Modeling of protostellar clouds and their observational properties

A physical model and two-dimensional numerical method for computing the evolution and spectra of protostellar clouds are described. The physical model is based on a system of magneto-gas-dynamical equations, including ohmic and ambipolar diffusion, and a scheme for calculating the thermal and ionization structure of a cloud. The dust and gas temperatures are determined when calculating the thermal structure of the cloud. The results of computing the dynamical and thermal structure of the cloud are used to model the transfer of continuum and molecular-line radiation in the cloud. Results are presented for clouds in hydrostatic and thermal equilibrium. The evolution of a rotating magnetic protostellar cloud that is compressed starting from a quasi-static equilibrium state is also considered. Spectral maps for optically thick lines of linear molecules are analyzed. The influence of the magnetic field and rotation can lead to a redistribution of angular momentum in the cloud and the formation of a characteristic rotational-velocity structure. As a result, the distribution of the velocity centroid of the molecular lines can acquire an hourglass shape. It is planned in future to use the developed program package and a model for the chemical evolution of clouds to interpret and model in detail observed starless and protostellar cores.     

Self-similar regimes for the collapse of magnetic protostellar clouds

Self-similar solutions describing the homogeneous, free, isothermal collapse of protostellar clouds are considered. One such solution correponds to the critical case of the propagation of a rarefaction wave near the time when it is focused in the central region of the cloud. The speed of the rarefaction front is finite and equal to three times the isothermal sound speed. The asymptotic distributions of gas-dynamical quantities in the central part of the collapsing cloud and the surrounding envelopes are considered at both early and late stages of compression, after the formation of an opaque core (protostar). These solutions are used in a magneto-kinematic approximation to study the geometry and evolution of the large-scale magnetic fields of collapsing protostellar clouds. All the solutions are verified using direct numerical simulations. It is shown that an initially uniform magnetic field acquires an “hourglass” geometry with time. The characteristic opening angles in the self-similar solutions are in satisfactory agreement with observations.     

Determining the parameters of massive protostellar clouds via radiative transfer modeling

A one-dimensional method for reconstructing the structure of prestellar and protostellar clouds is presented. The method is based on radiative-transfer computations and a comparison of theoretical and observed intensity distributions at both millimeter and infrared wavelengths. The radiative transfer of dust emission is modeled for specified parameters of the density distribution, central star, and external background, and the theoretical distribution of the dust temperature inside the cloud is determined. The intensity distributions at millimeter and IR wavelengths are computed and quantitatively compared with observational data. The best-fit model parameters are determined using a genetic minimization algorithm, which makes it possible to reveal the ranges of parameter degeneracy as well. The method is illustrated by modeling the structure of two infrared dark clouds IRDC-320.27+029 (P2) and IRDC-321.73+005 (P2). The derived density and temperature distributions can be used to model the chemical structure and spectral maps in molecular lines.     

A coupled,dynamical and chemical model for the prestellar core L1544: Comparison of modeled and observed C<Superscript>18</Superscript>O,HCO<Superscript>+</Superscript>, and CS emission spectra

We consider radiative transfer in C¹⁸O, HCO⁺, and CS molecular lines in a spherically symmetrical, coupled, dynamical and chemical model of a prestellar core whose evolution is determined by ambipolar diffusion. Theoretical and observed line profiles are compared for the well-studied core L1544, which may be a collapsing protostellar cloud. We study the relationship between the line shapes and model parameters. The structure of the envelope and kinematic parameters of the cloud are the most important factors determining the shape of the lines. Varying the input model parameters for the radiative transfer—the kinetic temperature and microturbulent velocity—within the limits imposed by observations does not result in any substantial variations of the line profiles. The comparison between the model and observed spectra indicates that L1544 displays a flattened structure, and is viewed at an oblique angle. A two-dimensional model is needed to reproduce this structure.     

