Convective Cells Research Articles

Research on Radar Echo Extrapolation Method by Fusing Environment Grid Point Field Information

Short-term extrapolation by weather radar observations is one of the main tools for making weather forecasts. Recently, deep learning has been gradually applied to radar extrapolation techniques, achieving significant results. However, for radar echo images containing strong convective systems, it is difficult to obtain high-quality results with long-term extrapolation. Additionally, there are few attempts and discussions to incorporate environmental factors governing the occurrence and development of convective storms into the training process. To demonstrate the positive effect of environmental factors on radar echo extrapolation tasks, this paper designs a three-dimensional convolutional neural network. The paper outlines the processing steps for matching radar echo images with environmental data in the spatio–temporal dimension. Additionally, it develops an experimental study on the effectiveness of seven physical elements and their combinations in improving the quality of radar echo extrapolation. Furthermore, a loss function is adopted to guide the training process of the model to pay more attention to strong convective systems. The quantitative statistical evaluation shows the critical success index (CSI) of our model’s prediction is improved by 3.42% (threshold = 40 dBZ) and 2.35% (threshold = 30 dBZ) after incorporating specific environmental field data. Two representative cases indicate that environmental factors provide essential information about convective systems, especially in predicting the birth, extinction, merging, and splitting of convective cells.

Oscillatory Porous Medium Ferroconvection in a Viscoelastic Magnetic Fluid with Non-Classical Heat Conduction

The classical stability analysis is used to examine the combined effect of viscoelasticity and the second sound on the onset of porous medium ferroconvection. The fluid and solid matrix are assumed to be in local thermal equilibrium. Considering the boundary conditions appropriate for an analytical approach, the critical values pertaining to both stationary and oscillatory instabilities are obtained by means of the normal mode analysis. It is observed that the oscillatory mode of instability is preferred to the stationary mode of instability. It is shown that the oscillatory porous medium ferroconvection is advanced through the magnetic forces, nonlinearity in magnetization, stress relaxation due to viscoelasticity, and the second sound. On the other hand, it is observed that the presence of strain retardation and porous medium delays the onset of oscillatory porous medium ferroconvection. The dual nature of the Prandtl number on the Rayleigh number with respect to the Cattaneo number is also delineated. The effect of various parameters on the size of the convection cell and the frequency of oscillations is also discussed. This problem may have possible implications for technological applications wherein viscoelastic magnetic fluids are involved.

Divergent convective outflow in large-eddy simulations

Abstract. Upper-tropospheric outflow is analysed in cloud-resolving large-eddy simulations. Thereby, the role of convective organization, latent heating, and other factors in upper-tropospheric divergent-outflow variability from deep convection is diagnosed using a set of more than 80 large-eddy simulations because the outflows are thought to be an important feedback from (organized) deep convection to large-scale atmospheric flows; perturbations in those outflows may sometimes propagate into larger-scale perturbations. Upper-tropospheric divergence is found to be controlled by net latent heating and convective organization. At low precipitation rates isolated convective cells have a stronger mass divergence than squall lines. The squall line divergence is the weakest (relative to the net latent heating) when the outflow is purely 2D in the case of an infinite-length squall line. At high precipitation rates the mass divergence discrepancy between the various modes of convection reduces. Hence, overall, the magnitude of divergent outflow is explained by the latent heating and the dimensionality of the outflow, which together create a non-linear relation.

MODELING OF HUMAN HEAT TRANSFER IN URBAN BUILDINGS WITH CONSIDERING THE EFFECT OF HEAT ISLANDS

Computer modeling of heat transfer in the air volume of residential buildings was carried out taking into ac-count the effect of heat islands. The model includes directly the air volume, limited on both sides by the surfaces of asphalt and the wall of the building, as well as a model of the human body located at a given distance from the wall. In accordance with the climatic features of the territory of the Oryol region in the summer months with low cloudiness, the initial conditions of the computational problem are formed, which determine the modes of heat ex-change of heated surfaces with the air of residential buildings. For each of these modes, numerical modeling of natu-ral convective processes in the considered air volume was carried out. For this, differential equations of energy, mo-tion and continuity are solved for the system "complex of heated surfaces - air volume" for each combination of initial conditions, as well as various positions of the human body model relative to the heated wall of the building. It has been established that as a result of heat exchange in the air volume, a convective cell is formed, the shape and dimen-sions of which are determined by the temperature regime of building walls and asphalt. The influence of heat transfer processes on the surface of the human body on the parameters of this cell is revealed. The shape of this cell is estimat-ed under various initial conditions. Differences in heat fluxes on the surfaces of the human body facing the building and away from it are estab-lished. The dependences of the convective heat transfer of a person on the distance between him and the heated wall of the building are obtained. The quantitative values of the parameters of convective heat transfer of the body under various heat transfer modes, in particular, the temperature and speed of air movement in the upward flow, as well as the values of natural convective heat transfer, are determined.

