Microphysical investigation of the seeder and feeder region of an Alpine mixed-phase cloud

. The seeder-feeder mechanism has been observed to enhance orographic precipitation in previous studies. However, the microphysical processes active in the seeder and feeder region are still being understood. In this paper, we investigate the seeder and feeder region of a mixed-phase cloud passing over the Swiss Alps, focusing on (1) fallstreaks of enhanced radar reﬂectivity originating from cloud top generating cells (seeder region) and (2) a persistent low-level feeder cloud produced by the boundary layer circulation (feeder region). Observations were obtained from a multi-dimensional set of instruments includ- 5 ing ground-based remote sensing instrumentation (Ka-band polarimetric cloud radar, microwave radiometer, wind proﬁler), in situ instrumentation on a tethered balloon system and ground-based aerosol and precipitation measurements. The cloud radar observations suggest that ice formation and growth was enhanced within cloud top generating cells, which is consistent with previous observational studies. However, uncertainties exist regarding the dominant ice formation mechanism within these cells. Here we propose different mechanisms that potentially enhance ice nucleation and growth in cloud top gen- 10 erating cells (convective overshooting, radiative cooling, droplet shattering) for ice growth and precipitation initiation. While most of the studies agree that generating cells have important implications for precipitation formation, less research has focused on the mechanisms that are responsible for the enhanced

1 Introduction occurred in the feeder region below.
Ice crystals can grow by various ice processes depending on the ambient conditions and the size distribution of cloud droplets and ice crystals (e.g., Marshall and Langleben, 1954;Fukuta and Takahashi, 1999;Bailey and Hallett, 2009;Connolly et al., 2012). For example, small ice crystals grow initially by diffusion of water vapor and thus their habit is determined by the ambient temperature and supersaturation (Magono and Lee, 1966;Bailey and Hallett, 2009). When ice crystals reach a critical 60 size, they can grow more efficiently by aggregation and riming. Aggregation involves the collision and coalescence between ice particles and is most efficient at temperatures higher than -10°C due to the presence of a thicker quasi-liquid layer, which enhances the stickiness of the ice particles (e.g., Lohmann et al., 2016b). Riming, which involves the collision of an ice particle with a supercooled cloud droplet that freezes upon contact, has often been observed in the feeder regions of clouds (Mitchell et al., 1990;Borys et al., 2000;Borys et al., 2003;Saleeby et al., 2009;Saleeby et al., 2011;Lowenthal et al., 2011; Size Velocity (Parsivel) disdrometers (OTT Parsivel2, OTT HydroMet, Germany; Tokay et al., 2014). Parsivel disdrometers can measure both the size and the fall velocity of hydrometeors that fall through a laser sheet (Löffler-Mang and Joss, 2000).
The size of the hydrometeor is estimated from the signal attenuation, whereas the fall velocity of the hydrometeor is obtained from the signal duration. Using the single particle size -fall velocity relationship, the observed particles can be classified into different hydrometeor classes, by applying different hydrometeor-dependent parameterizations (e.g., Yuter et al., 2006). 130 Precipitation particles in the size range between 0.2 mm and 25 mm are measured. The temporal resolution of the measurements is 30 s. Additionally, a Multi-Angle Snowflake Camera (MASC; Garrett et al., 2012) was installed at Laret (see Fig. 1), which took photographs of hydrometeors from three different angles and simultaneously measured their fall velocity. The MASC is sensitive to hydrometeors in the size range between 100 µm and 10 cm. Furthermore, a snow drift station was installed at Gotschnagrat, which provided data about wind-driven redistribution of snow (Walter et al., 2020). 135 Lastly, aerosols and INP properties were measured at the valley station Wolfgang (1630 m) and at the mountain-top station Weissfluhjoch (2700 m) (see Fig. 1). Aerosol instruments were connected to heated inlets for measurements of ambient air at each site. Additionally, ambient aerosols were collected approximately every 1.5 h with a high flow rate impinger (Coriolis µ, Bertin Technologies, France, operation at 300 lpm for 20 mins; Carvalho et al., 2008). The impinger collected aerosol particles larger than 0.5 µm in swirling liquid water and the aqueous solution was analyzed in drop-freezing instruments in order to 140 obtain INP concentration spectra from 0°C to approximately -20°C. The DRoplet Ice Nuclei Counter Zurich (DRINCZ; David et al., 2019) was operated at Wolfgang and the LED-based Ice Nucleation Detection Apparatus (LINDA; Stopelli et al., 2014) was run at Weissfluhjoch. Both drop-freezing instruments use a digital camera to detect freezing by a change in the light transmission through the aqueous solution. An intercomparison study was conducted between DRINCZ and LINDA. The differences in observations were within the instrumental uncertainty.

