Convergence Layer Research Articles

Development of Asymmetric Convection in a Tropical Cyclone under Environmental Uniform Flow and Vertical Wind Shear

AbstractIdealized numerical simulations have been carried out to reveal the complexity in the development of asymmetric convection in a tropical cyclone (TC) under the influence of an environment with either uniform flow, vertical wind shear (VWS), or both. Results show that rainwater is enhanced to the right of the motion in the outer rainband, but such enhancement occurs in the upshear-left area of the inner-core region. Additionally, due to the asymmetries introduced by environmental flow, wavenumber-1 temperature and height anomalies develop at a radius of ~1000 km in the upper levels. A sub-vortex aside from the TC center encompassing the wavenumber-1 warm center appears, and asymmetric horizontal winds emerge, which, in turn, changes the storm-scale (within 400 km) VWS. Deep convection in the inner core closely follows the changing storm-scale VWS when its magnitude is larger than 2 m s–1 and is located downshear of the storm-scale VWS in all the experiments with environmental flow. In the outer rainbands, the maximum boundary layer convergence is mainly controlled by the direction of motion and is located in the rear-right quadrant. These results extend upon the findings of previous studies in three aspects: (1) The discovery of the roughly linear combination effect from the uniform flow and large-scale VWS; (2) The development of upper-level asymmetric winds on a 1000-km scale through the interaction between the TC vortex and environmental flow, resulting in changes in the storm-scale VWS pattern within the TC area; (3) The revelation that TC asymmetric convection closely aligns with the direction-varying storm-scale VWS instead of the initially designated VWS.

Influences of Background Rotation on Secondary Eyewall Formation of Tropical Cyclones in Idealized f‐Plane Simulations

AbstractThis study investigates the background rotational influences on the secondary eyewall formation (SEF) in tropical cyclones (TCs) in quiescent f‐plane environments. For given initial structures, simulated vortices tend to experience earlier SEF at lower latitudes. Yet the size of the secondary eyewall does not change monotonically with the latitudes. Specifically, ∼20°N provides the optimal amount of background rotation for the largest secondary eyewall size without considering other environmental forcings. Different background rotation rates affect SEF mainly by modulating the outer‐core convection as well as the wind structures. Specifically, the lower rotation rate causes more outer‐core surface fluxes, thus facilitating the outer rainbands (ORBs) at larger radii. Yet the secondary eyewall does not necessarily form at larger radii at lower latitudes since the transition from the ORBs to secondary eyewall is localized in a region of boundary layer (BL) convergence preceded by accelerated tangential winds. Budget analysis reveals that the differences in the acceleration of outer‐core tangential winds among vortices at different latitudes are dominated by the radial flux of absolute vorticity. Due to the non‐uniform influences of background rotation on the BL inflow and absolute vorticity, the most efficient spin‐up of outer‐core tangential winds is achieved at a medium latitude of 20°N, which leads up to SEF at the largest radii. By comparison, for TCs at lower (higher) latitudes, the lower outer‐core absolute vorticity (radial inflow) limits the acceleration of outer‐core tangential winds, thus placing SEF at smaller radii.

Study on dynamic behavior of atomic diffusion at interface between TiAlN coating and WC matrix

The molecular dynamics method was used to simulate the dynamic behavior change of atomic diffusion at interface between TiAlN coating and WC matrix in the carbide tool with TiAlN coating. It was determined that the one-way diffusion of C atom to TiAlN coating resulted in serious lattice distortion on the surface. Meanwhile, the whole diffusion process was accompanied by the continuous increase of stress, resulting in gradual deformation of the material. The interface bonding performance also decreases. Then, the surface energy and atomic layer convergence are calculated by the first-principles method. The TiAlN crystal surface is stable at 8 atomic layers, and the WC crystal surface is stable at 6 atomic layers, and then a stable microinterface model can be built. The relaxation processing for the established model was performed to determine the diffusion path of C atom. Then, the energy barrier, adhesion work, interface energy and fracture toughness of different transition state structures in the diffusion path of C atom are calculated, and it is determined that with the deepening of the diffusion of C atom in the coating, the binding ability of the interface of the coating base and the performance of the coating tool are more and more serious damage. Finally, the cutting experiment of TiAlN coated tool is designed. According to the surface topography of TiAlN coated tool in different periods, the simulation and theoretical analysis mentioned above are verified, which provides a theoretical basis for the subsequent research on improving the performance of coated tool.

