Ice Particles Research Articles

The proposed mechanism of glow of mesosphere clouds

The question of the physical mechanism of electromagnetic radiation scattering by mesospheric (noctilucent) clouds is considered. A hypothesis has been expressed about the special electromagnetic characteristics of nanometer-sized ice particles that make up mesospheric clouds. Particle ice consists of a recently discovered crystalline modification of water — ice 0, formed by the condensation of vapor on dust particles at temperatures of –140…–23°C. Ice 0 is a ferroelectric, and upon contact with a dielectric, a layer with high electrical conductivity is formed. Due to plasmon resonance in nanosized layers, strong scattering of electromagnetic radiation occurs over a wide frequency range. This mechanism causes the glow of noctilucent clouds when illuminated by the radiation of the Sun.

Contribution of blowing-snow sublimation to the surface mass balance of Antarctica

Abstract. Blowing-snow sublimation is a key boundary layer process in polar regions and is the major ablation term in the surface mass balance (SMB) of the Antarctic ice sheet. This study updates the blowing-snow model in the Regional Atmospheric Climate Model (RACMO), version 2.3p3, incorporating blowing-snow sublimation into the prognostic equations for temperature and water vapour. These updates address numerical artefacts in the previous model version by replacing the uniformly discretised ice particle radius distribution, which limited the maximum ice particle radius to ≤ 50 µm, with a non-uniform distribution covering radii from 2 to 300 µm without additional computational overhead. The improved model is validated against meteorological observations from site D47 in Adélie Land, East Antarctica. The updates fix the numerical artefacts, successfully predicting the power-law variation in the blowing-snow flux with wind speed while improving the prediction of its magnitude. Additionally, a qualitative comparison with CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) satellite data shows that RACMO accurately forecasts the spatial pattern of monthly blowing-snow frequencies. The model also yields an average blowing-snow layer depth of 230±116 m at D47, matching typical satellite observation values. Results reveal that, without blowing snow, sublimation in Antarctica mainly occurs in summer (October–March), with minimal surface sublimation in winter (April–September). Introducing the blowing-snow model creates an additional sublimation mechanism primarily contributing in winter. From 2000–2012, model-integrated blowing-snow sublimation averaged 175±7 Gt yr−1, a 52 % increase from the previous version. Total sublimation, summing blowing-snow and surface sublimation, reached 234±10 Gt yr−1, 47 % higher than in simulations without the blowing-snow model. This increase leads to a 1.2 % reduction in the Antarctic ice sheet's integrated SMB. Additionally, changes in sublimation in coastal and lower escarpment zones underscore the importance of the model updates for Antarctic climatology.

Investigating secondary ice production in a deep convective cloud with a 3D bin microphysics model: Part I - Sensitivity study of microphysical processes representations

Secondary ice production (SIP) is a crucial phenomenon for explaining the formation of ice crystal clouds, especially when addressing the discrepancies between observed ice crystal number concentrations and ice nucleating particles (INPs). In this study, we investigate parameterizations of three SIP processes (Hallett-Mossop, fragmentation of freezing drops, and fragmentation due to ice–ice collision) by simulating a deep convective cloud observed during the HAIC/HIWC campaign with the 3D bin microphysics scheme DESCAM (DEtailed SCAvening and Microphysics model). The simulated mean cloud properties, including particle size distributions and ice crystal number concentration are compared with in situ probe observations obtained during the campaign. Simulation excluding SIP show a large underestimation of small ice crystals (< 1 mm diameter) for temperatures warmer than ‐30∘C. In our results, incorporating Hallett-Mossop and fragmentation due to ice–ice collision processes leads to ice crystal number concentrations close to observed values, thereby reducing discrepancies by two orders of magnitude. Our simulations also indicates that fragmentation of freezing drops affect minimally the properties of the cloud at its mature stage. Furthermore, we investigate the impact of fragments sizes resulting from SIP processes and show that the size of fragments generated from fragmentation due to ice–ice collision significantly influences the shape of ice particle size distribution. Employing various parameterizations of the ice crystal sticking efficiency reveals a notable impact on cloud properties. This study shows that SIP mechanisms are important and have to be considered for cold and mixed-phase clouds. However their parameterization lack reliability, highlighting the need for better quantifying these mechanisms. The companion paper, investigates the effects of SIP processes on the formation and the evolution of the deep convective system.

