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High‐latitudinal mixed‐phase clouds significantly affect Earth's radiative balance. Observations of cloud and radiative properties from two field campaigns in the Southern Ocean and Antarctica were compared with two global climate model simulations. A cyclone compositing method was used to quantify "dynamics‐cloud‐radiation" relationships relative to the extratropical cyclone centers. Observations show larger asymmetry in cloud and radiative properties between western and eastern sectors at McMurdo compared with Macquarie Island. Most observed quantities at McMurdo are higher in the western (i.e., post‐frontal) than the eastern (frontal) sector, including cloud fraction, liquid water path (LWP), net surface shortwave and longwave radiation (SW and LW), except for ice water path (IWP) being higher in the eastern sector. The two models were found to overestimate cloud fraction and LWP at Macquarie Island but underestimate them at McMurdo Station. IWP is consistently underestimated at both locations, both sectors, and in all seasons. Biases of cloud fraction, LWP, and IWP are negatively correlated with SW biases and positively correlated with LW biases. The persistent negative IWP biases may have become one of the leading causes of radiative biases over the high southern latitudes, after correcting the underestimation of supercooled liquid water in the older model versions. By examining multi‐scale factors from cloud microphysics to synoptic dynamics, this work will help increase the fidelity of climate simulations in this remote region. Plain Language Summary: The efficacy of climate prediction is largely dependent on accurately estimating Earth's energy budget in global climate models (GCMs). The Southern Ocean region has a distinct history of showing large biases in energy budget within GCMs. This region also shows complex interactions between large‐scale dynamical conditions (e.g., low‐pressure systems) and microscale processes (e.g., cloud properties). This work used two field deployments at Macquarie Island, Southern Ocean and McMurdo Station, Antarctica to understand these interactions. Observations were obtained from year‐long measurements by ground‐based instruments, which were further compared with two GCMs. The two models were found to have errors representing cloud properties at Macquarie Island (e.g., too much liquid and too little ice) and McMurdo Station (e.g., too little ice and liquid), as well as errors representing net surface longwave (terrestrial) radiation and shortwave (solar) radiation. The combination of the insufficient amounts of cloud ice and liquid in the models at McMurdo, Antarctica may be the main cause of too much solar radiation absorbed by Earth's surface over that region, which also have implications for polar ice melting and ocean circulation in that remote region. Key Points: Extratropical cyclone compositing shows more asymmetric cloud properties in eastern and western sectors at McMurdo than Macquarie IslandSimulated ice water path is too low at both sectors and both sites; liquid water path is too high (low) at Macquarie (McMurdo)Model radiation biases are affected by both cloud properties and synoptic dynamics (e.g., extratropical cyclones) [ABSTRACT FROM AUTHOR]

Stars form in the densest regions of molecular clouds; however, there is no universal understanding of the factors that regulate cloud dynamics and their influence on the gas-to-star conversion. This study considers the impact of Galactic shear on the rotation of giant molecular clouds (GMCs) and its relation to the solenoidal modes of turbulence. We estimate the direction of rotation for a large sample of clouds in the |$\mathrm{^{13}CO}$| / |$\mathrm{C^{18}O}$| (3–2) Heterodyne Inner Milky Way Plane Survey (CHIMPS) and their corresponding sources in a new segmentation of the |$\mathrm{^{12}CO}$| (3–2) High-Resolution Survey. To quantify the strength of shear, we introduce a parameter that describes the shear's ability to disrupt growing density perturbations within the cloud. Although we find no correlation between the direction of cloud rotation, the shear parameter, and the magnitude of the velocity gradient, the solenoidal fraction of the turbulence in the CHIMPS sample is positively correlated with the shear parameter and behaves similarly when plotted over Galactocentric distance. GMCs may thus not be large or long-lived enough to be affected by shear to the point of showing rotational alignment. In theory, Galactic shear can facilitate the rise of solenoidal turbulence and thus contribute to suppressing star formation. These results also suggest that the rotation of clouds is not strictly related to the overall rotation of the disc, but is more likely to be the imprint of Kelvin–Helmholtz instabilities in the colliding flows that formed the clouds. [ABSTRACT FROM AUTHOR]

This study investigates the rain-initiated mixing and variability in the mixing ratio of selected trace gases in the atmosphere over the central Amazon rain forest. It builds on comprehensive data from the Amazon Tall Tower Observatory (ATTO), spanning from 2013 to 2020 and comprising the greenhouse gases (GHGs) carbon dioxide (CO2) and methane (CH4); the reactive trace gases carbon monoxide (CO), ozone (O3), nitric oxide (NO), and nitrogen dioxide (NO2); and selected volatile organic compounds (VOCs). Based on more than 1000 analyzed rainfall events, the study resolves the trace gas mixing ratio patterns before, during, and after the rain events, along with vertical mixing ratio gradients across the forest canopy. The assessment of the rainfall events was conducted independently for daytime and nighttime periods, which allows us to elucidate the influence of solar radiation. The mixing ratios of CO2 , CO , and CH4 clearly declined during rainfall, which can be attributed to the downdraft-related entrainment of pristine air from higher altitudes into the boundary layer, a reduction of the photosynthetic activity under increased cloud cover, and changes in the surface fluxes. Notably, CO showed a faster reduction than CO2 , and the vertical gradient of CO2 and CO is steeper than for CH4. Conversely, the O3 mixing ratio increased across all measurement heights in the course of the rain-related downdrafts. Following the O3 enhancement by up to a factor of 2, NO , NO2 , and isoprene mixing ratios decreased. The temporal and vertical variability of the trace gases is intricately linked to the diverse sink and source processes, surface fluxes, and free-troposphere transport. Within the canopy, several interactions unfold among soil, atmosphere, and plants, shaping the overall dynamics. Also, the mixing ratio of biogenic VOCs (BVOCs) clearly varied with rainfall, driven by factors such as light, temperature, physical transport, and soil processes. Our results disentangle the patterns in the trace gas mixing ratio in the course of sudden and vigorous atmospheric mixing during rainfall events. By selectively uncovering processes that are not clearly detectable under undisturbed conditions, our results contribute to a better understanding of the trace gas life cycle and its interplay with meteorology, cloud dynamics, and rainfall in the Amazon. [ABSTRACT FROM AUTHOR]

Liquid hydrogen storage is an important way of hydrogen storage and transportation, which greatly improves the storage and transportation efficiency due to the high energy density but at the same time brings new safety hazards. In this study, the liquid hydrogen leakage in the storage area of a hydrogen production station is numerically simulated. The effects of ambient wind direction, wind speed, leakage mass flow rate, and the mass fraction of gas phase at the leakage port on the diffusion behavior of the liquid hydrogen leakage were investigated. The results show that the ambient wind direction directly determines the direction of liquid hydrogen leakage diffusion. The wind speed significantly affects the diffusion distance. When the wind speed is 6 m/s, the diffusion distance of the flammable hydrogen cloud reaches 40.08 m, which is 2.63 times that under windless conditions. The liquid hydrogen leakage mass flow rate and the mass fraction of the gas phase have a greater effect on the volume of the flammable hydrogen cloud. As the leakage mass flow rate increased from 5.15 kg/s to 10 kg/s, the flammable hydrogen cloud volume increased from 5734.31 m3 to 10,305.5 m3. The installation of a barrier wall in front of the leakage port can limit the horizontal diffusion of the flammable hydrogen cloud, elevate the diffusion height, and effectively reduce the volume of the flammable hydrogen cloud. This study can provide theoretical support for the construction and operation of hydrogen production stations. [ABSTRACT FROM AUTHOR]

The clouds have a great impact on Venus's energy budget and climate evolution, but its three‐dimensional structure is still not well understood. Here we incorporate a simple Venus cloud physics scheme into a flexible GCM to investigate the three‐dimensional cloud spatial variability. Our simulations show good agreement with observations in terms of the vertical profiles of clouds and H2SO4 vapor. H2O vapor is overestimated above the clouds due to efficient transport in the cloud region. The cloud top decreases as latitude increases, qualitatively consistent with Venus Express observations. The underlying mechanism is the combination of H2SO4 chemical production and meridional circulation. The mixing ratios of H2SO4 at 50–60 km and H2O vapors in the main cloud deck basically exhibit maxima around the equator, due to the effect of temperature's control on the saturation vapor mixing ratios of the two species. The cloud mass distribution is subject to both H2SO4 chemical production and dynamical transport and shows a pattern that peaks around the equator in the upper cloud while peaks at mid‐high latitudes in the middle cloud. At low latitudes, H2SO4 and H2O vapors, cloud mass loading and acidity show semidiurnal variations at different altitude ranges, which can be validated against future missions. Our model emphasizes the complexity of the Venus climate system and the great need for more observations and simulations to unravel its spatial variability and underlying atmospheric and/or geological processes. Plain Language Summary: On Venus, highly reflective clouds cover the surface entirely. This means that the clouds greatly impact Venus's current and, very likely, past energy budget. Therefore, understanding the Venus clouds is essential to constructing a full paradigm of the Venus climate and evolution. However, due to the lack of both three‐dimensional, long‐term observations and comprehensive climate models, the cloud spatial structure and its impact on atmospheric processes remain elusive. Here, we construct a three‐dimensional climate model that includes cloud physics and simple chemistry as the first step toward fully understanding the Venus clouds. Our simulated vertical profiles of the Venus clouds agree well with observations. We find that the condensable gases, sulfuric acid and water vapors in the cloud region become more abundant in the lower latitudes due to the temperature difference over different latitudes. The cloud top becomes lower as it approaches the polar region, and the underpinning processes are related to sulfuric acid chemical production and meridional circulation. The equatorial cloud structure shows semidiurnal features, which are related to the excited thermal tides in the Venus atmosphere. Our study is preparing for future Venus missions like EnVision, to maximize their science returns. Key Points: We construct a Venus climate model with cloud physics, and the cloud vertical structure agrees with observationsH2SO4 and H2O vapors in the middle cloud basically follow their SVMRs and show higher concentrations at low latitudesThe semidiurnal thermal tide affects H2SO4 and H2O vapors, cloud mass loading and acidity at different altitudes [ABSTRACT FROM AUTHOR]