Revisiting the evolution of downhill thunderstorms over Beijing: a new perspective from a radar wind profiler mesonet

Abstract. Downhill thunderstorms frequently occur in Beijing during the rainy seasons, leading to substantial precipitation. The accurate intensity prediction of these events remains a challenge, partly attributed to insufficient observational studies that unveil the thermodynamic and dynamic structures along the vertical direction. This study provides a comprehensive methodology for identifying both enhanced and dissipated downhill thunderstorms. In addition, a radar wind profiler (RWP) mesonet has been built in Beijing to characterize the pre-storm environment downstream of the thunderstorms at the foothill. This involves deriving vertical distributions of high-resolution horizontal divergence and vertical motion from the horizontal wind profiles measured by the RWP mesonet. A case study of an enhanced downhill thunderstorm on 28 September 2018 is carried out for comparison with a dissipated downhill thunderstorm on 23 June 2018, supporting the notion that a deep convergence layer detected by the RWP mesonet, combined with the enhanced southerly flow, favors the intensification of thunderstorms. Statistical analyses based on radar reflectivity from April to September 2018–2021 have shown that a total of 63 thunderstorm events tend to be enhanced when entering the plain, accounting for about 66 % of the total number of downhill thunderstorm events. A critical region for intensified thunderstorms lies on the downslope side of the mountains west to Beijing. The evolution of a downhill storm is associated with the dynamic conditions over the plain compared to its initial morphology. Strong westerly winds and divergence in the middle of troposphere exert a critical influence on the enhancement of convection, while low-level divergence may lead to dissipation. The findings underscore the significant role of an RWP mesonet in elucidating the evolution of a downhill storm.

Detecting irradiation defects in materials: A machine learning approach to analyze helium bubble images

Additive manufacturing technology has received significant attention in the field of nuclear materials due to its potential to improve the radiation resistance of materials and components. In our research, we propose to use 304 L stainless steel fabricated by Selective Laser Melting (SLM) as a replacement for traditional casting due to its superior performance and optimized manufacturing technique. During testing of its radiation resistance, we found that analyzing helium bubbles captured by transmission electron microscopy (TEM) is crucial for understanding and predicting material behavior under irradiation. However, this task typically involves manual counting, which is both time-consuming and prone to errors due to the fatigue of human annotators. To address this challenge, we present a novel machine learning model for automatic helium bubbles detection and counting through images. Our model leverages a fusion of traditional computer vision techniques with cutting-edge machine learning methods to achieve superior detection of helium bubbles in nuclear materials. This approach is based on two core designs: a novel generative model to generate training data and a gradient convergence layer to limit the range of parameters. Experiments show that our model outperforms previous state-of-the-art unsupervised detectors, and achieves highly accurate helium bubble segmentation in a few-shot scenario, with an F1 score typically exceeding 90 % and an average size error less than 0.1 nm. Our model achieves over 100 times more efficiency than manual counting, which takes approximately 20 s per image. Our work demonstrates a successful collaboration between the fields of material characterization and artificial intelligence (AI). By leveraging the respective strengths of material science and machine learning, we have achieved surprising results that could have a significant impact on the development of new materials and components for nuclear applications.

Nonisothermal analysis of two uniform boundary layer shear flows

AbstractThe heat transfer phenomenon on the multiphase flows plays an imperative role in several biological and industrial processes, like the oil production industries, catalytic reactors, energy losses in several thermal systems, energy storage, paper manufacture, and heat exchanger systems. Therefore, this study scrutinized the heat transfer characteristic between two uniform boundary layer shear flows with different strengths flowing in the same direction. This problem involves the simulation of the convergence of boundary layers with varying shear strengths. The nonlinear differential system is scrutinized and converted into dimensionless ordinary differential equations by employing appropriate dimensionless variables. The resulting set of highly nonlinear ordinary differential equations is resolved numerically utilizing the Matlab solver “bvp4c.” The resulting numerical solutions are used to construct graphs that illustrate and elucidate the impact of numerous physical parameters on flow patterns. For both fluids, results for the Nusselt number and shear stress are also presented graphically for various parameters. The acquired results demonstrate that the velocity profile upsurges for both upper and lower fluids by enhancing the shear parameter. Furthermore, the number of streamlines is enhanced by augmenting the values of the viscosities ratio parameter. The present problem applies to the trailing edge flow over a thin airfoil with camber.