Phototactic bioconvection with the combined effect of diffuse and oblique collimated flux on an algal suspension

The objective of this paper is mainly to investigate the combined effect of diffuse and oblique collimated flux on the onset of phototactic bioconvection. The onset of phototactic bioconvection is examined numerically in a finite-depth algal suspension via linear stability theory. At bioconvective instability, an unstable mode of disturbance shifts from a non-oscillatory (an overstable) to an overstable (a non-oscillatory) state at the variation in oblique incidence angle/diffuse flux for fixed parameters. If n convection cells are piled up on another vertically, then the bioconvective solution of the linear stability problem is called mode n. For some parameters, mode 2 instability is switched to mode 1 instability as the angle of incidence/diffuse flux varies. In addition, diffuse flux (or oblique collimated flux) enhances algal suspension stability (or instability).

Effects of strong fringing magnetic fields on turbulent thermal convection

We study the influence of fringing magnetic fields on turbulent thermal convection in a horizontally extended rectangular domain. The magnetic field is created in the gap between two semi-infinite planar magnetic poles, with the convection layer located near the edge of the gap. We employ direct numerical simulations in this set-up for fixed Rayleigh and small Prandtl numbers, but vary the fringe width by controlling the gap between the magnetic poles and the convection cell. The magnetic field generated by the magnets is strong enough to cease the flow in the high magnetic flux region of the convection cell. We observe that as the local vertical magnetic field strength increases, the large-scale structures become thinner and align themselves perpendicular to the longitudinal sidewalls. We determine the local Nusselt and Reynolds numbers as functions of the local Hartmann number (based on the vertical component of the magnetic field), and estimate the global heat and momentum transport. We show that the global heat transport decreases with increasing fringe width for strong magnetic fields but increases with increasing fringe width for weak magnetic fields. In the regions of large vertical magnetic fields, the convective motion becomes confined to the vicinity of the sidewalls. The amplitudes of these wall modes show a non-monotonic dependence on the fringe width.

SuperDARN Observations of the Two Component Model of Ionospheric Convection

AbstractWe use a 20 years database of Super Dual Auroral Radar Network (SuperDARN) observations to investigate the two component model of ionospheric convection. A convection pattern is included in the database if it is derived from at least 250 radar vectors and has a distribution of electric potential consistent with Dungey‐cycle twin vortex flow (a negative potential peak in the dusk cell and a positive potential peak in the dawn cell). We extract the locations of the foci of the convection cells from the SuperDARN convection patterns, and compare their dependencies on the north‐south component of the interplanetary magnetic field, IMF BZ, and the SuperMAG auroral electrojet index, SML. We use these parameters to define intervals of expected dayside or nightside dominated reconnection. Our results show that, under conditions favorable for dominant dayside reconnection, the dawn and dusk foci are shifted toward the dayside and that, under conditions favorable for dominant nightside reconnection, the dawn and dusk foci are shifted toward the nightside.

Effective control of two-dimensional Rayleigh–Bénard convection: Invariant multi-agent reinforcement learning is all you need

Rayleigh–Bénard convection (RBC) is a recurrent phenomenon in a number of industrial and geoscience flows and a well-studied system from a fundamental fluid-mechanics viewpoint. In the present work, we conduct numerical simulations to apply deep reinforcement learning (DRL) for controlling two-dimensional RBC using sensor-based feedback control. We show that effective RBC control can be obtained by leveraging invariant multi-agent reinforcement learning (MARL), which takes advantage of the locality and translational invariance inherent to RBC flows inside wide channels. MARL applied to RBC allows for an increase in the number of control segments without encountering the curse of dimensionality that would result from a naive increase in the DRL action-size dimension. This is made possible by the MARL ability for re-using the knowledge generated in different parts of the RBC domain. MARL is able to discover an advanced control strategy that destabilizes the spontaneous RBC double-cell pattern, changes the topology of RBC by coalescing adjacent convection cells, and actively controls the resulting coalesced cell to bring it to a new stable configuration. This modified flow configuration results in reduced convective heat transfer, which is beneficial in a number of industrial processes. We additionally draw comparisons with a conventional single-agent reinforcement learning (SARL) setup and report that in the same number of episodes, SARL is not able to learn an effective policy to control the cells. Thus, our work both shows the potential of MARL for controlling large RBC systems and demonstrates the possibility for DRL to discover strategies that move the RBC configuration between different topological configurations, yielding desirable heat-transfer characteristics.