Proboscis monkeys, Nasalis larvatus (Wurmb, 1787), are indigenous to the island of Borneo and are considered one of its most emblematic species. Today the conservation status of this primate is classified as Endangered on the IUCN Red List and listed under Appendix I of CITES, prohibiting all international commercial trade. In the Malaysian state of Sabah, the species is listed as totally protected and cannot be hunted. Continuing studies suggest that the number of proboscis monkeys has been decreasing in recent years. These studies have identified various factors contributing to this decline and its potential consequences. In order to carry out a thorough assessment of the conservation status of the species it is essential to have a good understanding of the animal’s ecology and habitat requirements and to use research-based approaches. One of such are species distribution models (SDMs), which in recent decades have become widely used tools in ecology by relating species occurrences to environmental data to gain ecological insights. In this work, we specifically evaluated the effect of environmental parameters such as cloud cover to predict the potential distribution of the proboscis monkey in Sabah. Cloud cover, a seemingly simple atmospheric phenomenon, exerts a profound influence on a wide range of ecological biological processes, yet the assessment of its importance has remained remarkably limited. For modelling purposes the ‘flexsdm’ R (v. 3.3.3) modelling package was employed for testing out the Maximum entropy (Maxent) algorithm, one of the most widely used SDM modelling methods. Model evaluation gave satisfactory results and the resulting model found a high level of suitability for proboscis monkeys in nearshore areas. A concerning discovery is that perhaps less than 13% of Sabah’s area is suitable habitat for proboscis monkeys, raising questions about their long-term viability. Cloud cover, particularly average annual cloudiness, is a key environmental factor influencing the distribution of proboscis monkeys in Sabah. The conversion of Borneo’s forests to oil palm plantations can negatively impact cloud properties, potentially threatening the monkeys’ habitat.

The 15 January 2022 eruption of Hunga volcano, Tonga, significantly impacted the Kingdom of Tonga as well as the wider Pacific region. The eruption column attained a maximum height of 58 km whilst the umbrella cloud reached a diameter approaching 600 km within about 3 h. The frequency of volcanic lightning generated during the eruption was also unprecedented, with the Vaisala Global Lightning Database (GLD360) recording over 3 × 105 strikes over a 2-h period. We have combined Himawari-8 satellite imagery with the spatiotemporal distribution of lightning strikes to constrain the dynamics of umbrella spreading and infer a timeline of events for the climactic phase of the eruption. Lightning was initially concentrated directly above Hunga, with an areal extent that grew with the observed eruption cloud. However, about 20 min after the eruption onset, radial structure appeared in the lightning spatial distribution, with strikes clustered both directly above Hunga and in an annulus of radius ~ 50 km. Comparison with satellite imagery shows that this annulus coincided with the umbrella cloud front. The lightning annulus and umbrella front grew synchronously to a radius of ~ 150 km before the umbrella cloud growth rate decreased whilst the annulus itself contracted to a smaller radius of about 50 km again. We interpret that the lightning annulus resulted from an enhanced rate of particle collisions and subsequent triboelectrification due to enhanced vorticity in the umbrella cloud head. Our results demonstrate that volcanic lightning observations can provide insights into the internal dynamics of umbrella clouds and should motivate more quantitative models of umbrella spreading. [ABSTRACT FROM AUTHOR]

Cavitation is a prevalent phenomenon within the domain of ship and ocean engineering, predominantly occurring in the tail flow fields of high-speed rotating propellers and on the surfaces of high-speed underwater vehicles. The re-entrant jet and compression wave resulting from the collapse of cavity vapour are pivotal factors contributing to cavity instability. Concurrently, these phenomena significantly modulate the evolution of cavitation flow. In this paper, numerical investigations into cloud cavitation over a Clark-Y hydrofoil were conducted, utilizing the Large Eddy Simulation (LES) turbulence model and the Volume of Fluid (VOF) method within the OpenFOAM framework. Comparative analysis of results obtained at different angles of attack is undertaken. A discernible augmentation in cavity thickness is observed concomitant with the escalation in attack angle, alongside a progressive intensification in pressure at the leading edge of the hydrofoil, contributing to the suction force. These results can serve as a fundamental point of reference for gaining a deeper comprehension of cloud cavitation dynamics. [ABSTRACT FROM AUTHOR]

The deployment of cloud computing, specifically Infrastructure as a Service (IaaS) clouds, have become an interested topic in recent years for the execution of compute-intensive scientific workflows. These platforms deliver on-demand connectivity to those infrastructure needed for workflow execution, providing customers to pay only for the service they utilize. As a result schedulers are forced to meet a quid-pro-quo among two main QoS criteria: cost and time. The maximum of this research work has been on making scheduling algorithms with the goal of reducing infrastructure costs as fulfilling a user-specified deadline. Few algorithms, on the other hand, have considered the problem of reducing workflow execution time while staying within a budget. This work consider on the latter scenario. We offer a Budget-based resource Provisioning and Scheduling (BPS) algorithm for scientific workflows used in IaaS service. This proposal was developed to face challenges specifically to clouds like resource performance variation, resource heterogeneity, infinite on-demand connectivity, and pay-as-you-go type (i.e. per-minute pricing). It is efficient of responding to the cloud dynamics, and is powerful in creating suitable solutions that fulfill a user-specified budget and reduce the makespan of the leveraged environment. At last, the experimental events confirms that it runs a workflow efficiently with respect to achieving budget of 94% and minimizing makespan of 29% than the state-of-the-art budget-aware algorithms. [ABSTRACT FROM AUTHOR]

The rapid advancement of microservice architecture in the cloud has led to the necessity of effectively detecting, classifying, and diagnosing run failures in microservice applications. Due to the high dynamics of cloud environments and the complex dependencies between microservices, it is challenging to achieve robust real-time system fault identification. This paper proposes an interpretable fault diagnosis framework tailored for microservice architecture, namely Multi-scale Learnable Transformation Graph for Fault Classification and Diagnosis(MTG_CD). Firstly, we employ multi-scale neural transformation and graph structure adjacency matrix learning to enhance data diversity while extracting temporal-structural features from system monitoring metrics Secondly, a graph convolutional network (GCN) is utilized to fuse the extracted temporal-structural features in a multi-feature modeling approach, which helps to improve the accuracy of anomaly detection. To identify the root cause of system faults, we finally conduct a coarse-grained level diagnosis and exploration after obtaining the results of classifying the fault data. We evaluate the performance of MTG_CD on the microservice benchmark SockShop, demonstrating its superiority over several baseline methods in detecting CPU usage overhead, memory leak, and network delay faults. The average macro F1 score improves by 14.05%. [ABSTRACT FROM AUTHOR]

The seeding effect of upper clouds on lower clouds affects the evolution of clouds, especially the seeding from upper ice clouds on lower stratiform clouds or convective clouds, which can stimulate the precipitation of lower clouds and even produce extreme precipitation. When seeders of the seeding cloud enter the feeding cloud, the interaction between cloud particles results in the change in macro- and micro-parameters of the feeding cloud. Based on the observation data of a ground-based Ka-band millimeter-wave cloud radar (MMCR) and microwave radiometer (MWR) in spring and autumn from 2021 to 2022, the seeder–feeder phenomenon among double-layer clouds in Xi'an, China, is studied. The study on 11 cases of seeder–feeder processes shows that the processes can be divided into three types by defining the height difference (HD) between the seeding cloud base and the feeding cloud top and the effective seeding depth (ESD). Through analysis of the reflectivity factor (Z) and the radial velocity (Vr) of cloud particles detected by the MMCR and on the retrieved cloud dynamics parameters (vertical velocity of airflow, Va , and terminal velocity of cloud particles, Vf), it is shown that the reflectivity factor and particle terminal velocity in the cloud are significantly enhanced during the seeder–feeder period for the three types of processes. But the enhancement magnitudes of the three seeder–feeder processes are different. The results also show that the impact of seeding on the feeding cloud is limited. The lower the height and thinner the thickness of the HD, the lower the height and thicker the thickness of the ESD. On the contrary, the higher the height and the thicker the thickness of the HD, the higher the height and the thinner the thickness of the ESD. [ABSTRACT FROM AUTHOR]