Journey of complex organic molecules: Formation and transport in protoplanetary disks

Complex organic molecules serve as indicators of molecular diversity. Their detection on comets, planets, and moons has prompted inquiries into their origins, particularly the conditions conducive to their formation. One hypothesis suggests that the UV irradiation of icy grains in the protosolar nebula generates significant molecular complexity, a hypothesis supported by experiments on methanol ice irradiation. We investigated the irradiation of methanol ice particles as they migrate through the protosolar nebula. Our objective is to ascertain whether the encountered conditions facilitate the formation of complex organics molecules, and we leverage experimental data in our analysis. We developed a two-dimensional model that describes the transport of pebbles during the evolution of the protosolar nebula, employing a Lagrangian scheme. This model computes the interstellar UV flux received by the particles along their paths, which we compared with experimental values. On average, particles ranging from 1 to 100 mu m in size, released at a local temperature of 20 K, undergo adequate irradiation to attain the same molecular diversity as methanol ice during the experiments within timescales of 25 kyr of protosolar nebula evolution. In contrast, 1 cm sized particles require 911 kyr of irradiation to reach similar molecular diversity, making comparable molecular complexity unlikely. Similarly, particles ranging from 1 to 100 mu m in size, released at a local temperature of 80 K, receive sufficient irradiation after 141 and 359 kyr. In contrast, 1 cm sized particles would require several million years to receive this level of irradiation, which is infeasible since they cross the iceline within approximately 500 kyr. The particles readily receive the irradiation dose necessary to generate the molecular diversity observed in the experiments within the outer regions of the disk. Our model, combined with future irradiation experiments, can provide additional insights into the specific regions where the building blocks of planets form.

Estimating the snow density using collocated Parsivel and Micro-Rain Radar measurements: a preliminary study from ICE-POP 2017/2018

Abstract. A new method is developed to derive the bulk density and bulk water fraction of a population of particles from collocated measurements from the Micro-Rain Radar (MRR) and Particle Size and Velocity disdrometer (Parsivel). A rigorous particle-scattering simulation, namely the T-matrix method, is applied to Parsivel's particle size distribution data to calculate the reflectivity (ZHH). The possible combinations of the particle's ice, air, and water are derived to compare them with the MRR-measured ZHH. The combination of the minimum water fraction and maximum ice fraction subsequently determines the bulk density (ρbulk). The proposed method is applied to the data collected from the International Collaborative Experiments for Pyeongchang 2018 Olympic and Paralympic winter games (ICE-POP 2018) projects and its pre-campaign. The estimated ρbulk was examined independently by a comparison of the liquid-equivalent snowfall rate (SR) of collocated Pluvio devices. The bias values are adequately low (SR: −0.25–0.06 mm h−1). The retrieved bulk density also shows good consistency with collocated Precipitation Imaging Package (PIP) retrievals. The results indicate the capability of the proposed algorithm to derive reliable ρbulk, leveraging the compact and easily deployable designs of MRR and Parsivel. The derived bulk density of the two warm–low cases (28 February and 7 March 2018) shares a similar transition as the systems were decaying. The higher bulk density and bulk water fraction were found in the coastal sites (BKC and GWU have a median value of ρbulk and are 0.05 to 0.12 g cm−3), typically accompanied by higher liquid-water constituents (mean values of the top 5 % bulk water fraction are 0.07 to 0.45) than the inland sites (YPO and MHS have a median value of ρbulk and are 0.06 to 0.10, and mean values of the top 5 % bulk water fraction are 0.001 to 0.008) during such synoptic conditions.

