Ice Collisions Research Articles

Dynamics of acoustically levitated ice impacts on smooth and textured surfaces: Effects of surface roughness, elasticity, and structure

Atmospheric ice collisions on exposed outdoor infrastructure are a rarely explored surface design challenge. A primary obstacle to realistic ice particles in the laboratory setting is freezing a droplet without a solid surface present and then allowing it to impact a substrate without physical intervention. Using acoustically levitated ice formation with subsequent release onto a controlled area, a third class of ice-countering system called “ice-impacting” is introduced. Stainless steel 316 (SS), epoxy resin-coated (ER), and laser-textured (LT) surfaces with known surface roughness, hardness, and structural characteristics were subjected to 40 ice droplet impacts each. The impact effect on surface properties and the effect of these properties on solid-solid interfacial impact dynamics, in turn, were examined using an analysis framework based on fundamental conservation laws. Elasticity was the most significant factor in droplet behaviour as the ER surface exhibited rebounding for 78 % of impacts, nearly double the rates of the stainless steel surfaces. However, surface roughness also played a role, particularly for droplets with rotational motion, as immobilization occurred for 66 % of impacts on the rougher LT surface. Moreover, the nanostructures on that textured surface resulted in droplet redirection perpendicular to the surface directionality. In contrast, the other surfaces experienced no consistent change in rebound angle. Elasticity also affected momentum retention: the ER surface had a translational restitution coefficient of 0.32 compared to 0.17 for the SS/LT surfaces. Surface roughness was a predominant aspect of energy retention, as the LT surface had a translational-to-rotational energy transfer coefficient of 0.07 (0.23 for the smoother surfaces), resulting in an overall energy retention coefficient of 0.09 compared to 0.28 for the SS and ER surfaces on average. The results show that the interplay between elasticity, roughness, and structure at a dynamic solid-solid interface must be considered to optimize their effectiveness when designing ice-countering surfaces.

Influence of Propeller–Ice Loads on the Wear Development in Stern Tube Bearings of Marine Propulsion Systems and Identification of Critical Operating Conditions

Abstract Increasing ship traffic in ice-covered waters leads to more frequent collisions between ship propellers and sea ice which causes extreme impulse loads on the propeller. These loads are transferred through the propeller shaft to the sliding bearings of the stern tube, especially, the aft stern tube bearings. Extreme bearing loads can lead to mixed friction regimes that cause wear in the bearings and eventually result in a failure of the entire propulsion system. The effect of ice-induced loads on the contact conditions in the sliding bearings is widely unknown. Thus, a study of the influence of these loads on the contact conditions and wear behavior in stern tube bearings resulting from observed sea ice conditions and operating conditions of the ship is necessary. This article aims to investigate the influence of ice collision loads on the contact conditions in the bearings of the stern tube of the research vessel SA Agulhas II. For this purpose, an elastohydrodynamic simulation and a multibody simulation based on field measurements were performed. As a result, this article identifies the operating condition thresholds (i.e., propeller torque and rotational speed) during propeller–ice collisions that cause mixed friction conditions in the bearings. On the basis of these conditions, a risk map is generated to assess the actual wear risk by including the frequency of occurrence of the corresponding mixed friction condition over the duration of a voyage.

Secondary Ice Production in Simulated Deep Convective Clouds: A Sensitivity Study