In this research, we delve into the influence of cloud condensation nuclei (CCN) and ice-nucleating particle (INP) concentrations on the morphology and abundance of ice particles in mixed-phase clouds, emphasizing the consequential impact of ice particle shape, number, and size on cloud dynamics and microphysics. Leveraging the synergy of the Advanced Microphysics Prediction System (AMPS) and the Kinematic Driver (KiD) model, we conducted simulations to capture cloud microphysics across diverse CCN and INP concentrations. The Passive and Active Microwave radiative TRAnsfer (PAMTRA) radar forward simulator further augmented our study, offering insights into how the concentrations of CCN and INPs affect radar reflectivities. Our experimental framework encompassed CCN concentrations ranging from 10 to 5000 cm -3 and INP concentrations from 0.001 to 10 L -1. Central to our findings is the observation that higher INP concentrations yield smaller ice particles, while an increase in CCN concentrations leads to a subtle growth in their dimensions. Consistent with existing literature, our results spotlight oblate-like crystals as dominant between temperatures of −20 and −16 °C. Notably, high-INP scenarios unveiled a significant prevalence of irregular polycrystals. The aspect ratio (AR) of ice particles exhibited a decline with the rise in both CCN and INP concentrations, highlighting the nuanced interrelation between CCN levels and ice particle shape, especially its ramifications on the riming mechanism. The forward-simulated radar reflectivities, spanning from -11.83 dBZ (low INP, 0.001 L -1) to 4.65 dBZ (high INP, 10 L -1), elucidate the complex dynamics between CCN and INPs in determining mixed-phase cloud characteristics. Comparable differences in radar reflectivity were also reported from observational studies of stratiform mixed-phase clouds in contrasting aerosol environments. Our meticulous analysis of KiD-AMPS simulation outputs, coupled with insights into aerosol-driven microphysical changes, thus underscores the significance of this study in refining our ability to understand and interpret observations and climate projections. [ABSTRACT FROM AUTHOR]

(1) Introduction: The subject of the present study concerns the analysis of the existence and long time evolution of the solar ~200 yr (de Vries/Suess) and ~2400 yr (Hallstadt) cycles during the recent part of the Wurm ice epoch and the Holocene, as well as their forcing on the regional East European climate during the last two calendar millennia. The results obtained here are compared with those from our previous studies, as well as with the results obtained by other authors and with other types of data. A possible scenario of solar activity changes during the 21st century, as well as different possible mechanisms of solar–climatic relationships, is discussed. (2) Data and methods: Two types of indirect (historical) data series for solar activity were used: (a) the international radiocarbon tree ring series (INTCAL13) for the last 13,900 years; (b) the Schove series of the calendar years of minima and maxima and the magnitudes of 156 quasi 11 yr sunspot Schwabe–Wolf cycles since 296 AD and up to the sunspot cycle with number 24 (SC24) in the Zurich series; (c) manuscript messages about extreme meteorological and climatic events (Danube and Black Sea near-coast water freezing), extreme summer droughts, etc., in Bulgaria and adjacent territories since 296 and up to 1899 AD, when the Bulgarian meteorological dataset was started. A time series analysis and χ2-test were used. (3) Results and analysis: The amplitude modulation of the 200 yr solar cycle by the 2400 yr (Hallstadt) cycle was confirmed. Two groups of extremely cold winters (ECWs) during the last ~1700 years were established. Both groups without exclusion are concentrated near 11 yr sunspot cycle extremes. The number of ECWs near sunspot cycle minima is about 2 times greater than that of ECWs near sunspot cycle maxima. This result is in agreement with our earlier studies for the instrumental epoch since 1899 AD. The driest "spring-summer-early autumn" seasons in Bulgaria and adjacent territories occur near the initial and middle phases of the grand solar minima of the Oort–Dalton type, which relate to the downward phases and minima of the 200 yr Suess cycle. (4) Discussion: The above results confirm the effect of the Sun's forcing on climate. However, it cannot be explained by the standard hypothesis for total solar irradiation (TSI) variations. That is why another hypothesis is suggested by the author. The mechanism considered by Svensmark for galactic cosmic ray (GCR) forcing on aerosol nuclei was taken into account. However, in the hypothesis suggested here, the forcing of solar X-ray flux changes (including solar flares) on the low ionosphere (the D-layer) and following interactions with the Earth's lithosphere due to the terrestrial electric current systems play a key role for aerosol nuclei and cloud generation and dynamics during sunspot maxima epochs. The GCR flux maximum absorption layer at heights of 35–40 km replaces the ionosphere D-layer role during the sunspot minima epochs. [ABSTRACT FROM AUTHOR]

We experimentally investigated a passive cavitation control approach to control partial and cloud cavitation on a National Advisory Committee for Aeronautics 0015 hydrofoil. For this approach, we implemented two different kinds of mesoscale bio-inspired riblets, known as scalloped riblets and sawtooth riblets, on the suction side of the hydrofoil near its leading edge. We studied the dynamics of partial and cloud cavitation on the hydrofoil with and without two kinds of riblets using a high-speed camera. In addition, we performed hydro-acoustic measurements to analyze the effects of this passive control on the cavitation induced noise in the wake of the hydrofoils. We considered flows at Reynolds numbers 0.5 × 106 and 0.6 × 106 with the hydrofoils at angles of attack of 8° and 10°. Results revealed that the cloud cavitation shedding on the hydrofoil suction surface was mitigated significantly due to the reduction in the re-entrant jet momentum. Also, the influence of tip vortex cavitation was reduced on the modified hydrofoils. Furthermore, the large-scale cavitation induced noise for the unmodified hydrofoil was located mostly at lower frequency in the range of 30 Hz, which was similar to the cavity shedding frequency. The small-scale vortex-induced noise concentrated at relative higher frequency between 100 and 120 Hz. The noise reduction in this study was achieved by scalloped and sawtooth riblets at low frequency domain and for some cases at higher frequency range by manipulating of the cavitation oscillation mechanism and elimination of a large-scale cavitation structure. This study provided new insight into controlling the destructive effects of cavitation using bio-inspired riblets, which should be relevant for various engineering applications. [ABSTRACT FROM AUTHOR]

Fast atmospheric processes such as deep convection and severe storms are challenging to observe and understand without adequate spatiotemporal sampling. Geostationary (GEO) imaging has the advantage of tracking these fast processes continuously at a cadence of the 10 min global and 1 min mesoscale from thermal infrared (TIR) channels. More importantly, the newly-available GEO-GEO stereo observations from our 3D-Wind algorithm provide more accurate height assignment for atmospheric motion vectors (AMVs) than those from conventional TIR methods. Unlike the radiometric methods, the stereo height is insensitive to radiometric TIR calibration of satellite sensors and can assign the feature height correctly under complex situation (e.g., multi-layer clouds and atmospheric inversion). This paper shows a case study from continuous GEO-GEO stereo observations over the Eastern Pacific during 1–5 February 2023, to highlight diurnal variations of clouds and dynamics in the planetary boundary layer (PBL), altocumulus/congestus, convective outflow and tropical tropopause layer (TTL). Because of their good vertical resolution, the stereo observations often show a wind shear in these cloud layers. As an example, the stereo winds reveal the classic Ekman spiral in marine PBL dynamics with a clockwise (counterclockwise) wind direction change with height in the Northern (Southern) Hemisphere subtropics. Over the Southeastern Pacific, the stereo cloud observations show a clear diurnal variation in the closed-to-open cell transition in the PBL and evidence of precipitation at a lower level from broken stratocumulus clouds. [ABSTRACT FROM AUTHOR]

Over the years, there have been discussions about the possibility of air pollution affecting the process of rain formation. In this study, we have developed a simplified model that represents the atmospheric dynamics and cloud microphysics to explore the impact of pollution on rain formation. We used an existing three-dimensional minimal model consisting of five equations, for which we added a simple bulk parametrization that represents the role of cloud condensation nuclei (CCN) in cloud formation processes. We conducted numerical tests using two CCN profiles, with either one or two accumulation layers and modified their abundance to explore the effects of different CCN concentrations and distributions. We conducted four numerical tests corresponding to the two aforementioned profiles with polluted and low-polluted scenarios. The numerical simulations suggested that a layer with high CCN concentration close to the surface tends to suppress precipitation, while the same concentration distributed over two layers tends to enhance the efficiency of rain formation. The simulations also showed that CCN particles far from the surface produced higher cloud tops and longer events, consistent with previous research. Although the model includes a stable representation of precipitating turbulent convection with bulk cloud microphysics, we expect its simplicity and conservation properties to allow for deeper theoretical analyses that can help us better understand the physical processes involved in the studied phenomenon. We hope this model will serve as a tool to explore different aerosol-related scenarios within the context of minimal models. [ABSTRACT FROM AUTHOR]

