We investigated the influence of DCCs on the distribution and properties of INPs in the UTLS by analyzing the results of the measurements carried out during Flight 15 (F15). Figure  shows the HALO flight track of F15, on 13 July 2021. After takeoff in Oberpfaffenhofen, HALO moved NE and then southward over Austria into Italy. Following a turn towards SW, HALO descended on its way to Brescia airport, where a dive was performed. Shortly after, the plane moved N and then E, performing a loop within and above the anvil cirrus cloud shown as the bright pink area in Fig. . Connected to this cloud, which developed close to Brescia, between 15:45 and 16:45 UTC, 95.6 mm of precipitation were measured at a meteorological ground station Astico a Pedescala (Fig. S12), which was located beneath the core of that DCC. Similar precipitation amounts were measured at another nearby weather station (Castana CMT). A significant increase in aerosol particle number concentration was observed in the cloud-free air close to cloud top and identified as cloud-free convective outflow (color code between 15:45 and 16:15 UTC in Fig. ; see Sect.  for more details). In the following, HALO again moved N into Germany where more DCCs were explored in a descending pattern before landing.

Figure a shows the flight track of F15 in terms of pressure as a cross section through the atmosphere, overlaid on ERA5 reanalysis data (relative humidity in green, cloud cover in blue/yellow, isotherms as black lines). Note that the interpolation of the hourly ERA5 data onto the flight track is prone to errors, especially for temporally and spatially confined features such as DCCs. These errors likely produce artifacts like the seemingly vertically broken up cloud structure which do not capture the continuous vertical extent of the developed DCCs during F15. Above the panel, specific flight sections are categorized according to the probed air masses. The color code here and on the flight track in panel a refers to the three HERA filters (for convenience named red, blue, orange) that were sampled and that represent (1) the lower troposphere including the atmospheric boundary layer (Fig. a, red lines), (2) in-cloud sections, i.e., convective updrafts and anvil cirrus (Fig.  a, dark blue lines), and (3) the DCC-influenced UTLS (Fig. a, orange lines). In other words, we consider the red filter as representative of aerosol particles and INPs inside the convective inflow, the blue filter as representative of CPRs and INPs inside a DCC, and the orange filter as representative of aerosol particles and INPs in the DCC-outflow-influenced UTLS. The corresponding filter sample location on the flight track is shown in Fig. S11.

In the following, we will outline the atmospheric sampling conditions and aerosol particle/CPR properties for each filter on the basis of Fig.  before moving on to the discussion of the respective INP spectra in Sect. . Hereafter, we will refer to the red filter as “convective inflow”, the blue filter as “in-cloud sections”, and the orange filter as “convective outflow”.

The convective inflow filter was sampled at the HASI inlet after takeoff and before landing in Oberpfaffenhofen, as well as during a dive over Brescia airport (red lines in Fig. a, i.e., in close vicinity of the DCC shown in Fig. ). Throughout this dive, 52 % of aerosol particles larger than 500 nm (cumulative sampled particle fraction CSPF, red line in Fig. c) were collected on the filter. Overall, 90 % of aerosol particles larger than 500 nm were sampled below 4 km, making the collected aerosol particles on this filter well representative for the DCC's inflow as well as particles potentially entrained into the DCC in the free troposphere.

During the filter sampling, the ambient temperatures ranged from -30 °C at the highest altitude (8.2 km, 360 hPa; see Fig. a) to 23 °C at the surface. Moist, warm, and aerosol-particle-laden air was prevalent in the lower troposphere between 630 and 950 hPa. Colder air with T < 25 °C was present between 950 hPa and the surface, likely caused by low-level outflow of nearby DCCs (see Skew-T diagram, Fig. S13 in the Supplement).

With the exception of a short in-cloud sampling section directly after takeoff at 13:08 UTC, the sample was exclusively collected outside cloud. Operating the HASI inside clouds might lead to artifacts due to hydrometeors shattering at the inlet . As a result, n500 (black dots in Fig. c) and the CSPF (red line in Fig. c) might be overestimated to an unknown degree during this short period. Potential effects on the INP results are discussed in Sect. .

Around 6600 mass spectra were recorded with the ALABAMA during the sampling of the convective inflow filter. The aerosol particles consisted mainly of ammonium nitrate (16 %), ammonium sulfate (24 %), potassium and sulfate (19 %) and BBA (19 %, Figs. d, S6). Sea salt aerosol particles and elemental carbon particles were present but in smaller fractions (4 % and 1 % respectively).