Abstract Multiple mechanisms have been proposed to explain secondary ice production (SIP), and SIP has been recognized to play a vital role in forming cloud ice crystals. However, most weather and climate models do not consider SIP in their cloud microphysical schemes. In this study, in addition to the default rime splintering (RS) process, two SIP processes, namely, shattering/fragmentation during freezing of supercooled rain/drizzle drops (DS) and breakup upon ice–ice collisions (BR), were implemented into a two-moment cloud microphysics scheme. Besides, two different parameterization schemes for BR were introduced. A series of sensitivity experiments were performed to investigate how SIP impacts cloud microphysics and cloud phase distributions in warm-based deep convective clouds developed in the central part of Europe. Simulation results revealed that cloud microphysical properties were significantly influenced by the SIP processes. Ice crystal number concentrations (ICNCs) increased up to more than 20 times and surface precipitation was reduced by up to 20% with the consideration of SIP processes. Interestingly, BR was found to dominate SIP, and the BR process rate was larger than the RS and DS process rates by four and three orders of magnitude, respectively. Liquid pixel number fractions inside clouds and at the cloud top decreased when implementing all three SIP processes, but the decrease depended on the BR scheme. Peak values of ice enhancement factors (IEFs) in the simulated deep convective clouds were 102–104 and located at −24°C with the consideration of all three SIP processes, while the temperature dependency of IEF was sensitive to the BR scheme. However, if only RS or RS and DS processes were included, the IEFs were comparable, with peak values of about 6, located at −7°C. Moreover, switching off the cascade effect led to a remarkable reduction in ICNCs and ice crystal mass mixing ratios. Significance Statement The cloud phase is found to have a significant impact on cloud evolution, radiative properties, and precipitation formation. However, the simulation of the cloud phase is a big challenge for cloud research because multiple processes are not well described or missing in numerical models. In this study, we implemented two secondary ice production (SIP) processes, namely, shattering/fragmentation during the freezing of supercooled rain/drizzle drops and breakup upon ice–ice collisions, which are missing in most numerical models. Sensitivity experiments were conducted to investigate how SIP impacts cloud microphysics and cloud phase in deep convective clouds. We found that SIP significantly impacts in-cloud and cloud-top phase distribution. We also identified that the collisional breakup of ice particles is the dominant SIP process in the simulated deep convective clouds.

Interaction between ice cover and floating platform simulated by dilated-polyhedron-based DEM

This study presents a dilated-polyhedron-based discrete element method (DPDEM) aimed at investigating the interaction between the self-propelled ice-resistant platform (IRSPP) and drifting sea ice. The IRSPP is treated as a rigid body anchored by a mooring system, providing six degrees of freedom (6-DOF) in translations and rotations. The simulation of the ice-IRSPP interaction utilizes the DPDEM, incorporating contact forces and bond-failure criteria to account for sea ice collisions and fractures, respectively. To address disparities between DEM sea ice and actual sea ice, as well as the random nature of fracture and fragmentation following IRSPP interaction, an analysis of the dimensional independence of DEM calculation elements is conducted. Additionally, the validity of DEM parameters is assessed by comparing the numerical ice resistance of various previous icebreakers with the Lindqvist formula. Then, the time history of structural ice forces, ice heeling moments, and platform motion responses under varying ice floe thicknesses are investigated. Furthermore, the influences of sea ice conditions on ice load and the value of the ice heeling moment for the IRSPP are analyzed.

Aerosol and dynamical contributions to cloud droplet formation in Arctic low-level clouds

