No evidence for a productive Hallett-Mossop process so far

2021 ◽  
Author(s):  
Susan Hartmann ◽  
Alice Keinert ◽  
Alexei Kiselev ◽  
Johanna Seidel ◽  
Frank Stratmann
Keyword(s):  
High Speed ◽  
Particle Number ◽  
Essential Elements ◽  
Number Concentration ◽  
Mixed Phase ◽  
Measuring System ◽  
Sugar Solution ◽  
Particle Number Concentration ◽  
Ice Particles ◽  
Mixed Phase Clouds

<p>Mixed-phase clouds are essential elements in Earth’s weather and climate system. Atmospheric observation of mixed-phase clouds occasionally demonstrated a strong discrepancy between the observed ice particle and ice nucleating particle number concentration of one to four orders of magnitude at modest supercooling [1-3, 5, 7]. Different secondary ice production (SIP) mechanisms have been hypothesized which can increase the total ice particle number concentration by multiplication of primary ice particles and hence might explain the observed discrepancy [2, 4, 6].</p> <p>In this study we focus on SIP as a result of droplet-ice collisions, commonly known as Hallett-Mossop [9] or rime-splintering process. Our main objectives are (i) to quantify secondary ice particles and (ii) to learn more about the underlying physics. Therefore, we develop a new experimental set-up (Ice Droplets splintEring on FreezIng eXperiment, IDEFIX) in which quasi-monodisperse supercooled droplets collide with a fixed ice particle. IDEFIX is designed to simulate atmospheric relevant conditions such as temperature, humidity, impact velocities and collision rates. The riming process is observed with high-speed video microscopy and an infrared measuring system. Further, the produced secondary ice particles are counted via impaction on a supercooled sugar solution. Preliminary results from a first measurement campaign suggest that we observed single SIP events but did not found evidence for a productive Hallett-Mossop process so far.  We plan to continue with rime-splintering experiment in order to gain better statistics and to expand the parameter space (e.g., droplet size distribution).</p> <p>[1] Crosier, J., et al. 2011, DOI: 10.5194/acp-11-257-2011.</p> <p>[2] Field, P.R., et al. 2016, DOI: 10.1175/amsmonographs-d-16-0014.1.</p> <p>[3] Hogan, R.J., et al. 2002, DOI: 10.1256/003590002321042054.</p> <p>[4] Korolev, A. and T. Leisner 2020, DOI: 10.5194/acp-20-11767-2020.</p> <p>[5] Mossop, S.C. 1985, DOI: 10.1175/1520-0477(1985)066<0264:toacoi>2.0.co;2.</p> <p>[6] Sotiropoulou, G., et al. 2020, DOI: 10.5194/acp-20-1301-2020.</p> <p>[7] Taylor, J.W., et al. 2016, DOI: 10.5194/acp-16-799-2016.</p>

Secondary Ice Production – development of a new experimental set-up

2021 ◽  
Author(s):  
Susan Hartmann ◽  
Alice Keinert ◽  
Alexei Kiselev ◽  
Frank Stratmann
Keyword(s):  
Particle Number ◽  
Number Concentration ◽  
Mixed Phase ◽  
Sugar Solution ◽  
Particle Number Concentration ◽  
Ice Particles ◽  
Thin Carbon ◽  
Set Up ◽  
Ice Production ◽  
Mixed Phase Clouds

