Cloud Trajectories Research Articles

Diurnal Patterns in the Observed Cloud Liquid Water Path Response to Droplet Number Perturbations

AbstractA key uncertainty in Aerosol‐cloud interactions is the cloud liquid water path (LWP) response to increased aerosols (λ). LWP can either increase due to precipitation suppression or decrease due to entrainment‐drying. Previous research suggests that precipitation suppression dominates in thick clouds, while entrainment‐drying prevails in thin clouds. The time scales of the two competing effects are vastly different, requiring temporally resolved observations. We analyze 3‐day Lagrangian trajectories of stratocumulus clouds over the southeast Pacific using 2019–2021 geostationary data. We find that clouds with a LWP exceeding 200 g m−2 exhibit a positive response, while clouds with lower LWP show a negative response. We observe a significant diurnal cycle in λ, indicating a more strongly negative daytime adjustment driven by entrainment‐drying. In contrast, at night, precipitation suppression can occasionally fully counteract the entrainment‐drying mechanism. Overall, λ appears weaker than previously suggested in studies that do not account for the diurnal cycle.

A Spraying Path Planning Algorithm Based on Point Cloud Segmentation and Trajectory Sequence Optimization

A Spraying Path Planning Algorithm Based on Point Cloud Segmentation and Trajectory Sequence Optimization

Cloud Trajectory Correction Prediction Method Combining Lightweight Tracking and Historical Information Feedback

Cloud Trajectory Correction Prediction Method Combining Lightweight Tracking and Historical Information Feedback

Development of parameter-free, two-fluid, viscous multiphase flow solver for cough-droplet simulations

Multiphase flows arise in various fields that involve complicated phenomena. Studies have shown that COVID-19 can occur via air microdroplets, and breathing jets with microdroplets turn into turbulent cloud or puffs in cases of coughing and sneezing (Bourouiba et al., 2014). Microdroplets are upturned by buoyancy in the turbulent cloud and transported without falling. Furthermore, they float in air for hours and can be transported over long distances (Mittal et al., 2020). This scenario also involves a mixed phase flow of air and droplets. To simulate these phenomena, a numerical model assuming mechanical and thermal non-equilibrium multiphase flow is required to predict the range of turbulent cloud transport. In this study, to better simulate the turbulent cloud trajectories, a viscosity term is added to a two-phase flow six-equation model (two-fluid modeling or effective-fluid modeling, EFM) developed by Liou et al. (2008). It is a development of a parameter-free, viscous multiphase flow code, based on a single-phase compressible finite-volume solver (Kitamura et al., 2013). This solver is validated in the Poiseuille flow and laminar-flat-plate problem with an isothermal wall through a comparison with the analytical solutions. A detailed simulation of coughing is performed. The location of the turbulent cloud upturned by buoyancy is compared with the data of past studies.

An Optimal Algorithm for Renewable Energy Generation Based on Neural Network

Solar energy is a costless and readily available form of energy that has shown to be one of the cleanest and most plentiful renewable energy sources. Various large-scale solar photovoltaic (PV) facilities are being utilized to minimize pollution and carbon emissions generated by fossil energy in many nations across the world. The power sequence of PV is influenced by a variety of diverse variables, and it is very unpredictable and volatile. Unlike the distributed PVs, the centralized PVs have the same intensity and location. The obstruction of clouds causes minor variations in the output power of the PV, making the power forecasting more difficult. To solve the aforementioned difficulties, this article provides a new neural network-based technique for PV power optimization and forecasting. The first stage is to create a cloud trajectory tracking system based on cloud photos taken from the ground. Second, a cloud trajectory tracking-based irradiance coefficient prediction model was built. Then, to increase forecast accuracy, build an error correcting model. For verification, data from a centralized solar power station was used. The results show that the proposed algorithm has technological applications and may greatly improve prediction accuracy.