Conflict resolution in the case of convective weather cell circumvention

This research analyzes the area required for the conflict resolution between aircraft in two flows impacted by a convective weather cell (CWC). The CWC is introduced as a constrained area, forbidden to flight through, which affects the air traffic flows. Prior the conflict resolution, two flows and their intersection are relocated away from the CWC area (thus enabling circumvention of the CWC), which is followed by a tuning of the relocated flows intersection angle in order to create the minimal size of the conflict zone (CZ—a circular area centered at the intersection of two flows, which provides aircraft enough space to completely resolve the conflict within). Therefore, the essence of the proposed solution is in providing conflict free trajectories for the aircraft in intersecting flows that are affected by the CWC, with the goal of minimizing the CZ size, so the finite occupied airspace for the conflict resolution and the CWC circumvention could be reduced. Compared to the best solutions and current industry practice, this article is focused in reduction of the airspace required for aircraft to aircraft and aircraft to weather conflict resolution, and not to distance travelled, time savings, and fuel consumption minimization. The conducted analysis in the MicrosoftExcel2010 confirmed the relevance of the proposed model and demonstrated variations in efficiency of the utilized airspace. The proposed model's transdisciplinary nature makes it potentially applicable in other fields of study, such as the conflict resolution between unmanned aerial vehicles (UAVs) and fixed objects like buildings. Building on this model and taking in consideration large and complex data sets, such as weather related data and flight data (aircraft position, speed, and altitude), we believe it is possible to conduct more sophisticated analyses that would take advantage of Big Data.

PyFLEXTRKR: a flexible feature tracking Python software for convective cloud analysis

Abstract. This paper describes the new open-source framework PyFLEXTRKR (Python FLEXible object TRacKeR), a flexible atmospheric feature tracking software package with specific capabilities to track convective clouds from a variety of observations and model simulations. This software can track any atmospheric 2D objects and handle merging and splitting explicitly. The package has a collection of multi-object identification algorithms, scalable parallelization options, and has been optimized for large datasets including global high-resolution data. We demonstrate applications of PyFLEXTRKR on tracking individual deep convective cells and mesoscale convective systems from observations and model simulations ranging from large-eddy resolving (∼100s m) to mesoscale (∼10s km) resolutions. Visualization, post-processing, and statistical analysis tools are included in the package. New Lagrangian analyses of convective clouds produced by PyFLEXTRKR applicable to a wide range of datasets and scales facilitate advanced model evaluation and development efforts as well as scientific discovery.

Natural convection in platonic solids

Natural convection in enclosures is a phenomenon significantly affected by the geometry of the physical domain, however, comparing different formats is challenging because features such as the characteristic length varies with the geometry. This study proposes examining natural convection in 3D convex regular polyhedra, also known as Platonic solids, using the number of faces as a parameter. Differentially heated enclosures were analyzed to investigate the effect of shape on fluid flow and energy distribution. By comparing the different solids, it was found that the dodecahedron and the icosahedron exhibit very similar behaviors and tend to be the more efficient shapes for improving convection heat transfer. In contrast, the tetrahedron is much less efficient due to its structure, which does not favor the presence of a single convective cell. In general, increasing the number of faces, which leads to a more spherical shape and eliminates sharp corners, tends to enhance fluid recirculation and increase the average Nusselt number. For example, the icosahedron showed a 12% increase in the Nusselt number compared to the commonly studied hexahedron for Ra = 106. On the other hand, the tetrahedron demonstrated a 50% decrease in the Nusselt number relative to the cube, making it the least efficient shape among those evaluated.

Atmospheric molecular blobs shape up circumstellar envelopes of AGB stars.