The homogeneous mixture model (HMM) is widely in use for simulation of cavitating flows. The mass transfer is typically ruled by simplified models whose efficiency is strictly dependent on the empirical choice of vaporization/condensation constants. In the present paper, we formulate a physically based mass-transfer model relying on the solution of the complete Rayleigh–Plesset (RP) equation. The latter can model the elasticity of the bubbles and non-linear interaction with the external pressure field. The model is tested in different configurations, also considering comparisons with the Schnerr–Sauer model (SSm) and the linearized version of the RP equation. The preliminary simplified tests show that the SS model responds statically to pressure variations and thus in not able to reproduce the actual dynamics of cavitation, under certain circumstances. On the other hand, the linearized RP model (RPl), although dynamically responsive to pressure variations, produces unrealistic small-amplitude bubble fluctuations, whereas the complete RP model (RPc) gives more realistic results. Tests on the performance of the SSm and RP models were carried out considering the turbulent flow in a convergent–divergent Venturi channel, already tested in numerical and experimental reference research. Here, we use the incompressible HMM. The study highlights various crucial aspects of the RPc model, emphasizing its own ability in replicating the shedding cycle as a three-dimensional, and non-stationary phenomenon. On the other hand, the SSm model results as a valid approximation for initial growth stages but fails to capture complex dynamics during the collapse phase. The results are consistent with recent literature findings, and refinements in grid resolution enhance accuracy in capturing the non-stationary sheet-to-cloud vapor dynamics. Neglecting compressibility may account for disparities between numerical and experimental outcomes, especially concerning shock waves generation and propagation. The RPc model emerges as a good candidate in reproducing bubble cloud dynamics and, in the next future, can be implemented in compressible HMM. [ABSTRACT FROM AUTHOR]

Aerosols erupted from volcanoes may significantly alter climate because they can impact cloud dynamics, radiation budget, and tropospheric chemistry. The optical and physical characteristics of the Spatio-temporal variation of aerosols and gases' impact on the atmosphere during the recent La Palma eruption have been examined in the current paper from 19 September to 31 October 2021. The result shows that before the La Palma eruption, the AOD value was 0.1 showing a clear sky. However, after the eruption daily mean AOD reached the highest values of 0.7 and 0.56, showing that La Palma had high aerosol loading when the eruption occurred. The 0.4 value Aerosol index was observed. The coarse mode aerosols contributed more to the overall aerosol load than fine mode aerosols, confirming their existence above La Palma. Analysis revealed that mixed aerosols were present over La Palma. Due to the powerful ash plume's ability to scatter sunlight, the high value of Single-Scattering Albedo (~ 0.99) was detected. The maximum concentration of SO2, HCHO, NO2, O3, and CO was found to be 60 mmol/m2, 120 µmol/m2, 70 µmol/m2, 129 mmol/m2, and 50 mmol/m2, respectively, over the La Palma region. The ash plume's trajectory by the forward trajectory and the Hybrid Single Particle Lagrangian Integrated Trajectory dispersion model showed the plume moving in the southwest direction. [ABSTRACT FROM AUTHOR]

In airborne data or model outputs, clouds are often defined using information about Liquid Water Content (LWC). Unfortunately LWC is not enough to retrieve information about the dynamical boundary of the cloud, that is, volume of turbulent air around the cloud. In this work, we propose an algorithmic approach to this problem based on a method used in time series analysis of dynamical systems, namely Recurrence Plot (RP) and Recurrence Quantification Analysis (RQA). We construct RPs using time series of turbulence kinetic energy, vertical velocity and temperature fluctuations as variables important for cloud dynamics. Then, by studying time series of laminarity (LAM), a variable which is calculated using RPs, we distinguish between turbulent and non‐turbulent segments along a horizontal flight leg. By selecting a single threshold of this quantity, we are able to reduce the number of subjective variables and their thresholds used in the definition of the dynamical cloud boundary. Plain Language Summary: Cloud is defined by the presence of liquid (or solid) water in the atmosphere. By agreeing on a certain threshold of liquid water content, one can define a cloud boundary. Cloud processes result in disturbances in the airflow around the cloud (turbulence). Its presence should allow the cloud dynamical boundary to be defined in a similar manner. However, a single simple variable, which could be used in an analogous way is not well defined. In this study we propose a method to define such a variable to distinguish between turbulent and non‐turbulent volumes around the cloud (i.e. determining dynamic cloud interface), adopting a method used in the study of dynamical systems. Based on recorded temperature and air velocity fluctuations characteristic for turbulent transport and mixing, a threshold of a variable named "laminarity" is used to define the dynamic cloud boundary on the aircraft trajectory. Key Points: A vector characterizing turbulence along the aircraft track based on velocity and temperature fluctuations is constructedA time series of this vector allows the construction of a Recurrence Plot, a tool used in studies of dynamical systemsA quantity named laminarity, derived from the Recurrence Plot, is used to detect turbulent and non‐turbulent regions [ABSTRACT FROM AUTHOR]

The purpose of this study is to understand the drivers of cloud droplet formation in orographic clouds. We used a combination of modeling, in-situ and remote sensing measurements at the high-altitude Helmos Hellenic Atmospheric Aerosol and Climate Change station ((HAC)2), which is located at the top of Mt. Helmos (1314 metres above sea level), Greece during the Cloud-AerosoL InteractionS in the Helmos background TropOsphere (CALISTHO) campaign in Fall 2021 (https://calishto.panacea-ri.gr/) to examine the origins of the aerosols (i.e., local aerosol from the Planetary Boundary Layer (PBL), or long-range transported aerosol from the Free Tropospheric Layer (FTL) contributing to the Cloud Condensation Nuclei (CCN), their characteristics (hygroscopicity, size distribution and mixing state), as well as the vertical velocities distributions and resulting supersaturations. We found that the characteristics of the PBL aerosol were considerably different from FTL aerosol and use the aerosol particle number and equivalent mass concentration of the black carbon (eBC) in order to determine when the (HAC)2 was within the FTL or PBL based on timeseries of the height of the PBL. During the (HAC)2 cloud events we sample a mixture of interstitial aerosol and droplet residues, which we characterize using a new approach that utilizes the in-situ droplet measurements to determine time periods where the aerosol sample is purely interstitial. From the dataset we determine the properties (size distribution and hygroscopicity) of the pre-cloud, activated and interstitial aerosol. The hygroscopicity of activated aerosol is found to be higher than that of the interstitial or pre-cloud aerosol. A series of closure studies with the droplet parameterization shows that cloud droplet concentration (N d) and supersaturation can be predicted to within 25 % of observations when the aerosol size distributions correspond to pre-cloud conditions. Analysis of the characteristic supersaturation of each aerosol population indicates that droplet formation in clouds is aerosol-limited when formed in FTL airmasses – hence droplet formation is driven by aerosol variations, while clouds formed in the PBL tend to be velocity limited and droplet variations are driven by fluctuations in vertical velocity. Given that the cloud dynamics do not vary significantly between airmasses, the variation in aerosol concentration and type is mostly responsible for these shifts in cloud microphysical state and sensitivity to aerosol. With these insights, remote sensing of cloud droplets in such clouds can be used to infer either CCN spectra (when in the FTL) or vertical velocity (when in the PBL). In conclusion, we show that a coordinated measurement of aerosol and cloud properties, together with the novel analysis approaches presented here allow for the determination of the drivers of droplet formation in orographic clouds and their sensitivity to aerosol and vertical velocity variations. [ABSTRACT FROM AUTHOR]

Cloud dynamics and their response to future climate change continue to present a significant source of uncertainty in climate predictions. Besides the average cloud properties, the diurnal cloud cycle (DCC) exerts a substantial influence on Earth's energy balance by reflecting solar radiation during the daytime and continuously absorbing and reemitting longwave radiation throughout the whole day. Previous studies have demonstrated that climate models exhibit certain discrepancies in simulating the DCC; however, less research attention has been paid to the patterns of these DCC biases and their impacts on modeling the Earth's energy balance. Here, we employ satellite data to compare DCC patterns in Coupled Model Intercomparison Project Phase 5 (CMIP5) and their latest versions in CMIP6 at both regional and global scales. We found that some of the latest climate models tend to have larger DCC biases when using satellite observations as the references, and the radiative effects due to DCC changes account for nearly 50% of the changes in total cloud radiative effects (CREs), suggesting that the DCC biases play a significant role in modelingthe global energy budget. We therefore call for improving cloud parameterization schemes with particular attention to their diurnal cycle to reduce their impacts on future climate projections. [ABSTRACT FROM AUTHOR]

