A high-resolution LES simulation method, medium and program product for TCBL wind field parameterization in gray area

Abstract

The present invention discloses a high-resolution LES simulation method, medium and program product for TCBL wind field parameterization in gray area. The method constructs an idealized initial gradient wind field of TCBL based on the modified Rankine vortex model, ensures the controllability and stability of the initial conditions by specifying key dynamic parameters, obtains thermodynamic profiles under different wind speed conditions based on synthetic analysis of tropical cyclone sounding data, and uses quadratic and logarithmic function fitting methods to correct at the bottom of the boundary layer. Through high-resolution grid configuration and dynamic boundary conditions, combined with the SGS-TKE closed model to process sub-grid turbulence, a dynamic correction mechanism is used to optimize the model's adaptability to strong rotation and high wind shear environments. In addition, the present invention maintains the stability of thermodynamic variables through large-scale tendency correction, and outputs high-resolution three-dimensional wind field and turbulence statistical benchmark data, which are used to verify and improve the turbulence parameterization scheme of TCBL at gray area resolution.

Description

Technical Field

[0001] The present invention belongs to the technical field of meteorological numerical simulation and turbulence parameterization, and relates to high-resolution numerical simulation of tropical cyclone boundary layer wind field. Specifically, it is a high-resolution LES simulation method, medium and program product of TCBL wind field for gray zone parameterization. By constructing an idealized LES simulation framework based on a modified Rankine vortex model, reliable benchmark data is provided to improve the gray zone resolution parameterization scheme, thereby providing a scientific basis for improving the accuracy of tropical cyclone numerical prediction. Background Art

[0002] As the main area for momentum, heat and water vapor exchange between tropical cyclones and the ocean or land, the tropical cyclone boundary layer (TCBL) has a decisive influence on the overall dynamic behavior of the cyclone due to its wind field distribution, turbulence characteristics and energy exchange process. However, due to the complexity and highly nonlinear characteristics of the TCBL, accurate simulation of its wind field has always been a major technical challenge in numerical weather forecasting. With the improvement of numerical model resolution, the horizontal resolution of modern numerical weather forecast models has gradually entered the Grey Zone range of 0.1-1 km. In this resolution range, it is difficult for numerical models to simultaneously resolve the explicit large-scale components of turbulence and the parameterized subgrid-scale (SGS) components, resulting in a significant decrease in the accuracy of simulation results. The core problem of the Grey Zone resolution is that this scale range can neither fully resolve the turbulence structure nor accurately characterize the small-scale turbulence characteristics through traditional turbulence parameterization schemes. For the simulation of TCBL wind fields, the Grey Zone resolution problem is particularly prominent, which directly affects the accuracy of tropical cyclone intensity simulation and path prediction.

[0003] At present, the research on gray zone resolution is mainly focused on developing scale-aware parameterization schemes that adapt to different atmospheric layers. The core idea is to construct a subgrid-scale turbulent kinetic energy (SGS-TKE) proportional function that varies with grid resolution through experimental fitting and theoretical analysis, so as to dynamically adjust the parameterization intensity of subgrid turbulence at gray interval resolution, reduce the overestimation or underestimation of subgrid turbulence by the model, and improve the simulation accuracy. However, the scale-dependent functions of most current scale-aware parameterization schemes are mainly based on the research and development of conventional convective boundary layer (CBL) or stable boundary layer (SBL), and lack systematic verification data for TCBL characteristics. Especially in the environment of strong rotation effect and high wind shear of TCBL, the applicability and accuracy of existing parameterization schemes are difficult to be effectively evaluated due to the lack of reliable high-resolution benchmark solutions.

[0004] Large Eddy Simulation (LES) is a small-scale simulation method that analyzes large-scale turbulence and parameterizes sub-grid turbulence. It simulates turbulent flow by directly analyzing large-scale turbulent eddies and parameterizing sub-grid scale eddies. It can capture the spatial distribution characteristics and temporal variation of turbulence at a high resolution and is an important means to study turbulent processes in complex boundary layers. In particular, at high resolution, LES can explicitly distinguish the main turbulent structures in TCBL, providing an important reference for the development and improvement of parameterization schemes at gray-zone resolution. However, the current high-resolution LES research on TCBL still faces many challenges: first, the existing LES closed model is mainly developed for conventional boundary layers, and its applicability in the strong rotation and high wind shear environment of TCBL needs to be verified; second, the huge demand for computing resources limits its wide application in the development of parameterization schemes; in addition, there is a lack of a systematic simulation framework to provide reliable benchmark data for verifying and improving parameterization schemes at gray-zone resolution.

[0005] In summary, the turbulence structure of TCBL is significantly different from that of the traditional boundary layer. The existing numerical models and scale-aware similarity functions cannot effectively simulate the TCBL wind field at the gray zone resolution. There are problems such as inapplicability of parameterization schemes, insufficient representation of sub-grid scale turbulence, and poor adaptability of LES closed models to strong rotation and wind shear. Therefore, in order to improve the simulation accuracy of TCBL wind fields at gray zone resolution, a high-resolution LES simulation method for TCBL wind fields oriented to gray zone parameterization is developed. By providing a reliable benchmark solution, a scientific basis is provided for improving the turbulence parameterization scheme at gray zone resolution, which is a technical problem that needs to be solved urgently to improve the numerical prediction accuracy of tropical cyclones (TCs). Summary of the invention