Abstract. The Arctic is one of the most rapidly warming regions of the globe. Low-level clouds and fog modify the energy transfer from and to space and play a key role in the observed strong Arctic surface warming, a phenomenon commonly termed “Arctic amplification”. The response of low-level clouds to changing aerosol characteristics throughout the year is therefore an important driver of Arctic change that currently lacks sufficient constraints. As such, during the NASCENT campaign (Ny-Ålesund AeroSol Cloud ExperimeNT) extending over a full year from October 2019 to October 2020, microphysical properties of aerosols and clouds were studied at the Zeppelin station (475 m a.s.l.), Ny-Ålesund, Svalbard, Norway. Particle number size distributions obtained from differential mobility particle sizers as well as chemical composition derived from filter samples and an aerosol chemical speciation monitor were analyzed together with meteorological data, in particular vertical wind velocity. The results were used as input to a state-of-the-art cloud droplet formation parameterization to investigate the particle sizes that can activate to cloud droplets, the levels of supersaturation that can develop, the droplet susceptibility to aerosol and the role of vertical velocity. We evaluate the parameterization and the droplet numbers calculated through a droplet closure with in-cloud in situ measurements taken during nine flights over 4 d. A remarkable finding is that, for the clouds sampled in situ, closure is successful in mixed-phase cloud conditions regardless of the cloud glaciation fraction. This suggests that ice production through ice–ice collisions or droplet shattering may have explained the high ice fraction, as opposed to rime splintering that would have significantly reduced the cloud droplet number below levels predicted by warm-cloud activation theory. We also show that pristine-like conditions during fall led to clouds that formed over an aerosol-limited regime, with high levels of supersaturation (generally around 1 %, although highly variable) that activate particles smaller than 20 nm in diameter. Clouds formed in the same regime in late spring and summer, but aerosol activation diameters were much larger due to lower cloud supersaturations (ca. 0.5 %) that develop because of higher aerosol concentrations and lower vertical velocities. The contribution of new particle formation to cloud formation was therefore strongly limited, at least until these newly formed particles started growing. However, clouds forming during the Arctic haze period (winter and early spring) can be limited by updraft velocity, although rarely, with supersaturation levels dropping below 0.1 % and generally activating larger particles (20 to 200 nm), including pollution transported over a long range. The relationship between updraft velocity and the limiting cloud droplet number agrees with previous observations of various types of clouds worldwide, which supports the universality of this relationship.

A bin microphysics parcel model investigation of secondary ice formation in an idealised shallow convective cloud

Abstract. We provide the first systematic study of ice formation in idealised shallow clouds from collisions of supercooled water drops with ice particles (mode 2). Using the University of Manchester bin microphysics parcel model, we investigated the sensitivity of ice formation due to mode 2 for a wide range of parameters, including aerosol particle size distribution, updraft speed, cloud-base temperature, cloud depth, ice-nucleating particle concentration, and freezing fraction of mode 2. We provide context to our results with other secondary ice production mechanisms as single mechanisms and combinations (rime splintering, spherical freezing fragmentation of drops (mode 1), and ice–ice collisions). There was a significant sensitivity to aerosol particle size distribution when updraft speeds were low (0.5 m s−1); secondary ice formation did not occur when the aerosol particle size distribution mimicked polluted environments. Where secondary ice formation did occur in simulated clouds, significant ice formation in the shallower clouds (1.3 km deep) was due to mode 2 or a combination which included mode 2. The deeper clouds (2.4 km deep) also had significant contributions from rime splintering or ice–ice collisional breakup secondary ice production (SIP) mechanisms. While simulations with cloud-base temperatures of 7 ∘C were relatively insensitive to ice-nucleating particle concentrations, there was a sensitivity in simulations with cloud-base temperatures of 0 ∘C. Increasing the ice-nucleating particle concentration delayed ice formation. Our results suggest that collisions of supercooled water drops with ice particles may be a significant ice formation mechanism within shallow convective clouds where rime splintering is not active.