Atmospheric deposition is an important source of the micronutrient selenium for terrestrial ecosystems and food chains. However, the factors determining the total concentrations and chemical forms (speciation) of selenium in atmospheric deposition remain poorly understood. Here, aerosol samples were collected weekly over 5 years at Pic du Midi Observatory (French Pyrenees), alongside highly temporally resolved samples of aerosols, precipitation, and cloud water taken during a 2-month campaign. Firstly, measurements of selenium, other elements, and water isotopes were combined with sophisticated modelling approaches (aerosol–chemistry–climate SOCOL-AERv2 model and air parcel backward trajectories and Lagrangian moisture source analyses). Aerosol selenium measurements agreed well with SOCOL-AERv2-predicted values, and interestingly, higher fluxes of selenium and other elements were associated with deep convective activity during thunderstorms, highlighting the importance of local cloud dynamics in high deposition fluxes. Our results further indicate the coupling of element and water cycles from source to cloud formation, with decoupling during precipitation due to below-cloud scavenging. Secondly, selenium speciation was investigated in relation to sulfur speciation, organic composition, and moisture sources. While in the 5-year aerosol series, selenite (Se IV) was linked to anthropogenic source factors, in wet deposition it was related to pH and Atlantic moisture sources. We also report an organic selenium fraction, tracing it back to a marine biogenic source in both aerosols and wet deposition. With a comprehensive set of observations and model diagnostics, our study underscores the role of weather system dynamics alongside source contributions in explaining the atmospheric supply of trace elements to surface environments. [ABSTRACT FROM AUTHOR]

The study of cloud and droplet dynamics during potential transmission events, such as coughing, is essential for understanding the spread and deposition of aerosols and droplets carrying airborne diseases. This paper reports the refinement of a complex model that couples momentum, temperature, and humidity for accurately simulating the dynamics of aerosol clouds and the dispersion of larger droplets under various conditions within an environmental chamber. The model is then employed to quantify aerosol/droplet exposure of a person standing 1 m away from a host. In addition, a statistical framework sheds light on the impact of backward coupling (droplet to cloud), which is negligible compared to forward coupling (cloud to droplet). The near-field study also provides detailed information on droplet behavior, laying the foundation for large-scale far-field studies. [ABSTRACT FROM AUTHOR]

This study investigates the rain-initiated mixing and variability in the concentration of selected trace gases in the atmosphere over the central Amazon rain forest. It builds on comprehensive data from the Amazon Tall Tower Observatory (ATTO), spanning from 2013 to 2020 and comprising the greenhouse gases (GHG) carbon dioxide (CO2) and methane (CH4), the reactive trace gases carbon monoxide (CO), ozone (O3), nitric oxide (NO), and nitrogen dioxide NO2 (NO2) as well as selected volatile organic compounds (VOC). Based on more than 1000 analyzed rainfall incidents, the study resolves the trace gas concentration patterns before, during, and after the rain events, along with its vertical concentration gradients across the forest canopy. The assessment of the rainfall events was conducted independently for daytime and nighttime periods, which allows us to elucidate the influence of solar radiation. The concentrations of CO2, CO, and CH4 clearly declined during rainfall, which can be attributed to the downdraft-related entrainment of pristine air from higher altitudes into the boundary layer, a reduction of the photosynthetic activity under increased cloud cover, as well as changes in the surface fluxes. Notably, CO showed a faster reduction than CO2, and the vertical gradient of CO2 and CO is steeper than for CH4. Conversely, the O3 concentration increased across all measurement heights in the course of the rain-related downdrafts. Following the O3 enhancement by up to a factor of two, NO and VOC concentrations decreased, whereas NO2 increased. The temporal and vertical variability of the trace gases is intricately linked to the diverse sink and source processes, surface fluxes, and free troposphere transport. Within the canopy, several interactions unfold among soil, atmosphere, and plants, shaping the overall dynamics. Also, the concentration of biogenic VOC (BVOC) clearly varied with rainfall, driven by factors such as light, temperature, physical transport, and soil processes. Our results disentangle the patterns in trace gas concentration in the course of the sudden and vigorous atmospheric mixing during rainfall events. By selectively uncovering processes that are not clearly detectable under undisturbed conditions, our results contribute to a better understanding of the trace gas life cycle and its interplay with meteorology, cloud dynamics, and rainfall in the Amazon and beyond. [ABSTRACT FROM AUTHOR]

We present a mathematical framework for describing the dynamical evolution of an ejecta cloud generated by a generic ejecta source model. We consider a piezoelectric sensor fielded in the path of an ejecta cloud, for experimental configurations in which the ejecta are created at a singly shocked planar surface and fly ballistically through vacuum to the stationary sensor. To do so, we introduce the concept of a time- and velocity-dependent ejecta "areal mass function." We derive expressions for the analytic ("true") accumulated ejecta areal mass at the sensor and the measured ("inferred") value obtained via the standard method for analyzing piezoelectric voltages. In this way, we derive an exact expression and upper bound for the error imposed upon a piezoelectric ejecta mass measurement (in a perfect system) by the assumption of instantaneous creation, which is commonly required for momentum diagnostic analyses. This error term is zero for truly instantaneous source models; otherwise, the standard piezoelectric analysis is guaranteed to overestimate the true mass. When combined with a piezoelectric dataset, this framework provides a unique solution for the ejecta particle velocity distribution, subject to the assumptions inherent in the data analysis. The framework also leads to strong boundary conditions that any ejecta source model must satisfy in order to be consistent with apparently global properties of piezoelectric measurements from a wide range of experiments. We demonstrate this methodology by applying it to the Richtmyer–Meshkov instability+self-similar velocity distribution ejecta source model currently under development at Los Alamos National Laboratory. [ABSTRACT FROM AUTHOR]

This review presents an insight into our current knowledge of the atmospheres of the planets Venus, Mars, Jupiter, Saturn, Uranus and Neptune, the satellite Titan, and those of exoplanets. It deals with the thermal structure, aerosol properties (hazes and clouds, dust in the case of Mars), chemical composition, global winds, and selected dynamical phenomena in these objects. Our understanding of atmospheres is greatly benefitting from the discovery in the last 3 decades of thousands of exoplanets. The exoplanet properties span a broad range of conditions, and it is fair to expect as much variety for their atmospheres. This complexity is driving unprecedented investigations of the atmospheres, where those of the solar systems bodies are the obvious reference. We are witnessing a significant transfer of knowledge in both directions between the investigations dedicated to Solar System and exoplanet atmospheres, and there are reasons to think that this exchange will intensity in the future. We identify and select a list of research subjects that can be conducted at optical and infrared wavelengths with future and currently available ground-based and space-based telescopes, but excluding those from the space missions to solar system bodies. [ABSTRACT FROM AUTHOR]

Model equations approximating the system of Boltzmann equations for a multicomponent gas are investigated. Methods for determining parameters in relaxation terms corresponding to cross-collision integrals are analyzed. Numerical solutions based on three model systems and the Boltzmann equations are compared as applied to the following problems: relaxation of a mixture to equilibrium, shock wave structure, and the dynamics of a vapor-gas cloud generated by pulsed laser irradiation of a target. It is shown that the parameters in the relaxation operators influence the degree of difference in the solutions produced by the various models. [ABSTRACT FROM AUTHOR]

The mass transport rate of wind‐borne particles, and indeed the fluid stress required for their entrainment, is strongly governed by inter‐particle cohesion arising from water retained through adsorption and capillary force. This paper reports on a series of wind tunnel experiments in which high‐speed photography was used to record the motion of dry sand particles as they impinged on test beds of systematically varied target gravimetric pore water content (0% ≤ W ≤ 10%). The wind friction velocity was preset to 0.33 m s−1, sufficient to maintain a saltation cloud above an upwind strip of dry sand, which then was blown over the wetted surface. Discrete particle trajectories were identified in the camera images using expected particle area searching–particle tracking velocimetry (EPAS‐PTV). Adding progressively more water produced an exponential decrease in the normalized particle number density over the test surface. The largest response was achieved by wetting the bed surface to just 2%. To reduce the number of particles by a further 40%, it was necessary to add eight times more water, signifying a diminishing return regarding water use. Relative to particles either rebounding or splashed from a dry bed, the total particle velocity increased incrementally by a factor between 1.5 and 2 with increasing water content. Increasing amounts of pore water were associated with progressively higher saltation trajectories, reaching a plateau beyond W ~8%. The spatio‐temporal adjustment in the sand cloud was observed to be extremely rapid. There is no consensus in the literature on how to measure the water content that effectively governs aeolian transport. In this study, all approaches to sampling W produced strong correlation (R2 ≥ 0.85). Sampling the topmost grains, however, provided the most accurate prediction of the normalized number density over the full range of water content. [ABSTRACT FROM AUTHOR]