[0006] 1. Purpose of the invention

[0007] The existing parameterization schemes for simulating tropical cyclone boundary layer (TCBL) wind fields at gray zone resolution (0.1-1 km) are not applicable enough, there is a lack of reliable high-resolution benchmark data for verifying and improving parameterization schemes, and the existing large eddy simulation (LES) Abstract: In order to solve at least one of the above and other technical problems in the prior art, the present invention aims to provide a high-resolution LES simulation method, medium and program product for gray-zone parameterization of TCBL wind field, by constructing an idealized high-resolution LES simulation framework of TCBL wind field based on the modified Rankine vortex model to explicitly analyze the large-scale turbulence structure and parameterize the sub-grid turbulent kinetic energy, and combining the large-scale tendency correction mechanism of thermodynamic and kinetic profiles to optimize the initialization of wind field and profile structure, and by improving the LES turbulence closure model to adapt to the turbulence characteristics of strong rotation and high wind shear environment in TCBL, finally, through high-resolution LES simulation, the benchmark data that can be used to verify and improve the gray-zone resolution scale perception parameterization scheme is obtained, so as to provide a scientific basis for the development of gray-zone resolution turbulence parameterization scheme suitable for TCBL characteristics, and improve the accuracy of TCBL wind field simulation and the accuracy and reliability of tropical cyclone numerical forecast.

[0008] (II) Technical solution

[0009] In order to achieve the purpose of the invention and solve the technical problems, the present invention adopts the following technical solutions:

[0010] The first invention object of the present invention is to provide a high-resolution LES simulation method for TCBL wind field for gray zone parameterization, which is used to generate reliable benchmark data of tropical cyclone boundary layer (TCBL) wind field at gray zone resolution (0.1-1km) through high-resolution large eddy simulation (LES), and provide support for the optimization of gray zone resolution turbulence parameterization scheme. The method at least includes the following steps when implemented:

[0011] SS1. Construction of idealized wind field based on modified Rankine vortex model

[0012] Based on the modified Rankine vortex model, an idealized initial gradient wind field of TCBL is constructed, and the large-scale conditions of the initial gradient wind field of TCBL are integrated by specifying key dynamic parameters, wherein the key dynamic parameters include at least the gradient wind speed V , its radial gradient , radial distance from the cyclone center r , Maximum wind speed radius R max and the power law exponent that controls the decay of tangential wind speed with radial distance n , in order to maintain the controlled conditions of the initial gradient wind field of TCBL, reduce the complexity of the overall tropical cyclone vortex feedback mechanism, and ensure the controllability and simulation stability of the initial state of the TCBL wind field;

[0013] SS2. Construct high-resolution LES grid and set boundary conditions

[0014] Under the framework of high-resolution LES, a three-dimensional computational domain with a horizontal range of 5-10 km and a vertical range of 3-5 km is constructed as the simulation area. The horizontal grid resolution is set to 10-100 m, and the vertical grid resolution is half of the horizontal grid resolution. At the same time, periodic boundary conditions are set in two orthogonal horizontal directions to avoid wind field distortion caused by boundary effects. In the vertical direction, a no-slip lower boundary and an upper boundary with fixed potential height are set, and the top boundary is set to a wind speed free sliding boundary and a constant potential temperature boundary condition. In the area above 2 km, Rayleigh Damping layers to suppress gravity wave reflections;

[0015] SS3. Initialize thermodynamic profiles and perform large-scale trend correction

[0016] Based on the synthetic analysis of tropical cyclone sounding data, the thermodynamic variable profiles under different wind speed conditions are obtained and used as the initial thermodynamic conditions of LES simulation and the reference profiles during the simulation process. The thermodynamic variables include at least the potential temperature, i and specific humidityq , and introduce a large-scale tendency correction (nudging term) in the LES simulation process to dynamically adjust the thermodynamic variables in the simulation area to evolve toward the reference profile to maintain the potential temperature and specific humidity profile structure. The expression of the large-scale tendency correction term is:

[0017]

[0018] in, i ( z )and q ( z ) are the specified heights in the simulation area z The horizontal average potential temperature and specific humidity on i r ( z )and q r ( z ) are the corresponding reference potential temperature and specific humidity profile values, t n To ease the time scale;

[0019] SS4. Resolving large-scale turbulent structures and parameterizing sub-grid turbulent kinetic energy

[0020] Based on the LES framework, the turbulence simulation and numerical solution of the tropical cyclone boundary layer in the simulation area are implemented, the large-scale turbulent eddy structure in the TCBL is explicitly resolved, and the sub-grid scale turbulent kinetic energy SGS-TKE closed model is adopted. By considering the influence of strong rotation and high wind shear of TCBL on sub-grid scale turbulent transport and anisotropy, and dynamically adjusting the model coefficients according to local wind shear and stability parameters, the unresolved sub-grid scale turbulence is parameterized. At the same time, the control equations are discretized using a high-order precision numerical discretization format to ensure the accurate transfer and dissipation of turbulent energy, and to achieve high-precision simulation of turbulent characteristics and energy distribution;

[0021] SS5. Perform LES simulation integration and monitor state evolution

[0022] Preset the total duration and time step of the LES simulation, perform time integration to advance the evolution of the wind field and thermodynamic variables until the preset total simulation duration is reached, and monitor the state evolution of the key variables of the TCBL wind field during the simulation to ensure that the simulation reaches a quasi-steady state, wherein the state evolution of the key variables at least includes the change of the boundary layer height and the 10-meter wind speed, the boundary layer height is defined as the height at which the momentum flux drops to 5% of the surface value, and the quasi-steady state criterion is that the change rate of the boundary layer height and the 10-meter wind speed is less than a preset threshold;

[0023] SS6. Output LES simulation results and perform post-processing

[0024] The TCBL wind field data generated based on high-resolution LES simulation is output, and the output results are post-processed and analyzed to generate a benchmark data set including TCBL three-dimensional wind field, temperature field, humidity field and various turbulence statistics, which is used to verify and improve the turbulence parameterization scheme of TCBL at gray zone resolution.