Radar Echo Recognition of Gust Front Based on Deep Learning

Gust fronts (GFs) belong to the boundary layer convergence system. A strong GF can cause serious wind disasters, so its automatic monitoring and identification are very helpful but difficult in daily meteorological operations. By collecting convective weather processes in Hubei, Jiangsu, and other regions of China, 1422 GFs from 106 S-band new-generation weather radar (CINRAD/SA) volume scan data are labeled as positive samples by means of human–computer interaction, and the same number of negative samples are randomly tagged from no GF radar data. A deep learning dataset including 2844 labels with a positive and negative sample ratio of 1:1 is constructed, and 80%, 10%, and 10% of the dataset are separated as training, validation, and test sets, respectively. Then, the training dataset is expanded to 273,120 samples by data augmentation technology. Since the height of a GF is generally less than 1.5 km, three deep-learning-based models are trained for GF automatic recognition according to the distance from the radars. Three models (M1, M2, M3) are trained with the data at a 0.5° elevation angle from 65 to 180 km away from the radars, at 0.5° and 1.5° angles from 40 to 65 km, and at 0.5°, 1.5°, and 2.4° angles within 40 km, respectively. The precision, confusion matrix, and its derived indicators including receiver operating characteristic curve (ROC) and the area under ROC (AUC) are used to evaluate the three models by the test set. The results show that the identification precisions of the models are 97.66% (M1), 90% (M2), and 90.43% (M3), respectively. All the hit rates are over 89%, the false positive rates are less than 11%, and the critical success indexes (CSIs) surpass 82%. In addition, all the optimal critical points on the ROC curves are close to (0, 1), and the AUC values are above 0.93. These results suggest that the three models can effectively achieve the automatic discrimination of GFs. Finally, the models are demonstrated by three GF events detected with Qingpu, Nantong, and Cangzhou radars.

Boosting Communication Efficiency in Federated Learning for Multiagent-Based Multimicrogrid Energy Management.

Privacy of user is becoming increasingly significant in constructing efficient multiagent energy management systems for multimicrogrid (MMG). As an emerging privacy-protection method, federated learning (FL) has been used to prevent data breaches in the MMG-related field. However, with the ever-growing participants, the underlying communication burden existing in FL is evident. Besides, since the neural network layers collectively determine an agent's performance, the possible difference in layer convergence speeds would cause the inconsistency problem, that is, the FL may degrade the convergence rate of those fast-convergent layers, which weakens the overall performance of the agent. To address these issues, a communication-efficient FL (CEFL) algorithm is proposed in this study. Considering the cooperative relationship among layers, a layer evaluation (LE) mechanism is developed in CEFL to evaluate layer contribution through the Shapley value (SV), a profit distribution approach for coalitions. In this way, only partial layers with the highest contributions are selected to be uploaded to the server. In addition, instead of average parameters aggregation, a communication-efficient parameter aggregation method is proposed in CEFL to update the parameters of the global model (GM), in which an aggregation model (AM) is developed to receive parameters for aggregation. The performance of the proposed CEFL is verified by the numerical analysis of MMGs with 3-8 MGs participating. Furthermore, experiments investigate the influence of the hyperparameter in the CEFL and also demonstrate performance improvements, compared with the other four state-of-the-art algorithms.

Ubiquitous Sea Surface Temperature Anomalies Increase Spatial Heterogeneity of Trade Wind Cloudiness on Daily Time Scale