Human action recognition method based on historical point cloud trajectory characteristics

Human action recognition method based on historical point cloud trajectory characteristics

Detection of the Milky Way reflex motion due to the Large Magellanic Cloud infall

The Large Magellanic Cloud is the most massive satellite galaxy of the Milky Way, with an estimated mass exceeding a tenth of the mass of the Milky Way. Just past its closest approach of about 50 kpc, and flying by the Milky Way at an astonishing speed of 327 km/s, the Large Magellanic Cloud can affect our Galaxy in a number of ways, including dislodging the Milky Way disc from the Galactic centre-of-mass. Here, we report evidence that the Milky Way disc is moving with respect to stellar tracers in the outer halo ($40<r<120$ kpc) at $v_{\rm travel}=32^{+4}_{-4}$ km/s, in the direction $(\ell,b)_{\rm apex}=(56^{+9}_{-9},-34^{+10}_{-9})$ degrees, which points at an earlier location on the LMC trajectory. The resulting reflex motion is detected in the kinematics of outer halo stars and Milky Way satellite galaxies with accurate distances, proper motions and line-of-sight velocities. Our results indicate that dynamical models of our Galaxy cannot neglect gravitational perturbations induced by the Large Magellanic Cloud infall, nor can observations of the stellar halo be treated in a reference frame that does not correct for disc reflex motion. Future spectroscopic surveys of the stellar halo combined with Gaia astrometry will allow for sophisticated modelling of the Large Magellanic Cloud trajectory across the Milky Way, constraining the dark matter distribution in both galaxies with unprecedented detail.

Gravity theory tests with observations of stars near the black hole at the Galactic Center

One could say that 2018 is very special year since 55 years ago quasars were discovered, the Kerr solution has been found and the First Texas Symposium on Relativistic Astrophysics has been organized. In addition, 50 years ago, in 1968 the pulsar discovery paper has been published and the black hole concept has presented by J. A. Wheeler in his groundbreaking paper which was based on his report in December 1967. In last years remarkable achievements have been done in gravitational physics and related observations, in particular, gravitational waves and binary black holes with high stellar masses have been discovered, VLT, Keck and GRAVITY observe trajectories of bright stars and gas clouds near the Galactic Center (GC) with improving accuracy. It is clear that the Galactic Center (Sgr A*) is a specific place. Our Sun is located at a distance around 8 kpc from the Galactic Center (GC). Earlier, astronomers suggested a number of different including exotic ones such as boson stars, fermion balls, neutrino balls, a cluster of neutron stars. Some of these models are ruled out or significantly constrained with consequent observations. A supermassive black hole with mass around 4 × 106 Mʘ is the most realistic model for GC. Precision observations of bright stars near the Galactic Center and observations of bright structures near the black hole at the Galactic Center to reconstruct shadow structure around the black hole with current and future observational VLBI facilities such as the Event Horizon Telescope give opportunities to test alternative theories of gravity. In particular, we got a graviton mass constraint which is comparable and consistent with constraints obtained recently by the LIGO-Virgo collaboration. We consider opportunities to improve current graviton mass mass constraints with future observations of bright stars. Similarly, from an analysis of bright star trajectories one could constrain a tidal charge which was predicted by a gravity theory with an additional dimension.

A modal analysis of the size distribution for an hollow-cone spray in cross-flow

Studying sprays in cross-flow is a challenge as well in the design of combustion engines as for spray cooling of heat exchanger. In the latest applications, small particles with high cooling efficiency are injected in the air flow. Some studies have documented particle velocities and diameters in spray plume using Phase Doppler Analysis or photographic techniques. The present contribution focusses on the particle spatial distribution during their far-field dispersion in airflow. Size distribution measurements inside sprays were made with a high spatial resolution using a Phase Doppler Analyzer. Afterwards, the particle size in measurement planes are analysed using a statistical procedure of data analysis, which breaks down the particle cloud into groups. It uses the same concept than “Modal Models”, whose decompose the aerosol cloud into different modes or bins. This method is applied to a spray generated with an hollow-cone nozzle, in both with and without airflow. The clustering approach allows to identify a cloud of fine particles, that is spatially distinct of the coarse and intermediate groups. In a resting atmosphere, coarse particles are concentrated in the periphery of the spray whereas small droplets are confined in the centre, revealing the typical shape of hollow-cone nozzle spray. Cloud trajectories of coarse, intermediate and fine modes are dissociated in cross flow conditions. The classification facilitates the trajectory monitoring for each group and localisation of falling regions: the fall of coarse particles may be roughly approximated with the equation of motion for a single coarse particle. The fine and intermediate particles falls more rapidly than the equation’s prognostic. Noticeable lateral deviations of clouds are also observed. The kidney shape observed for the coarse cloud fits the thermal footprint of spray on heat exchanger. Other shapes, like horse-shoe and vortex-bag, are founded for intermediate and fine particles. Large particles acts as curtain and induces airflow perturbations that are associated with the particular shape of fine and intermediate clouds. The modal analysis provides an efficient tool for studying particles and should be further used with 2 or 3-dimensional measurements in order to study drift vortices.