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The cumulative INP concentration was calculated following eq. (4) in Vali (2019): using the temperature-dependent frozen fraction F F (T ), the volume of an individual aliquot V a (50 µL at Wolfgang, 100 µL at Weissfluhjoch) and the normalization factor C, which converts the concentration to standard liters of ambient air. C was calculated for each sample by considering the flow rate of the impinger F impinger (300 lpm), the sampling time t sample (usually 150 20 min), the end volume of the liquid V liquid (approx. 15 mL) and the conversion factor from liters to standard liters C stdL (including the ambient temperature T ambient and pressure p ambient at each site and the reference temperature T ref = 273.15 K and pressure p ref = 1013.25 hPa). According to the specifications above, the minimal detectable concentration (limit of detection) at Wolfgang was 6.3 · 10 −4 stdL −1 and at Weissfluhjoch 3.5 · 10 −4 stdL −1 .
3 Description of the case study 155 The synoptic weather situation over Europe on 8 March 2019 was characterized by a large-scale westerly flow with several low pressure systems (Fig. 2a). This strong westerly flow persisted for several days and brought moist air from the Atlantic towards central Europe. A low-pressure system located over Scandinavia produced a small-scale disturbance on its southern edge, which crossed Switzerland during the day and reached Davos in the afternoon. The presented case study was observed during the passage of this small-scale disturbance, which arrived in Davos at around 15 UTC and lasted until 19 UTC.

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During the passage of the cloud system, the temperature at Davos decreased from 3°C to -2°C (∆T = -5°C) and the temperature at Weissfluhjoch decreased from -5°C to -7.5°C (∆T = -2.5°C). The vertical temperature profile of a radiosonde ascent is shown in Figure 2b. The radiosonde was launched from Payerne, which is located around 200 km upstream of Davos. The temperatures measured at Davos, Gotschnagrat and Weissfluhjoch were slightly warmer (1-2°C) than the temperature measured to 15 m s −1 above 3000 m. Below 2400 m, the wind speed was lower (< 5 m s −1 ) and the flow was coming from the north-east (confined by the Davos valley). This pattern in the low-level wind field can be explained by shielding effects due to the mountain barrier B1 located upstream of Wolfgang (Fig. 1b), resulting in a decoupled low-level flow in the lee of the mountain barrier. A strong decrease in wind speed was observed above 2700 m between 17:45 UTC and 18:30 UTC. In addition, the wind direction veered from 250°to 280°during this time period. This change in the wind pattern coincides with the period of the strongest 175 precipitation event at Wolfgang (Fig. 4e) and could potentially have contributed to the glaciation of the MPC. Furthermore, enhanced wind shear was observed near cloud top (> 10 m s −1 km −1 ) with a maximum of 20 m s −1 km −1 corresponding to the most intense precipitation peak (cf. Fig. 3b, Fig. 4e). Another layer of enhanced wind shear was observed between 2500 m and 3000 m, due to the interaction of the large-scale flow with the mountain barrier B1 (Fig. 1). Wolfgang. The vertical wind shear (s) was calculated from the wind profiler observations, considering changes in the scalar wind speed and direction (u) between two adjacent height levels (z) (s = u 2 −u 1 z 2 −z 1 ). The gray line in (b) shows the cloud radar reflectivity contour of -30 dBZ, which indicates the cloud top height. An overview of the observed microphysical cloud structure is shown in Figure 4. The radar reflectivity shows that the precipitation began at 15:10 UTC and was convective in nature ( Fig. 4a). At around 17:30 UTC, the reflectivity increased at all altitudes and the highest precipitation rates were observed at the surface (Fig. 4e). The period of high reflectivity (> 10 dBZ) lasted for about one hour. After this period, the cloud top lowered from 5000 m to 2800 m and the precipitation ended shortly 185 after 18:40 UTC. The bulk of the precipitation originated at cloud top as can be seen from the fallstreak