Abstract The impact of weak submeso- to mesoscale SST anomalies on daily averaged trade cumulus cloudiness is investigated using satellite observations that have been validated against shipboard measurements from the Atlantic Tradewind Ocean–Atmosphere Mesoscale Interaction Campaign (ATOMIC). Daily spatial SST anomalies are identified from GOES–POES Blended SST analysis within a 10° × 10° region during January and February 2020. Daily averaged cloud fraction and 10-m neutral wind from satellite observations and reanalysis are composited over the identified SST features, using a common coordinate system based on the near-surface background wind directions. Composites of satellite cloud fraction show a statistically significant increase of cloudiness over the SST warm core with a reduction of cloudiness away from it. These responses are largely the same but with opposite signs over SST cold anomalies, suggesting that spatial heterogeneity in SST can locally imprint on daily cloud fraction. Composites of daily 10-m wind speed and wind convergence anomalies from both satellite and reanalysis show that surface wind speed is increased over SST warm anomalies, implying enhanced turbulence over warmer SSTs. Correspondingly, the surface convergence anomalies in these composites are located around the maximum downwind SST gradient, offset downwind from the cloudiness anomalies. These results indicate that the response of daily cloudiness to these SST anomalies is more likely generated by spatial variability of surface-driven turbulence and surface fluxes rather than that of surface or boundary layer convergence.

Observations of Boundary Layer Convergence Lines and Associated Updrafts in the U.S. Southern Great Plains

Abstract Boundary layer convergence lines (CLs) are highly effective at deep-convection initiation (DCI), suggesting that their associated updraft properties differ from those of more widespread turbulent updrafts in the planetary boundary layer (PBL). This study exploits observations at the Atmospheric Radiation Measurement Southern Great Plains (ARM SGP) observatory in Oklahoma from 2011 to 2016 to quantify CL properties and their relation to turbulent PBL eddies preceding CL arrival. Two independent methods for estimating CL properties are developed at two locations in the SGP region, both relying on the assumption of a 2D circulation in the CL-normal plane but using different combinations of instruments. The first (the radar method) relies mainly on scanning radar data and is applied to 61 CLs passing near a high-resolution scanning radar based in Nardin, Oklahoma, while the second (the surface method) relies mainly on surface wind data and is applied to 68 CLs crossing the SGP facility in nearby Lamont, Oklahoma. Mean daytime (1000–1900 LST) CL width (∼2 km) and convergence magnitude (∼0.003 s−1) are similar for both methods, and mean daytime CL depth is ∼0.75 km. The two methods disagree at night (0000–1000 and 1900–2400 LST), where the surface method estimates wider and weaker CLs than the radar method. This difference may stem from the radar beam overshooting the shallow, highly stable nocturnal PBL. The largest CL updrafts are slightly wider (∼20%) and stronger (∼40%) than the largest PBL updrafts in the pre-CL period, generating 50%–100% larger updraft mass fluxes over most of the PBL depth. Significance Statement Deep convection is commonly initiated by boundary layer convergence lines (CLs), which are associated with intense surface-based wind convergence and strong updrafts that may lift air to saturation. Although CLs form regularly, they are far less common than ordinary, short-lived turbulent thermals in the daytime boundary layer. To better understand why CLs are so effective at deep-convection initiation, we observationally quantify their morphologies and strengths and compare these properties to those of surrounding turbulent updrafts. Perhaps surprisingly, the CLs are found to exhibit only slightly larger scales and strengths as the turbulent updrafts. Although these marginal increases help to explain the preference for storms to initiate along CLs, they likely are not the whole story.

The niche and value creation mechanism of the innovation ecosystem of crowd innovation space: a multi-case study

ABSTRACT Twelve crowd innovation spaces (from China) are selected as case samples, and the niche distribution model of the crowd innovation space’s innovation ecosystem is constructed based on structural hole theory. Further, this research reveals the interactive relationship and value creation mechanism among the innovation ecosystem's components from the value co-creation theory perspective. The research draws the following conclusions from three aspects: (1) The niche of the components of the crowd innovation space ecosystem is characterised by multiple levels, which can be divided into the core layer, convergence layer, and support layer. (2) In the innovation ecosystem, crowd innovation space is at the convergence layer. By filling structural holes, the innovation ecosystem can reach the ‘no holes’ state. Thus, it can promote the connection of the components of the innovation ecosystem to form a network of innovation resources such as knowledge and technology; (3) The value creation in the crowd innovation space’s innovation ecosystem is two-dimensional. Based on whether there is direct interaction or not, value creation can be divided into value co-creation and value auxiliary-creation. Relationship embeddedness and value co-creation are two important mechanisms of value creation in the innovation ecosystem of crowd innovation space.