Histotripsy is a non-thermal focused ultrasound ablation method that destroys tissue through the generation and activity of acoustic cavitation bubble clouds. Intrinsic threshold histotripsy uses single-cycle pulses to generate bubble clouds when the dominant negative pressure phase exceeds an intrinsic threshold of ∼25–30 MPa. The ablation efficiency is dependent upon the size and density of bubbles within the bubble cloud. This work investigates the effects of dual-frequency pulsing schemes on the bubble cloud behavior and ablation efficiency in intrinsic threshold histotripsy. A modular 500 kHz:3 MHz histotripsy transducer treated agarose phantoms using dual-frequency histotripsy pulses with a 1:1 pressure ratio from 500 kHz and 3 MHz frequency elements and varying arrival times for the 3 MHz pulse relative to the arrival of the 500 kHz pulse (−100 ns, 0 ns, and +100 ns). High-speed optical imaging captured cavitation effects to characterize bubble cloud and individual bubble dynamics. The effects of dual-frequency pulsing on lesion formation and ablation efficiency were also investigated in red blood cell (RBC) phantoms. Results showed that the single bubble and bubble cloud size for dual-frequency cases were intermediate to published results for the component single-frequencies of 500 kHz and 3 MHz. Additionally, bubble cloud size and dynamics were shown to be altered by the arrival time of the 3 MHz pulse with respect to the 500 kHz pulse, with more uniform cloud expansion and collapse observed for early (−100 ns) arrival. Finally, RBC phantom experiments showed that dual-frequency exposures were capable of generating precise lesions with smaller areas and higher ablation efficiencies than previously published results for 500 kHz or 3 MHz. Overall, results demonstrate dual-frequency histotripsy's ability to modulate bubble cloud size and dynamics can be leveraged to produce precise lesions at higher ablation efficiencies than previously observed for single-frequency pulsing. [ABSTRACT FROM AUTHOR]

We introduce an innovative two-week educational block course held at the University of Bonn during the 2023 winter semester, focusing on Cloud Model 1 (CM1) and its convection-permitting capabilities. During the course, students gained essential skills in setting up and customizing CM1 simulations on high-performance computing clusters, while delving into deep moist convection dynamics. An additional introduction to three-dimensional visualization software allowed the participants to transform numerical data into compelling visualizations, deepening their insights into cloud dynamics. Students applied their gained knowledge in research projects of their own choice that will be presented here and in the supplementary material. [ABSTRACT FROM AUTHOR]

The seeding effect of upper clouds on lower clouds affects the evolution of clouds, especially the seeding from upper ice clouds on lower stratiform clouds or convective clouds, which can stimulate the precipitation of lower clouds and even produce extreme precipitation. Because when seeders of seeding cloud enter the feeding cloud, the interaction between cloud particles results in the change of macro and micro parameters of the feeding cloud. Based on the observation data of the ground-based Ka-band millimeter-wave cloud radar (MMCR) and microwave radiometer (MWR) in spring and autumn from 2020 to 2022, the seeder-feeder phenomenon among double-layer clouds in China Xi'an was studied. The study on 11cases of seeder-feeder processes shows that the processes can be divided into three categories by defining the height difference (HD) between the seeding cloud base and the feeding cloud top, and the effective seeding depth (ESD). Through the analysis on the reflectivity factor and the radial velocity of cloud particles detected by MMCR and on the retrieved cloud dynamics parameters (vertical velocity of airflow and falling velocity of cloud particles), it is shown that the reflectivity factor in the cloud are significantly enhanced during the seeder-feeder period for the three types of processes. But there are different enhancements among the reflectivity factor profiles for the three seeder-feeder processes. The results also showed the limited depth as seeders entering the top of the feeding cloud. The lower and thinner the HD height was, the lower and thicker the ESD height was. On the contrary, the higher the HD height, the higher and thinner the ESD height. [ABSTRACT FROM AUTHOR]

Results of experiments on injection of dense plasma clouds created by a small-scale coaxial generator into vacuum and large-volume background plasma in an ambient magnetic field are presented. The regime of an "infinite" background medium that allows studying the plasma-cloud dynamics on the scale of about one meter in the directions perpendicular and parallel to a quasi-uniform magnetic field is realized on "Krot" plasma device. The dynamics of the diamagnetic cavity appearing upon magnetic-field expulsion by a plasma blob, the electromagnetic noise appearing in the cavity, along with the evolution of plasma-cloud structure during injection and at the stage of its decay, were studied. It is demonstrated that the key properties of the cloud dynamics that are typical of the active space and high-energy laboratory experiments, including complete expulsion of the magnetic field from the cloud and development of the flute instability at its boundary, are reproduced at low injection speed (below 30 km/s) and low plasma energy (on the order of 0.1 J). [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to examine the dynamism of causal relationships among cloud computing (CC) adoption factors in the Indian context, considering the perspectives of both the cloud adopter and cloud provider. Design/methodology/approach: The case-study method has been used to understand the dynamics among the factors. Using data from specific cases in India, causal loop diagrams (CLDs) have been developed. System dynamic modeling (SDM) and simulation are used to study the relationships and their effect on the adoption rate. Findings: The results revealed that adoption of CC depends on various factors such as persuasion (time-saving, cost-saving and word of mouth) and constraint factors (security and financial loss). However, it is seen that the adoption rate is very sensitive to changes in adoption per contact and word of mouth. Further, the adopter firm has a quicker time to market, which gives an added advantage to the firm. Also, with CC services, a firm can fulfill its projects or clients' requirements with little to no upfront investment in information technology (IT) services. Practical implications: Lack of security, standardization and undefined service-level agreements are a few pressing issues that make it difficult for firms to evaluate the performance and reliability of services. Hence, immediate attention is needed to make transparent policies on CC and its services, thereby building trust. Originality/value: This is the first and only work that has tried to explore and empirically test the dynamics of critical factors while making an adoption decision, considering both the adopter and provider perspectives. This study shows the journey of a firm, starting from being a prospective adopter to an adopter and continuous user. The work also empirically tested how adopters of technology benefit from the technology. [ABSTRACT FROM AUTHOR]

The vertical structure of three polar lows is described using profiling radar, lidar, and passive remote sensors deployed at a coastal site in northern Norway. The data were collected as part of the Cold‐air Outbreaks in the Marine Boundary Layer Experiment (COMBLE). These data are examined in the context of satellite imagery, operational weather radar reflectivity imagery, and output from the AROME Arctic model. A comparison to satellite images shows that AROME‐Arctic captured the polar lows well. All three polar lows form in marine cold‐air outbreaks and are surrounded by open‐cellular convection typical of such outbreaks. Two of the lows form in a forward shear environment and one under reverse shear. Initially, the three polar lows are comma shaped; two of them transition to be more spiraliform at their mature stage and have mostly cloud‐free warm cores. The warm cores are the result of a warm‐seclusion process. All three lows have stratiform precipitation bands, marked by little cloud liquid water, and rather high surface precipitation rate. The vertical drafts and turbulence in these stratiform clouds are generally weak. All three lows also have convective clouds, which have stronger vertical drafts, stronger turbulence, and pockets of high liquid water content. [ABSTRACT FROM AUTHOR]

Abstract In airborne data or model outputs, clouds are often defined using information about Liquid Water Content (LWC). Unfortunately LWC is not enough to retrieve information about the dynamical boundary of the cloud, that is, volume of turbulent air around the cloud. In this work, we propose an algorithmic approach to this problem based on a method used in time series analysis of dynamical systems, namely Recurrence Plot (RP) and Recurrence Quantification Analysis (RQA). We construct RPs using time series of turbulence kinetic energy, vertical velocity and temperature fluctuations as variables important for cloud dynamics. Then, by studying time series of laminarity (LAM), a variable which is calculated using RPs, we distinguish between turbulent and non‐turbulent segments along a horizontal flight leg. By selecting a single threshold of this quantity, we are able to reduce the number of subjective variables and their thresholds used in the definition of the dynamical cloud boundary.

For typical flow velocities in the interstellar medium (ISM), the Kelvin–Helmholtz instability (KHI) may result in the development of structures in molecular clouds near the interface between the clouds and H  ii regions flowing past them (Berné et al. 2010). Ambipolar diffusion (AD) is one of the significant mechanisms considered frequently in the dynamics of molecular clouds. It may play a relevant role in the development of the KHI in the interface of the H  ii region and the molecular clouds. Here, we examine the role of AD in the evolution of the KHI, using linear perturbation analysis. We model the interaction of two regions as a planar discontinuity separating two fluids in relative motion. Linear analysis, for a certain range of magnetosonic Mach number of flow (⁠|$\mathcal {M}_{sA1}\lt 1$|⁠), shows that AD has a destabilizing effect on the KHI and consequently decreases the e-fold time-scale of instability. The results indicate that AD is more effective on the KHI for large magnetosonic Mach numbers than for low magnetosonic Mach numbers. This may give rise to the development of larger numbers of KH structures in high-velocity flows. The results also indicate that AD is more effective for perturbation wavelengths |$\lambda _{\rm KH} \ \lt \ 1\rm pc$| than for |$\lambda _{\rm KH}\gt 1\rm pc$|⁠. This nominates a length-scale (⁠|$L=1 \rm \, pc$|⁠) above which AD is not important for the formation of KH structures. Conforming to the results, AD is proposed as a triggering factor in the development of the small-scale KH structures in the regions of high-velocity streams in ISM. [ABSTRACT FROM AUTHOR]

