A numerical simulation method and system for severe convective precipitation

Abstract

The invention discloses a method and system for numerical simulation of severe convective precipitation, the method comprising: obtaining a real-time data set of severe convective precipitation, designing different boundary layer parameterization schemes to perform numerical simulation of severe convective precipitation; using the real-time data set of severe convection to evaluate simulation results of different boundary layer parameterization schemes to obtain evaluation results, analyzing the southwest vortex and boundary layer structure based on the evaluation results and by comparing the simulation results of the vertical layer to obtain analysis results; according to the analysis results, performing parameter optimization on vertical mixing intensity algorithms of different boundary layer parameterization schemes to obtain optimization results, analyzing the difference in simulation of the southwest vortex by different boundary layer parameterization schemes according to the optimization results, obtaining different low vortex center positions and precipitation intensity mechanisms, and proposing a new idea and method for the action mechanism of the atmospheric boundary layer and the southwest vortex in Yunnan Province.

Description

Technical Field

[0001] The invention relates to the field of meteorology and numerical simulation technology, and in particular to a numerical simulation method and system for severe convective precipitation. Background Art

[0002] Precipitation in Yunnan Province is a very complex process, and its mechanism involves many factors. First, the cyclonic circulation or low-pressure vortex with closed contours formed by the southwest vortex on the leeward slope of the Qinghai-Tibet Plateau forms an α-scale cyclonic low-pressure system on the 700 or 850hPa isobaric surface in southwest my country under the interaction of the special terrain of the Qinghai-Tibet Plateau and the atmospheric circulation. The occurrence and development of its low vortex is one of the important factors causing the intensity, frequency and range of heavy precipitation in Yunnan Province. Second, although large-scale dynamic processes are the main cause of the occurrence and development of heavy rain, the boundary layer and land surface processes will affect the intensity and center position of heavy rain. Especially in Yunnan Province, which is located in the mountainous plateau terrain, the small and medium-scale systems are very active during the rainy season under the influence of multiple monsoons and complex terrain, and severe weather such as heavy precipitation occurs frequently and suddenly. The interaction between the occurrence and development of the southwest vortex and the thermal and dynamic processes of the atmospheric boundary layer is closely related to the heavy rain weather in Yunnan Province. The planetary boundary layer (PBL) is at the bottom of the troposphere and is the layer most closely related to human activities. Because it is in direct contact with the earth's surface, it is most affected by the heat, water vapor and kinetic energy of the earth's surface. The most important feature of the boundary layer is turbulence and its daily variation. Through turbulence, the boundary layer transmits the solar energy of the earth's surface during the day to the upper air in the form of sensible heat and latent heat; at night, ground radiation cooling will also affect the upper atmosphere. However, the turbulent motion of the atmosphere in the boundary layer is very complex, and people's understanding of turbulence is still very superficial. In modern numerical weather forecasting technology, a variety of parameterization schemes are still used to statistically describe the exchange of turbulent heat, humidity and kinetic energy. The boundary layer parameterization scheme will inevitably have uncertainty and inaccuracy when describing turbulent motion, which may ultimately lead to large deviations in the forecast results of weather phenomena.

[0003] At present, the simulation and forecast of the Southwest Vortex and its rainstorms are still the difficulties and key points of research and business. The Southwest Vortex is a small cyclonic vortex located in the middle and lower layers of the troposphere. Its precipitation is characterized by small range, strong suddenness and heavy rainfall, and often causes urban waterlogging, mountain torrents, landslides and mudslides. Due to the influence of the complex terrain and multi-scale system on the east side of the Qinghai-Tibet Plateau, the understanding of the fine structure of the Southwest Vortex is still limited. Its occurrence and development mechanism and the physical mechanism that triggers high-impact weather processes are still not very clear. There are still differences in the understanding of the climatological characteristics of the Southwest Vortex. Therefore, its precipitation forecast is very difficult and is also the weakest aspect of numerical weather forecasting. To solve this problem, a large number of simulation studies on the Southwest Vortex and its rainstorms have been carried out at home and abroad. The numerical model's research on the Southwest Vortex often focuses on the impact of the large-scale circulation background, and lacks research on the atmospheric boundary layer structure and the laws of turbulence occurrence and development. This system with strong locality and small temporal and spatial scales is the basis for studying severe convective precipitation in Yunnan Province. However, due to the failure to fully consider the interaction mechanism between the atmospheric boundary layer and the southwest vortex and the lack of monitoring data on turbulence in the atmospheric boundary layer, the numerical simulation of the interaction between the atmospheric boundary layer and the southwest vortex and the impact of precipitation in Yunnan Province has progressed slowly. Summary of the invention

[0004] In view of the above existing problems, the present invention is proposed.

[0005] Therefore, the present invention provides a numerical simulation method and system for severe convective precipitation to solve the impact of the mechanism of occurrence and development of the atmospheric boundary layer on precipitation, improves the analysis of the influencing mechanism applied to severe convective precipitation in Yunnan Province, and provides some basis and ideas for the numerical forecast of severe convective precipitation in Yunnan Province.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0007] In a first aspect, the present invention provides a numerical simulation method for severe convective precipitation, comprising:

[0008] Obtain a real-time severe convective precipitation data set and design different boundary layer parameterization schemes to perform numerical simulations of severe convective precipitation;

[0009] Using the severe convection real-time data set to evaluate simulation results of different boundary layer parameterization schemes, obtaining evaluation results, and analyzing the southwest vortex and boundary layer structure based on the evaluation results and in comparison with the simulation results of the vertical layer, obtaining analysis results;

[0010] According to the analysis results, the vertical mixing intensity algorithm of different boundary layer parameterization schemes is optimized to obtain optimization results. According to the optimization results, the differences in the simulation of the southwest vortex by different boundary layer parameterization schemes are analyzed to obtain different low vortex center positions and precipitation intensity mechanisms.