pattern of enhanced radar reflectivity (> 10 dBZ, Fig. 4a). The contour frequency by altitude diagram (CFAD, Fig. 5) of the radar reflectivity ( Fig.   5a) indicates a rapid increase in the radar reflectivity near cloud top, suggesting that the ice crystals were formed in the layer between 5000 m and 4000 m. The ice crystals rapidly grew to large sizes between 4000 m and 3000 m, before they partly sublimated in the layer between 3000 m and 2000 m, as indicated by the decreasing radar reflectivity ( Fig. 4a and 5a) and Doppler 190 velocity ( Fig. 4b and 5b) below 3000 m (assuming horizontal homogeneity). The majority of upward motion was observed above 3500 m ( Fig. 4b and 5b). It is important to note that the measured vertical Doppler velocity is the sum of the particle fall speed and the air motion. Thus, as the ice particles grow to larger sizes while falling towards the ground, their fall speed increases and therefore mask the updrafts more easily. The Doppler velocity CFAD shows large variations between -4 m s −1 8 https://doi.org/10.5194/acp-2020-772 Preprint. Discussion started: 9 October 2020 c Author(s) 2020. CC BY 4.0 License.   Evans et al., 2005;Ikeda et al., 2007;Crosier et al., 2014;Kumjian et al., 2014;Plummer et al., 2014;Rosenow et al., 2014;Plummer et al., 2015;Rauber et al., 2015) as will be further discussed in Section 4.2.

Results and Discussion
Ice particles that formed within the seeder region interact with other cloud particles while falling through the cloud and thus influence the microphysics of the feeder region below. The low-level cloud structure was observed with the tethered balloon system HoloBalloon (see Fig. 6). The balloon-borne measurements indicate the presence of a low-level liquid layer that was In the following, we will further investigate the origin of ice particles that formed within generating cells. Numerous studies have observed enhanced ice formation and growth in these updraft regions (Houze Jr et al., 1981;Hogan et al., 2002;Plum-275 mer et al., 2014;Ikeda et al., 2007;Crosier et al., 2014;Kumjian et al., 2014;Rauber et al., 2015). For example  found that the ICNC was enhanced by a factor of 2 to 3 within the core region of generating cells compared to the region between the cells. While most of the studies agree that radiative cooling is a major driver for the formation and maintenance of cloud top generating cells, less research has focused on the reason for the enhanced ICNCs that were observed within these cells. Here we provide potential reasons from an INP-cloud perspective and propose possible mechanisms by con- particles (> 400 -600 µm; derived from particle size distribution in Fig. 7b) formed near cloud top and grew to these large sizes while falling to the surface. This criterion is based on the assumption that the large ice particles did not sublimate completely prior to reaching the surface. The ICNC observed near cloud base was in the same order of magnitude as the ICNC retrieved from the remote sensing observations (red dots in Fig. 11) using the method described in Bühl et al. (2019). The comparison between the observed ICNC of large ice particles (ICNC > 500 µm ) and the INP concentration at cloud top shows a discrepancy 295 between the observed INP concentration and ICNC during certain time periods (Fig. 11), suggesting that the ICNC cannot be solely explained by primary ice nucleation, but that other mechanisms were active.
Static instability driven by cloud top radiative cooling can produce strong updrafts (Fig. 8b) and lead to convective overshooting of cloud top generating cells (see red arrows in Fig. 8a). This convective overshooting can decrease the cloud top temperature and therefore increase the ICNC formed by primary ice nucleation. For example, the cloud top height during GC1 increased by 300 500 m from 4500 m to 5000 m. Considering the observed temperature profile in Figure 2b, the cloud top temperature decreased by 3.6°C from -21°C (at the average cloud top height) to -24.6°C (at 5000 m) upon convective overshooting. Consequently, the INP concentration increased by a factor of 3.3 from 0.3 L −1 to 1 L −1 (Fig. 10) due to the colder cloud top temperature.