In this research, we delve into the influence of cloud condensation nuclei (CCN) and ice-nucleating particles (INP) concentrations on the morphology and abundance of ice particles in mixed-phase clouds, emphasizing the consequential impact of ice particle shape, number, and size on cloud dynamics and microphysics. Leveraging the synergy of the Advanced Microphysics Prediction System (AMPS) and the Kinematic Driver (KiD) model, we conducted simulations to capture cloud microphysics across diverse CCN and INP concentrations. The Passive and Active Microwave radiative TRAnsfer (PAMTRA) radar forward simulator further augmented our study, offering insights into how the concentrations of CCN and INP affect radar reflectivities. Our experimental framework encompassed CCN concentrations ranging from 10 to 5000 cm−3 and INP concentrations from 0.001 to 10 L−1. Central to our findings are the observation that increased INP concentrations yield smaller ice particles, while a surge in CCN concentrations leads to a subtle growth in their dimensions. Consistent with existing literature, our results spotlight plate-like crystals as dominant between temperatures of −20 to −16 °C. Notably, high INP scenarios unveiled a significant prevalence of irregular polycrystals. The Aspect Ratio (AR) of ice particles exhibited a decline with the rise in both CCN and INP concentrations, highlighting the nuanced interrelation between CCN levels and ice particle shape, especially its ramifications on the riming mechanism. The forward-simulated radar reflectivities, spanning from −11.83 dBZ (low-INP, 0.001 L−1) to 4.65 dBZ (high-INP, 10 L−1), elucidate the complex dynamics between CCN and INP in determining mixed-phase cloud characteristics. Comparable differences in radar reflectivity were also reported from observational studies of stratiform mixed-phase clouds in contrasting aerosol environments. Our meticulous analysis of KiD-AMPS simulation outputs, coupled with insights into aerosol-driven microphysical changes, thus underscores the significance of this study in refining our ability to understand and interpret observations and climate projections. [ABSTRACT FROM AUTHOR]

Using multi‐satellite observations, the cloud dynamic and microphysical characteristics were revealed during the rapid intensification (RI) of super‐typhoon Nanmadol (2022). As the storm intensifies, the eyewall contracts, the upper‐level divergence strengthens, and the cirrus cloud increases, leading to stronger upper‐level radial outflow and the vertical updraft. Meanwhile, it is found that there exists a dynamically attractive area in the outer rainbands, where particles grow effectively and form "a small amount of large particles" around 300 km from the eye. A theory of cloud dynamics‐microphysics interaction, called "tunnel theory," is further proposed to explain the generation, accumulation, and concentrated downflow of large particles in the outer rainbands during RI. Results suggest the unique feature of particle distribution in the outer rainbands could be a potential indicator for RI. Plain Language Summary: The rapid intensification (RI) of tropical cyclones (TCs) becomes more frequent in recent years, but the TC RI forecasts still remain challenging. Better understanding of the physical processes associated with RI of TCs would essentially improve its forecasting capability. The cloud dynamical and microphysical processes, especially their interactions that respond to RI are not well explored. In this study, the cloud macro and micro characteristics associated with RI of a super‐typhoon Nanmadol (2022) over the western Pacific are investigated using multiple satellites observations. The storm underwent RI during 15–16 September 2022, and it has wreaked havoc on Japan's most cities as it moved across the Japanese island afterward with a track length of about 1,120 km. It is found inside Nanmadol as well as other typhoons that a few large particles tend to occur in the outer rainbands during RI, due to the interaction of cloud dynamical and microphysical processes. Such unique feature of particle distribution in the outer rainbands could be a potential indicator for RI, and should also be paid attention to in model forecasting of typhoon precipitation. Key Points: First satellite‐based observational study on the interaction of cloud dynamics and microphysics during typhoon rapid intensification (RI)The eyewall contracts, the upper‐level divergence strengthens, and the convection column increases, providing kinetic energy for typhoon RIA "tunnel theory" is proposed for the generation, accumulation, and downflow of large particles in the outer rainbands during typhoon RI [ABSTRACT FROM AUTHOR]

• Method to forecast 1-min irradiance based on post-processing NWP output using ML. • Findings are proven to be generalizable throughout the Netherlands. • Feature importance can be thoroughly examined. • Algorithm suitable for operational application at day-ahead lead times. Accurate forecasts of solar irradiance are required for the large-scale integration of solar photovoltaic (PV) systems. Fluctuations of energy generation in the order of minutes can lead to issues on the electricity grid, therefore reliable forecasts of minute-to-minute irradiance variability are required. However, state of the art numerical weather predictions (NWP) deliver forecasts at a much coarser temporal resolution, e.g. hourly, missing crucial information on meteorological variability such as clouds. In this work we present a methodology to forecast minute-to-minute irradiance variability in terms of its probability density function (PDF) based on hourly NWP results, by applying statistical postprocessing using machine learning. The algorithm is tested using the 2.5 × 2.5 km2 HARMONIE-AROME (HA) mesoscale model as input, with 1-minute irradiance observations for 18 meteorological stations throughout the Netherlands used as a ground truth. The applicability of the algorithm to 31 × 31 km2 global-scale models is investigated using ERA5 reanalysis data, which yields comparable accuracies. We find that almost half of the inaccuracy of the postprocessed result is due to errors in the radiation forecast of the NWP model used as input. Finally, the proposed post-processing algorithm is compared to the next generation weather models based on high resolution Large Eddy Simulation (LES), at 75 m horizontal grid spacing, on a case study spanning four days. While LES underestimates values of high irradiance due to lack of 3D radiative effects, it enables detailed analysis of cloud and irradiance dynamics at high spatial and temporal resolution unreachable by statistical postprocessing. [ABSTRACT FROM AUTHOR]

The increasing penetration of solar energy leaves power grids vulnerable to fluctuations in the solar radiation that reaches the surface of the Earth due to the projection of cloud shadows. Therefore, an intra-hour solar forecasting algorithm is necessary to reduce power instabilities caused by the impact of moving clouds on energy generation. The most accurate intra-hour solar forecasting methods apply convolutional neural networks to a series of visible light sky images. Instead, this investigation uses data acquired by a novel infrared sky imager on a solar tracker, which is capable of maintaining the Sun in the center of the images throughout the day and, at the same time, reducing the scattering effect produced by the Sun's direct radiation. In addition, infrared sky images allow the derivation and extraction of physical cloud features. The cloud dynamics are analyzed in sequences of images to compute the probability of the Sun intercepting air parcels in the sky images (i.e., voxels). The method introduced in this investigation fuses sky condition information from multiple sensors (i.e., pyranometer, sky imager, solar tracker, weather station) and feature sources using a multi-task deep learning architecture based on recurrent neural networks. The proposed deterministic and Bayesian architectures reduce computation time by avoiding convolutional filters. The proposed intra-hour solar forecasting algorithm reached a forecast skill of 18.6% with a forecasting horizon of 8 min. Consequently, the proposed intra-hour solar forecasting method can potentially reduce the operational costs of power grids with high participation of solar energy. • Novel multi-task intra-hour solar forecast fusing information from multiple sensors. • The performances of different extracted features are compared for a solar forecast. • An innovative method to compute the probability of an air parcel occluding the Sun's. • The proposed methodology simplifies the models by avoiding convolutional filters. • Bayesian implementation of the optimal architecture to quantify the uncertainty. [ABSTRACT FROM AUTHOR]

An idealized large eddy simulation (LES) has been performed to understand the dynamics of cumulus clouds over the Bay of Bengal using the Weather Research and Forecasting (WRF) model. Cumulus clouds play a key role in the atmospheric convection process. However, despite their importance, they are not well represented in global climate models (GCMs). Moreover, cumulus clouds involve a transition from shallow to deep clouds (or congestus clouds), and GCMs are unable to capture this phenomenon. The development of cumulus clouds is very pronounced over the Bay of Bengal region, and its dynamics has not yet been fully explored. In the present study, a gradual transition phenomenon of shallow cumulus to deep cumulus (congestus) at the development stage and understanding the evolution of clouds and flux transport is investigated. Different cloud parameters at shallow and deep cumulus congestus stages are examined. It is observed that the shallow clouds have a higher magnitude of entrainment than that of deep clouds, and the rate of decrease in entrainment with height is also higher for the shallow clouds. Moreover, the detrainment rate is higher in the case of shallow cumulus clouds as well. This means that as the clouds have transitioned from shallow cumulus to deep congestus clouds, both entrainment and detrainment rates decrease. This important finding will be quite useful in developing future parameterizations for cumulus clouds. A negative correlation between the entrainment rate and cloud core vertical velocity is observed which is supported by previous studies. [ABSTRACT FROM AUTHOR]