During their thermally pulsing phase, asymptotic giant branch (AGB) stars eject material that forms extended dusty envelopes1. Visible polarimetric imaging found clumpy dust clouds within two stellar radii of several oxygen-rich stars2-6. Inhomogeneous molecular gas has also been observed in multiple emission lines within several stellar radii of different oxygen-rich stars, including W Hya and Mira7-10. At the stellar surface level, infrared images have shown intricate structures around the carbon semiregular variable R Scl and in the S-type star π1 Gru11,12. Infrared images have also shown clumpy dust structures within a few stellar radii of the prototypical carbon AGB star IRC+10°216 (refs. 13,14), and studies of molecular gas distribution beyond the dust formation zone have also shown complex circumstellar structures15. Because of the lack of sufficient spatial resolution, however, the distribution of molecular gas in the stellar atmosphere and the dust formation zone of AGB carbon stars is not known, nor is how it is subsequently expelled. Here we report observations with a resolution of one stellar radius of the recently formed dust and molecular gas in the atmosphere of IRC+10°216. Lines of HCN, SiS and SiC2 appear at different radii and in different clumps, which we interpret as large convective cells in the photosphere, as seen in Betelgeuse16. The convective cells coalesce with pulsation,causing anisotropies that, together with companions17,18, shape its circumstellar envelope.

Surface-temperature-induced Marangoni effects on developing buoyancy-driven flow

To investigate the initial development of the Rayleigh–Bénard–Marangoni (RBM) instability in a relatively deep domain, direct numerical simulations for a large range of Marangoni and Rayleigh numbers were performed. In the simulations, the surface was assumed to be flat and surface cooling was modelled by a constant heat flux. The small-scale dynamics of the flow and temperature fields near the surface was fully resolved by using a non-uniform vertical grid distribution. A detailed investigation of the differences in physical mechanisms that drive the Rayleigh- and Marangoni-dominated instabilities is presented. To this end, various properties such as the maturation rate of convection cells, the fluctuating kinetic energy and the surface characteristic length scale were studied. It was confirmed that buoyancy forces and surface-temperature-gradient-driven Marangoni forces enhance one another in promoting the development of the RBM instability. When using a relevant measure of the effective thermal boundary layer thickness as length scale, both the critical Marangoni and Rayleigh numbers, obtained for the purely Marangoni- and purely Rayleigh-driven instabilities, were found to be in good agreement with the literature.

Temperature variations in caves induced by atmospheric pressure variations—Part 2: Unveiling hidden thermal signals

In underground cavities, temperature variations of the order of 10−3°C are permanently induced by the variations of atmospheric pressure, even at great depths, with couplings of the order of 0.2 to 20 × 10−3°C/hPa depending on frequency. In the first part of this study, we established the atmospheric pressure to temperature transfer function (TF) as a function of frequency from 8 × 10−7 to 8 × 10−4 Hz. Here, we use this TF to calculate the expected PIT variations, which, after being subtracted from the observed time-series, provide residual temperature time-series. We calculated such temperature residuals in four natural caves in France: Esparros, Aven d'Orgnac, Pech Merle and Chauvet-Pont d'Arc Caves, the last two containing unique prehistoric wall paintings. Temperature signals, as small as a few 10−3°C, due to human presence, are then conspicuous, with evidence of relaxation longer than several days and long-term cumulative effects. In addition, we observe temperature signals suggesting non-stationary states characterized by several processes which are not necessarily easy to separate, such as transient air currents, due to barometric winds or locally semi-confined convection cells, transient infiltration, or energy dissipation by evaporation-condensation at the rock surface. This background thermal agitation displays a scale-free amplitude spectrum, from 2 × 10−5 to 4 × 10−4 Hz, of the form f−α, with α varying from 0.1 to 0.6 depending on the site. Furthermore, at the Chauvet Cave, a weak but unambiguous peak emerges during some months at a period of about 82.2 ± 0.8 minutes, suggesting a Helmholtz-type resonance. Small but significant temperature signals are therefore detected in underground cavities once the effect of atmospheric pressure variations is corrected for. These signals reveal subtle coupled processes whose knowledge is essential to evaluate preservation strategies and to establish conditions for resilience of underground systems under artificial or natural influence including climate change.