Effects from Time Dependence of Ice Nucleus Activity for Contrasting Cloud Types

Abstract The role of time-dependent freezing of ice nucleating particles (INPs) is evaluated with the “Aerosol–Cloud” (AC) model in 1) deep convection observed over Oklahoma during the Midlatitude Continental Convective Cloud Experiment (MC3E), 2) orographic clouds observed over North California during the Atmospheric Radiation Measurement (ARM) Cloud Aerosol Precipitation Experiment (ACAPEX), and 3) supercooled, stratiform clouds over the United Kingdom, observed during the Aerosol Properties, Processes And Influences on the Earth’s climate (APPRAISE) campaign. AC uses the dynamical core of the WRF Model and has hybrid bin–bulk microphysics and a 3D mesoscale domain. AC is validated against coincident aircraft, ground-based, and satellite observations for all three cases. Filtered concentrations of ice (>0.1–0.2 mm) agree with those observed at all sampled levels. AC predicts the INP activity of various types of aerosol particles with an empirical parameterization (EP), which follows a singular approach (no time dependence). Here, the EP is modified to represent time-dependent INP activity by a purely empirical approach, using our published laboratory observations of time-dependent INP activity. In all simulated clouds, the inclusion of time dependence increases the predicted INP activity of mineral dust particles by 0.5–1 order of magnitude. However, there is little impact on the cloud glaciation because the total ice is mostly (80%–90%) from secondary ice production (SIP) at levels warmer than about −36°C. The Hallett–Mossop process and fragmentation in ice–ice collisions together initiate about 70% of the total ice, whereas fragmentation during both raindrop freezing and sublimation contributes <10%. Overall, total ice concentrations and SIP are unaffected by time-dependent INP activity. In the simulated APPRAISE case, the main causes of persistence of long-lived clouds and precipitation are predicted to be SIP in weak embedded convection and reactivation following recirculation of dust particles in supercooled layer cloud.

Conditions favorable for secondary ice production in Arctic mixed-phase clouds

Abstract. The Arctic is very susceptible to climate change and thus is warming much faster than the rest of the world. Clouds influence terrestrial and solar radiative fluxes and thereby impact the amplified Arctic warming. The partitioning of thermodynamic phases (i.e., ice crystals and water droplets) within mixed-phase clouds (MPCs) especially influences their radiative properties. However, the processes responsible for ice crystal formation remain only partially characterized. In particular, so-called secondary ice production (SIP) processes, which create supplementary ice crystals from primary ice crystals and the environmental conditions that they occur in, are poorly understood. The microphysical properties of Arctic MPCs were measured during the Ny-Ålesund AeroSol Cloud ExperimENT (NASCENT) campaign to obtain a better understanding of the atmospheric conditions favorable for the occurrence of SIP processes. To this aim, the in situ cloud microphysical properties retrieved by a holographic cloud imager mounted on a tethered balloon system were complemented by ground-based remote sensing and ice-nucleating particle measurements. During the 6 d investigated in this study, SIP occurred during about 40 % of the in-cloud measurements, and high SIP events with number concentrations larger than 10 L−1 of small pristine ice crystals occurred in 4 % of the in-cloud measurements. This demonstrates the role of SIP for Arctic MPCs. The highest concentrations of small pristine ice crystals were produced at temperatures between −5 and −3 ∘C and were related to the occurrence of supercooled large droplets freezing upon collision with ice crystals. This suggests that a large fraction of ice crystals in Arctic MPCs are produced via the droplet-shattering mechanism. From evaluating the ice crystal images, we could identify ice–ice collision as a second SIP mechanism that dominated when fragile ice crystals were observed. Moreover, SIP occurred over a large temperature range and was observed in up to 80 % of the measurements down to −24 ∘C due to the occurrence of ice–ice collisions. This emphasizes the importance of SIP at temperatures below −8 ∘C, which are currently not accounted for in most numerical weather models. Although ice-nucleating particles may be necessary for the initial freezing of water droplets, the ice crystal number concentration is frequently determined by secondary production mechanisms.

Dependencies of Four Mechanisms of Secondary Ice Production on Cloud-Top Temperature in a Continental Convective Storm