Evaluation of Physical Microphysical Property Retrieval Algorithms During the 2020 IMPACTS Field Campaign

Abstract The NASA Investigation of Microphysics and Precipitation for Atlantic Coast Threatening Snowstorms (IMPACTS) field campaign provides high-quality, high-altitude aircraft lidar (532 nm), radar (W-band) and in-cloud microphysical aircraft data taken during wintertime storm events impacting the United States. This study evaluates two mass-dimensional relationships (Brown and Francis (1995, BF95); Heymsfield (2014, H14) and two lidar-radar microphysical retrieval algorithms (Cloudsat and CALIPSO Ice Cloud Property Product (2C-ICE); VarPy (a variational method derived from the satellite lidar-radar data community)) to estimate aircraft-retrieved volume extinction coefficient (σ), ice water content (IWC), and effective radius (re) during the 2020 IMPACTS deployment. BF95 and H14 have a close 1:1 correlation (R2 = 0.98) with in-situ observations of σ. However, only BF95 displays a linear, consistent, and almost temperature-independent low bias for IWC and re, which likely arises from the environmental conditions used to determine each. Unlike the field-campaign-derived BF95 and H14 relationships, VarPy and 2C-ICE directly ingest the aircraft-based lidar and radar data to simulate σ, IWC, and re. For all three microphysical parameters, VarPy and 2C-ICE retrieval errors became notably more pronounced around the dendritic growth zone (−15°C to −10°C) and near freezing (≥−5°C), which suggests that both algorithms experience difficulty addressing riming and aggregation processes and with larger particles (dendrites and plates) due in part to their simplified ice particle assumptions. However, the mean-melt diameter ice-particle assumption did yield more accurate IWC estimates, which led to slightly better overall results for VarPy.

Micro-Scale Ice Shoveling Effect Induced by Magnetic-Responsive Microfins.

Icing is ubiquitous in nature and engineering applications, and imposes threats to road and air transportations, wind energy infrastructures, etc. However, current active de-icing solutions, especially the most popular one, i.e., heating, suffer from high energy consumption whilst passive methods are often ineffective at high-speed, long-term, or large-particle conditions. Herein, a promising strategy adopting magnetic-responsive microfins (MRS)featuring reversible deformations is developed for de-icing. A novel micro-scale ice shoveling effect induced by the localized destruction of the ice adhesion interface owing to the inhomogeneous deformation is demonstrated, and its dependence on the ice particle size and temperature is investigated. An analytical model is proposed to describe the mechanism of this effect, showing a linear relation between the position of the magnet and the induced force agreeing well with experiments, leading to a system straightforward to predict and control. Specifically, the de-icing capacity of the surface becomes prominent when small-scale ice particles merge to large ones, providing a promising solution for applications on aircraft, wind turbines, etc., as the first of its kind to remove large particles under high-speed conditions effectively.

Rainfall Enhancement Downwind of Hills Due to Stationary Waves on the Melting Level and the Extreme Rainfall of December 2015 in the Lake District of Northwest England

This paper investigates how stationary gravity waves generated by flow over orography enhance rainfall, with particular attention to the role of induced waves in the melting level. The findings reveal a new mechanism by which gravity wave flow focuses precipitation, amplifying rainfall intensity downwind of hills. This mechanism, which depends on the differential velocities of rain and snow, offers fresh insights into how orographic effects can intensify rainfall. A two-dimensional diagnostic model based on linear gravity wave theory is used to investigate the record-breaking rainfall of December 2015 in the Lake District of northwest England. The pattern of ascent is shown to have a qualitatively good fit to that of the Met Office’s operational high-resolution UKV model averaged over 24 h, suggesting that orographically excited stationary waves were the principal cause of the rain. Precipitation trajectories imply that a persistent downstream elevated wave caused by the Isle of Man supported a spray of seeding ice particles directed towards the Lake District, and that these grew whilst suspended in strong upslope flow before being focused by the undulating melting-level into intense shafts of rain.

Water ice particles detected by SELENE's Spectral Profiler at lunar shadowed regions in various local times and latitudes