<p>Mixed-phase clouds are essential elements in Earth’s weather and climate system. Aircraft measurements of mixed-phase clouds demonstrated a strong discrepancy between the observed ice particle and ice nucleating particle number concentration of one to four orders of magnitude [1-4]. Different secondary ice production (SIP) mechanisms have been hypothesized which can increase the total ice particle number concentration by multiplication of primary ice particles and hence might explain the observed discrepancy [5-7].</p><p>In a joint project of KIT and Tropos, we focus on the investigation two SIP processes: shattering of large freezing droplets (KIT) and SIP as a result of droplet-ice collisions (Tropos), commonly known as Hallett-Mossop [9] or rime-splintering process. Thereby, we aim at a quantitative understanding of the SIP underlying physical mechanisms, utilizing a newly developed experimental set-up (Ice Droplets splintEring on FreezIng eXperiment, IDEFIX).  </p><p>IDEFIX is based on a modular concept and consists of three modules, i.e., the SIP chamber, the growth section, and the ice particle detector. We developed two different versions of the SIP chamber: in the KIT-SIP chamber a freezing drizzle droplet is levitated in electrodynamic balance; and in the TROPOS-SIP chamber quasi-monodisperse droplets collide with an ice particle which is fixed on thin carbon fibers. IDEFIX is designed to match realistic fall or impact velocities and collision rates of the droplets with the ice particle. The SIP process will be observed with high-speed video microscopy and an infrared measuring system. In the growth section, which features supersaturated conditions with respect to ice, the presumably small secondarily produced ice particles will be grown to detectable sizes. Finally, to count the number of secondarily produced ice particles either an optical particle spectrometer will be used for distinguishing between droplets and ice particles, or the ice particles will be impacted on a metastable sugar solution. Currently, we characterize velocity, temperature and humidity fields of the TROPOS-collision chamber and determine droplet-ice particle collision rates.</p>

The microphysical characters of wintertime mixed-phase clouds in North China.

2021 ◽  
Author(s):  
Xuexu Wu ◽  
Minghuai Wang ◽  
Daniel Rosenfeld ◽  
Delong Zhao ◽  
Deping Ding
Keyword(s):  
Water Content ◽  
North China ◽  
Particle Number ◽  
Number Concentration ◽  
Mixed Phase ◽  
Ice Crystals ◽  
Particle Number Concentration ◽  
Aggregation Process ◽  
Higher Temperature ◽  
Mixed Phase Clouds

<p>We use aircraft observation data to investigate the microphysical characters of wintertime mixed-phase clouds in North China, including the cloud particle number concentration (N<sub>c</sub>), the liquid water content (LWC), the ice particle number concentration (N<sub>i</sub>), the ice water content (IWC), the particle spectrum distributions (PSDs) and the effective diameter (D<sub>e</sub>). For wintertime mixed-phase clouds, the average N<sub>c</sub> and N<sub>i</sub> were 170±154 cm<sup>-3</sup> and 26±39 L<sup>-1</sup>, respectively; the average LWC and IWC were 0.05±0.06 and 0.07±0.09g/m<sup>3</sup>, respectively; the D<sub>e</sub> for cloud particles was 10±4 μm. When compared to the results from other regions, including East Europe, North America, Southern Ocean and Tibetan Plateau, we found that the wintertime mixed-phase cloud in North China has larger N<sub>c</sub>, smaller LWC, IWC and D<sub>e</sub>, and narrower PSDs. The main reason might be the larger aerosol loading and smaller water content in the atmosphere in winter in North China. With increasing temperature, N<sub>c</sub> and LWC increased, but N<sub>i</sub> and D<sub>e</sub> decreased. The dominate physical processes in wintertime mixed-phase cloud were aggregation process and riming process. As the temperature increased, the peak concentration of ice PSD decreased, but N<sub>i</sub> increased and the ice PSD became wider, indicating more ice crystals and the ice crystals became larger at higher temperature. With temperature increasing, the ice habit also changed, and the amount of plates, irregular crystals and their aggregates increased. What’s more, with the existence of larger LWC at higher temperature, the ice crystals gradually tightened and their surface became more complicated as well. Therefore, both aggregation process and riming process were more active at higher temperature, but riming process changed much more. This work fills the gap in the observation of wintertime mixed-phase clouds in north China, and the results suggest that the wintertime mixed-phase clouds have some unique microphysical characters.</p><div> </div>

Impact of Urban Pollution on Organic-Mediated New-Particle Formation and Particle Number Concentration in the Amazon Rainforest