[0025] The second inventive object of the present invention is to provide a computer program product, comprising computer instructions for executing the above-mentioned gray zone oriented parameterized TCBL wind field high-resolution LES simulation method.

[0026] The third inventive object of the present invention is to provide a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the above-mentioned gray zone-oriented parameterized TCBL wind field high-resolution LES simulation method is implemented.

[0027] (III) Technical Effect

[0028] Compared with the prior art, the gray zone parameterized TCBL wind field high-resolution LES simulation method, medium and program product of the present invention have the following beneficial and significant technical effects:

[0029] (1) The present invention constructs an idealized TCBL initial gradient wind field based on the modified Rankine vortex model, and integrates large-scale conditions by specifying key dynamic parameters (such as gradient wind speed, radial gradient, and maximum wind speed radius, etc.), effectively reducing the complexity of the overall vortex feedback mechanism of the tropical cyclone, while enhancing the controllability and stability of the initial conditions. In addition, the present invention adopts a high-resolution LES framework, reasonably sets the computational domain size and grid resolution, and cooperates with periodic horizontal boundary conditions and vertical boundary conditions with damping layers, effectively avoiding the influence of boundary effects on simulation results. At the same time, the hierarchical grid design significantly reduces the demand for computing resources and improves simulation efficiency.

[0030] (2) The present invention adopts a high-resolution LES framework, and by reasonably setting the computational domain size and grid resolution, and coordinating periodic horizontal boundary conditions and vertical boundary conditions with damping layers, the influence of boundary effects on simulation results is effectively avoided. At the same time, the hierarchical grid design significantly reduces the demand for computing resources and improves simulation efficiency. In addition, by introducing a thermodynamic variable profile optimization scheme combined with sounding observation data, quadratic functions and logarithmic functions are used for fitting at the bottom of the boundary layer, and the transition zone at the top of the boundary layer is smoothed, the accurate characterization and effective maintenance of the TCBL thermodynamic structure are achieved, ensuring the physical rationality of the simulation results.

[0031] (3) The present invention uses a sub-grid scale turbulent kinetic energy (SGS-TKE) closed model to deal with unresolved small-scale turbulence. By introducing a dynamic correction mechanism that considers the strong rotation and high wind shear environment of TCBL, the model coefficients are optimized and the parameterization capability of sub-grid turbulence is enhanced. At the same time, the vertical shear effect of the near-surface layer is dynamically corrected by the Sullivan correction term to more accurately capture the anisotropic characteristics of turbulence in the surface friction layer. During the LES simulation process, the present invention dynamically adjusts the evolution of thermodynamic variables to the reference profile by combining large-scale tendency correction, and monitors the evolution of wind field states by implementing LES simulation integration, and finally outputs a high-resolution TCBL three-dimensional wind field and turbulence statistics benchmark data set. These data can be directly used to verify and improve the turbulence parameterization scheme at gray zone resolution, providing a scientific basis for the development of scale-aware parameterization methods suitable for TCBL. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 It is a schematic diagram of the implementation process of the gray zone parameterized TCBL wind field high-resolution LES simulation method according to an embodiment of the present invention.

[0033] Figure 2 The following table shows the physical quantities (horizontal wind speed) in different cases (V25, V35, V45, CBL and SBL). u , tangential wind speed v and position temperature i ), where (a)-(c) are the vertical profiles of V25, V35 and V45 cases, (d)-(f) are the vertical profiles of CBL case, and (g)-(i) are the vertical profiles of SBL case. These data are obtained after 6 hours of integration.

[0034] Figure 3 The figure shows the characteristic distribution diagram of the grid-scale turbulent kinetic energy (SGS-TKE) under different working conditions as the grid size changes in the embodiment of the present invention. Δx / h Indicates the grid scale Δx Boundary layer height h The ratio of the vertical axis represents the SGS-TKE ratio Psgse , where (a)-(c) correspond to LES simulations under TCBL conditions with wind speeds of 25m / s, 35m / s and 45m / s at a height of 10 meters, respectively, (d) is the convective boundary layer CBL condition, (e) is the stable boundary layer SBL condition, and (f) is a comparison of the partial similarity functions derived from the five conditions and the Shin&Hong scheme. DETAILED DESCRIPTION

[0035] In order to make the purpose, technical scheme and advantages of the implementation of the present invention clearer, the technical scheme in the embodiment of the present invention will be described in more detail below in conjunction with the drawings in the embodiment of the present invention. The described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. The embodiments described below with reference to the drawings are exemplary and are intended to be used to explain the present invention, and should not be understood as limiting the present invention. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0036] The present invention aims to provide a high-resolution LES simulation method for TCBL wind field with gray zone parameterization, which is used to generate reliable benchmark data of tropical cyclone boundary layer (TCBL) wind field with gray zone resolution (0.1-1 km) through high-resolution large eddy simulation (LES), and provide support for the optimization of gray zone resolution turbulence parameterization scheme. Figure 1 As shown, the implementation process of this method includes at least the following steps:

[0037] SS1. Construction of idealized wind field based on modified Rankine vortex model

[0038] In the implementation of the present invention, the idealized initial gradient wind field of TCBL is first constructed by modifying the Rankine vortex model. The model integrates the large-scale conditions of the initial gradient wind field of TCBL by specifying key dynamic parameters, where the key dynamic parameters include the gradient wind speed V , its radial gradient , radial distance from the cyclone center r , Maximum wind speed radius R max and the power law exponent that controls the decay of tangential wind speed with radial distance n Etc. Through these parameter controls, the controlled conditions of the TCBL initial gradient wind field can be maintained, the complexity of the overall tropical cyclone vortex feedback mechanism can be reduced, and the controllability and simulation stability of the TCBL initial state of the wind field can be ensured.