A Novel Cloud Removal Method Based on IHOT and the Cloud Trajectories for Landsat Imagery

Cloud removal is a prerequisite for the application of Landsat datasets, as such satellite images are invariably contaminated by clouds. Clouds affect the transmission of radiation signal to different degrees because of their different thicknesses, shapes, heights and distributions. Existing methods utilize pixel replacement to remove thick clouds and pixel correction techniques to rectify thin clouds in order to retain the land surface information in contaminated pixels. However, a major limitation of these methods refers to their deficiency in retrieving land surface reflectance when both thick clouds and thin clouds exist in the images, as the two types of clouds differ in the transmission of radiation signal. As most remotely sensed images show rather complex cloud contamination patterns, an efficient method to alleviate both thin and thick cloud effects is in need of development. To this end, the paper proposes a new method to rectify cloud contamination based on the cloud detection of iterative haze-optimized transformation (IHOT) and the cloud removal of cloud trajectory (IHOT-Trajectory). The cloud trajectory is able to take consideration of signal transmission for different levels of cloud contamination, which characterizes the spectral response of a certain type of land cover under increasing cloud thickness. Specifically, this method consists in four steps. First, the cloud thicknesses of contaminated pixels are estimated by the IHOT. Second, areas affected by cloud shadows are marked. Third, cloud trajectories are fitted with the aid of neighboring similar pixels under different cloud thickness. Last, contaminated areas are rectified according to the relationship between the land surface reflectance and the IHOT. The experimental results indicate that the proposed approach is able to effectively remove both the thin and thick clouds and erase the cloud shadows of Landsat images under different scenarios. In addition, the proposed method was compared with the dark object subtraction (DOS), the modified neighborhood similar pixel interpolator (MNSPI) and the multitemporal dictionary learning (MDL) methods. Quantitative assessments show that the IHOT-Trajectory method is superior to the other cloud removal methods overall. For specific spectral bands, the proposed method performs better than other methods in visible bands, whereas it does not necessarily perform better in infrared bands.

Spatial distribution of volcanic ash deposits of 2011 Puyehue-Cordón Caulle eruption in Patagonia as measured by a perturbation in NDVI temporal dynamics

Volcanic ash fallout is a recurrent environmental disturbance in forests, arid and semi-arid rangelands of Patagonia, South America. The ash deposits over large areas are responsible for several impacts on ecological processes, agricultural production and health of local communities. Public policy decision making needs monitoring information of the affected areas by ash fallout, in order to better orient social, economic and productive aids. The aim of this study was to analyze the spatial distribution of volcanic ash deposits from the eruption of Puyehue-Cordón Caulle in 2011, by identifying a sudden change in the Normalized Difference Vegetation Index (NDVI) temporal dynamics, defined as a perturbation located in the time series. We applied a sparse-wavelet transform using the Basis Pursuit algorithm to NDVI time series obtained from the Moderate Resolution Image Spectroradiometer (MODIS) sensor, to identify perturbations at a pixel level. The spatial distribution of the perturbation promoted by ash deposits in Patagonia was successfully identified and characterized by means of a perturbation in NDVI temporal dynamics. Results are encouraging for the future development of a new platform, in combination with data from forecasting models and tracking of ash cloud trajectories and dispersion, to inform stakeholders to mitigate impact of volcanic ash on agricultural production and to orient public intervention strategies after a volcanic eruption followed by ash fallout over a wide region.