Abstract Various mechanisms of secondary ice production (SIP) cause multiplication of numbers of ice particle, after the onset of primary ice. A measure of SIP is the ice enhancement ratio (“IE ratio”) defined here as the ratio between number concentrations of total ice (excluding homogeneously nucleated ice) and active ice-nucleating particles (INPs). A convective line observed on 11 May 2011 over the Southern Great Plains in the Mesoscale Continental Convective Cloud Experiment (MC3E) campaign was simulated with the “Aerosol–Cloud” (AC) model. AC is validated against coincident MC3E observations by aircraft, ground-based instruments, and satellite. Four SIP mechanisms are represented in AC: the Hallett–Mossop (HM) process of rime splintering, and fragmentation during ice–ice collisions, raindrop freezing, and sublimation. The vertical profile of the IE ratio, averaged over the entire simulation, is almost uniform (102 to 103) because fragmentation in ice–ice collisions dominates at long time scales, driving the ice concentration toward a theoretical maximum. The IE ratio increases with both the updraft (HM process, fragmentation during raindrop freezing, and ice–ice collisions) and downdraft speed (fragmentation during ice–ice collisions and sublimation). As reported historically in aircraft sampling, IE ratios were predicted to peak near 103 for cloud-top temperatures close to the −12°C level, mostly due to the HM process in typically young clouds with their age less than 15 min. At higher altitudes with temperatures of −20° to −30°C, the predicted IE ratios were smaller, ranging from 10 to 102, and mainly resulted from fragmentation in ice–ice collisions.

Estimation of ice loads on offshore structures using simulations of level ice-structure collisions with an influence coefficient method

During their service, ice-class vessels are exposed to ice collision loads. Precise estimation of such ice loads is essential to the design of ice-class vessels. Due to difficulties encountered in real measurement of ice loads, a simple yet logically straightforward method, namely the influence coefficient method (ICM), has been widely employed to convert strain data to ice pressures. However, the method's accuracy and reliability depend on how strain gauges are arranged and load cells are divided accordingly. This study investigated those aspects in order to enhance the accuracy and reliability of the ICM in estimating ice loads incurred in collisions of ice with offshore structures. It began by developing a numerical model of level ice-structure interactions. For this, an ice-material model applying the Drucker-Prager (DP) plasticity model combined with an element erosion technique's simplified damage mechanics was developed. The developed numerical model was verified by comparing its results with the relevant model test data and corresponding numerical results available in the open literature, and good agreement was achieved. Next, the present study performed, based on the numerical simulation strategy thus validated, simulations of level ice collisions with actual offshore structures showing inflexible and deformable behaviors. Subsequently, a finite element (FE) model of the structures’ instrumented area, which is the same as the scantling used in the ice collision simulation, was developed to construct an influence coefficient matrix for the ICM. The structural responses, including stress/strain data and ice-contact pressure observed numerically, were then applied to an investigation of the ICM capability. The effects of the strain gage arrangements and corresponding load cells on the estimation of the local ice pressures acting on actual offshore structures were demonstrated. The proposed procedure is expected to provide insights into how the ICM can be improved in reliably and cost-effectively estimating ice loads on ice-class offshore structures.

Microphysical processes producing high ice water contents (HIWCs) in tropical convective clouds during the HAIC-HIWC field campaign: dominant role of secondary ice production

Abstract. High ice water content (HIWC) regions in tropical deep convective clouds, composed of high concentrations of small ice crystals, were not reproduced by Weather Research and Forecasting (WRF) model simulations at 1 km horizontal grid spacing using four different bulk microphysics schemes (i.e., the WRF single‐moment 6‐class microphysics scheme (WSM6), the Morrison scheme and the Predicted Particle Properties (P3) scheme with one- and two-ice options) for conditions encountered during the High Altitude Ice Crystals (HAIC) and HIWC experiment. Instead, overestimates of radar reflectivity and underestimates of ice number concentrations were realized. To explore formation mechanisms for large numbers of small ice crystals in tropical convection, a series of quasi-idealized WRF simulations varying the model resolution, aerosol profile, and representation of secondary ice production (SIP) processes are conducted based on an observed radiosonde released at Cayenne during the HAIC-HIWC field campaign. The P3 two-ice category configuration, which has two “free” ice categories to represent all ice-phase hydrometeors, is used. Regardless of the horizontal grid spacing or aerosol profile used, without including SIP processes the model produces total ice number concentrations about 2 orders of magnitude less than observed at −10 ∘C and about an order of magnitude less than observed at −30 ∘C but slightly overestimates the total ice number concentrations at −45 ∘C. Three simulations including one of three SIP mechanisms separately (i.e., the Hallett–Mossop mechanism, fragmentation during ice–ice collisions, and shattering of freezing droplets) also do not replicate observed HIWCs, with the results of the simulation including shattering of freezing droplets most closely resembling the observations. The simulation including all three SIP processes produces HIWC regions at all temperature levels, remarkably consistent with the observations in terms of ice number concentrations and radar reflectivity, which is not replicated using the original P3 two-ice category configuration. This simulation shows that primary ice production plays a key role in generating HIWC regions at temperatures <-40 ∘C, shattering of freezing droplets dominates ice particle production in HIWC regions at temperatures between −15 and 0 ∘C during the early stage of convection, and fragmentation during ice–ice collisions dominates at temperatures between −15 and 0 ∘C during the later stage of convection and at temperatures between −40 and −20 ∘C over the whole convection period. This study confirms the dominant role of SIP processes in the formation of numerous small crystals in HIWC regions.