Guest Editorial to the Special Issue: Lessons Learned from post-2008 Wenchuan Earthquake Community Recovery

Identifying the spatial extent of volcanic ash clouds in the atmosphere and forecasting their direction and speed of movement has important implications for the safety of the aviation industry, community preparedness and disaster response at ground level. Nine regional Volcanic Ash Advisory Centres were established worldwide to detect, track and forecast the movement of volcanic ash clouds and provide advice to en route aircraft and other aviation assets potentially exposed to the hazards of volcanic ash. In the absence of timely ground observations, an ability to promptly detect the presence and distribution of volcanic ash generated by an eruption and predict the spatial and temporal dispersion of the resulting volcanic cloud is critical. This process relies greatly on the heavily manual task of monitoring remotely sensed satellite imagery and estimating the eruption source parameters (e.g. mass loading and plume height) needed to run dispersion models. An approach for automating the quick and efficient processing of next generation satellite imagery (big data) as it is generated, for the presence of volcanic clouds, without any constraint on the meteorological conditions, (i.e. obscuration by meteorological cloud) would be an asset to efforts in this space. An automated statistics and physics-based algorithm, the Automated Probabilistic Eruption Surveillance algorithm is presented here for auto-detecting volcanic clouds in satellite imagery and distinguishing them from meteorological cloud in near real time. Coupled with a gravity current model of early cloud growth, which uses the area of the volcanic cloud as the basis for mass measurements, the mass flux of particles into the volcanic cloud is estimated as a function of time, thus quantitatively characterising the evolution of the eruption, and allowing for rapid estimation of source parameters used in volcanic ash transport and dispersion models.

     

Modeling of rapid variability in the spectral line profiles of Wolf-Rayet stars

Profiles of variable emission lines in the spectra of Wolf-Rayet stars are calculated using a stochastic cloud model for the inhomogeneous atmospheres of early-type stars. The model assumes that most of the line flux is formed in cold, dense condensations (clouds) that move through a rarified inter-cloud medium whose density monotonically decreases outwards. The formation of clouds is taken to be stochastic. Wavelet analysis is used to estimate the parameters of cloud ensembles. The model can reproduce the general pattern of line-profile variability observed in the spectra of Wolf-Rayet stars.     

The formation and evolution of the most massive stars

We consider the formation of massive stars under the assumption that a young star accretes material from the protostellar cloud through its accretion disk while losing gas in the polar directions via its stellar wind. The mass of the star reaches its maximum when the intensity of the gradually strengthening stellar wind of the young star becomes equal to the accretion rate. We show that the maximum mass of the forming stars increases with the temperature of gas in the protostellar cloud T ₀, since the rate at which the protostellar matter is accreted increases with T ₀. Numerical modeling indicates that the maximum mass of the forming stars increases to ～900 M _⊙ for T ₀ ～ 300 K. Such high temperatures of the protostellar gas can be reached either in dense star-formation regions or in the vicinity of bright active galactic nuclei. It is also shown that, the lower the abundance of heavy elements in the initial stellar material Z, the larger the maximum mass of the star, since the mass-loss rate due to the stellar wind decreases with decreasing Z. This suggests that supermassive stars with masses up to 10⁶ M _⊙ could be formed at early stages in the evolution of the Universe, in young galaxies that are almost devoid of heavy elements. Under the current conditions, for T ₀ = (30–100) K, the maximum mass of a star can reach ～100M _⊙, as is confirmed by observations. Another opportunity for the most massive stars to increase their masses emerges in connection with the formation and early stages of evolution of the most massive close binary systems: the most massive stars can be produced either by coalescence of the binary components or via mass transfer in such systems.     

Variations in the accretion rate and luminosity in gravitationally unstable protostellar disks

Self-consistent modeling of a protostar and protostellar disk is carried out for early stages of their evolution. The accretion rate at distances of sevral astronomical units from the protostar is appreciably variable, which is reflected in the protostar’s luminosity. The amplitude of the variations in the accretion rate and luminosity grows together with the sampling period, as a consequence of the nature of gravitationally unstable protostellar disks. A comparison of model luminosity variations with those derived from observations of nearby sites of star formation shows that the model variations are appreciably lower than the observed values for sampling periods of less than 10 years, indicating the presence of additional sources of variability on small dynamical distances from the protostar.     

