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Low-level mixed-phase clouds (MPCs) are common in the Arctic. Both local and large-scale phenomena influence the properties and lifetime of MPCs. Arctic fjords are characterized by complex terrain and large variations in surface properties. Yet, not many studies have investigated the impact of local boundary layer dynamics and their relative import...
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... sensitivity test allowing only 2 min gaps in the liquid layer showed the only major difference to be in the occurrence frequency of P-MPCs, while the properties of the clouds or the seasonal cycle of P-MPC occurrence did not differ substantially. Figure 6 shows the occurrence of each weather type (used to determine the regional free-tropospheric wind direction; see Sect. 3.3) in our period of study, and the fraction of those times when a P-MPC was identified. ...
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... wind direction for the weather type anticyclonic was west (not shown). On the other hand, winds from north and east (weather types N, NE, and E) brought P-MPCs to the site less often. The weather types which are most commonly associated with P-MPCs can be determined by combining the occurrence frequency of each weather type and its P-MPC fraction (Fig. 6). Consequently, P-MPCs were most often associated with the weather types W, SW, and anticyclonic, which include almost half (48 %) of all ...
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... 50th, and 75th percentiles, the dot the mean, and the whiskers the 5th and 95th percentiles. The medians for different weather types were found to differ on a 95 % confident level. high amounts of liquid, compared to the north-northeasterly winds, which are drier and colder and are associated with less frequent P-MPC occurrence and lower LWP (Figs. 6, 7b, and 8a). Owing to the complexity of ice microphysical processes, such a direct relationship cannot be found between atmospheric humidity and temperature (Fig. 8) and IWP (Fig. 7c). On the other hand, as already noted above, Fig. 7 shows a clear contrast between the properties of easterly and westerly P-MPCs. These differences cannot ...
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... effects local winds have on the P-MPC were evaluated using the weather type together with the surface wind direction as a proxy for the wind conditions at Ny-Ålesund (Sect. 3.4). The most common wind situation for the P-MPC at Ny-Ålesund is a southeasterly surface wind underlying westerly and southwesterly upper winds (Figs. 4, 6). Hence, the wind turns from the surface upwards to the almost opposing direction by 1.5 km height (Fig. 4c). Directional wind shear is therefore commonplace for P-MPC at Ny-Ålesund (Fig. 4b), either in or below the cloud layer. The magnitude of the wind direction change varies with the free-tropospheric wind. The only exception are ...
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... influence of local winds on the P-MPC was found to be limited. Figure 13a shows the fraction of time with P-MPC occurring (similarly to Fig. 6) for each weather type and surface wind direction combination. Weather types cyclonic and anticyclonic are somewhat hard to interpret, as these are associated with varying free-tropospheric wind directions above the site and were therefore not included. The low number of cases with southwest and northwest surface wind limits the ...
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... Cloudnet delivers, e.g., a classification of the atmospheric conditions, distinguishing between clear sky, different cloud types 130 (ice, liquid, mixed-phase), and the presence of aerosols and insects, for each time-height pixel. Because of technical limitations, the Cloudnet product starts at a height of 182 m and can therefore miss the presence of low-level stratus clouds, which are common in the Arctic (Gierens et al., 2020;). The additional low-level stratus detection developed by was used to mask these cases. ...
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... Low-level stratus. The Arctic is known for its high occurrence of low-level clouds 31 , which are frequently located below the lowest detection limit of most remote-sensing instruments 19,94 . Yet, these clouds are often still too high for ground-based in-situ sensors. ...
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... For all cloud-phase regimes, fPBAPs were mostly present at lower d-excess values. Regional aerosol sources are important for cloud formation and evolution in the Arctic (Gierens et al., 2020), and this seems to be reflected here. ...