[0039] As a preference, the initial wind field is at the maximum wind speed radius R max Inboard tangential wind speed V t Using a linear growth function Simulate, exceed the maximum wind radius R max Tangential wind speed V t Modeled as a power law function of the radial distance from the cyclone center , maximum wind radius R max Tangential wind speed V t The radial gradient of ,in, k 1 , k 2 is the dimensionless coefficient of the model, n To control the power law exponent of the attenuation of tangential wind speed with radial distance, V max is the maximum tangential wind speed, R max is the maximum wind speed radius, r is the radial distance from the center of the cyclone.

[0040] As a more preferred example, the gradient wind speed V The value range is 35-65m / s, and is set according to the target wind speed: 25m / s at a height of 10 meters. V =44m / s, 35m / s 10m height tangential wind speed case V =58m / s, 45m / s 10m height tangential wind speed case V =65m / s; when determining the radial gradient, the power law relationship The calculations were performed with the tangential wind speeds at 10 m height of 25 m / s and 35 m / s. n =0.7, 45m / s 10m height tangential wind speed case n =0.75; Maximum wind radius R max The selection corresponds to different target wind speeds: 25m / s 10m height tangential wind speed case R max =110km, 35m / s tangential wind speed at 10m height R max =75km, 45m / s tangential wind speed at 10m height R max =40km.

[0041] By using the modified Rankine vortex model, the initial conditions of the wind field can be effectively simplified, and the complex feedback mechanism of the overall wind field can be effectively reduced by controlling the radial attenuation characteristics of the wind speed. Especially in the boundary layer, the reasonable configuration of the radial gradient of the wind speed and the maximum wind speed radius can make the simulation results closer to the actual physical situation and improve the stability and physical consistency of the simulation.

[0042] SS2. Construct high-resolution LES grid and set boundary conditions

[0043] Under the framework of high-resolution LES, a three-dimensional computational domain with a horizontal range of 5-10 km and a vertical range of 3-5 km is constructed as the simulation area. The horizontal grid resolution is set to 10-100 m, and the vertical grid resolution is half of the horizontal grid resolution. At the same time, periodic boundary conditions are set in two orthogonal horizontal directions to avoid wind field distortion caused by boundary effects. In the vertical direction, a no-slip lower boundary and an upper boundary with fixed potential height are set, and the top boundary is set to a wind speed free sliding boundary and a constant potential temperature boundary condition. In the area above 2 km, Rayleigh Damping layer to suppress gravity wave reflection.

[0044] As a preferred option, the specific parameters of the three-dimensional computational domain are set as follows: the horizontal range is 5 km × 5 km, the vertical height is 3 km; the horizontal grid resolution is uniformly set to Δx = Δy = 10m, hierarchical grids are used in the vertical direction, and the area below 2km is taken Δz =5m, 2-3km interval Δz =12.5m; the thickness of the Rayleigh damping layer is set to 1km, the damping coefficient increases linearly with height, and the maximum damping coefficient is 0.003s -1 ; At the same time, in order to further reduce the impact of boundary effects, a buffer zone of 100 grid points is set around the simulation area to reduce the numerical instability at the boundary. In addition, in the area near the maximum wind speed radius, the grid resolution should be finer to improve the resolution accuracy of the area, and in the location far away from the key area, the grid density should be appropriately reduced to save computing resources. This grid optimization method can not only ensure the simulation accuracy of the key area, but also reduce the amount of calculation and achieve efficient simulation.

[0045] SS3. Initialize thermodynamic profiles and perform large-scale trend correction

[0046] Based on the synthetic analysis of tropical cyclone sounding data, the present invention obtains the thermodynamic variable profiles under different wind speed conditions and uses them as the initial thermodynamic conditions of LES simulation and the reference profiles during the simulation process. The thermodynamic variables include at least potential temperature i and specific humidity q , and introduce a large-scale tendency correction (nudging term) in the LES simulation process to dynamically adjust the thermodynamic variables in the simulation area to evolve toward the reference profile to maintain the potential temperature and specific humidity profile structure. The expression of the large-scale tendency correction term is:

[0047]

[0048] in, i ( z )andq ( z ) are the specified heights in the simulation area z The horizontal average potential temperature and specific humidity on i r ( z )and q r ( z ) are the corresponding reference potential temperature and specific humidity profile values, t n To ease the time scale.

[0049] As a preference, tropical cyclone sounding data are based on historical observation data or model synthesis data of typical tropical cyclones, and a synthesis method based on wind speed classification at 10 meters is used to obtain thermodynamic profiles of tropical cyclones of different intensities, where the potential temperature profile at the bottom 200 meters of the boundary layer is obtained using The quadratic function fitting of The logarithmic function fit of z is the height, i 0 , q 0 are the initial potential temperature and initial specific humidity of the near-surface layer, z 0 is the characteristic height, a 1 , a 2 , b 1 are the fitting coefficients and are determined based on near-surface observation data. The thermodynamic profile is smoothed in the 500m transition zone near the top of the boundary layer to avoid sharp vertical gradients. Meanwhile, the stability of the thermodynamic profile is maintained through large-scale inclination correction during the simulation.