The minimum stellar mass in early galaxies

The conditions for the fragmentation of the baryonic component during mergers of dark matter halos in the early Universe are studied. We assume that the baryonic component undergoes a shock compression. The characteristic masses of protostellar molecular clouds and the minimum masses of protostars originating in these clouds decrease with increasing halo mass. This may indicate that the initial stellar mass function in more massive galaxies was shifted towards lower masses during the initial stages of their formation. This would result in an increase in the number of stars per unit mass of the halo, i.e., in an increase in the efficiency of star formation.     

The dynamics of the shock disruption of interstellar clouds

The effect of the structural irregularity of an interstellar cloud on the dynamics of its disruption by a shock from a supernova is studied. Irregular clouds are disrupted twice as fast as spherical clouds. However, fragments of irregular clouds preserve their enhanced density for long times without being mixed with the intercloud gas. The fraction of shock energy that is converted to the kinetic energy of the fragments is 50% higher than in the disruption of a spherical cloud. Shocks are not able to trigger the gravitational compression of clouds.     

Numerical simulation of deep convective cloud seeding using liquid carbon dioxide

In this study, a one-dimensional transient cumulonimbus cloud is modeled to be seeded by liquid CO₂. The model includes microphysical and dynamical processes associated with glaciogenic seeding by homogenous ice nucleation and two thermal terms associated with seeding by ?90 ºC liquid CO₂. For this model, the study concentrates on five types of hydrometeors, namely, cloud droplet, cloud ice, snow, hail/graupel, and rain. Point and horizontal seeding methods are implemented to observe their implications for rainfall enhancement, amount of hail/graupel production, vertical cloud extension, and radar’s reflectivity. In addition, the seeding temperature effects on the rainfall and microphysical processes are investigated. The results of the study show that, the rainfall enhancement and rainfall intensity in the point seeding case are more than those in the horizontal seeding. Moreover, the study reveals that, there is a vertical cloud extension enhancement of 0.5 km for clouds with top height of 10.5 km. The most important sources of the rain water production are found to be the accretion of cloud water by rain (P _RACW) and by snow (P _SACW), and for the graupel production is dry growth of the graupel (P _GDRY). The results of this study are confirmed by the results of other investigators and are found to be comparable with the recorded data at rain gauge stations.     

基于CloudSat卫星资料的新疆三大山区不同类型云高特征研究

作为空中水资源的重要组成部分,云在地球水循环过程和气候系统中扮演着重要角色,不同高度的云因其物理特性和动力过程的不同而对人工增水作业具有不同的指示意义. 采用2007年1月至2008年12月的美国宇航局（NASA）云卫星（CloudSat） 2B-CLDCLASS资料,从不同类型云的高度分布特征分析了新疆阿尔泰山、天山和昆仑山区的云水资源情况.结果表明：各个季节三大山区高层云所占比例均较大,在20%以上,其中,天山山区和昆仑山区雨层云所占比例也较大,在15%以上. 三大山区不同云的云顶和云底高度年变化趋势基本一致,昆仑山区各类型云的平均云顶和云底的高度最大,阿尔泰山区的最低.     

The nonthermal radio emission of WR 140 in a model with colliding two-phase winds

We present a model in which the nonthermal radio emission of binary systems containing Wolf-Rayet and O components is due to collisions between clouds belonging to dense phases of the wind of each star. The relativistic electrons are generated during the propagation of fast shock waves through the clouds and their subsequent de-excitation. The initial injection of superthermal particles is due to photoionization of the de-excited cold gas by hard radiation from the shock front. Therefore, the injection takes place in cloud regions fairly far from the front. Further, the superthermal electrons are accelerated by the betatron mechanism to relativistic energies during the isobaric compression of the cloud material, when most of the gas radiates its energy. Collisions between the clouds can occur far beyond the contact boundary between the rarefied wind components. Thus, the model avoids the problem of strong low-frequency absorption of the radiation.     