The ICNC > 500 µm measured near cloud base lied below the extrapolated INP concentration at -25°C before 18 UTC (Fig. 11), suggesting that the observed ICNC > 500 µm near cloud base can be solely explained by primary ice nucleation and convective 305 overshooting. After 18 UTC, the ICNC > 500 µm measured near cloud base lied above the convective overshooting line (Fig. 11), suggesting that other processes were occurring.
For example, the positive feedback between supercooled liquid water, radiative cooling and turbulence that has been observed near cloud tops (e.g., Morrison et al., 2012) might have contributed to enhanced ice formation. The presence of supercooled liquid can lead to strong longwave radiative cooling (e.g., Possner et al., 2017). This radiative cooling decreases the stability 310 near cloud top, which causes turbulent motions, which in turn can produce further supercooled liquid water. The magnitude of the longwave radiative cooling strongly depends on the cloud phase, the liquid water content and particle size distribution, among other factors (e.g., Turner et al., 2018). Indeed, the LWP, as measured by the microwave radiometer, was enhanced within generating cells (see Fig. 8d) and thus likely increased the longwave radiative cooling at cloud top. The question is by how much the radiative cooling was enhanced within generating cells due the increased cloud liquid water compared to their 315 surrounding regions. Previous studies observed longwave radiative cooling rates in the range of 1 -5 K h −1 near cloud top (e.g., Chen and Cotton, 1987;Pinto, 1998;Jiang et al., 2000;Rasmussen et al., 2002;Morrison et al., 2011;Morrison et al., 2012;Possner et al., 2017;Turner et al., 2018;Eirund et al., 2019). Additionally, Turner et al. (2018) computed radiative heating rate (RHR) profiles in the atmosphere as a function of cloud type and LWP by using an observational data set. According to Turner et al. (2018), an increase in the LWP from 50 g m −2 to 150 g m −2 (e.g., GC2 in Fig. 8) can cause an increase in the longwave 320 radiative cooling rate from around 1.7 K h −1 to 2.9 K h −1 (∆RHR = 1.2 K h −1 ). This could potentially cool the cloud top temperature by 0.3 K, if a lifetime of around 15 min is assumed for cloud top generating cells (i.e., 1.2 K h −1 × 15 min = 0.3 K), and increase the INP concentration from 0.3 L −1 to 0.35 L −1 (factor 1.2, see Fig. 10). Thus, longwave radiative cooling only plays a minor role in enhancing primary ice nucleation. Nevertheless, longwave radiative cooling is of major importance for the production of radiatively driven turbulence near cloud top and thus for maintaining generating cells.

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Other mechanisms must be active to explain the increased ICNCs after 18 UTC. For instance, the enhanced updrafts in generating cells allow all hydrometeors to grow to larger sizes. It is unlikely that the larger cloud droplet size would significantly increase primary ice nucleation by immersion freezing, which is the dominant ice nucleation mechanism in MPCs (e.g., Ansmann et al., 2008;De Boer et al., 2011;Westbrook and Illingworth, 2011), but it can play an important role for SIP. For example, the freezing of drizzle-sized droplets can release a large number of small secondary ice particles (e.g, Langham and 330 Mason, 1958;Mason and Maybank, 1960;Lauber et al., 2018;Korolev and Leisner, 2020). This process is known as droplet shattering and has been observed to be strongly dependent on the cloud droplet size and to be potentially effective over a large temperature range (Lauber et al., 2018). Previous field studies have observed the presence of drizzle-sized droplets in the size range of 100 µm -300 µm in regions of strong vertical updrafts (e.g, Hauf and Schröder, 2006;Ikeda et al., 2007). A single shattering event has the potential to produce hundreds of ice crystals. Thus, droplet shattering could increase the ICNC in   Figure 12. Firstly, primary ice nucleation in generating cells can be increased due to convective overshooting or radiative cooling. The ICNC observed before 18 UTC can likely be explained by these two mechanisms, since the INP concentration and the ICNC > 500 µm measured near cloud base agreed within the same order of magnitude (Fig. 11). We found that the contribution from convective overshooting (factor 3.3) was larger than that of radiative cooling (factor 1.2) in the present study. On the other 345 hand, the ICNC of large particles measured at the surface after 18 UTC exceeded the INP concentration by almost one order of magnitude, suggesting that SIP processes such as droplet shattering might be active within generating cells. However, more targeted studies are necessary to understand which mechanisms are responsible for enhanced ice formation and growth within generating cells. In particular, in situ measurements of the cloud properties within generating cells and their environmental conditions (e.g., temperature, updrafts, INP conditions) are of major importance to address these questions.