Processes of water (OH and H2O) migration on the Moon remain unclear, prompting active research. Understanding lunar water migration requires investigation of the trapping and diffusion properties of water at various latitudes and local times. This study analyzed visible to near-infrared spectral data obtained by the Spectral Profiler (SP) onboard SELENE for shadowed regions at various local times and latitudes, not limited to the polar permanently shadowed regions. We assessed SP data for shadowed regions in 60 areas, each spanning a 10° × 10° latitude–longitude grid. Of the 1,061,907 analyzed shadowed-region data, 41,385 at various latitudes exhibited significant absorption in the 1.25 and 1.5 µm bands, indicating water ice particles. Data with the two absorption features suggest the presence of a water ice frost layer covering the lunar surface or suspended water ice particles above the lunar surface, at various latitude shadowed regions. Our spectral simulations have quantified the ice particles as being 0.1–1 µm in diameter, with a column density of 10–4–10–3 kg/m2. The spectral parameters for band absorption at the 1.5 µm band show symmetry between morning and evening sides, which is potentially attributed to the absence of variations in ice grain size and quantity. The 1.5 µm band absorption shows an increasing trend toward terminator regions, indicating variation in the water ice distribution and likely reflecting temperature conditions for water retention. The latitudinal trend of ice grain size and quantity remains uncertain because of the observed noise levels. Observations of water ice particles in shadowed regions at various latitudes and local times can provide new constraints on trapping and diffusion processes of lunar water migration.

Effect of secondary ice production processes on the simulation of ice pellets using the Predicted Particle Properties microphysics scheme

Abstract. Ice pellets can form when supercooled raindrops collide with small ice particles that can be generated through secondary ice production processes. The use of atmospheric models that neglect these collisions can lead to an overestimation of freezing rain. The objective of this study is therefore to understand the impacts of collisional freezing and secondary ice production on simulations of ice pellets and freezing rain. We studied the properties of precipitation simulated with the Predicted Particle Properties (P3) microphysics scheme for two distinct secondary ice production processes. Improvements to the representation of ice pellets and ice crystals in P3 were analyzed by simulating an ice pellet storm that occurred over eastern Canada in January 2020. Those simulations showed that adding secondary ice production processes increased the accumulation of ice pellets but led to unrealistic size distributions of precipitation particles. Realistic size distributions of ice pellets were obtained by modifying the collection of raindrops by small ice particles and the merging criteria of ice categories in P3.

Comparison of the Morrison and WDM6 Microphysics Schemes in the WRF Model for a Convective Precipitation Event in Guangdong, China, Through the Analysis of Polarimetric Radar Data

Numerical weather prediction (NWP) models are indispensable for studying severe convective weather events. Research demonstrates that the outcomes of convective precipitation simulations are profoundly influenced by the choice between single or double-moment schemes for ice precipitation particles and the categorization of rimed ice. The advancement of dual-polarization radar has enriched the comparative validation of these simulations. This study simulated a convective event in Guangdong, China, from May 7 to 8, 2017, employing two bulk microphysical schemes (Morrison and WDM6) in the WRF v4.2 model. Each scheme was divided into two versions: one representing rimed ice particles as graupel (Mor_G, WDM6_G) and the other as hail (Mor_H, WDM6_H). The simulation results indicated negligible differences between the rimed ice set as graupel or hail particles, for both schemes. However, the Morrison schemes (Mor_G, Mor_H) depicted a more accurate raindrop size distribution below the 0 °C height level. A further analysis suggested that disparities between the Morrison and WDM6 schemes could be attributed to the intercept parameter (N0) setting for snow and graupel/hail in WDM6 scheme. The prescribed snow and graupel/hail N0 of WDM6 scheme might influence the melting processes, leading to a higher number concentration but a reduced mass-weighted diameter of raindrops. Reducing the intercept parameter for snow and graupel/hail in the WDM6 scheme could potentially enhance the simulation of convective precipitation. Conversely, the increase in N0 might deteriorate the precipitation simulation performance of the WDM6_G scheme, whereas the WDM6_H scheme exhibits minimal sensitivity to such changes.

A combined experimental-mathematical study on the kinetics of dry ice sublimation under different airflow velocities and blowing modes

The sublimation rate of dry ice, crucial for its cooling performance, is typically influenced by environmental temperature, pressure, and specific surface area. However, the effect of wind speed under forced air convection is not well understood, and current sublimation kinetic models inadequately capture this influence, leading to discrepancies between simulations and experiments. This study examines the sublimation kinetics of static dry ice particles under varying wind speeds and blowing modes. A mathematical model was developed to determine the sublimation kinetic parameters by integrating the Clausius-Clapeyron equation, mass transfer theory, and hybrid particle swarm optimization (HPSO) algorithm. These parameters were then used to create a cooling model for a small insulated box, and the results were validated against experimental data. The findings show that increasing wind speed enhances the sublimation rate of dry ice, with upward-blowing conditions resulting in higher rates than side-blowing conditions. The model’s predictions closely match experimental data, with a maximum mass change deviation of less than 3 % and a maximum temperature deviation of less than 4 °C, demonstrating high reliability.

