. One possible explanation is that as aerosols approached the highly variable or very low cloud bases due to activation into cloud particles (i.e. scavenging), leaving a relatively thin layer of depletion (Hoffmann et al., 2015;Solomon et al., 2015). The surface winds were north-easterly or westerly during most profiles (6), with 1 profile occurring during south-easterly winds. It is possible that some combination of rapid changes in thermodynamic structure of the boundary layer from clouds, humidity, and precipitation originating from storm systems from predominantly over the Arctic Ocean 345 causes the discrepancy between aerosol and thermodynamic profiles.
The flight conditions and seasonality during the cases and outlier profiles are summarized in Figure 9. The TBS flew over a range of vertical coverage, including below (89% of all 282 profiles with POPS data), in (48%), and above cloud (25%). The https://doi.org/10.5194/acp-2020-989 Preprint. Discussion started: 7 October 2020 c Author(s) 2020. CC BY 4.0 License.
conditions during the TBS flights were mostly cloudy (91%) and precipitation occurred during 17% of the 282 profiles ( Figure   9a). Cases where the concentrations of the aerosols at the ground were equivalent to those at cloud base (14% of the 63 profiles 350 containing POPS measurements at the ground and cloud base), and cases with gradients (16%), and intermittent layers (63%) are shown in Figure 9b. Most of the aerosol was found below as compared to above cloud (38% of the profile subset had higher aerosol concentrations above cloud as opposed to 62% having higher concentrations below). The below-cloud environment (i.e., coupled/well-mixed versus decoupled/stratified) reflected the aerosol vertical structure (i.e., concentrations at the ground were similar or dissimilar to those just below cloud base) for most of the profiles (89%). 355 The conditions and cases are further broken down into seasons (Figure 9c). The spring only had no profiles where the ground aerosol was equivalent to the cloud base in terms of number concentrations and was chiefly impacted by gradients (40% of the spring profiles with POPS observations at the ground and cloud base) and intermittent layers of aerosols (60%), which is expected from long-range transported haze aerosol. It is possible the relatively low and variable clouds (i.e., low mean cloud base heights with large standard deviations) in the spring (Figure 7) influenced the variable aerosol distributions, particularly 360 the decreasing aerosol concentrations when approaching cloud base due to cloud scavenging of aerosol. The summer's high aerosol number concentrations were likely a result of less efficient wet scavenging-relatively little precipitation (Figure 9c) in combination with higher clouds (Figure 7) during the summer flights. Additionally, aerosols were predominantly found in layers in the below-cloud environment, possibly due to a mixture of sources from regionally-transported wildfire, local oilfield, and marine biological emissions and inefficient below-cloud mixing (Figure 9c). Most cases where the ground-based aerosol 365 concentrations were equivalent to those near cloud base existed in the fall when the below-cloud environment was mixed far more often than spring and summer. For the 63 profiles, precipitation was highest (lowest) in fall (summer), when the lowest (highest) aerosol concentrations were observed, indicating wet scavenging played a role in controlling the aerosol population below-cloud in combination with a reduction of aerosol sources in the fall.

Summary 370
We present a summary of findings from routine TBS measurements of aerosol number concentrations in tandem with groundbased measurements of aerosols, atmospheric state, and cloud macrophysical properties in northern Alaska from two consecutive years and during multiple seasons. To directly address the question posed regarding the representativeness of ground-based measurements of aerosols to those aloft, we compiled data from all TBS flights and disseminated into profiles, evaluating how the profiles were structured during each season and relative to cloud base. This representativeness was observed 375 only 14% of the time, mostly during the fall months and infrequently during the late spring. The other 86% of the time, aerosol structure existed as increasing or decreasing gradients up to cloud base, or in intermittent layers in the below-cloud environment. The vertical distribution of the aerosols can be explained by a combination of known seasonal sources on the North Slope of Alaska and observed thermodynamic structure and wet scavenging from clouds and precipitation. These findings afford novel information on aerosol vertical structure in the Arctic, especially where traditional platforms such as 380 remote sensing and manned aircraft fail to provide ample coverage. This study represents the first to directly evaluate intraseasonal aerosol vertical properties under the context of the below-cloud Arctic environment.
Overall, the TBS is a useful tool that can fill in key observational gaps of aerosols by affording detailed information on aerosol profiles. In tandem with an understanding of common aerosol sources and auxiliary measurements on cloud and precipitation properties and atmospheric thermodynamic and kinematic structure, the vertical distribution of aerosol number can be 385 explained. This detailed information is crucial for appropriately simulating aerosol-cloud interaction processes, which are especially challenging to model in the Arctic. DOE ARM aims to achieve a richer observational dataset of TBS aerosol measurements through plans for additional flights at a variety of locations and environments for the ARM program, including at ARM fixed sites and for major field campaigns, with deployments including filter sampling for offline aerosol chemical and microphysical property analyses. We recommend that future efforts by the more general Arctic aerosol community should        https://doi.org/10.5194/acp-2020-989 Preprint. Discussion started: 7 October 2020 c Author(s) 2020. CC BY 4.0 License. Figure 9: Statistics from all profiles with POPS data (282 total) during the ARM TBS campaigns, including a) when the POPS flew 475 below, in, and above cloud and conditions during the flights (clear or cloudy), and precipitation. Out of the profiles that POPS was operational at cloud base and at the ground (63 total), b) shows cases where aerosol concentrations were equivalent and not equal at ground and cloud base. When not equal, cases are categorized into an increasing or decreasing gradient with height when intermittent layers were present, and cases where below-cloud mixing can explain the stratification of the aerosol. Also shown are cases where the POPS measured above and below cloud within the same profiles (42 total) and which cases had higher aerosol

concentrations below and above cloud. c) shows various conditions by season from b). The number of cases is provided for a) and b). The number of profiles per season is provided in c).
https://doi.org/10.5194/acp-2020-989 Preprint. Discussion started: 7 October 2020 c Author(s) 2020. CC BY 4.0 License.