Investigation of diocotron modes in toroidally trapped electron plasmas using non-destructive method

Experiments with trapped electron plasmas in a SMall Aspect Ratio Toroidal device (SMARTEX-C) have demonstrated a flute-like mode represented by oscillations on capacitive (wall) probes. Although analogous to diocotron mode observed in linear electron traps, the mode evolution in toroids can have interesting consequences due to the presence of in-homogeneous magnetic field. In SMARTEX-C, the probe signals are observed to undergo transition from small, near-sinusoidal oscillations to large amplitude, non-linear “double-peaked” oscillations. To interpret the wall probe signal and bring forth the dynamics, an expression for the induced current on the probe for an oscillating charge is derived, utilizing Green's Reciprocation Theorem. Equilibrium position, poloidal velocity of the charge cloud, and charge content of the cloud, required to compute the induced current, are estimated from the experiments. Signal through capacitive probes is thereby computed numerically for possible charge cloud trajectories. In order to correlate with experiments, starting with an intuitive guess of the trajectory, the model is evolved and tweaked to arrive at a signal consistent with experimentally observed probe signals. A possible vortex like dynamics is predicted, hitherto unexplored in toroidal geometries, for a limited set of experimental observations from SMARTEX-C. Though heuristic, a useful interpretation of capacitive probe data in terms of charge cloud dynamics is obtained.

Homogeneous ice formation in convective cloud outflow regions

Homogeneous droplet freezing in the warm cirrus regime (230–240 K) is investigated along idealized convective cloud trajectories using a spectral parcel model developed to track droplet freezing events accurately. The novel model is described and used to study ice formation from rapidly ascending (vertical velocity 0.6–6 m s−1) air parcels containing cloud condensation nuclei (CCN) and liquid water droplets. Homogeneous freezing events in warm cirrus are affected by latent heat exchange and produce a mode of small ice crystals with maximum dimensions 10–100 μm after initial supersaturation quenching. During the formation stage, ice‐crystal number concentrations formed homogeneously in convective cloud outflow are hardly affected by ice‐crystal settling and depend sensitively on vertical velocity. In the case of CCN activation into cloud water droplets prior to or along with freezing, relative humidity variations also result in widely varying ice numbers that are insensitive to CCN solubility. These results offer pointers on how further progress can be achieved in simulating and better understanding the formation of upper tropospheric ice clouds originating from convective detrainment zones.

Volcanic ash modeling with the online NMMB-MONARCH-ASH v1.0 model: model description, case simulation, and evaluation

Abstract. Traditionally, tephra transport and dispersal models have evolved decoupled (offline) from numerical weather prediction models. There is a concern that inconsistencies and shortcomings associated with this coupling strategy might lead to errors in the ash cloud forecast. Despite this concern and the significant progress in improving the accuracy of tephra dispersal models in the aftermath of the 2010 Eyjafjallajökull and 2011 Cordón Caulle eruptions, to date, no operational online dispersal model is available to forecast volcanic ash. Here, we describe and evaluate NMMB-MONARCH-ASH, a new online multi-scale meteorological and transport model that attempts to pioneer the forecast of volcanic aerosols at operational level. The model forecasts volcanic ash cloud trajectories, concentration of ash at relevant flight levels, and the expected deposit thickness for both regional and global configurations. Its online coupling approach improves the current state-of-the-art tephra dispersal models, especially in situations where meteorological conditions are changing rapidly in time, two-way feedbacks are significant, or distal ash cloud dispersal simulations are required. This work presents the model application for the first phases of the 2011 Cordón Caulle and 2001 Mount Etna eruptions. The computational efficiency of NMMB-MONARCH-ASH and its application results compare favorably with other long-range tephra dispersal models, supporting its operational implementation.

Experimental study of oblique particle clouds in water

Laboratory experiments were conducted to investigate the dynamics of oblique particle cloud in stagnant water. Previous laboratory studies on vertically downward particle clouds indicated the importance of nozzle diameter do and mass of sand particles in form of an aspect ratio of Lo/do where Lo is the length of occupied sand particle in a pipe. In addition, particle size plays an important role in mixing capability of particle clouds. 30 laboratory experiments were carried out to consider the effects of Lo/do, particle size D50, angle of release θ, and release height H. In order to generalize the outcome of the present study, both particle size and release height were normalized to form Stokes number St and release number η. Three classes of particle size were identified for 0 < St < 1 and a relatively wide range of aspect ratio 0.8 ≤ Lo/do ≤ 40.1 was formed by changing the mass of sand particles. To consider the effects of release angle and release height, four release angles of θ=15°, 30°, 45°, and 60° were chosen and three release numbers of η=8.5, 13.2, and 17 were selected. Trajectories of particle clouds were identified based on the position of cloud front. Empirical formulations were developed to model the path of the frontal head of oblique particle clouds. Using a theoretical approach, the location of particle fall out was estimated within ± 10% accuracy. Variations of the frontal velocity of particle clouds in vertical direction were investigated and an empirical equation was proposed based on dimensional analysis to predict the frontal velocity at different initial conditions. Mixing efficiency of particle clouds was characterized by entrainment coefficient αe. The entrainment coefficients of particle clouds were computed using the theoretical entrainment hypothesis. It was found that the Stokes number can significantly alter the mixing capability of particle clouds. The influence of controlling parameters on particle−particle interactions can be studied by estimating the drag reduction due to particle grouping effects. The averaged drag coefficients Cd of particle clouds were calculated from momentum equation and a semi-empirical model was proposed to estimate the drag reduction of particle clouds. Significant drag reduction occurred in particle clouds in comparison with individual particles.