Convection Initiation Associated with a Boundary Layer Convergence Line over a Real-World Sharp Vegetation-Contrast Area

Abstract Convection initiation (CI) has remained a major challenge in weather forecasting worldwide. The Hetao area in North China, the location of Asia’s largest irrigation area, contains highly heterogeneous vegetation where near-surface convergence lines (boundaries) parallel to the oasis–desert border often emerge over the desert and initiate convection. This study investigated the evolution of such a boundary and its influence on the CI process where a series of cells were successively initiated along the boundary on 4 June 2013. Our results indicated that uneven surface heating across the oasis–desert border produced mesoscale thermal circulation. The westerly oasis breeze in the thermal circulation converged with the southerly background wind and formed a boundary over the desert along the high-temperature contrast line. A middle-hemisphere westerly trough further enhanced uplift and facilitated CI. Our simulation revealed that the first 30-dBZ parcels in each cell originated from either the desert side at a low level or the oasis side at a middle level, rather than from the oasis at a low level, as indicated by previous idealized studies. Southerly low-level parcels veered above the boundary and experienced a longer lifting time over the desert, while western parcels originating from the oasis experienced a shorter lifting time and smaller vertical displacement, resulting in middle-level parcels instead of low-level parcels that reached their level of free convection. Even though CI occurred over a surface boundary without a near-surface stable layer, the inflow may have originated from middle levels rather than in contact with the surface. Significance Statement The purpose of this study is to understand the evolution of a real-world near-surface convergence line and the associated deep convection initiation (CI) along the border of Asia’s largest irrigation area and the desert in northern China. Notably, previous works have mainly focused on shallow convection over uneven vegetation distributions based on idealized simulations, which may be quite different from real-world interactions between thermal circulation and background flow. Our results highlight different parcel sources in different convections initiated by the same convergence line, which is different from the idealized situation where parcels mainly originate from the low-level oasis side.

The Roles of Atmospheric and Air–Sea Interaction Processes in Causing the Eastward Extension of the Western North Pacific Monsoon Trough in Boreal Summer

What causes the eastward extension of the climatological monsoon trough over the western North Pacific in the boreal summer was investigated through both observational analyses and numerical simulations. It was found that the highest SST is always located to the east of maximum precipitation, and this asymmetric SST pattern favors the eastward extension of the monsoon trough through SST induced boundary layer convergence. A mixed-layer heat budget analysis further indicates that the SST asymmetry arises primarily from the asymmetric pattern of cloud-modified downward shortwave radiation. In addition, two internal atmospheric mechanisms are identified. Firstly, there is a zonal asymmetry in the lower-tropospheric moisture advection. Southeasterlies to the east of the convection, in association with the subtropical high advect high mean moisture from south, leads to low-level moistening to the east of the convective center. Secondly, the heating-induced Kelvin wave response leads to a boundary layer convergence ahead of the convection. Both the processes lead to the setup of a convectively unstable stratification to the east, favoring the eastward extension of the monsoon trough. Two sets of the WRF model experiments that specify a fixed and a time-dependent SST field confirm the roles of the aforementioned atmospheric internal processes as well as the air–sea interaction process in causing the eastward progression of the climatological monsoon trough over the western North Pacific.

Large-scale background and role of quasi-biweekly moisture transport in the extreme Yangtze River rainfall in summer 2020

A severe flooding hit southern China along the Yangtze River in summer 2020. The floods were induced by extreme rains, and the associated dynamic and thermodynamic conditions are investigated using daily gridded rainfall data of China and NCEP-NCAR reanalysis. It is found that the June–July rainfall over the Yangtze River Basin (YRB) experienced pronounced subseasonal variation in 2020, dominated by a quasi-biweekly oscillation (QBWO) mode. The southwestward-moving anomalous QBWO circulation was essentially the fluctuation of cold air mass related to the tropospheric polar vortex or trough-ridge activities over the mid-high latitude Eurasian in boreal summer. The southwestward-transport of cold air mass from mid-high latitudes and the northeastward-transport of warm and moist air by the strong anomalous anticyclone over the western North Pacific provided important large-scale circulation support for the extreme rainfall in the YRB. The analysis of streamfunction of water vapor flux demonstrates that a large amount of water vapor eastward zonal transport from the Bay of Bengal and Indo-China and northward transport from the South China Sea provided the background moisture supply for the rainfall. The quasi-biweekly anomalies of potential and divergent component of vertically integrated water vapor flux played an important role in maintaining the subseasonal variability of rainfall in June–July of 2020. The diagnosis of moisture tendency budget shows that the enhanced moisture closely related to the quasi-biweekly fluctuated rainfall was primarily attributed to the moisture convergence. Further analysis of time-scale decomposition in the moisture convergence indicates that the convergence of background mean specific humidity by the QBWO flow and convergence of QBWO specific humidity by the mean flow played dominant roles in contributing to the positive moisture tendency. In combination with adiabatic ascent over the YRB induced by the warm temperature advection, the boundary layer moisture convergence strengthened the upward transport of water vapor to moisten the middle troposphere, favoring the persistence of rainfall during June–July. The vertical moisture transport associated with boundary layer convergence was of critical importance in causing low-level tropospheric moistening. By comparison, the horizontal moisture advection played a secondary important role in the quasi-biweekly oscillation of rainfall in June–July 2020.