[0050] Further preferably, the large-scale tendency correction execution strategy of the present invention includes the following sub-steps:

[0051] SS31. Set the easing time scale t n = 5min, control thermodynamic variables (such as potential temperature i and specific humidity q ) The rate of evolution toward the reference profile, avoiding instability caused by drastic adjustments;

[0052] SS32. The intensity of the dip correction is linearly reduced to zero in the transition zone with a thickness of 500 m at the top of the boundary layer. The mathematical expression is: ,in, z BLH represents the TCBL boundary layer height, which is dynamically calculated by the Richardson number method or the turbulent kinetic energy integration method;

[0053] SS33. The sea surface temperature is set to the surface air temperature plus 2°C to simulate the influence of the sea-air temperature difference on the thermodynamic evolution in the cyclone system and improve the simulation accuracy of the thermodynamic process in the surface layer of tropical cyclones;

[0054] SS34. Update the large-scale bias correction term once at the end of each time step ( i r , q r ), and the thermodynamic profiles are horizontally averaged before updating to reduce local noise, specifically:

[0055]

[0056] in A is the horizontal area of ​​the simulation region, ( x , y , z ) is the three-dimensional coordinate of any point in the simulation area;

[0057] SS35. When updating the tendency correction term, the gradient limiting method is used to avoid large instantaneous changes to ensure the rationality and stability of large-scale forcing:

[0058]

[0059] in, is the variable to be corrected (e.g. i or q ), The preset maximum correction range.

[0060] SS4. Resolving large-scale turbulent structures and parameterizing sub-grid turbulent kinetic energy

[0061] Based on the LES framework, turbulence simulation and numerical solution of the tropical cyclone boundary layer in the simulation area are implemented, the large-scale turbulent eddy structure in the TCBL is explicitly analyzed, and the sub-grid scale turbulent kinetic energy SGS-TKE closed model is adopted. By considering the influence of strong rotation and high wind shear of TCBL on sub-grid scale turbulent transport and anisotropy, and dynamically adjusting the model coefficients according to local wind shear and stability parameters, the unresolved sub-grid scale turbulence is parameterized. At the same time, the control equations are discretized using a high-order precision numerical discrete format to ensure the accurate transfer and dissipation of turbulent energy, so as to achieve high-precision simulation of turbulent characteristics and energy distribution.

[0062] Preferably, the sub-grid scale turbulent kinetic energy SGS-TKE closed model includes a standard TKE part using the Deardorff scheme in the entire computational domain and a Sullivan correction term for the near-ground layer, and the Sullivan correction term only takes effect in the area below 100 m from the ground; the time advancement adopts the third-order Runge-Kutta format, the spatial term is discretized using the fifth-order upwind difference format, and the time step is set to 0.5 seconds to ensure the numerical stability of the calculation.

[0063] Preferably, the dynamic Smagorinsky model is used to process the subgrid stress, and the model coefficients are calculated by averaging the local area. C s :

[0064]

[0065] in, L ij is the Leonard stress term, M ij is a model-related term, <•> represents the local spatial average, and anisotropic effects are additionally considered in strong shear regions. And the specific form of the Sullivan correction term in the near-surface layer is ,in, t ij is the subgrid-scale stress tensor, D is the filtering scale, l s is the characteristic length scale of the turbulent structure in the near-surface layer, | S | cl is the classical definition of shear rate, S ij is the strain rate tensor, Represents the velocity component U i , U j In the vertical direction x 3 This correction term improves the simulation of turbulence near the ground by taking into account the influence of the vertical gradient.

[0066] SS5. Perform LES simulation integration and monitor state evolution

[0067] The total duration and time step of the LES simulation are preset, and time integration is performed to advance the evolution of the wind field and thermodynamic variables until the preset total simulation duration is reached. During the simulation, the state evolution of the key variables of the TCBL wind field is monitored to ensure that the simulation reaches a quasi-steady state. The state evolution of the key variables includes at least the changes in the boundary layer height and the 10-meter wind speed. The boundary layer height is defined as the height where the momentum flux drops to 5% of the surface value. The quasi-steady-state criterion is that the rate of change of the boundary layer height and the 10-meter wind speed is less than the preset threshold.

[0068] Preferably, the total simulation time can be set to 6 hours, of which the first 4 hours are the adjustment period and the last 2 hours are the analysis period; the simulation results output three-dimensional field data every 6 minutes; the quasi-steady state judgment criteria are: the relative change rate of the TCBL wind field boundary layer height and the 10-meter wind speed is less than 1% in multiple consecutive time steps, and the shape of the momentum flux profile remains stable.

[0069] Preferably, the following turbulence statistics are simultaneously recorded and analyzed during the LES simulation process: Reynolds stress components, vertical distribution of turbulent kinetic energy, momentum flux profile, effective eddy viscosity coefficient, turbulence length scale and potential temperature flux, to verify the physical rationality of the simulation results. When the time rate of change of these turbulence statistics is less than the preset threshold, the LES simulation is considered to have reached a quasi-steady state.