Characterization of cumulus cloud fields using trajectories in the center of gravity versus water mass phase space: 2. Aerosol effects on warm convective clouds

AbstractIn Part I of this work a 3‐D cloud tracking algorithm and phase space of center of gravity altitude versus cloud liquid water mass (CvM space) were introduced and described in detail. We showed how new physical insight can be gained by following cloud trajectories in the CvM space. Here this approach is used to investigate aerosol effects on cloud fields of warm cumuli. We show a clear effect of the aerosol loading on the shape and size of CvM clusters. We also find fundamental differences in the CvM space between simulations using bin versus bulk microphysical schemes, with the bin scheme precipitation expressing much higher sensitivity to changes in aerosol concentrations. Using the bin microphysical scheme, we find that the increase in cloud center of gravity altitude with increase in aerosol concentrations occurs for a wide range of cloud sizes. This is attributed to reduced sedimentation, increased buoyancy and vertical velocities, and increased environmental instability, all of which are tightly coupled to inhibition of precipitation processes and subsequent feedbacks of clouds on their environment. Many of the physical processes shown here are consistent with processes typically associated with cloud invigoration.

In situ observations and sampling of volcanic emissions with NASA and UCR unmanned aircraft, including a case study at Turrialba Volcano, Costa Rica

Abstract Scientific knowledge of transient and difficult-to-access airborne volcanic emissions comes primarily from remote sensing observations, and a few in situ data from sporadic heroic or inadvertent airborne encounters. In the past, patchy knowledge of the composition and behaviour of such plumes from explosive volcanic eruptions, and associated drifting ash and gas clouds, have centrally contributed to unwanted and dangerous aircraft encounters that have put crews at risk and, in some cases, greatly damaged aircraft. Thus, improved knowledge of boundary conditions and plume composition, as inputs to both mass retrieval and predictive models for cloud trajectories , would be of benefit. In this paper, we describe how small robotic unmanned aerial vehicles (sUAVs) can address a variety of measurements that are typically beyond the reach of, and sometimes too dangerous for, manned aircraft. The direct measurements and sampling that can be achieved by sUAVs address serious gaps in knowledge of volcanic processes, and provide important validation data for estimations of volcanogenic ash and gas concentrations gleaned using remote sensing techniques. These data, in turn, constrain key proximal and distal boundary conditions for aerosol and gas transport models on which are based a number of decisions and evaluations by hazard responders and regulatory agencies. We briefly describe a case study from our ongoing field study at Turrialba Volcano in Costa Rica, where we are conducting an international campaign of systematic airborne in situ measurements of volcanogenic SO 2 and other gases, as well as aerosols, with sUAVs and aerostats (e.g. tethered balloons and kites), in conjunction with data acquisitions by the Advanced Spaceborne Thermal Emission and Reflection (ASTER) radiometer onboard the NASA Terra Earth orbital platform. To our knowledge, this is the first such systematic in situ UAV- and aerostat-based observation programme for SO 2 and particulates in a volcanic plume for correlation with orbital data. We preliminarily report good agreement between our UAV/aerostat and ASTER SO 2 retrievals within a 5 km radius of the volcano summit, at altitudes of up to 12 500 ft ( c. 3850 m) above sea level (asl) for concentrations within the range of 5–20 ppmv (ppm by volume). Additional work continues.