The in-cloud filter was sampled at the HALO-CVI in various parts and stages of DCCs (see flight sections marked in blue in Fig. a). The first sampling section collected 8 % of the filter's large CPRs (d > 500 nm, see CSPF in Fig. c) and was sampled in DCC anvil cirrus at temperatures predominantly between -40 and -50 °C (see black isotherms in Fig. a). The CSPF in the second section was 70 % , sampling strong DCC updrafts over Italy at 260 hPa and -45 °C ambient temperatures (Fig. c). Finally, in the last section, the CSPF was 22 %, sampling in an aged DCC over Germany in both anvil cirrus and the mixed-phase regime in a descending pattern. Here, the ambient temperature ranged from -50 to -10 °C. Thus, this sample represents CPRs in DCCs, predominantly collected in updraft regions at ambient temperatures < -40 °C.

Around 4900 mass spectra were recorded during sampling of the in-cloud filter. The chemical composition analysis of the collected CPRs shows that 26 % of the particles consisted of mineral dust, 7 % of sea spray and 35 % of organic material (Figs. d, S6). Mineral dust fractions in anvil cirrus are typically 20 %–30 %, while values are enhanced up to 54 % within convective core updrafts (see Sect. S4 for more details on mineral dust composition).

Aerosol particles were collected in the UTLS between 150 and 350 hPa ambient pressure on the convective outflow filter. Ambient temperatures spanned -30 to -54 °C, with the majority of sampling below -40 °C (see two orange flight sections and black isotherms, Fig. a). The filter was sampled almost exclusively outside cloud, except for a short in-cloud sampling section at 14:54 UTC (see IWC in Fig. b). Since the CSPF during this in-cloud section was only 1 %, we consider this filter representative for the aerosol particles in the cloud-free air in the DCC outflow.

During the first sampling period from 14:50 to 15:12 UTC, the CSPF was 25 % (orange line in Fig. c). Trace gas concentrations remained on typical upper tropospheric levels with carbon monoxide concentrations < 100 ppbv, methane concentrations CH4 < 1.95 ppmv and ozone concentrations O3 < 150 ppbv (Figs. S10 and b), indicating UTLS background conditions and no recent influence of DCCs. Concentrations of aerosol particles larger than 500 nm (n500) were relatively low (< 1 standard cm⁻³) compared to the lower troposphere with n500 of ∼2 standard cm⁻³. Single-particle mass spectrometry measurements reveal the presence of BBA particles in the upper troposphere at a particle number fraction of around 30 % (Fig. d).

During the second sampling period from 15:46 to 16:49 UTC, aerosol particles were collected above DCCs in the stratosphere with CO < 50 ppbv, CH4 < 1.9 ppmv and O3 > 300 ppbv during most of the time (Figs. S10 and b). For the majority of this sampling period, the stratospheric aerosol was dominated by particles containing meteoric materials dissolved in sulfuric acid (; ; see Fig. d).

Remarkably, between 15:55 and 16:10 UTC, the water vapor mixing ratio increased from background values of 2.5 to 4 ppmv (Fig. S10a), the CO concentration slightly increased from < 50 ppbv to above 60 ppbv (Fig. S10b), and n500 increased from 0.4 to up to 10 standard cm⁻³ (Fig. c). Variations in trace gas concentrations are connected to variations in aerosol particle number concentrations in such a way that periods of high number concentrations occur contemporaneously with the trace gas composition shifted towards more tropospheric values.

Within this short 15 min period of high aerosol particle concentrations, the CSPF was 45 % (Fig. c). The fractions of mineral dust and BBA type particles are drastically increased to 20 % and 30 %, respectively (Figs. d, S5). A potential pathway for the aerosol particles into the stratosphere is revealed by Cirrus Properties from SEVIRI (CiPS) cloud top height satellite products, showing that the aerosol particles were sampled downwind of a DCC overshooting top (Fig. ). This overshooting top reached its maximum altitude (12.9 km) about 30 min prior and about 50 km south of the flight track. Due to the limited temporal and spatial resolution of the satellite product, the maximum altitude of the peak height of the overshooting top is likely underestimated, which explains the difference between flight altitude of 13.7 and 12.9 km maximum CiPS cloud top height. The intensity of this DCC is also evident in ground precipitation measurements reaching precipitation rates of 95.6 mmh-1 (Fig. S12). Altogether, the most obvious explanation for the high aerosol particle concentrations in the stratosphere between 15:55 and 16:10 UTC is recent upward transport from the troposphere via DCCs into the lower stratosphere, where the aerosol mixed with stratospheric air masses in the convective outflow.