2021 ◽  
Vol 55 (8) ◽  
pp. 4357-4367
Author(s):  
Bin Zhao ◽  
Jerome D. Fast ◽  
Neil M. Donahue ◽  
Manish Shrivastava ◽  
Meredith Schervish ◽  
...  
Keyword(s):  
Particle Number ◽  
Urban Pollution ◽  
Particle Formation ◽  
Number Concentration ◽  
Amazon Rainforest ◽  
Particle Number Concentration ◽  
New Particle Formation

scholarly journals Modeling particle nucleation and growth over northern California during the 2010 CARES campaign

2015 ◽  
Vol 15 (21) ◽  
pp. 12283-12313 ◽  
Author(s):  
A. Lupascu ◽  
R. Easter ◽  
R. Zaveri ◽  
M. Shrivastava ◽  
M. Pekour ◽  
...  
Keyword(s):  
Size Distribution ◽  
Particle Number ◽  
Particle Formation ◽  
Number Concentration ◽  
Aerosol Size Distribution ◽  
Particle Nucleation ◽  
Particle Number Concentration ◽  
New Particle Formation ◽  
Organic Vapors ◽  
Diurnal Variability

Abstract. Accurate representation of the aerosol lifecycle requires adequate modeling of the particle number concentration and size distribution in addition to their mass, which is often the focus of aerosol modeling studies. This paper compares particle number concentrations and size distributions as predicted by three empirical nucleation parameterizations in the Weather Research and Forecast coupled with chemistry (WRF-Chem) regional model using 20 discrete size bins ranging from 1 nm to 10 μm. Two of the parameterizations are based on H2SO4, while one is based on both H2SO4 and organic vapors. Budget diagnostic terms for transport, dry deposition, emissions, condensational growth, nucleation, and coagulation of aerosol particles have been added to the model and are used to analyze the differences in how the new particle formation parameterizations influence the evolving aerosol size distribution. The simulations are evaluated using measurements collected at surface sites and from a research aircraft during the Carbonaceous Aerosol and Radiative Effects Study (CARES) conducted in the vicinity of Sacramento, California. While all three parameterizations captured the temporal variation of the size distribution during observed nucleation events as well as the spatial variability in aerosol number, all overestimated by up to a factor of 2.5 the total particle number concentration for particle diameters greater than 10 nm. Using the budget diagnostic terms, we demonstrate that the combined H2SO4 and low-volatility organic vapor parameterization leads to a different diurnal variability of new particle formation and growth to larger sizes compared to the parameterizations based on only H2SO4. At the CARES urban ground site, peak nucleation rates are predicted to occur around 12:00 Pacific (local) standard time (PST) for the H2SO4 parameterizations, whereas the highest rates were predicted at 08:00 and 16:00 PST when low-volatility organic gases are included in the parameterization. This can be explained by higher anthropogenic emissions of organic vapors at these times as well as lower boundary-layer heights that reduce vertical mixing. The higher nucleation rates in the H2SO4-organic parameterization at these times were largely offset by losses due to coagulation. Despite the different budget terms for ultrafine particles, the 10–40 nm diameter particle number concentrations from all three parameterizations increased from 10:00 to 14:00 PST and then decreased later in the afternoon, consistent with changes in the observed size and number distribution. We found that newly formed particles could explain up to 20–30 % of predicted cloud condensation nuclei at 0.5 % supersaturation, depending on location and the specific nucleation parameterization. A sensitivity simulation using 12 discrete size bins ranging from 1 nm to 10 μm diameter gave a reasonable estimate of particle number and size distribution compared to the 20 size bin simulation, while reducing the associated computational cost by ~ 36 %.