Microwave scattering properties of ice crystal particles during the melting process

Ice crystal particles play an important role in the study of cloud resolution, climate models, and radiative forcing. During the melting process, significant changes occur in the microphysical properties of ice crystal particles, such as the ice phase state, morphology, and mixing state. This process further affects the scattering and radiation characteristics properties of ice crystal particles. In this study, we constructed a non-spherical and inhomogeneous particle model based on the melting process of ice crystal particles. The scattering properties of melting ice crystal particles under four selected microwave frequency bands (92 GHz, 220 GHz, 280 GHz, and 340 GHz) are investigated by using discrete dipole approximation (DDA) method. The influence of ice crystal content (ICC) and particle aspect ratio on the scattering properties of ice crystal particles under thin coating and medium coating conditions are emphasized. The results show that the melting process significantly affects the scattering properties of melting ice crystal particles in a frequency dependent manner. Additionally, even slight melting of ice crystal particles leads to drastic changes in their scattering properties. Furthermore, we found that the morphology of ice crystal nuclei has a significant impact on their scattering characteristics even at medium levels of melting degree. In summary, this study confirms that it is essential to consider morphology and inhomogeneous characteristics during the melting process for microwave detection of ice crystal particles. This research may have significant implications for studies related to detection and inversion techniques for ice crystal particles.

The Characteristics of Precipitation with and without Bright Band in Summer Tibetan Plateau and Central-Eastern China

The bright band (BB) is an important symbol of the ice–water transition zone in stratiform precipitation, and the presence or absence of BB will lead to different microphysical processes. In this paper, the characteristics of BB and precipitation characteristics with and without BB in summer at Tibetan Plateau (TP) as well as Central-eastern China (CEC) are analyzed by using Global Precipitation Measurement (GPM) and the fifth generation ECMWF atmospheric reanalysis of the global climates (ERA5) datasets. The results show the freezing level height and BB height in TP are 0.5 km higher than those in CEC. With the increase in rain rate, the BB height decreases in TP but increases in CEC. The BB width becomes wider with the increase in maximum radar reflectivity. Secondly, the maximum reflectivity factor and particle diameter of stratiform precipitation with BB appear at 5 km, while the maximum reflectivity factor of stratiform precipitation without BB and convective precipitation appear near the ground. The particle diameter first decreases and then increases from the cloud top to the ground. Thirdly, the land surface temperature of convective precipitation is about 2.5 °C higher than stratiform precipitation with BB, indicating higher land surface temperatures are more likely to trigger convection. Lastly, BB can lead to a decrease in brightness temperature and an increase in polarized difference at 89 GHZ and 166 GHZ in CEC, likely due to the increasing ice particles in stratiform precipitation with BB.

Prediction of thermal conductivity of frozen soils from basic soil properties using ensemble learning methods

Thermal conductivity is one of the important properties required for understanding the frozen soils behavior. There are several models available in the literature for the prediction of thermal conductivity of frozen soils based on the proportions of unfrozen water, ice, gas, and soil particles. In this study, two ensemble learning methods-based models; namely, the Random Forest (RF) model and the Least Squares Boosting (LSB) model, are extended to estimate the thermal conductivity of frozen soils. These models utilize basic soil properties as input parameters that include water content, dry density, temperature, and fractions of gravel, sand, silt, and clay, can be measured easily, or determined. Additionally, seven widely used thermal conductivity models, referred to as the traditional models for frozen soils, were evaluated. Both the RF and LSB models, as well as the traditional models, were assessed using data of 823 tests derived from 43 soils with different textures that were gathered from the literature. The results highlight that the traditional models have their strengths and limitations in terms of their use for different types of soils. In contrast, the proposed ensemble learning methods-based models provide higher prediction accuracy compared to the traditional models and can be applied to all soil types and temperature ranges. Furthermore, estimation from the ensemble learning methods-based models can be used to provide probability of multi-dimensional analysis of frozen soils.