Detection and Reporting of Wireless Channel Congestion and Interference in Connected Vehicle Networks

Connected vehicle (CV) wireless networks based on dedicated short-range communications (DSRC), European Telecommunications Standards Institute (ETSI) intelligent transportation systems (ITS-G5), and C-V2X technologies are susceptible to interference from both unintentional emitters and non-CV devices that may be authorized to share the same or adjacent bands. Such interference may lead to unreliable communication and disruption of CV services with a particular impact on safety-related applications. Surprisingly, considering the safety-critical nature of CV applications, there is no simple mechanism for detecting congestion or interference in such networks over wide areas. To address this gap, we propose and demonstrate that both interference and congestion in DSRC and ETSI ITS-G5 networks can be detected simply and inexpensively using capabilities that are already incorporated into the IEEE 802.11p standard, specifically the flags and statistics generated mostly in the physical layer (physical layer convergence procedure and physical medium dependent) state machines. Such a capability could be realized through a relatively minor software upgrade but would resolve a longstanding but underappreciated concern that CV networks are vulnerable to both congestion and a variety of short-range interferers but lack the capability to detect or report this. Although our focus was on DSRC and ITS-G5, similar considerations apply to related schemes such as C-V2X.

Numerical predictions of internal waves and surface thermal signatures by underwater vehicles in density-stratified water using OpenFOAM

The accurate and efficient prediction of the flow and temperature fields on water surface modulated by internal waves induced by underwater vehicles in a density-stratified ocean can serve as the basis for indirect detection. The disturbance of an underwater object on density-stratified water can be considered as the mixing of two incompressible fluids: freshwater and saltwater. Furthermore, the modulation effect of internal waves on the convergence and divergence of flow field and thermal skin layer is captured at the air–water interface. Therefore, in this study, a CFD solver called “interMixing_skin_Foam” based on OpenFOAM is proposed. It can manage three incompressible fluids, two of which disperse, and the interface between the immiscible fluids (air–water) is captured using the VOF technique. In addition, the energy equation is implemented to investigate the thermal signature variations at the air–water interface. Comparison analysis of experimental results and those obtained from the CFD solver “twoLiquidMixing_skin_Foam” developed in a previous study, wherein only two incompressible fluids were considered, is performed for standard cases in literature. Subsequently, the influence of the air–water interface on the flow and temperature fields is studied for a submerged sphere travelling horizontally in linearly and strongly density-stratified water.

Improving Bundle Routing in a Space DTN by Approximating the Transmission Time of the Reliable LTP

Because the operation of space networks is carefully planned, it is possible to predict future contact opportunities from link budget analysis using the anticipated positions of the nodes over time. In the standard approach to space delay-tolerant networking (DTN), such knowledge is used by contact graph routing (CGR) to decide the paths for data bundles. However, the computation assumes nearly ideal channel conditions, disregarding the impact of the convergence layer retransmissions (e.g., as implemented by the Licklider transmission protocol (LTP)). In this paper, the effect of the bundle forwarding time estimation (i.e., the link service time) to routing optimality is analyzed, and an accurate expression for lossy channels is discussed. The analysis is performed first from a general and protocol-agnostic perspective, assuming knowledge of the statistical properties and general features of the contact opportunities. Then, a practical case is studied using the standard space DTN protocol, evaluating the performance improvement of CGR under the proposed forwarding time estimation. The results of this study provide insight into the optimal routing problem for a space DTN and a suggested improvement to the current routing standard.