Volcanic ash forecast during the June 2011 Cordón Caulle eruption

We modelled the transport and deposition of ash from the June 2011 eruption from Cordon Caulle volcanic complex, Chile. The modelling strategy, currently under development at the Argentinean Naval Hydrographic Service and National Meteorological Service, couples the weather research and forecasting (WRF/ARW) meteorological model with the FALL3D ash dispersal model. The strategy uses volcanological inputs inferred from satellite imagery, eruption reports and preliminary grain-size data obtained during the first days of the eruption from an Argentinean ash sample collection network. In this sense, the results shown here can be regarded as a quasi-syn-eruptive forecast for the first 16 days of the eruption. Although this article describes the modelling process in the aftermath of the crisis, the strategy was implemented from the beginning of the eruption, and results were made available to the Buenos Aires Volcanic Ash Advisory Centers and other end users. The model predicts ash cloud trajectories, concentration of ash at relevant flight levels, expected deposit thickness and ash accumulation rates at relevant localities. Here, we validate the modelling strategy by comparing results with satellite retrievals and syn-eruptive ground deposit measurements. Results highlight the goodness of the combined WRF/ARW-FALL3D forecasting system and point out the usefulness of coupling both models for short-term forecast of volcanic ash clouds.

Physics-based, reduced-order gas cloud with radiative transport model for rapid simulation of hyperspectral infrared sensors

Peter A. KottkeGeorgia Institute of TechnologyGeorge W. Woodruff School of MechanicalEngineering701 Ferst DriveAtlanta, Georgia 30332-0405E-mail: pk57@mail.gatech.eduAndrei G. FedorovGeorgia Institute of TechnologyGeorge W. Woodruff School of MechanicalEngineering and Parker H. Petit Institute ofBioengineering and Bioscience701 Ferst DriveAtlanta, Georgia 30332-0405Abstract. We have developed a reduced-order, physics-based model ofgas cloud transport and combined it with an approximate formulation ofthe equation of radiative transport to enable efficient prediction of spectralirradiation for simulation of hyperspectral infrared sensors. The resultingcombined model is easily implemented, providing a rapid and flexiblein silico experimentation capability. The gas cloud model is based onthe entrainment hypothesis and predicts cloud trajectories in three-dimensions, with elevation changes occurring primarily due to buoyancyeffects and with spreading and accompanying dilution and cooling occur-ring due to a turbulence dominated growth mechanism. The radiationtransport model is simplified through an approximate treatment of scatter-ing that transforms the governing equation from an integro-differentialequation to an ordinary differential equation. The conjugate model hasbeen combined with a simple sensor model and has been validatedthrough comparison to results from large-scale field tests. The utility ofthe simulations has also been demonstrated through inclusion in a largeralgorithm development and analysis program, the chem/bio algorithmdevelopment kit.

COMPARISON OF GENERAL RELATIVISTIC AND PSEUDO-NEWTONIAN DESCRIPTION OF MAGELLANIC-CLOUDS MOTION IN THE FIELD OF MILKY WAY

We test precision of the Cosmological Paczynski–Wiita (CPW) potential reflecting properties of the Schwarzschild–de Sitter (SdS) spacetimes in modeling dynamical phenomena related to galaxy motion. We consider a simplified model of Magellanic Clouds moving in the field of Milky Way as test particles. Time evolution of their position along trajectories obtained in the CPW framework using the notion of Newtonian time is compared to the one obtained in the fully general relativistic (GR) approach when the time evolution is expressed in terms of time related to the location of Earth in the Galaxy field. The differences in the position-evolution of the Magellanic Clouds obtained in the CPW and GR approaches are given for appropriately chosen values of the Milky Way mass. It is shown that the integrated relativistic corrections represent ~10-5 part of the Newtonian CPW predictions for the orbital characteristics of the motion and slightly grow with Galaxy mass growing, being at least by one order higher than the local scaling GR corrections. The integrated orbital GR corrections thus could be important only in very precise modeling of the motion of Magellanic Clouds. The CPW framework is used to show that, quite surprisingly, the influence of the cosmological constant on the Magellanic Clouds motion can be strong and significantly alters the trajectories of Magellanic Clouds and time evolution along them. The relative contribution of the cosmological constant is ~10-1 or higher. It is most profoundly demonstrated by the increase of the binding mass that represents 22% for Small Magellanic Cloud and even 47% for Large Magellanic Cloud, putting serious doubts on gravitational binding to the Milky Way in the later case.