Secondary ice production processes in feeder cloud
Ice crystals that formed in the seeder region can grow by microphysical interactions with other cloud particles while falling through the cloud layer and thus influence the microphysics of the entire cloud. For example, if large ice particles fall through a supercooled liquid layer, they can initiate the glaciation of the cloud layer through the WBF process and/or grow by riming.
Furthermore, the total number of nodes (Fig. 8c) shows multi-peaked situations below 3300 m, indicating the presence of multiple particle populations with different fall speed. This suggest that secondary ice particles might be produced in the feeder region of the cloud. In the following, we investigate the importance of ice growth and SIP in the feeder region by analyzing the phase-resolved cloud properties measured in situ with the HoloBalloon platform. In particular, the analysis of the ice crystal habit and size can provide important information about the formation and growth history of ice particles. Figure 13 shows a representative set of ice particle images observed by HOLIMO as a function of height and time. It can be 360 seen that ice crystal habits varied greatly during the passage of the cloud system. For example, the images indicate the presence of numerous columns between 17:00 UTC and 17:20 UTC at altitudes above 1780 m (yellow boxes), which are known to grow at temperatures between -3°C and -10°C (Magono and Lee, 1966;Bailey and Hallett, 2009). Furthermore, irregular shaped particles were abundant (green boxes), consistent with previous studies (e.g., Korolev et al., 1999;Stoelinga et al., 2007). A large fraction of graupel and rimed particles was observed between 17 UTC and 17:40 UTC (red boxes). After 18 UTC, the ice 365 crystals became more aggregated (blue boxes) and less rimed (see also MASC data in Fig. 14d), suggesting a decrease in the amount of liquid water available for riming. Furthermore, small pristine ice crystals (plates and columns) were present over the entire period (see Fig. 15c and purple boxes in Fig. 13).
The large variability in ice crystal habit and size suggests that the ice crystals have formed and grown in different regions. As discussed in Section 4.2, it is likely that the heavily rimed ice particles and large dendrites (Fig. 13) were produced within 370 the seeder region of the cloud and gained mass by riming and deposition while falling through the cloud. On the other hand, the small pristine ice crystals were likely formed within the feeder region of the cloud. Previous studies have found that small pristine ice crystals (< 100 µm) were spatially correlated with their environment of origin (e.g., . For example, it is possible that the observed columns originated within the multi-peaked structures (Fig. 8c), as the temperature below 3000 m was in the temperature regime of columnar growth (Bailey and Hallett, 2009). Pristine plates likely grew in the 375 lowest part of the cloud, where the prevailing temperature was above -3°C. These small ice crystals (< 100 µm) could have formed either by primary ice nucleation or by SIP processes within the feeder cloud and rapidly grown by diffusion to larger sizes (e.g., . The contribution of primary ice nucleation to the observed ICNC can be estimated from the measured INP concentration (Fig. 10), which was below the minimal detectable concentration (6.3 · 10 −4 stdL −1 ; see Section 2) at a temperature of -3°C. Thus, the minimal detectable concentration of 6.3 · 10 −4 stdL −1 represents an upper limit for 380 the INP concentration within the feeder region. The ICNC of particles smaller than 100 µm in diameter observed in the feeder cloud (1 -2 L −1 ; Fig. 14a) exceeded the INP concentration by three orders of magnitude, suggesting that primary ice nucleation alone cannot explain the small ice crystals observed.