Between 16:15 and 16:45 UTC, again typical UTLS background conditions predominated during the sampling of stratospheric aerosol 3 to 4 km above anvil cirrus. In this 30 min time period, the CSPF was 24 %.

Because of the complicated flight trajectory, and as outlined above, the convective in- and outflow filters contain a modest contribution from UTLS background aerosol, i.e., retrieved INP concentrations are somewhat underestimated and can be regarded as minimum estimates for the in- and outflow INP concentrations. Because all filter samples in this case study feature a different degree of “dilution”, i.e., sampling in the low-INP background regime, a direct quantitative comparison of the INP concentrations on the filters is not feasible. However, we can quasi-quantitatively compare the INP concentration of the case study filters to the UTLS background INP concentration. In any case, the shapes of the INP-temperature spectra can be compared to analyze differences in the INP characteristics of the case study filter samples.

Figure c shows that the mean INP concentration of the convective inflow filter (red line) exceeds the UTLS INP background concentration by a factor of 10–50 throughout the temperature range. As stated above, the INP concentration of the filter sample should be regarded as a lower estimate, meaning that the difference between INP concentrations in the convective inflow and the UTLS background is likely even larger than shown in Fig. c. As stated above, the short in-cloud sampling period at the HASI described above likely artificially increased aerosol particle number concentrations (see Sect. S3 for more details).

INPs active at high temperatures (Teff > -15 °C) are present with at least 0.12 sl-1(red line, Fig. ). Throughout the investigated temperature range, the lower limit INP concentration of the convective inflow filter is in the range of typical mid-latitude INP concentrations at ground level .

Figure a and b show the activated INP fraction, i.e., the INP concentration normalized by the concentration of aerosol particles/CPRs larger than 500 nm (n500; e.g., ). This variable, which also links to a commonly used INP parameterization , was chosen for convenient inter-sample comparison of the INP-temperature spectra characteristics. It is preferred over the normalization of INP number to the sampling volume for this case study due to the limitations listed above.

The activated INP fraction of the in-cloud filter (dark blue line in Fig. a increases by 2 orders of magnitude within the narrow temperature range of -13.5 and -16.5 °C (blue shading in Fig. a). The activated INP fraction spectrum slope down to -25 °C is less steep as the INP concentration merely increases by a factor of 10. Sampling of CPRs within DCCs during other CIRRUS-HL research flights resulted in activated INP fraction spectra of similar shape (see light blue curves, Fig. b, shading same as in panel a), i.e., a steep increase between ∼ -13.5 and ∼ -16.5 °C with the fraction of INPs active above -14 °C remaining comparatively small.

Compared to the shape of the activated INP fraction spectrum of the convective inflow filter (red line in Fig. a, the in-cloud filter differs significantly, as INPs effective above -15 °C are present in the convective inflow but barely detected in the CPRs. INPs effective below -20 °C are present in both, the convective inflow and the in-cloud filter (Fig. a).

The activated INP fraction spectrum of the convective outflow filter (orange line in Fig. a) exhibits a distinct pattern, i.e., a steep increase by at least 2 orders of magnitude between -17 and -19.5 °C (indicated by the orange shading). Between -20 to -26 °C, the slope is markedly shallower, increasing only by a factor of 2. This pattern resembles the activated INP fraction spectrum of the in-cloud filter (blue line in Fig. ). However, the temperature range of the steep increase is shifted towards lower temperatures by 3 to 5 °C for the convective outflow filter. Compared to the activated INP fraction spectrum of the convective inflow filter (red line in Fig. a), with its shallow increase over the investigated temperature range, the steep slope and absence of high-temperature INPs above -17 °C for the convective outflow filter are remarkable.

Figure d shows the derived INP concentration of the convective outflow filter (orange line) in comparison to the UTLS background INP concentrations (green line). The concentrations of INPs active below -20 °C on the convective outflow filter exceed UTLS background concentrations by at least 2 orders of magnitude. It is also worth mentioning that the convective outflow filter features the highest INP concentrations measured throughout the entire CIRRUS-HL campaign, despite the likely underestimation of the actual INP concentration in the convective outflow regions due to “dilution” with UTLS background aerosol. The observed high INP concentration below -20 °C could indicate a potential enrichment of low-temperature INPs in DCC outflows. However, precise quantification is not feasible here, as it would require more targeted sampling of inflow and outflow of DCCs.