Total column density variations of ozone (O<Subscript>3</Subscript>) in presence of different types of clouds

The zenith sky scattered light spectra were carried out using zenith sky UV-visible spectrometer in clear and cloudy sky conditions during May-November 2000 over the tropical station Pune (18°32′N, 73°51′E). These scattered spectra are obtained in the spectral range 462–498 nm between 75° and 92° solar zenith angles (SZAs). The slant column densities (SCDs) as well as total column densities (TCDs) of NO₂, O₃, H₂O and O₄ are derived with different SZAs in clear and cloudy sky conditions. The large enhancements and reductions in TCDs of the above gases are observed in thick cumulonimbus (Cb) clouds and thin high cirrus (Ci) clouds, respectively, compared to clear sky conditions. The enhancements in TCDs of O₃ appear to be due to photon diffusion, multiple Mie-scattering and multiple reflections between layered clouds or isolated patches of optically thick clouds. The reductions in TCDs due to optically thin clouds are noticed during the above period. The variations in TCDs of O₃ measured under cloudy sky are discussed with total cloud cover (octas) of different types of clouds such as low clouds (C _L ), medium clouds (C _M ) and high clouds (C _H ) during May-November 2000. The variations in TCDs of O₃ measured in cloudy sky conditions are found to be well matched with cloud sensitive parameter colour index (CI) and found to be in good correlation. The TCD_cloudy are derived using airmass factors (AMFs) computed without considering cloud cover and CI in radiative transfer (RT) model, whereas TCD_model are derived using AMFs computed with considering cloud cover, cloud height and CI in RT model. The TCD_model is the column density of illuminated cloudy effect. A good agreement is observed between TCD_model, TCD_Dob and TCD_GOME.     

Reconstruction of cloud-contaminated satellite remote sensing images using kernel PCA-based image modelling

The presence of clouds can restrict the potential uses of remote sensing satellite imagery in extracting information and interpretation. Automatic detection and removal of clouds which hide significant information in the image is an important task in remote sensing. Hence, our aim is to detect clouds and restore the missing information in order to make the image ready for further analysis and applications. Due to the difference in nature and appearance, thick and thin clouds are dealt separately. Thick cloud is detected using an efficient Fuzzy C-Means (FCM) clustering algorithm, while thin cloud is detected using a simple region growing technique. In order to reconstruct the missing pixels, we utilize the prior knowledge about the statistics of the specific image class. Kernel principal component analysis (KPCA)-based image model is obtained using a set of training images. Missing area in the image is restored after an iterative projection operation and gradient descent algorithm. In short, an image lying out of the modelled image space is iteratively modified to obtain the restored image and that would be in the image space according to the obtained nonlinear low-dimensional and sparse KPCA image model. To illustrate the performance of the proposed method, a thorough experimental analysis on FORMOSAT multi-spectral images is done using MATLAB platform. When compared to the two recent existing techniques, our proposed method is superior and makes a promising tool for thick and thin cloud removal in multi-spectral satellite images.     

Self-similar focusing of rarefaction waves in relativistic collapsing clouds

The development of an inhomogeneous collapse of an initially homogeneous cloud in pressure equilibrium with an external medium is considered in a general-relativistic treatment. It is shown that a rarefaction wave propagating from the outer boundary toward the center of the cloud forms in the initial stage of the collapse. The rarefaction front moves through the collapsing gas at the sound speed, and separates the cloud material into an inner, uniform core and an outer, inhomogeneous envelope. Our analysis distinguishes two possible collapse regimes, depending on the ratio of the focusing time for the rarefaction wave and the free-fall time for the cloud. In massive clouds, the focusing time for the rarefaction wave exceeds the free-fall time, and the collapse of such clouds inevitably leads to the formation of an event horizon and black hole. In low-mass clouds, the focusing time is less than the free-fall time. After the focusing, the collapse of such clouds is fully inhomogeneous, and can be appreciably slowed by the pressure gradient. The compression of a cloud in a transitional regime separating these two scenarios is studied. In this case, a self-similar collapse regime is realized in the central part of the cloud near the focusing time for the rarefaction wave. The constructed self-similar solution describes both early stages in the compression up to the focusing of the rarefaction wave and later stages with the accretion of gas onto the black hole that is formed. Asymptotic distributions of quantities in the inhomogeneous region at large distances from the rarefaction front and in the accreting envelope are found. The structure of space-time in the vicinity of the black hole that is formed at the center of the cloud as a result of the focusing of the rarefaction wave is discussed.     