Evaluation of the COSMO model (v5.1) in polarimetric radar space – impact of uncertainties in model microphysics, retrievals and forward operators

Abstract. Sensitivity experiments with a numerical weather prediction (NWP) model and polarimetric radar forward operator (FO) are conducted for a long-duration stratiform event over northwestern Germany to evaluate uncertainties in the partitioning of the ice water content and assumptions of hydrometeor scattering properties in the NWP model and FO, respectively. Polarimetric observations from X-band radar and retrievals of hydrometeor classifications are used for comparison with the multiple experiments in radar and model space. Modifying the critical diameter of particles for ice-to-snow conversion by aggregation (Dice) and the threshold temperature responsible for graupel production by riming (Tgr), was found to improve the synthetic polarimetric moments and simulated hydrometeor population, while keeping the difference in surface precipitation statistically insignificant at model resolvable grid scales. However, the model still exhibited a low bias (lower magnitude than observation) in simulated polarimetric moments at lower levels above the melting layer (−3 to −13 ∘C) where snow was found to dominate. This necessitates further research into the missing microphysical processes in these lower levels (e.g. fragmentation due to ice–ice collisions) and use of more reliable snow-scattering models to draw valid conclusions.

Comment on “Review of experimental studies of secondary ice production” by Korolev and Leisner (2020)

Abstract. This is a comment on the review by Korolev and Leisner (2020, hereafter KL2020). The only two laboratory/field studies ever to measure the breakup in ice–ice collisions for in-cloud conditions were negatively criticised by KL2020, as were our subsequent theoretical and modelling studies informed by both studies. First, hypothetically, even without any further laboratory experiments, such theoretical and modelling studies would continue to be possible, based on classical mechanics and statistical physics. They are not sensitive to the accuracy of lab data for typical situations, partly because the nonlinear explosive growth of ice concentrations continues until some maximum concentration is reached. To a degree, the same final concentration is expected regardless of the fragment number per collision. Second, there is no evidence that both lab/field observational studies characterising fragmentation in ice–ice collisions are either mutually conflicting or erroneous such that they cannot be used to represent this breakup in numerical models, contrary to the review. The fact that the ice spheres of one experiment were hail sized (2 cm) is not a problem if a universal theoretical formulation, such as ours, with fundamental dependencies, is informed by it. Although both lab/field studies involved head-on collisions, rotational kinetic energy for all collisions generally is only a small fraction of the initial collision kinetic energy (CKE) anyway. Although both lab/field experiments involved fixed targets, that is not a problem since the fixing of the target is represented via CKE in any energy-based formulation such as ours. Finally, scaling analysis suggests that the breakup of ice during sublimation can make a significant contribution to ice enhancement in clouds, again contrary to the impression given by the review.