Secondary ice production processes are necessary to explain the observed ICNC in the low-level liquid layer. As the cloud droplets in the low-level feeder cloud were small (< 50 µm in diameter, Fig. 7a), droplet shattering was likely not the responsible 385 mechanism. However, as the temperature at 1900 m was around -3°C and large rimed particles (Fig. 14a) and cloud droplets larger than 25 µm in diameter (Fig. 14b) were observed in the low-level liquid layer, the Hallett-Mossop process may have been active (Hallett and Mossop, 1974;Mossop, 1978). Another mechanism that could have led to the production of secondary ice particles in the low-level feeder cloud is ice particle fragmentation upon ice-ice collisions (e.g., Vardiman, 1978;Takahashi et al., 1995). As the low-level liquid layer contained small pristine and large rimed ice particles (Fig. 13), which have different terminal fall velocities and therefore enhanced collision efficiencies, this suggests that collisional ice fragmentation may have been occurring. Indeed, the ice crystal images in Figure 13 indicate the presence of ice fragments. Therefore, based on the temporal evolution of the cloud properties (Fig. 14a, b), we suggest that ice particle fragmentation upon collision was the dominant SIP process after 18 UTC, since the CDNC and in particular the number of large cloud droplets decreased after 18 UTC (Fig. 14b). In contrast, the presence of large cloud droplets (> 25 µm) before 18 UTC suggests that both the  Mossop process and collisional ice fragmentation contributed to the observed ICNC.
Previous studies have observed large discrepancies between the INP concentration and ICNC in the feeder region of clouds (e.g., Rogers and Vali, 1987;Lloyd et al., 2015;Beck et al., 2018;Lowenthal et al., 2019). These observations were frequently conducted at mountain-top research stations or near mountain slopes, where ICNCs of several hundreds to thousands per liter have been reported (e.g., Rogers and Vali, 1987;Lloyd et al., 2015;Lowenthal et al., 2019). These large ICNCs were attributed 400 to the influence of surface processes such as blowing snow (Rogers andVali, 1987, Geerts et al., 2015), hoar frost (Lloyd et al., 2015), riming on snow-covered surfaces (Rogers and Vali, 1987) or ice crystal enhancement through turbulence and convergence (Beck et al., 2018), whereas the contribution of SIP processes has been suggested to be minor or has been difficult to assess (Lloyd et al., 2015, Beck et al., 2018. By performing balloon-borne measurements in a mountain valley, we measured ICNC two order of magnitude lower than previous observations at mountain-tops (1 -10 L −1 instead of 100 -1000 L −1 ) and 405 thus were able to significantly reduce the impact of surface processes. Based on the observed INP concentration (Fig. 10) and ICNC (Fig. 14a), we suggest that SIP processes contributed up to 1-2 L −1 to the observed ICNC and thus accounted for up to ( Fig. 14a) cannot be solely explained by SIP within the feeder cloud, since the observed increase was primarily due to large ice particles (> 300 µm, see Fig. 7b). This increase in ICNC can likely be attributed to a change in the microphysics within the 410 seeder region, which initiated the glaciation of the MPC.
If only a small concentration of secondary ice particles is captured by updrafts or turbulence within the feeder region and lifted aloft, they can initiate further ice formation and growth at temperatures well above typical INP activation temperatures and have a significant impact on the development of the cloud (e.g., cloud properties, glaciation, lifetime). While the CDNC decreased above 1850 m, the vertical profiles of the ICNC showed no height dependence over the 200 m height interval (Fig.   415 15a). This suggests that SIP was active over the entire low-level liquid layer. However, due to the limited vertical extent of the profiles, we cannot make a final statement regarding the impact of SIP within the feeder region on the cloud microphysics aloft.
Further observations in 'surface-decoupled' environments (i.e., reduced influence of surface processes) with a larger vertical extent are required to assess the role of SIP in feeder clouds. This is important, as it can lead to the formation of precipitation in clouds which otherwise may not have produced significant precipitation.