Evaluation of the Aggregation Efficiency Modeling at Colder Atmospheric Temperatures in Comparison to Satellite Observations

Abstract Aggregation efficiency in the upper troposphere is highly uncertain because of the lack of laboratory experiments and aircraft measurements, especially at atmospheric temperatures below −30°C. Aggregation is physically broken down into collision and sticking. In this study, theory-based parameterizations for the collision efficiency and sticking efficiency are newly implemented into a double-moment bulk cloud microphysics scheme. Satellite observations of the global ice cloud distribution are used to evaluate the aggregation efficiency modeling. Sensitivity experiments of 9-day global simulations using a high-resolution climate model show that the use of collision efficiency parameterization causes a slight increase in the cloud ice amount above the freezing level over the tropics to midlatitudes and that the use of our new sticking efficiency parameterization causes a significant increase in the cloud ice amount and a slight decrease in the snow amount particularly in the upper troposphere over the tropics. The increase/decrease in the cloud ice/snow amount in the upper troposphere over the tropics is consistent with the vertical profile of radar echoes. Moreover, the ice fraction of the cloud optical thickness is still underestimated worldwide. Finally, the cloud radiative forcing increases over the tropics to reduce the bias in the radiation budget. These results indicate that our new aggregation efficiency modeling reasonably functions even at atmospheric temperatures below −30°C; however, further improvements in the ice cloud modeling are needed. Significance Statement Long-standing biases in the radiative budget in climate models indicate the existence of a missing mechanism to realistically represent the ice cloud growth in the upper troposphere. This study focuses on aggregation efficiency, which has been assumed to be a tuning parameter to optimize the global radiative budget. Therefore, this study employs a theory-based parameterization to calculate the aggregation efficiency. According to the parameterization, aggregation efficiency in high clouds varies by the growth stage of the individual ice particles. As a result, small ice crystals are likely to grow more slowly, and the lifetime of cirrus clouds is prolonged to enhance cloud radiative forcing, particularly over the tropics. These results are promising for reducing the biases observed in climate models.

Microphysical Evolution in Mixed-Phase Midlatitude Marine Cold-Air Outbreaks

Abstract Five cold-air outbreaks are investigated with aircraft offshore of continental northeast America. Flight paths aligned with the cloud-layer flow from January through March span cloud-top temperatures from −5° to −12°C, in situ liquid water paths of up to 500 g m−2, while in situ cloud droplet number concentrations exceeding 500 cm−3 maintain effective radii below 10 μm. Rimed ice is detected in the four colder cases within the first cloud pass. After further fetch, ice particle number concentrations reaching 2.5 L−1 support an interpretation that secondary ice production is occurring. Rime splintering is clearly evident, with dendritic growth increasing ice water contents within deeper clouds with colder cloud-top temperatures. Buoyancy fluxes reach 400–600 W m−2 near the Gulf Stream’s western edge, with 1-s updrafts reaching 5 m s−1 supporting closely spaced convective cells. Near-surface rainfall rates of the three more intense cold-air outbreaks are a maximum near the Gulf Stream’s eastern edge, just before the clouds transition to more open-celled structures. The milder two cold-air outbreaks transition to lower-albedo cumulus with little or no precipitation. The clouds thin through cloud-top entrainment. Significance Statement Cold-air outbreaks off of the eastern U.S. seaboard are visually spectacular in satellite imagery, with overcast, high-albedo clouds transitioning to more broken cloud fields. We use data from the recent NASA Aerosol Cloud Meteorology Interactions over the Western Atlantic Experiment (ACTIVATE) aircraft campaign to examine the microphysics and environmental context of five such outbreaks. We find the clouds are not ice-deprived, but updrafts still supply significant liquid water. Cloud transitions are encouraged through near-surface rain for the deeper clouds, and otherwise, clouds thin and break through mixing in drier air from above. These observations support understanding and further modeling examining how mixed-phase cloud microphysics affect cloud reflectivity and surface rainfall rates, important for both weather and climate forecasting.

On the impact of the vertical structure of Martian water ice clouds on nadir atmospheric retrievals from simultaneous EMM/EXI and TGO/ACS-MIR observations.