Atmospheric deposition is an important source of the essential trace element selenium (Se) to terrestrial ecosystems and food chains. The fate of Se supplied to surface environments by atmospheric deposition strongly depends on total Se concentrations as well as its chemical form (speciation). However, the factors determining total Se and its speciation in atmospheric deposition remain poorly understood. Here, we applied different chemical measurements to aerosol samples taken at a weekly resolution over 5 years (2015–2019), as well as precipitation and cloud water samples taken during a field campaign of two months in 2019 at Pic du Midi Observatory (French Pyrenees; 2877 m a.s.l.) and combined these observations with sophisticated modelling approaches. The high-altitude site enables the investigation of local and long-range elemental transport from both marine and continental sources and the role of different weather systems in elemental deposition. Total concentrations of trace elements were measured in aerosol extracts and wet deposition, and Se speciation was obtained with an optimized chromatographic method coupled to inductively coupled plasma tandem mass spectrometry (LC-ICP-MS/MS). These analyses were combined with molecular organic compound analysis by pyrolysis-gas chromatography mass spectrometry (Py-GC-MS). For modelling the source contributions to Se, we used a combination of i) a Eulerian approach with the atmospheric aerosol-chemistry-climate model SOCOL-AERv2, and ii) a Lagrangian approach with air parcel backward trajectories and a moisture source diagnostics. While weekly Se measurements in the 2015–2020 aerosol time series agreed very well (r ~0.8) with SOCOL-AERv2 model results, the higher Se concentrations (>0.05 ng·m-3) observed in summer were underestimated by the model. We could explain these higher concentrations in summer by convection related to thunderstorms that led to high aerosol loadings and which are not resolved explicitly in the model. In addition, convective events, associated with continental moisture sources, also explained the highest concentrations of Se and most other trace elements in wet deposition, due to efficient below cloud scavenging, indicating the importance of local cloud dynamics on the supply of Se and other, essential and non-essential, trace elements to surface environments. While data for water isotopes in precipitation indicated an uncoupling of hydrological and trace element cycling related to below cloud scavenging, cloud water isotopes and trace elements showed high correlations indicating that the water and trace element cycles are strongly coupled from the source to the formation of clouds with a possible decoupling occurring during precipitation. Furthermore, cloud water showed more regional trace element and moisture sources than precipitation samples. With this comprehensive set of observations and model diagnostics we could explain inorganic Se speciation in unprecedented detail by linking moisture sources and organic chemical compounds in aerosols to speciation data of Se and S, indicating local vs long-range transport and anthropogenic vs natural Se sources. We report for the first-time organic Se in precipitation (and aerosols), for which we could elucidate a marine biogenic source. Our study thus provides new insights into the factors explaining atmospheric deposition of Se and other trace elements and highlights the importance of weather system dynamics in addition to source contributions for the atmospheric supply of trace elements to surface environments. [ABSTRACT FROM AUTHOR]

Through a combination of idealized simulations and real-world data, researchers are uncovering how internal feedbacks and large-scale motions influence cloud dynamics. [ABSTRACT FROM AUTHOR]

We performed a sensitivity study on the life span of a numerically simulated storm using the parameterization of the ventilation coefficient. This is an expanded sequel to our previous study, where the ventilation effect of precipitation particles (snow, rain, and hail) was either halved or doubled as a whole. In this study, we tested the sensitivity of the ventilation coefficient for different precipitation particles and compared that with the previous results. In the present study, we changed the ventilation coefficient in two scenarios: (1) only the rain category was changed; (2) only the snow and hail categories were changed. The results show that these different scenarios lead to different evolution paths for the storm. In general, reducing the ventilation effect of rain leads to quick dissipation, whereas enhancing the ventilation of either rain or snow/hail leads to the development of multicellular storms. An analysis of the physical mechanisms leading to such results is provided. This study shows yet another example of how a change in a cloud's microphysical parameterization can lead to a profound change in its larger-scale dynamical process. [ABSTRACT FROM AUTHOR]

We present a variety of analyses of the turbulent dynamics of the boundary of a photodissociation region (PDR) in the Carina Nebula using high resolution ALMA observations. Using principal component analysis, we suggest that the turbulence in this molecular cloud is driven at large scales. Analysis of the centroid velocity structure functions indicate that the turbulence is dominated by shocks rather than local (in k -space) transport of energy. We further find that length-scales in the range 0.02–0.03 pc are important in the dynamics of this cloud and this finding is supported by analysis of the dominant emission structure length-scale. These length-scales are well resolved by the observational data and we conclude that the apparent importance of this range of scales is physical in origin. Given that it is also well within the range strongly influenced by ambipolar diffusion, we conclude that it is not primarily a product of turbulence alone, but is more likely to be a result of the interplay between gravity and turbulence. Finally, through comparison of these results with previous observations of H2 emission from the Western Wall, we demonstrate that observations of a PDR can be used to probe the internal structure of the undisturbed portion of a molecular cloud. [ABSTRACT FROM AUTHOR]

Task scheduling algorithms based on reinforce learning (RL) have been important methods with which to improve the performance of cloud platforms; however, due to the dynamics and complexity of the cloud environment, the action space has a very high dimension. This not only makes agent training difficult but also affects scheduling performance. In order to guide an agent's behavior and reduce the number of episodes by using historical records, a task scheduling algorithm based on adaptive priority experience replay (APER) is proposed. APER uses performance metrics as scheduling and sampling optimization objectives with which to improve network accuracy. Combined with prioritized experience replay (PER), an agent can decide how to use experiences. Moreover, this algorithm also considers whether a subtask is executed in a workflow to improve scheduling efficiency. Experimental results on Tpc-h, Alibaba cluster data, and scientific workflows show that a model with APER has significant benefits in terms of convergence and performance. [ABSTRACT FROM AUTHOR]

The main energy input to the polar regions in winter is the advection of warm, moist air from lower latitudes. This makes the polar climate sensitive to the temperature and moisture of extrapolar air. Here, we study this sensitivity from an air-mass transformation perspective. We perform simulations of an idealized maritime air mass brought into contact with sea ice employing a three-dimensional large-eddy simulation model coupled to a one-dimensional multilayer sea ice model. We study the response of cloud dynamics and surface warming during the air-mass transformation process to varying initial temperature and humidity conditions of the air mass. We find in all cases that a mixed-phase cloud is formed, initially near the surface but rising continuously with time. Surface warming of the sea ice is driven by downward longwave surface fluxes, which are largely controlled by the temperature and optical depth of the cloud. Cloud temperature, in turn, is robustly constrained by the initial dewpoint temperature of the air mass. Since dewpoint only depends on moisture, the overall result is that surface warming depends almost exclusively on initial humidity and is largely independent of initial temperature. We discuss possible climate implications of this result}in particular, for polar amplification of surface warming and the role played by atmospheric energy transports. [ABSTRACT FROM AUTHOR]

Cloud forests are highly diverse mountain ecosystems, but habitat loss and fragmentation threaten many species with extinction. Demographic parameters are essential to implement effective conservation actions and to understand the mechanisms of species coexistence, but there are very few population models with transition matrices for fern species. We evaluated the demographic dynamics of three coexisting fern species of different growth form in a cloud forest in eastern central Mexico for six years. The matrix analyses showed that the populations of a trunk‐forming fern (Cyathea divergens) and a short caulescent fern (Marattia laxa) were stable while the population of a trunkless, herbaceous fern (Parablechnum schiedeanum) was decreasing. Survival was the demographic process of the life cycle that contributed the most to the population growth of the three species. As expected, with shorter longevity and high precocity, P. schiedeanum exhibited the demographic pattern of herbaceous species. In contrast, with greater longevity and a longer maturation period, the demography of C. divergens and M. laxa was more comparable with that of tree species. Our results support the hypothesis that the demography of the tropical fern species can be compared with life‐history strategies of angiosperms and gymnosperms. [ABSTRACT FROM AUTHOR]

Releasing diffuse artificial clouds into the space environment using a rocket or spacecraft can modify the natural plasma state. This uses space itself as a laboratory for studying plasma phenomena that cannot be reproduced on the ground. The Space Measurement of A Rocket‐released Turbulence (SMART) mission will inject a beam of barium neutral vapor into the ionosphere and perpendicular to the Earth's magnetic field. Barium atoms will be photoionized, forming an ion ring distribution that is unstable to lower hybrid waves. Large amplitude lower hybrid waves nonlinearly scatter to whistler and magnetosonic waves that can propagate out to the magnetosphere. This paper details the theory, modeling, and simulation we used to design this release experiment to optimize the energy in the plasma waves under a variety of constraints. A product of this analysis is quantitative predictions for some in situ and remote measurements. Hydrocode simulations of barium vapourization and acceleration via shaped charge provide the initial state of the neutral beam. We optimize the apogee, orientation, and position of the payload and instruments. Cloud dynamics are simulated with a direct simulation Monte Carlo technique, which includes photoionization with metastable barium states, collisions with the neutral background atmosphere, optical line emission, gravity, and electromagnetic forces. We predict the plasma density measured by the instrument payload and the remotely measured optical intensity. We also examine how the plasma wave growth differs at the measurement location compared to the bulk of the barium cloud. Key Points: A variety of models and simulations are combined to optimize plasma wave energy in a neutral beam injection experimentModeling provides quantitative predictions of measurements (e.g., plasma density, beam velocity, total barium produced, optical intensity)We discuss the many details that arose between concept and implementation of the experiment, and how these affected mission design [ABSTRACT FROM AUTHOR]