Mixed-phase clouds (MPCs) are key players in the Arctic climate system due to their role in modulating solar and terrestrial radiation. Such radiative interactions rely, among other factors, on the ice content of MPCs, which is regulated by the availability of ice-nucleating particles (INPs). While it appears that INPs are associated with the presence of primary biological aerosol particles (PBAPs) in the Arctic, the nuances of the processes and patterns of INPs and their association with clouds and moisture sources have not been resolved. Here, we investigated for a full year the abundance of and variability in fluorescent PBAPs (fPBAPs) within cloud residuals, directly sampled by a multiparameter bioaerosol spectrometer coupled to a ground-based counterflow virtual impactor inlet at the Zeppelin Observatory (475 m a.s.l.) in Ny-Ålesund, Svalbard. fPBAP concentrations (10−3–10−2 L−1) and contributions to coarse-mode cloud residuals (0.1 to 1 in every 103 particles) were found to be close to those expected for high-temperature INPs. Transmission electron microscopy confirmed the presence of PBAPs, most likely bacteria, within one cloud residual sample. Seasonally, our results reveal an elevated presence of fPBAPs within cloud residuals in summer. Parallel water vapor isotope measurements point towards a link between summer clouds and regionally sourced air masses. Low-level MPCs were predominantly observed at the beginning and end of summer, and one explanation for their presence is the existence of high-temperature INPs. In this study, we present direct observational evidence that fPBAPs may play an important role in determining the phase of low-level Arctic clouds. These findings have potential implications for the future description of sources of ice nuclei given ongoing changes in the hydrological and biogeochemical cycles that will influence the PBAP flux in and towards the Arctic.
... Several studies investigated liquid and mixed-phase clouds in the Arctic (e.g. Gierens et al. (2020)). In this region with only sparse data coverage, the observations brought new insights about cloud processes, especially regarding polar night radiative effects, and helped to evaluate the ICON-Large Eddy Simulation model by simulating Arctic mixed-phase clouds (Schemann and Ebell, 2020). ...
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... Risk uncertainty simulation can be anticipated in several ways. According to (Gierens et al., 2020), one is sensitivity analysis. The parameters that will make significant changes to the analysis output and how much these parameters can change will be known by sensitivity analysis. ...
... Risk uncertainty simulation can be anticipated in several ways. According to (Gierens et al., 2020), one is sensitivity analysis. Sensitivity analysis helps identify parameters that will make significant changes to the analysis output and how much these parameters can change. ...
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... Due to the limited depth of LLMPCs, information on cloud top temperature (CTT) allows us to constrain the ice habits that are nucleated Myagkov et al., 2016). Furthermore, the wide range of liquid water path (LWP) values typically observed, from a few tens up to 400 g m 2 (Chellini et al., 2022;Gierens et al., 2020), allows us to discriminate between scenarios with varying likelihood of riming. Hence, the wide spectrum of conditions provided by Arctic LLMPCs makes them ideal natural laboratories to test the dependence of the turbulence-ice-growth interaction on ice habits and varying supercooled liquid availability conditions. ...
Plain Language Summary
Liquid and frozen precipitation mainly forms by collision and subsequent aggregation of small particles. Collisions between cloud particles, such as droplets and ice crystals, are thought to be increased by turbulence. While this effect has been intensively studied for liquid‐only clouds, the impact of turbulence on ice‐ice collisional growth (aggregation) and ice‐liquid collisional growth (riming) is expected but has so far been poorly quantified. We study the effect of turbulence on aggregation and riming based on a long‐term remote‐sensing data set of low‐level clouds containing both ice and liquid particles, recorded at the Arctic site of Ny‐Ålesund, Svalbard. Cloud radar observations are used to retrieve the dissipation rate of turbulent kinetic energy (i.e., the eddy dissipation rate; EDR), which is the relevant quantity driving increases in collision rates, and to characterize ice particle properties. We find evidence that higher EDR regimes enhance the aggregation of particles, and are associated with signatures of increased ice particle concentration, possibly caused by the production of particle fragments upon collision. In temperature regimes more favorable to riming, turbulence dramatically enhances the particles' fall velocity, denoting higher degrees of riming. Our findings thus highlight a key role of turbulence for the formation of precipitable ice.
... Mixed-phase clouds (MPCs) are a crucial part of the Arctic climate system. Observations have shown that MPCs occur about 40 % of the time (e.g., at Barrow, Alaska, or Ny-Ålesund, Svalbard;Shupe, 2011;Gierens et al., 2020), can persist up to several days (Zuidema et al., 2005), and can span hundreds of kilometers by forming organized cloud streets during cold-air outbreaks (Müller et al., 1999). MPCs play a critical role in the Arctic hydrological cycle and radiation budget, having, on average, a positive surface radiative forcing (Shupe and Intrieri, 2004;Kay and L'Ecuyer, 2013). ...