Similarly shaped INP concentration spectra were observed for other filters collected in the vicinity of DCCs at high altitude during other CIRRUS-HL research flights (light brown lines in Fig. d). Note that these filters were not exclusively collected in the outflow of DCCs as sampling also occurred in regions with UTLS background concentrations and in clouds. In other words, compared to the presented case study, these samples were collected under less well-defined sampling conditions, likely leading to a smoothing of the INP concentration spectra. Nonetheless, the similarity in shapes of the spectra indicate that the case study's convective outflow filter is not an isolated case.

In the following, we propose a mechanism to explain the observed INP characteristics in and around DCCs. We infer that these characteristics are driven by the interplay between ice formation, ice growth, and precipitation in the mixed-phase cloud regime of DCCs, as the range of the steep slope in the INP spectra, which is located between -15 and -21 °C, coincides with typical glaciation temperatures of mixed-phase clouds .

Figure  shows a schematic cross section of a DCC. For the description, we follow two types of INPs, precipitating (green) and non-precipitating (purple), on their trajectories through the cloud. In the updraft in the lower part of the DCC, potential INPs are quickly activated to cloud droplets and experience supercooling . Following the green trajectories, ice crystals formed through immersion freezing induced by INPs active at high temperatures (> -20 °C) grow fast via the Wegner-Bergeron-Findeisen process (WBF) at ambient temperature spanning around -10 to -20 °C . These grown ice crystals collect rime due to their increased surface area and high terminal velocity, which further accelerates the growth process , making them likely to precipitate first from the DCC . Consequently, the high-temperature INPs, which initiated the first formation of the ice crystals in the DCC would be efficiently removed from the updraft via precipitation. Such effective removal of high-temperature INPs by precipitation has been observed before and explains their absence in the in-cloud and convective outflow filter samples (see Fig. a). However, this does not explain why many INPs, initiating freezing at temperatures around -20 °C and below, are present in the outflow of DCCs featuring cloud top temperatures of -50 °C.

Following the purple trajectories, low-temperature INPs initiate freezing further up in the DCC at temperatures below -20 °C. In this temperature range, diffusional ice growth is slowed down and riming is suppressed . Consequently, precipitation formation is less efficient and small ice crystals are effectively transported upward to the anvil and into the outflow , where they sublimate and the contained INPs are released. From there, the INPs will/may sediment to lower altitudes, making them available for primary ice formation in mid- and upper tropospheric clouds. Single particle chemical analysis of CPRs shows an enhanced particle type fraction of mineral dust (Fig. d). Given that mineral dust particles are very efficient INPs in the relevant temperature range of this study, they are the most likely candidate for the observed freezing activity in the in-cloud sample. However, since total INP concentrations are at least 4 orders of magnitude lower than total CPR number concentrations, the bulk CPR composition alone is not sufficient to unambiguously identify the INP subset.

In our case study, the separation between efficient and inefficient precipitation scavenging of INP occurred in a narrow temperature range between -15 and -21 °C. One possible explanation for such a narrow temperature range is rapid glaciation within the DCC updraft, caused by riming and secondary ice production (SIP). A variety of different SIP processes have been proposed , e.g., ice-ice collisions and fracturing of supercooled large droplets during freezing. The latter has been suggested as a very effective and rapid glaciation process in convective clouds . The DCC studied here likely had a cloud base temperature of 15 to 20 °C (see Fig. S13 for more details), providing the required preconditions for the formation of supercooled large droplets through collisional coalescence in the form of a sufficiently deep, warm cloud region. Thus, we consider rapid glaciation of the DCC in the temperature range between −15 and −21 °C as a likely cause of the observed segregation between high-temperature, precipitating INPs and low-temperature, non-precipitating INPs.

The microphysical pathways governing the interaction between INPs and DCC are inherently complex and remain incompletely understood, in part because they are poorly constrained by in-situ observations within active convection . Processes such as SIP, ice growth, aggregation, and phase partitioning of hydrometeors may all contribute to the observed INP characteristics, yet current knowledge does not allow these mechanisms to be quantified or disentangled in great detail for this case study.