scholarly journals Measurement of nonvolatile particle number size distribution

2016 ◽  
Vol 9 (1) ◽  
pp. 103-114 ◽  
Author(s):  
G. I. Gkatzelis ◽  
D. K. Papanastasiou ◽  
K. Florou ◽  
C. Kaltsonoudis ◽  
E. Louvaris ◽  
...  
Keyword(s):  
Size Distribution ◽  
Black Carbon ◽  
Biomass Burning ◽  
Particle Number ◽  
Number Concentration ◽  
Experimental Methodology ◽  
Particle Number Concentration ◽  
Scanning Mobility Particle Sizer ◽  
Number Size Distribution ◽  
Particle Sizer

Abstract. An experimental methodology was developed to measure the nonvolatile particle number concentration using a thermodenuder (TD). The TD was coupled with a high-resolution time-of-flight aerosol mass spectrometer, measuring the chemical composition and mass size distribution of the submicrometer aerosol and a scanning mobility particle sizer (SMPS) that provided the number size distribution of the aerosol in the range from 10 to 500 nm. The method was evaluated with a set of smog chamber experiments and achieved almost complete evaporation (> 98 %) of secondary organic as well as freshly nucleated particles, using a TD temperature of 400 °C and a centerline residence time of 15 s. This experimental approach was applied in a winter field campaign in Athens and provided a direct measurement of number concentration and size distribution for particles emitted from major pollution sources. During periods in which the contribution of biomass burning sources was dominant, more than 80 % of particle number concentration remained after passing through the thermodenuder, suggesting that nearly all biomass burning particles had a nonvolatile core. These remaining particles consisted mostly of black carbon (60 % mass contribution) and organic aerosol (OA; 40 %). Organics that had not evaporated through the TD were mostly biomass burning OA (BBOA) and oxygenated OA (OOA) as determined from AMS source apportionment analysis. For periods during which traffic contribution was dominant 50–60 % of the particles had a nonvolatile core while the rest evaporated at 400 °C. The remaining particle mass consisted mostly of black carbon with an 80 % contribution, while OA was responsible for another 15–20 %. Organics were mostly hydrocarbon-like OA (HOA) and OOA. These results suggest that even at 400 °C some fraction of the OA does not evaporate from particles emitted from common combustion processes, such as biomass burning and car engines, indicating that a fraction of this type of OA is of extremely low volatility.

scholarly journals Predicting the morphology of ice particles in deep convection using the super-droplet method: development and evaluation of SCALE-SDM 0.2.5-2.2.0, -2.2.1, and -2.2.2

2020 ◽  
Vol 13 (9) ◽  
pp. 4107-4157 ◽  
Author(s):  
Shin-ichiro Shima ◽  
Yousuke Sato ◽  
Akihiro Hashimoto ◽  
Ryohei Misumi
Keyword(s):  
Method Development ◽  
Cloud Condensation Nuclei ◽  
Deep Convection ◽  
Cloud Microphysics ◽  
Mixed Phase ◽  
Computational Time ◽  
Ice Particles ◽  
Mass Dimension ◽  
Mixed Phase Clouds ◽  
Droplet Method

Abstract. The super-droplet method (SDM) is a particle-based numerical scheme that enables accurate cloud microphysics simulation with lower computational demand than multi-dimensional bin schemes. Using SDM, a detailed numerical model of mixed-phase clouds is developed in which ice morphologies are explicitly predicted without assuming ice categories or mass–dimension relationships. Ice particles are approximated using porous spheroids. The elementary cloud microphysics processes considered are advection and sedimentation; immersion/condensation and homogeneous freezing; melting; condensation and evaporation including cloud condensation nuclei activation and deactivation; deposition and sublimation; and coalescence, riming, and aggregation. To evaluate the model's performance, a 2-D large-eddy simulation of a cumulonimbus was conducted, and the life cycle of a cumulonimbus typically observed in nature was successfully reproduced. The mass–dimension and velocity–dimension relationships the model predicted show a reasonable agreement with existing formulas. Numerical convergence is achieved at a super-particle number concentration as low as 128 per cell, which consumes 30 times more computational time than a two-moment bulk model. Although the model still has room for improvement, these results strongly support the efficacy of the particle-based modeling methodology to simulate mixed-phase clouds.

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