Riming is a key precipitation formation process in mixed-phase clouds which efficiently converts cloud liquid to ice water. Here, we present two methods to quantify riming of ice particles from airborne observations with the normalized rime mass, which is the ratio of rime mass to the mass of a size-equivalent spherical graupel particle. We use data obtained during the HALO-(AC)3 aircraft campaign, where two aircraft collected radar and in situ measurements that were closely spatially and temporally collocated over the Fram Strait west of Svalbard in spring 2022. The first method is based on an inverse optimal estimation algorithm for the retrieval of the normalized rime mass from a closure between cloud radar and in situ measurements during these collocated flight segments (combined method). The second method relies on in situ observations only, relating the normalized rime mass to optical particle shape measurements (in situ method). We find good agreement between both methods during collocated flight segments with median normalized rime masses of 0.024 and 0.021 (mean values of 0.035 and 0.033) for the combined and in situ method, respectively. Assuming that particles with a normalized rime mass smaller than 0.01 are unrimed, we obtain average rimed fractions of 88 % and 87 % over all collocated flight segments. Although in situ measurement volumes are in the range of a few cubic centimeters and are therefore much smaller than the radar volume (about 45 m footprint diameter at an altitude of 500 m above ground, with a vertical resolution of 5 m), we assume they are representative of the radar volume. When this assumption is not met due to less homogeneous conditions, discrepancies between the two methods result. We show the performance of the methods in a case study of a collocated segment of cold-air outbreak conditions and compare normalized rime mass results with meteorological and cloud parameters. We find that higher normalized rime masses correlate with streaks of higher radar reflectivity. The methods presented improve our ability to quantify riming from aircraft observations.
... The fjord is oriented northwestsoutheast and is surrounded by plateaus and mountains of about 500-1000 m altitude. Their presence affects the local wind circulation and the advection of air masses (Maturilli and Kayser, 2017;Gierens et al., 2020;Schön et al., 2022). ...
Clouds play an important role in controlling the radiative energy budget of the Arctic atmospheric boundary layer. To quantify the impact of clouds on the radiative heating or cooling of the lower atmosphere and of the surface, vertical profile observations of thermal-infrared irradiances were collected using a radiation measurement system carried by a tethered balloon. We present 70 profiles of thermal-infrared radiative quantities measured in summer 2020 during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition and in autumn 2021 and spring 2022 in Ny-Ålesund, Svalbard. Measurements are classified into four groups: cloudless, low-level liquid-bearing cloud, elevated liquid-bearing cloud, and elevated ice cloud. Cloudless cases display an average radiative cooling rate of about −2 K d−1 throughout the atmospheric boundary layer. Instead, low-level liquid-bearing clouds are characterized by a radiative cooling up to −80 K d−1 within a shallow layer at cloud top, while no temperature tendencies are identified underneath the cloud layer. Radiative transfer simulations are performed to quantify the sensitivity of radiative cooling rates to cloud microphysical properties. In particular, cloud top cooling is strongly driven by the liquid water path, especially in optically thin clouds, while for optically thick clouds the cloud droplet number concentration has an increased influence. Additional radiative transfer simulations are used to demonstrate the enhanced radiative importance of the liquid relative to ice clouds. To analyze the temporal evolution of thermal-infrared radiation profiles during the transitions from a cloudy to a cloudless atmosphere, a respective case study is investigated.
... Here, the temporal difference between the measurements due to the ascent or descent time of the platform needs to be considered. A more common approach to studying the CRE is the utilization of radiative transfer simulations (e.g., Kay and L'Ecuyer, 2013;Shupe et al., 2015;Ebell et al., 2020;Barrientos-Velasco et al., 2022). Such simulations are based on the input of cloud properties. ...
... Yet, investigations of small-scale processes require the application of models and measurements with a smaller footprint, as offered by ground-based remote-sensing approaches. Shupe et al. (2015) and Ebell et al. (2020), for instance, each have investigated 2 years of ground-based remote sensing and radiative transfer simulations at the land-based sites in Utqiaġvik, USA, and Ny-Ålesund, Svalbard, respectively. Barrientos-Velasco et al. (2022) studied radiative fluxes observed dur- ing the Polarstern cruise PS106 (cruise track is shown in Fig. 1, Wendisch et al., 2019) performed in May-July 2017 in the marginal sea ice zone, north and north-east of Svalbard, of the Arctic Ocean and contrasted them with radiative transfer simulations as well as satellite observations. ...