Ice multiplication from ice–ice collisions in the high Arctic: sensitivity to ice habit, rimed fraction, ice type and uncertainties in the numerical description of the process

Abstract. Atmospheric models often fail to correctly reproduce the microphysical structure of Arctic mixed-phase clouds and underpredict ice water content even when the simulations are constrained by observed levels of ice nucleating particles. In this study we investigate whether ice multiplication from breakup upon ice–ice collisions, a process missing in most models, can account for the observed cloud ice in a stratocumulus cloud observed during the Arctic Summer Cloud Ocean Study (ASCOS) campaign. Our results indicate that the efficiency of this process in these conditions is weak; increases in fragment generation are compensated for by subsequent enhancement of precipitation and subcloud sublimation. Activation of collisional breakup improves the representation of cloud ice content, but cloud liquid remains overestimated. In most sensitivity simulations, variations in ice habit and prescribed rimed fraction have little effect on the results. A few simulations result in explosive multiplication and cloud dissipation; however, in most setups, the overall multiplication effects become substantially weaker if the precipitation sink is enhanced through cloud-ice-to-snow autoconversion. The largest uncertainty stems from the correction factor for ice enhancement due to sublimation included in the breakup parameterization; excluding this correction results in rapid glaciation, especially in simulations with plates. Our results indicate that the lack of a detailed treatment of ice habit and rimed fraction in most bulk microphysics schemes is not detrimental for the description of the collisional breakup process in the examined conditions as long as cloud-ice-to-snow autoconversion is considered.

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

Abstract. 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 including 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 were 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 generating cells (convective overshooting, radiative cooling, droplet shattering) and attempt to estimate their potential contribution from an ice nucleating particle perspective. Once ice formation and growth within the seeder region exceeded a threshold value, the mixed-phase cloud became fully glaciated. Local flow effects on the lee side of the mountain barrier induced the formation of a persistent low-level feeder cloud over a small-scale topographic feature in the inner-Alpine valley. In situ measurements within the low-level feeder cloud observed the production of secondary ice particles likely due to the Hallett–Mossop process and ice particle fragmentation upon ice–ice collisions. Therefore, secondary ice production may have been partly responsible for the elevated ice crystal number concentrations that have been previously observed in feeder clouds at mountaintop observatories. Secondary ice production in feeder clouds can potentially enhance orographic precipitation.

A numerical solver for coupled dynamic simulation of glacial ice impacts considering hydrodynamic-ice-structure interaction

Glacial ice features pose great threats on the safety of ships and offshore structures in the arctic. House sized bergy bits or growlers are of particular concern because of the detection capability limits of marine radars. Analysis and design of structures against collisions from such glacial ice bodies has always been challenging due to the complicated hydrodynamic-ice-structure interaction.This paper proposes a numerical solver for coupled simulation of glacial ice impacts accounting for the effects of hydrodynamic-ice-structure interaction. The solver adopts user subroutines provided in LS-DYNA and combines three different modules, i.e. the BWH (Bressan-Williams-Hill) criterion for the prediction of fracture of steels, a hydrostatic pressure dependent plasticity-based material model for constitutive modelling of ice, and the linear potential flow theory for hydrodynamic loads.The proposed solver is verified and calibrated to ice resistance data from field tests and is then applied to simulate ice collisions on a semi-submersible platform column. Collision scenarios with both in-plane 3DOF and full 6DOF ice motions are considered. The results are discussed with respect to ice motion trajectories, ice crushing and structural damage under the combined action of ice indentation and sliding loads. The dissipated energy predicted by external dynamic models is compared with simulation results and discussed.