[0070] SS6. Output LES simulation results and perform post-processing

[0071] After the LES simulation is completed, the TCBL wind field data generated based on the high-resolution LES simulation is output, and the output results are post-processed and analyzed to generate a benchmark data set including the TCBL three-dimensional wind field, temperature field, humidity field and various turbulence statistics, which is used to verify and improve the turbulence parameterization scheme of TCBL at gray zone resolution.

[0072] Preferably, the post-processing analysis of the LES simulation output results at least includes calculating the horizontally averaged momentum flux and heat flux profiles, analyzing the turbulence energy spectrum characteristics, evaluating the turbulence intensity and length scale at different altitudes, and statistically analyzing the three-dimensional distribution characteristics of the sub-grid turbulent kinetic energy. These results are then compared and verified with existing observational data and theoretical analysis, providing a more comprehensive data basis for verifying and improving the turbulence parameterization scheme of TCBL at gray zone resolution.

[0073] Under the LES simulation framework of the embodiment of the present invention, a systematic simulation study is conducted for different wind speed intensity conditions and different boundary layer stability states. Figure 2 The physical quantities (horizontal wind speed) in different cases (V25, V35, V45, CBL and SBL) are shown. u , tangential wind speed v and position temperature i), these results are key simulation data obtained by LES simulation of the tropical cyclone boundary layer (TCBL) and other typical boundary layers (convective boundary layer CBL and stable boundary layer SBL) at gray zone resolution for 6 hours. These data are obtained through high-resolution integration and provide an important reference for the optimization of gray zone parameterization schemes. Specifically:

[0074] The simulation results for different wind speed and intensity conditions are as follows: Figure 2 As shown in (a)-(c), V25, V35 and V45 represent three typical intensity cases with tangential wind speeds of 25m / s, 35m / s and 45m / s at a height of 10 meters. Figure 2 As can be seen in (a), as the cyclone intensity increases, the thickness of the inflow layer gradually decreases and the maximum inflow velocity increases accordingly, which is consistent with the observed characteristics of strong tropical cyclones. Figure 2 (b) shows that the change of wind speed with height shows obvious shear characteristics in the boundary layer, and the greater the wind speed, the stronger the shear. Figure 2 (c) shows the relatively stable stratification characteristics in the boundary layer. Figure 2 df in the figure shows that it has significantly different dynamic and thermal characteristics. The radial wind speed and tangential wind speed profiles ( Figure 2 d,e) in the boundary layer show a relatively uniform distribution, which reflects the full development of turbulent mixing under neutral conditions. Figure 2 f) shows typical neutral stratification characteristics and remains basically unchanged within the boundary layer. The simulation results of the stable boundary layer SBL case ( Figure 2 gi) shows another typical state, radial wind speed ( Figure 2 g) shows obvious wind shear near the ground, with the tangential wind speed ( Figure 2 In the middle h), there are obvious jet characteristics in the lower layer, and the potential temperature profile ( Figure 2 (i) in the figure shows typical stable stratification characteristics, and the temperature inversion phenomenon near the ground is very obvious.

[0075] These simulation results fully verify that the LES simulation method proposed in the present invention can accurately capture the key dynamic and thermal characteristics of TCBL under different conditions. Especially when dealing with strong wind shear and different stability conditions, the model shows good adaptability and stability. At the same time, these high-resolution simulation results provide reliable benchmark data for further research and improvement of turbulence parameterization schemes under gray zone resolution. By comparing the simulation results of different cases, it can be clearly seen that the change law of boundary layer structure with cyclone intensity and stability state is of great guiding significance for in-depth understanding of the dynamic characteristics of TCBL and the development of corresponding parameterization schemes. These results also confirm that the simulation method proposed in the present invention has strong universality and reliability in dealing with complex boundary layer conditions.

[0076] In order to better illustrate the advantages and necessity of the method of the present invention, Figure 3 Showing the subgrid-scale TKE ratios for different boundary layer types (TCBL, CBL, and SBL) Psgse Resolution with scale Δx / h The change relationship of Δx is the horizontal grid resolution, h is the boundary layer height. Figures (a)-(e) correspond to the LES simulation results of TCBL (V25, V35, V45), CBL and SBL under different wind speed conditions. The box plots in the figure show Psgse At different scales of resolution Δx / h The center line represents the median, the box edge represents the interquartile range, and the dotted line represents the maximum and minimum values ​​after removing outliers. Figure (f) shows the similarity function (red curve) fitted based on the simulation results and the similarity function in the Shin&Hong scheme (black dotted line).

[0077] from Figure 3 It can be seen that all boundary layer types Psgse All follow Δx / h This indicates that at coarser resolutions, a larger proportion of the turbulent kinetic energy needs to be parameterized. Δx / h Next, TCBL Psgse Significantly higher than CBL and SBL, especially in the gray area resolution range (0.08< Δx / h <1). This indicates that the subgrid-scale turbulent kinetic energy SGS-TKE in TCBL is more important and requires more sophisticated treatment. In addition, the similarity function of TCBL is significantly different from that of CBL and SBL, which indicates that the scale-aware parameterization scheme developed based on CBL or SBL may not be applicable to TCBL. The similarity function of Shin & Hong's scheme also underestimates the TCBL's gray-scale resolution. PsgseThese results indicate that when simulating TCBL wind fields at gray-zone resolution, it is necessary to pay more attention to the effects of subgrid-scale turbulence and develop scale-aware parameterization schemes that are more suitable for TCBL. The high-resolution LES simulation method proposed in this invention is designed to solve this problem. By generating high-precision TCBL wind field benchmark data, it provides support for the optimization of gray-zone resolution turbulence parameterization schemes.