Near-Cloud Atmospheric Ingredients for Deep Convection Initiation

Abstract A lack of routine environmental observations located near deepening cumulus congestus clouds limits verification of important theorized and simulated updraft–environment interaction processes occurring during deep convection initiation (CI). We analyze radiosonde profiles collected during several hundred CI events near a mountain range in central Argentina during the CACTI field campaign. Statistical analyses illustrate environmental conditions supporting radar-observed CI outcomes that span a spectrum of convective cell depths, widths, and durations, as well as events lacking precipitating convection. Tested environmental factors include a large variety of sounding-derived measurements of CAPE, CIN, moisture, terrain-relative winds, vertical shear, and lifted parcel properties, with supplemental model reanalysis of background larger-scale vertical motion. CAPE and CIN metrics do not consistently differentiate CI success from failure. Only a few environmental factors contain consistent monotonic relationships among the spectrum of cloud depths achieved during CI: (i) the depth and strength of background ascent, and (ii) the component of low-level flow oriented parallel to the ridgeline. These metrics suggest that the ability of the surrounding flow to lift parcels to their LFC and terrain-modified flow are consistently relevant processes for CI. Low- to midlevel relative humidity strongly discriminated between CI and non-CI events, likely reflecting entrainment-driven dilution processes. However, we could not confidently conclude that relative humidity similarly discriminated robust from marginal CI events. Circumstantial evidence was found linking cell width, an important cloud property governing the probability of CI, to LCL height, boundary layer depth, depth and magnitude of the CIN layer, and ambient wind shear.

Numerical Study on Characteristics of Convection and Temperature Evolution in Microchannel of Thermal Flowmeter.

During practical usage, thermal flowmeters have a limited range of applications. The present work investigates the factors influencing thermal flowmeter measurements and observes the effects of buoyancy convection and forced convection on the flow rate measurement sensitivity. The results show that the gravity level, inclination angle, channel height, mass flow rate, and heating power affect the flow rate measurements by influencing the flow pattern and the temperature distribution. Gravity determines the generation of convective cells, while the inclination angle affects the location of the convective cells. Channel height affects the flow pattern and temperature distribution. Higher sensitivity can be achieved with smaller mass flow rates or higher heating power. According to the combined influence of the aforementioned parameters, the present work investigates the flow transition based on the Reynolds number and the Grashof number. When the Reynolds number is below the critical value corresponding to the Grashof number, convective cells emerge and affect the accuracy of flowmeter measurements. The research on influencing factors and flow transition presented in this paper has potential implications for the design and manufacture of thermal flowmeters under different working conditions.

Emergence of a Euglena bioconvection spot controlled by non-uniform light

Microorganisms possess taxes, which are the behavioral response to stimuli. The interaction between taxis and fluid dynamic instability leads to a macroscopic flow called bioconvection. In this study, we demonstrated that an isolated, single, three-dimensional bioconvection cell can exist within Euglena suspension. The isolated convection cell was named a “bioconvection spot.” To reveal the formation of this bioconvection spot in a cylindrical container, position-control experiments were designed in a non-uniform light environment. Upon exposure of Euglena suspensions to varying light conditions with white and red regions, Euglena was determined to aggregate into the red (darker) region. This was attributed to its phototactic response of Euglena, causing its movement toward a darker environment and away from a strong light. Thus, the bioconvection spot was created by manipulating the local cell density of the suspension and the light environments. Using our experimental setup, we observed the structure of the spot and established that it radiated pulses of local cell densities of Euglena.

Double diffusive Buoyancy‐driven flow in a fluid‐saturated elliptical annulus with a neural network‐based prediction of heat and mass transfer

AbstractThis paper presents a numerical study of buoyancy‐driven double‐diffusive convection within an elliptical annulus enclosure filled with a saturated porous medium. An in‐house built FORTRAN code has been developed, and computations are carried out in a range of values of Darcy–Rayleigh number Ram (10 ≤ Ram ≤ 500), Lewis number Le (0.1 ≤ Le ≤ 10), and the ratio of buoyancy forces N (−5 ≤ N ≤ 5). In addition, three methods are used, namely the multi‐variable polynomial regression, the group method of data handling (GMDH), and the artificial neural network (ANN) for the predictions of heat and mass transfer rates. First, results are successfully validated with existing numerical and experimental data. Then, the results indicated that temperature and concentration distributions are sensitive to the Lewis number and thermal and mass plumes are developing in proportion to the Lewis number. Two particular values of Lewis number Le = 2.735 and Le = 2.75 captured the flow's transition toward an asymmetric structure with a bifurcation of convective cells. The average Nusselt number tends to have an almost asymptotic value for Le » 5. For the case of aiding buoyancies N > 1, the average Nusselt Number decreased by 33% when the Lewis number increased to its maximum value. Then, it increased by 10% when the Lewis number increased to Le = 1 for the case of opposing buoyancies N < 1 and then decreased by 33% when the Lewis number increased to its maximum value., contrary to the behavior of the average Sherwood number that increased by 700% for both cases N > 1 and N < 1. New correlations of , and as a function of Ram, Le, and N are derived and compared with GMDH and ANN methods, and the ANN method showed higher performance for the prediction of and with R2 exceeding 0.99.