Identifying precursor of Sumatra squall line

Sumatra Squall Line (SSL) is a detectable mesoscale meteorological phenomenon at least prior to 3 hour using Doppler radar imagery interpretation. By identifying precursors, SSL can be detected 6-12 hours earlier before the occurences. Infrared data from MTSAT satellite were used to identify clusters of SSL clouds which then produce two types of SSL with different orientations, namely Northwest SSL (oriented northwest - southeast) and Northeast SSL (oriented northeast - southwest). Wind, helicity, and moisture transport were selected as precursor variables due to their importance information of squall line. The results of the precursor variable pattern comparison in the case of SSL with non-SSL showed clear differences. Bottom layer convergence and the westerlies wind patterns were proven to be formed in SSL cases. Helicity concentration was related to orientation of SSL cloud cluster. The convergence of moisture transport was detected 6 hours before the SSL occurences.

Non-linear intensification of monsoon low-pressure systems by the BSISO

Abstract. More than half of the rainfall brought to the Indian subcontinent by the summer monsoon is associated with low-pressure systems (LPSs). Yet their relationship with the boreal summer intraseasonal oscillation (BSISO) – the dominant intraseasonal forcing on the monsoon – is only superficially understood. Using reanalysis data, we explore the relationship between the BSISO and LPS intensity, propagation and precipitation, and associated underlying mechanisms. The BSISO has a large impact on mean monsoon vorticity and rainfall as it moves northward – maximising both in phases 2–3 over southern India and phases 5–6 over northern India – but a much weaker relationship with total column water vapour. We present evidence that LPS genesis also preferentially follows these phases of the BSISO. We identify significant relationships between BSISO phase and LPS precipitation and propagation: for example, during BSISO phase 5, LPSs over northern India produce 51 % heavier rainfall and propagate northwestward 20 % more quickly. Using a combination of moisture flux linearisation and quasi-geostrophic theory, we show that these relationships are driven by changes to the underlying dynamics rather than the moisture content or thermodynamic structure of the monsoon. Using the example of LPSs over northern India during BSISO phase 5, we show that the vertical structure of anomalous vorticity can be split into contributions from the BSISO background circulation and the non-linear response of the LPS to anomalous BSISO circulation. Complementary hypotheses emerge about the source of this non-linear vorticity response: non-linear frictional convergence and secondary barotropic growth. We show that both are important. The BSISO imparts greater meridional shear on the background state, supporting LPS intensification. The BSISO background and non-linear LPS response both contribute significantly to anomalous boundary layer convergence, and we show through vortex budget arguments that the former supports additional LPS intensification in boundary layer, while the latter supports faster westward propagation. This work therefore yields important insights into the scale interactions controlling one of the dominant synoptic systems contributing to rainfall during the monsoon.

The Effect of Aluminum Particle Size on the Formation of Reactive Jet

In order to study the morphology characteristics of the PTFE/Al reactive shaped charge jet and the chemical reaction during the jet formation, PTFE/Al reactive liners with aluminum particle sizes of 5 μm and 100 μm were prepared. The parameters of the Johnson–Cook constitutive model of PTFE/Al reactive materials (RMs) were obtained through quasi-static compression experiments and SHPB (Split Hopkinson Pressure Bar) experiments. X-ray imaging technology was used to photograph the shape of reactive shaped charges jet at two different time points. The AUTODYN secondary development technology was used to simulate the jet formation, and the simulation results are compared with the experimental results. The results show that the simulation results are close to the experimental results, and the error is in the range of 4–8%. Through analysis, it is observed that the RMs reacted during the PTFE/Al reactive shaped charge jet formation, and due to the convergence of the inner layer of the liner during the jet formation, the chemical reaction of the jet is from inside to outside. Secondly, the particle size of aluminum powder has an influence on the chemical reaction and morphology of the jet. During the jet formation, there were fewer RMs reacted when the PTFE/Al reactive liners were prepared with 100 μm aluminum powder. Compared with 5 μm aluminum powder, when the aluminum powder is 100 μm, the morphology of the jet is more condensed, which is conducive to generating greater penetration depth.