[0078] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention is described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A high-resolution LES simulation method for TCBL wind field with gray zone parameterization, characterized in that: The method comprises at least the following steps when implemented: SS1. Construct an idealized initial gradient wind field for TCBL based on the modified Rankine vortex model, and integrate the large-scale conditions of the initial gradient wind field for TCBL by specifying key dynamic parameters, where the key dynamic parameters include at least the gradient wind speed. V , its radial gradient , radial distance from the cyclone center r , Maximum wind speed radius R max and the power law exponent that controls the decay of tangential wind speed with radial distance n ; SS2. Under the high-resolution LES framework, a three-dimensional computational domain with a horizontal range of 5-10 km and a vertical range of 3-5 km is constructed as the simulation area. The horizontal grid resolution is set to 10-100 m, and the vertical grid resolution is half of the horizontal grid resolution. At the same time, periodic boundary conditions are set in two orthogonal horizontal directions, and a no-slip lower boundary and a fixed potential height upper boundary are set in the vertical direction. The top boundary is set to a wind speed free sliding boundary and a constant potential temperature boundary condition, and a periodic boundary condition is set in the area above 2 km. Rayleigh Damping layers to suppress gravity wave reflections; SS3. Based on the synthetic analysis of tropical cyclone sounding data, the thermodynamic variable profiles under different wind speed conditions are obtained and used as the initial thermodynamic conditions of LES simulation and the reference profiles during the simulation process. The thermodynamic variables include at least the potential temperature, θ and specific humidity q , and introduce a large-scale tendency correction (nudging term) in the LES simulation process to dynamically adjust the thermodynamic variables in the simulation area to evolve toward the reference profile to maintain the potential temperature and specific humidity profile structure. The expression of the large-scale tendency correction term is: in, θ ( z )and q ( z ) are the specified heights in the simulation area z The horizontal average potential temperature and specific humidity on θ r ( z )and q r ( z ) are the corresponding reference potential temperature and specific humidity profile values, τ n To ease the time scale; SS4. Based on the LES framework, the turbulence simulation and numerical solution of TCBL in the simulation area are implemented, and the large-scale turbulent eddy structure in TCBL is explicitly resolved. The SGS-TKE closed model is used to consider the influence of strong rotation and high wind shear of TCBL on sub-grid scale turbulence transport and anisotropy, and the model coefficients are dynamically adjusted according to the local wind shear and stability parameters to parameterize the unresolved sub-grid scale turbulence. At the same time, the control equations are discretized using a high-order precision numerical discretization format; SS5. Preset the total duration and time step of the LES simulation, perform time integration to advance the evolution of the wind field and thermodynamic variables, and monitor the state evolution of the key variables of the TCBL wind field during the simulation to ensure that the simulation reaches a quasi-steady state. The state evolution of the key variables at least includes the changes in the boundary layer height and the 10-meter wind speed. The boundary layer height is defined as the height at which the momentum flux drops to 5% of the surface value. The quasi-steady state criterion is that the rate of change of the boundary layer height and the 10-meter wind speed is less than the preset threshold; SS6. Output the TCBL wind field data generated based on LES simulation, and perform post-processing analysis on the output results to generate a benchmark data set including TCBL three-dimensional wind field, temperature field, humidity field and various turbulence statistics, which is used to verify and improve the TCBL turbulence parameterization scheme at gray zone resolution.

2. The gray zone parameterized TCBL wind field high-resolution LES simulation method according to claim 1 is characterized in that: In step SS1, the initial wind field is at the maximum wind speed radius R max Inboard tangential wind speed V t Using a linear growth function Simulate, exceed the maximum wind radius R max Tangential wind speed V t Power law function Simulate the maximum wind radius R max Tangential wind speed V t The radial gradient of ,in, k 1. k 2 is the dimensionless coefficient, n To control the power law exponent of the attenuation of tangential wind speed with radial distance, V max is the maximum tangential wind speed, R max is the maximum wind speed radius, r is the radial distance from the center of the cyclone.

3. The gray zone parameterized TCBL wind field high-resolution LES simulation method according to claim 1 is characterized in that: In step SS1, the gradient wind speed V The value range is 35-65m / s, and is set according to the target wind speed: 25m / s at a height of 10 meters. V =44m / s, 35m / s 10m height tangential wind speed case V =58m / s, 45m / s 10m height tangential wind speed case V =65m / s; when determining the radial gradient, the power law relationship The calculations were performed with the tangential wind speeds at 10 m height of 25 m / s and 35 m / s. n =0.7, 45m / s 10m height tangential wind speed case n =0.75; Maximum wind radius R max The selection corresponds to different target wind speeds: 25m / s 10m height tangential wind speed case R max =110km, 35m / s tangential wind speed at 10m height R max =75km, 45m / s tangential wind speed at 10m height R max =40km.

4. The TCBL wind field high-resolution LES simulation method for gray zone parameterization according to claim 1 is characterized in that: In step SS2, the specific parameters of the three-dimensional calculation domain are set as follows: the horizontal range is 5km×5km, the vertical height is 3km; the horizontal grid resolution is uniformly set to Δx = Δy = 10m, hierarchical grids are used in the vertical direction, and the area below 2km is taken Δz =5m, 2-3km interval Δz =12.5m; the thickness of the Rayleigh damping layer is set to 1km, the damping coefficient increases linearly with height, and the maximum damping coefficient is 0.003s -1 ; At the same time, a buffer zone of 100 grid points is set around the simulation area.