Satellite observations of smoke–cloud–radiation interactions over the Amazon rainforest

Abstract. The Amazon rainforest routinely experiences intense and long-lived biomass burning events that result in smoke plumes that cover vast regions. The spatial and temporal extent of the plumes and the complex pathways through which they interact with the atmosphere have proved challenging to measure for purposes of gaining a representative understanding of smoke impacts on the Amazonian atmosphere. In this study, we use multiple collocated satellite sensors on board AQUA and TERRA platforms to study the underlying smoke–cloud–radiation interactions during the diurnal cycle. An 18-year time series for both morning and afternoon overpasses is constructed, providing collocated measurements of aerosol optical depth (AOD; column-integrated aerosol extinction), cloud properties, top-of-atmosphere radiative fluxes, precipitation, and column water vapour content from independent sources. The long-term time series reduces the impact of interannual variability and provides robust evidence that smoke significantly modifies the Amazonian atmosphere. Low loadings of smoke (AOD ≤ 0.4) enhance convective activity, cloudiness, and precipitation, but higher loadings (AOD > 0.4) strongly suppress afternoon convection and promote low-level cloud occurrence. Accumulated precipitation increases with convective activity but remains elevated under high smoke loadings, suggesting fewer but more intense convective cells. Contrasting morning and afternoon cloud responses to smoke are observed, in line with recent simulations. Observations of top-of-atmosphere radiative fluxes support the findings and show that the response of low-level cloud properties and cirrus coverage to smoke results in a pronounced and consistent increase in top-of-atmosphere outgoing radiation (cooling) of up to 50 W m−2 for an AOD perturbation of +1.0. The results demonstrate that smoke strongly modifies the atmosphere over the Amazon via widespread changes to the cloud field properties. Rapid adjustments work alongside instantaneous radiative effects to drive a stronger cooling effect from smoke than previously thought, whilst contrasting morning and afternoon responses of liquid and ice water paths highlight a potential method for constraining aerosol impacts on climate. Increased drought susceptibility, land use change, and deforestation will have important and widespread impacts on the region over the coming decades. Based on this analysis, we anticipate that further increases in anthropogenic fire activity will associated with an overall reduction in regional precipitation and a negative forcing (cooling) on the Earth's energy budget.

A Merger‐Formation Bow Echo Caused by Low‐Level Mesovortex in South China

AbstractThis work studied a high winds‐producing bow echo that occurred over South China in the pre‐rainy season using radar observations and high‐resolution analyses from the Variational Doppler Radar Analysis System. The bow echo developed from a quasi‐linear convective system (QLCS) and acquired a well‐defined bow shape after merging with a pre‐line convective cell (CC). Interestingly, the rear‐inflow jet (RIJ), which has been well recognized to play a key role in the formation of a bow echo, was not found in this merger‐formation bow echo (MFBE). The reason is that the QLCS developed in the monsoon environment of high humidity and weak vertical wind shear, leading to a weak cold pool and line‐end vortices. A new pathway of bow echo formation was proposed which highlighted the importance of the low‐level mesovortex (MV) on the leading edge of the QLCS. Vertical vorticity budget analyses revealed that the MV originated from a weak vertical vorticity band ahead of the QLCS and grew rapidly during the merger, because of the enhanced low‐level convergence in between which led to vortexgenesis via vertical stretching of vertical vorticity. The up‐scale growth of the MV produced a RIJ‐like flow wrapping cyclonically from north of the QLCS which forced the system to bulge out and finally evolve into a bow echo. This MV contributed foremost to the near‐surface gales as well. These findings shed light on the diverse formation mechanisms of bow echoes and associated high winds in the moist monsoon environment of South China.