... Shupe et al. (2015) reported that the largest biases were found for clear-sky and ice-cloud situations. In the study by Ebell et al. (2020), a large difference between the observed and simulated fluxes was found during the summer months, which was attributed to clouds missed by the observations. Barrientos-Velasco et al. (2022) reported similar challenges for the ground-based observations for low-level mixed-phase clouds and ice clouds. ...
Quantifying the role of clouds in the earth's radiation budget is essential for improving our understanding of the drivers and feedback mechanisms of climate change. This holds in particular for the Arctic, the region currently undergoing the most rapid changes. This region, however, also poses significant challenges to remote-sensing retrievals of clouds and radiative fluxes, introducing large uncertainties in current climate data records. In particular, low-level stratiform clouds are common in the Arctic but are, due to their low altitude, challenging to observe and characterize with remote-sensing techniques. The availability of reliable ground-based observations as reference is thus of high importance. In the present study, radiative transfer simulations using state-of-the-art ground-based remote sensing of clouds are contrasted with surface radiative flux measurements to assess their ability to constrain the cloud radiative effect. Cloud radar, lidar, and microwave radiometer observations from the PS106 cruise in the Arctic marginal sea ice zone in summer 2017 were used to derive cloud micro- and macrophysical properties by means of the instrument synergy approach of Cloudnet. Closure of surface radiative fluxes can only be achieved by a realistic representation of the low-level liquid-containing clouds in the radiative transfer simulations. The original, most likely erroneous, representation of these low-level clouds in the radiative transfer simulations led to errors in the cloud radiative effect of 54 W m−2. In total, the proposed method could be applied to 11 % of the observations. For the data, where the proposed method was utilized, the average relative error decreased from 109 % to 37 % for the simulated solar and from 18 % to 2.5 % for the simulated terrestrial downward radiative fluxes at the surface. The present study highlights the importance of jointly improving retrievals for low-level liquid-containing clouds which are frequently encountered in the high Arctic, together with observational capabilities both in terms of cloud remote sensing and radiative flux observations. Concrete suggestions for achieving these goals are provided.
... This study uses microphysical process rates to determine which processes contribute most to phase changes in Arctic low-50 level clouds (LLC). The focus lies on Svalbard, where LLCs frequently occur (Gierens et al., 2020;Nomokonova et al., 2019). Svalbard has an above average occurrence of MPCs (45-60 %) in comparison to the rest of the Arctic (30-50 %, Mioche et al., 2015) making the location ideal for studying the phase-partitioning of clouds. ...
... This was done by first selecting all grid boxes which are cloudy using a threshold for the hydrometeor concentration of 10 −8 kg kg −1 (same as in Kiszler et al.,75 2023; Schemann and Ebell, 2020) above which a grid box is defined as cloudy. For a cloud to be classified as low-level, the cloud top height must be below 2.5 km (same as Gierens et al., 2020;Chellini et al., 2022). Additionally, precipitating hydrometeors are not differentiated from non-precipitating ones. ...
Current general circulation models struggle to capture the phase-partitioning of clouds accurately, either overestimating or underestimating the supercooled liquid substantially. This impacts the radiative properties of clouds. Therefore, it is of interest to understand which processes determine the phase-partitioning. In this study, microphysical process rates are analyzed to study what role each phase-changing process plays in low-level Arctic clouds. Several months of cloud-resolving ICON simulations using a two-moment cloud microphysics scheme, are evaluated. The microphysical process rates are extracted using a diagnostic tool introduced here, which runs only the microphysical parameterisation using previously simulated days. It was found that the importance of a process varies for the polar night and polar day, although phase changes that involve the vapour phase dominate. Additionally, the dependence of each process on the temperature, vertical wind and saturation was evaluated. Going a step further, we used the combined evaporation and deposition rates to demonstrate the Wegener-Bergeron-Findeisen process occurrence. This study helps to better understand how microphysical processes act in different regimes. It additionally shows which processes play an important role and contribute to the phase-partitioning in low-level Arctic clouds. Therefore, these processes can be better targeted for improvements in the model that aim to better represent the phase-partitioning of Arctic low-level mixed-phase clouds.