5. The TCBL wind field high-resolution LES simulation method for gray zone parameterization according to claim 1 is characterized in that: In step SS3, tropical cyclone sounding data are based on historical observation data or model synthesis data of typical tropical cyclones, and the thermodynamic profiles of tropical cyclones of different intensities are obtained by using a synthesis method classified by wind speed at 10 meters. The potential temperature profile at the bottom 200 meters of the boundary layer is obtained by using The quadratic function fitting of The logarithmic function fit of z is the height, θ 0. q 0 are the initial potential temperature and initial specific humidity of the near-surface layer, z 0 is the feature height, a 1. a 2. b 1 are the fitting coefficients and are determined based on the near-surface observation data. The thermodynamic profile is smoothed in the 500 m transition zone near the top of the boundary layer to avoid sharp vertical gradients. At the same time, the stability of the thermodynamic profile is maintained through large-scale inclination correction during the simulation process.

6. The gray zone parameterized TCBL wind field high-resolution LES simulation method according to claim 1 is characterized in that: In step SS3, the large-scale trend correction execution strategy includes: SS31. Set the easing time scale τ n =5min, to control the evolution rate of thermodynamic variables toward the reference profile and avoid instability caused by drastic adjustments; SS32. The intensity of the dip correction is linearly reduced to zero in the transition zone with a thickness of 500 m at the top of the boundary layer. The mathematical expression is: ,in, z BLH represents the TCBL boundary layer height; SS33. The sea surface temperature is set to the surface air temperature plus 2°C to simulate the influence of the sea-air temperature difference on the thermodynamic evolution in the cyclone system and improve the simulation accuracy of the thermodynamic process in the surface layer of tropical cyclones; SS34. Update the large-scale bias correction term once at the end of each time step ( θ r , q r ), and the thermodynamic profiles are horizontally averaged before updating to reduce local noise, specifically: in A is the horizontal area of ​​the simulation region, ( x , y , z ) is the three-dimensional coordinate of any point in the simulation area; SS35. When updating the trend correction term, the gradient limiting method is used to avoid large instantaneous changes to ensure the rationality and stability of large-scale forcing: in, is the variable to be corrected, It is the preset maximum correction range.

7. The gray zone parameterized TCBL wind field high-resolution LES simulation method according to claim 1 is characterized in that: In step SS4, the sub-grid scale turbulent kinetic energy SGS-TKE closed model includes a standard TKE part using the Deardorff scheme in the entire computational domain and a Sullivan correction term for the near-surface layer, and the Sullivan correction term only works in the area below 100 m from the ground; The time marching adopts the third-order Runge-Kutta scheme, the spatial terms are discretized using the fifth-order upwind difference scheme, and the time step is set to 0.5 seconds to ensure the numerical stability of the calculation.

8. The gray zone parameterized TCBL wind field high-resolution LES simulation method according to claim 7 is characterized in that: In step SS4, the dynamic Smagorinsky model is used to process the subgrid stress, and the model coefficients are calculated by averaging the local area. C s : in, L ij is the Leonard stress term, M ij is a model-dependent term, <•> represents the local spatial average, anisotropic effects are additionally considered in strong shear regions, and where: The specific form of the Sullivan correction term in the near-surface layer is: , in, τ ij is the subgrid-scale stress tensor, Δ is the filtering scale, l s is the characteristic length scale of the turbulent structure in the near-surface layer, | S | cl is the classical definition of shear rate, S ij is the strain rate tensor, Represents the velocity component U i , U j In the vertical direction x 3 on the gradient.

9. The gray zone parameterized TCBL wind field high-resolution LES simulation method according to claim 1 is characterized in that: In step SS5, the total simulation time is set to 6 hours, of which the first 4 hours are the adjustment period and the last 2 hours are the analysis period; the simulation results output three-dimensional field data every 6 minutes; the quasi-steady state judgment criteria are: the relative change rate of the TCBL wind field boundary layer height and the 10-meter wind speed is less than 1% in multiple consecutive time steps, and the shape of the momentum flux profile remains stable.

10. The gray zone parameterized TCBL wind field high-resolution LES simulation method according to claim 1 is characterized in that: In step SS5, the following turbulence statistics are recorded and analyzed simultaneously during the LES simulation process: Reynolds stress components, vertical distribution of turbulent kinetic energy, momentum flux profile, effective eddy viscosity coefficient, turbulence length scale and potential temperature flux, which are used to verify the physical rationality of the simulation results. When the time rate of change of these turbulence statistics is less than the preset threshold, the LES simulation is considered to have reached a quasi-steady state.

11. The gray zone parameterized TCBL wind field high-resolution LES simulation method according to claim 1 is characterized in that: In step SS6, the post-processing analysis of the LES simulation output results includes at least calculating the horizontally averaged momentum flux and heat flux profiles, analyzing the turbulence energy spectrum characteristics, evaluating the turbulence intensity and length scale at different heights, and statistically analyzing the three-dimensional distribution characteristics of the sub-grid turbulent kinetic energy. These results are then compared and verified with existing observational data and theoretical analysis.

12. A computer program product comprising computer instructions, characterized in that: Used to implement the gray zone parameterized TCBL wind field high-resolution LES simulation method described in any one of claims 1 to 11 above.

13. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the high-resolution LES simulation method for TCBL wind field with gray zone parameterization described in any one of claims 1 to 11 is implemented.

Images