Conclusions
In this paper, we investigated the microphysical evolution of a mixed-phase cloud passing over the Swiss Alps using a multidimensional set of observations and instruments including (1) ground-based remote sensing, (2) in situ microphysical observations on a tethered balloon system, (3) INP measurements and (4) surface precipitation measurements. A particular emphasis was placed on studying the microphysics within cloud top generating cells and a persistent low-level feeder cloud from an 425 aerosol-cloud-precipitation perspective. The key findings are summarized as follows: -The microphysical structure of the MPC was observed with a vertically-pointing Ka-band polarimetric cloud radar and with a tethered balloon system. The phase transition from a liquid to an ice cloud was observed during the passage of the cloud system. It is likely that the Wegener-Bergeron-Findeisen process contributed to the glaciation of the MPC.
Regarding the vertical cloud structure, generating cells with enhanced radar reflectivity were observed near the cloud 430 top, which acted as a seeder region and produced fallstreaks of enhanced radar reflectivity. Furthermore, the decoupled boundary layer circulation in the lee of the mountain barrier produced local updrafts and turbulence, which led to the formation of a persistent low-level feeder cloud.
-The cloud radar and microwave radiometer observations suggest that ice formation and growth as well as liquid water production was enhanced within cloud top generating cells. While numerous studies have observed enhanced ICNCs 435 within generating cells, uncertainties exist regarding their ice formation mechanism. Here we proposed different processes and discussed their potential contribution. Cooling associated with convective overshooting was suggested to increase the INP concentration by a factor of 3.3, whereas radiative cooling was estimated to increase the ICNC formed by primary ice nucleation only by a factor of 1.2. In addition, secondary ice production through droplet shattering was of the MPC.
-The co-existence of small pristine ice crystals and large rimed ice particles was observed in the low-level feeder cloud, suggesting the occurrence of secondary ice production. By using a tethered balloon to observe the feeder cloud in the mountain valley, we were able to significantly reduce the influence of surface processes compared to previous observations at mountain tops and to investigate the contribution of secondary ice production in the feeder region of clouds.

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The ICNC of small ice crystals (< 100 µm) measured near cloud base exceeded the INP concentration by three orders of magnitude. Conditions favorable for the Hallett-Mossop process and ice particle fragmentation upon ice-ice collisions were found. We suggest that secondary ice production in the feeder cloud increased the ICNC by a factor of 2.
Overall, this study observed the temporal and spatial evolution of the microphysics within the seeder and feeder region of a MPC passing over the Swiss Alps. We found that a significant increase in ice formation and growth within the seeder region 450 can induce the glaciation of the MPC. In addition, we found that secondary ice production mechanisms were active in the feeder cloud, which initiated ice formation at temperatures where no INP were detectable. This case study demonstrates that secondary ice production can occur in different cloud regions and have important implications for precipitation initiation and the lifetime of MPCs in general. Further studies are required to understand the role of secondary ice production both in the seeder and feeder regions of clouds. These studies should include vertically-resolved in situ observations of the microphysical 455 properties, aerosol properties (e.g., INP) and environmental conditions (e.g., temperature, vertical updraft velocity) over the entire cloud depth and should be performed in a 'surface-decoupled' environment (i.e., reduced influence of surface processes).
Appendix A: The use of the maximum Doppler velocity as a proxy for regions with updrafts and liquid water In the framework of the present study, the maximum Doppler velocity was used as a proxy to identify regions with updrafts and liquid water. The maximum Doppler velocity v max was derived from the Doppler spectra as shown in Figure A1a. In order 460 to be more robust regarding the presence of extreme values, v max was defined as follows: v max = maximum Doppler velocity where Z >= (Z min + 0.1 · (Z max − Z min )) where Z min and Z max are the minimum and maximum radar reflectivity. To validate whether v max can also be used to identify regions with liquid water, it was compared to the LWP measured by the microwave radiometer. Since the LWP is integrated over the whole vertical column, the vertically-integrated v max is shown in Figure A1b. A positive correlation was found between 465 v max and the LWP with a Spearman rank correlation coefficient of 0.5 significant at the 5% level. Based on this result, we assume that v max can be used as a proxy for updraft regions and regions with liquid water.