Multiple Environmental Influences on the Lightning of Cold-Based Continental Cumulonimbus Clouds. Part I: Description and Validation of Model

AbstractIn this two-part paper, influences from environmental factors on lightning in a convective storm are assessed with a model. In Part I, an electrical component is described and applied in the Aerosol–Cloud model (AC). AC treats many types of secondary (e.g., breakup in ice–ice collisions, raindrop-freezing fragmentation, rime splintering) and primary (heterogeneous, homogeneous freezing) ice initiation. AC represents lightning flashes with a statistical treatment of branching from a fractal law constrained by video imagery.The storm simulated is from the Severe Thunderstorm Electrification and Precipitation Study (STEPS; 19/20 June 2000). The simulation was validated microphysically [e.g., ice/droplet concentrations and mean sizes, liquid water content (LWC), reflectivity, surface precipitation] and dynamically (e.g., ascent) in our 2017 paper. Predicted ice concentrations (~10 L−1) agreed—to within a factor of about 2—with aircraft data at flight levels (−10° to −15°C). Here, electrical statistics of the same simulation are compared with observations. Flash rates (to within a factor of 2), triggering altitudes and polarity of flashes, and electric fields, all agree with the coincident STEPS observations.The “normal” tripole of charge structure observed during an electrical balloon sounding is reproduced by AC. It is related to reversal of polarity of noninductive charging in ice–ice collisions seen in laboratory experiments when temperature or LWC are varied. Positively charged graupel and negatively charged snow at most midlevels, charged away from the fastest updrafts, is predicted to cause the normal tripole. Total charge separated in the simulated storm is dominated by collisions involving secondary ice from fragmentation in graupel–snow collisions.

Experimental Study of Sea Ice Motion in Waves

Abstract To better understand the interactions between ships and ice, analyze ice–ice collisions, and provide parameters for the design of ships and offshore structures, it is important to study th...

Establishment and Verification of a Constitutive Model of Ice Material Considering the Effect of Temperature

The increase in global warming has secured the arctic region as a research hotspot, and the existence of ice floes and massive icebergs poses a great challenge to the navigational safety of polar ships. For the finite simulation of ship–ice collisions, a reasonable description of the ice constitutive model is the most important factor for the accuracy of ice load prediction and structural deformation assessment. Due to the complex physical properties of natural sea ice materials, there are still many difficulties in achieving a widely accepted ice material model. In this paper, a constitutive model of ice material considering the influence of temperature is established and embedded into finite element software LS-DYNA, and the material property parameters are validated and analyzed. Then, the drop test in a published paper is recapitulated by the numerical simulation with the proposed method, and the results are compared. Good agreement is attained between the numerical simulation and published results. The influences of temperature and drop height are discussed, and the results show that both of them have an important effect on structural deformation. The research results can be used for ice load prediction and polar ship structure design.

The impact of secondary ice production on Arctic stratocumulus

Abstract. In situ measurements of Arctic clouds frequently show that ice crystal number concentrations (ICNCs) are much higher than the number of available ice-nucleating particles (INPs), suggesting that secondary ice production (SIP) may be active. Here we use a Lagrangian parcel model (LPM) and a large-eddy simulation (LES) to investigate the impact of three SIP mechanisms (rime splintering, break-up from ice–ice collisions and drop shattering) on a summer Arctic stratocumulus case observed during the Aerosol-Cloud Coupling And Climate Interactions in the Arctic (ACCACIA) campaign. Primary ice alone cannot explain the observed ICNCs, and drop shattering is ineffective in the examined conditions. Only the combination of both rime splintering (RS) and collisional break-up (BR) can explain the observed ICNCs, since both of these mechanisms are weak when activated alone. In contrast to RS, BR is currently not represented in large-scale models; however our results indicate that this may also be a critical ice-multiplication mechanism. In general, low sensitivity of the ICNCs to the assumed INP, to the cloud condensation nuclei (CCN) conditions and also to the choice of BR parameterization is found. Finally, we show that a simplified treatment of SIP, using a LPM constrained by a LES and/or observations, provides a realistic yet computationally efficient way to study SIP effects on clouds. This method can eventually serve as a way to parameterize SIP processes in large-scale models.