Retrieving the optical depth of the Martian clouds (τcld) is a powerful way to monitor their spatial and temporal evolution. However, such retrievals from nadir imagery rely on several assumptions, including the vertical structure of the clouds in the atmosphere. Here we compare the results of cloud optical depth retrievals at 320 nm from the Emirates eXploration Imager (EXI) onboard the Emirates Mars Mission (EMM) “Hope” orbiter performed using a basic uniform cloud profile used in previous studies and using derived cloud profiles obtained from near-simultaneous Solar Occultation observations in the 3.1–3.4 μm spectral range from the Middle-Infrared channel of the Atmospheric Chemistry Suite (ACS) instrument onboard the ESA Trace Gas Orbiter (TGO). We show that the latitudinal dependence of the cloud vertical profiles can have a strong impact on the nadir retrievals; neglecting it can lead to a significant underestimation of τcld in the polar regions (up to 25 % to 50 %, depending on the vertical distribution of the dust in the atmosphere) and to a lesser extent, to an overestimation of τcld around the equator. We also discuss the impact of a vertically-dependent particle size profile, as previous studies have shown the presence of very small water ice particles at the top of the clouds. From this analysis, we provide recommendations for the improvement of water ice cloud parameterization in radiative transfer algorithms in nadir atmospheric retrievals.

Particle Dynamics Study on Influencing Factors of Ice Slurry Flow Characteristics in District Cooling Systems

In district cooling systems, substituting the conventional cooling medium with ice slurry represents an ideal approach to achieve economical operation. During pipeline transportation, ice slurry exhibits heterogeneous flow characteristics distinct from those of pure fluids. Consequently, investigating the flow field characteristics of non-homogeneous ice slurry, quantitatively analyzing the rheological variations and flow resistance laws due to the uneven distribution of ice particles, and standardizing the comprehension and depiction of flow patterns within ice slurry pipes hold significant theoretical importance and practical value. This study analyzes the heterogeneous isothermal flow characteristics of ice slurry in a straight pipe by employing particle dynamics and the Euler–Euler dual-fluid model. Taking into account the impact of ice particles’ non-uniform distribution on the rheological properties of ice slurry, a particle concentration diffusion equation is incorporated to develop an isothermal flow resistance model for ice slurry. The flow behavior of ice slurry with initial average ice particle fractions (IPFs) ranging from 0% to 20% in DN20 horizontal straight and elbow pipes is examined. The findings reveal that the degree of heterogeneous flow in ice slurry is inversely proportional to the initial velocity and directly proportional to the initial concentration of ice particles. When the flow velocity is close to 0.5 m/s, the flow resistance of ice particles exhibits a linear positive correlation with changes in flow velocity, whereas the flow resistance of the fluid-carrying phase displays a linear negative correlation. As the flow rate increases to 1 m/s, the contribution of each phase to the total flow resistance becomes independent of the initial velocity parameter. Additionally, the drag fraction of the ice particle phase is positively associated with the initial concentration of ice particles. Furthermore, the phenomenon of “secondary flow” arises when ice slurry flows through an elbow, enhancing the mixing of ice particles with the carrier fluid. The extent of this mixing intensifies with a decrease in the turning radius and an increase in the initial velocity.

Revisiting Contrail Ice Formation: Impact of Primary Soot Particle Sizes and Contribution of Volatile Particles.

Aircraft contrails, formed largely on soot particles in current flights, are important for aviation's non-CO2 climate impact. Here we show that the activation of nonvolatile soot particles during contrail formation is likely determined by the sizes of primary soot particles rather than the effective sizes of soot aggregates as assumed in previous studies, which can explain less-than-unity fractions of soot particles forming contrail ice particles as recently observed during ECLIF (Emission and CLimate Impact of alternative Fuels) campaigns. The smaller soot primary sizes compared to aggregate sizes delay the onset of contrail ice formation, increase the maximum plume supersaturation reached in the contrail plume, and thus increase the probability of small volatile particles contributing to the total contrail ice particle number. This study suggests that the range of conditions for volatile plume particles to contribute significantly to the contrail ice number budget is wider than previously thought. As the aviation industry is moving toward sustainable aviation fuel and/or lean-burning engine technology, which is expected to reduce not only the emission index of nonvolatile soot particles but also the sizes of primary soot particles, this study highlights the need to better understand how the combined changes may affect contrail formation, contribution of volatile particles, and climate impacts.