Using naive Bayes classifier for classification of convective rainfall intensities based on spectral characteristics retrieved from SEVIRI

This paper presents a new algorithm to classify convective clouds and determine their intensity, based on cloud physical properties retrieved from the Spinning Enhanced Visible and Infrared Imager (SEVIRI). The convective rainfall events at 15 min, 4 × 5 km spatial resolution from 2006 to 2012 are analysed over northern Algeria. The convective rain classification methodology makes use of the relationship between cloud spectral characteristics and cloud physical properties such as cloud water path (CWP), cloud phase (CP) and cloud top height (CTH). For this classification, a statistical method based on ‘naive Bayes classifier’ is applied. This is a simple probabilistic classifier based on applying ‘Bayes’ theorem with strong (naive) independent assumptions. For a 9-month period, the ability of SEVIRI to classify the rainfall intensity in the convective clouds is evaluated using weather radar over the northern Algeria. The results indicate an encouraging performance of the new algorithm for intensity differentiation of convective clouds using SEVIRI data.     

Aerosol particles in the Mexican East Pacific. Part II: Numerical simulations of the impact of enhanced CCN on precipitation development

A number of studies have explored the effect of anthropogenic emissions on the development and evolution of precipitation in different types of clouds; however, the magnitude of the effect is still not clear, particularly for the case of deep, mixed-phase clouds. In this study, changes in the parameterization of the autoconversión process were introduced in the Advanced Regional Prediction System (ARPS) model to further evaluate this question. The simulations were initialized with cloud droplet distributions measured from an instrumented C-130 aircraft flying 600-800 km offshore in the intertropical convergence zone during the East Pacific Investigations of Climate (EPIC) project. Two contrasting cases were selected, one with and the other without the influence of anthropogenic aerosols. The simulations indicate that the increased cloud condensation nuclei (CCN) concentrations lead to a delay in the formation of rain and to a decrease in precipitation that reaches the surface as a result of the inhibition of the autoconversion of cloud water to rain water and the subsequent delay in the formation of hail. In addition, hail forms at higher levels in the cloud for the case of anthropogenic CCN. The most important process in the production of rain water in both cases is the melting of hail. A decrease in the mass of hail that falls below the freezing level in the polluted case, leads to a decrease in the resulting precipitation at the surface. Changes in the initial concentration of CCN do not appear to influence the storm strength in terms of updrafts and cloud top height, suggesting little sensitivity of the cloud dynamics. A control case simulation using the old microphysics scheme produces much more precipitation than either of the clean and polluted cases. In addition, the clean case with the modified parameterization shows a better agreement to observations than the control case. It is suggested to use the new scheme to simulate deep convective development over tropical maritime regions.     

Analysis of Cloud Scale Error of Low Resolution Satellite Based on GF-4 and Its Influence on Downward Radiation Calculation

In order to study the scale error of low resolution meteorological satellite cloud detection and its impact on the calculation of downlink radiation, cloud detection using high resolution stationary satellite GF-4 data and error analysis were carried out. Firstly, the cloud detection of GF-4 data is carried out by using visible channel threshold method and time series method, and the error of cloud detection results of Himawari-8 and FY-2 (FY-2G, FY-2E) is analyzed based on the results of GF-4 cloud detection.In the study area, FY-2G, FY-2E and Himawari-8 cloud images could distinguish the clouds and clear sky. The main reason for the error was the scale effect produced by different spatial resolution satellites(the differences caused by cloud detection algorithms are not discussed here).Most of the errors occurred in the areas of thin clouds and broken clouds.High resolution data could detect broken clouds, while low resolution data lead to false and missed detection. On this basis, the error of remote sensing calculation of short wave radiation was analyzed,and it was found that the error of the actual cloud amount in the pixel would bring significant error to the estimation of the downward radiation.The relative error of the instantaneous downward radiation in the selected test area was -173.52%, and the maximum relative error of shortwave radiation was -20.20%.The results show that the high resolution stationary satellite data can significantly improve the estimation accuracy of the downlink shortwave radiation in the regions with more broken clouds.