[0011] As a preferred solution of the numerical simulation method of severe convective precipitation described in the present invention, the evaluation of different boundary layer parameterization schemes includes:

[0012] The scoring function is used to evaluate different boundary layer parameterization schemes, and the precipitation classification at different time points is tested to obtain the optimal combination of boundary layer parameterization schemes.

[0013] As a preferred embodiment of the numerical simulation method for severe convective precipitation described in the present invention, the analysis of the southwest vortex and the boundary layer structure includes:

[0014] The simulation results of the vertical layer were compared with the L-band high-altitude meteorological radar's second-level encrypted detection data for analysis, and the vertical structures of the vertical potential temperature stratification and humidity stratification of the boundary layer under the influence of the southwest vortex weather system were obtained by numerical simulation and observation.

[0015] As a preferred embodiment of the numerical simulation method for severe convective precipitation described in the present invention, the method further comprises:

[0016] The difference in the calculation of mixing intensity by different boundary layer parameterization schemes affects the boundary layer height. The higher the boundary layer height, the greater the mixing intensity of the boundary layer, and the heat and water vapor are transferred upward.

[0017] As a preferred solution of the numerical simulation method of severe convective precipitation described in the present invention, wherein: designing different boundary layer parameterization schemes to perform numerical simulation on severe convective precipitation includes:

[0018] Different mainstream boundary layer parameterization schemes are set, and the cumulus convection parameterization scheme is turned off. The severe convective precipitation parameterization scheme with the greatest adaptability is adopted for other physical processes.

[0019] As a preferred solution of the numerical simulation method of severe convective precipitation described in the present invention, the vertical mixing intensity algorithm of different boundary layer parameterization schemes is optimized by:

[0020] Based on the analysis and verification of the meteorological mechanism of the southwest vortex and boundary layer structure, the optimal boundary layer parameterization scheme combination for severe convective precipitation is selected to reduce the vertical mixing intensity and weaken the turbulent mixing in the daytime boundary layer and the entrainment flux at the top of the boundary layer.

[0021] As a preferred solution of the numerical simulation method of severe convective precipitation described in the present invention, the difference between different boundary layer parameterization schemes in simulating the southwest vortex includes:

[0022] The local and nonlocal characteristics of the boundary scheme determine whether turbulent exchange can occur at altitudes where the modes are not adjacent;

[0023] For different boundary layer schemes, different vertical mixing intensity coefficients are used to affect the energy and water vapor distribution in the boundary layer;

[0024] Stronger mixing makes the boundary layer hotter, reduces the mixing intensity, and makes the lower boundary layer wetter.

[0025] In a second aspect, the present invention provides a numerical simulation system for severe convective precipitation, comprising:

[0026] Numerical simulation module, used to obtain the actual data set of severe convective precipitation and design different boundary layer parameterization schemes to perform numerical simulation of severe convective precipitation;

[0027] An evaluation and analysis module, used to evaluate the simulation results of different boundary layer parameterization schemes using the severe convection real-time data set to obtain evaluation results, and to analyze the southwest vortex and boundary layer structure based on the evaluation results and in comparison with the simulation results of the vertical layer to obtain analysis results;

[0028] The optimization module is used to optimize the parameters of the vertical mixing intensity algorithm of different boundary layer parameterization schemes according to the analysis results to obtain optimization results, analyze the differences in the simulation of the southwest vortex by different boundary layer parameterization schemes according to the optimization results, and obtain different low vortex center positions and precipitation intensity mechanisms.

[0029] In a third aspect, the present invention provides a computing device, comprising:

[0030] Memory and processor;

[0031] The memory is used to store computer executable instructions, and the processor is used to execute the computer executable instructions. When the computer executable instructions are executed by the processor, the steps of the numerical simulation method of severe convective precipitation are implemented.

[0032] In a fourth aspect, the present invention provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the steps of the numerical simulation method of severe convective precipitation.

[0033] Compared with the prior art, the present invention has the following beneficial effects: the present invention can more accurately capture the key factors affecting severe convective precipitation in Yunnan Province by finely simulating the interaction between the atmospheric boundary layer and the southwest vortex. This interaction includes the exchange of heat, momentum and water vapor in the boundary layer, as well as the generation, development and movement of the southwest vortex, which have an important impact on the formation and distribution of precipitation. It realizes the comparison and analysis of different boundary layer parameterization schemes, including the simulation evaluation of different boundary layer parameterization schemes adopted by the WRF mesoscale forecast model (YSU, MYJ, ACM2, etc.). This comparative analysis helps to determine the boundary layer parameterization scheme that best suits the actual situation in Yunnan Province, thereby further improving the refinement level of precipitation forecasting. By optimizing the algorithm of vertical mixing intensity in the boundary layer scheme, the energy and water vapor distribution in the atmospheric boundary layer during the southwest vortex precipitation process is improved, and a new idea and method are proposed for the action mechanism of the atmospheric boundary layer and the southwest vortex in Yunnan Province. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0035] Figure 1 The figure is a schematic diagram of the overall process logic of the numerical simulation method of severe convective precipitation described in one embodiment of the present invention. DETAILED DESCRIPTION

[0036] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0037] Example 1

[0038] Reference Figure 1 , which is an embodiment of the present invention, provides a numerical simulation method for severe convective precipitation, comprising:

[0039] S100: Obtain the actual severe convective precipitation data set and design different boundary layer parameterization schemes to perform numerical simulations of severe convective precipitation;

[0040] S200: using the severe convection real-time data set to evaluate the simulation results of different boundary layer parameterization schemes, obtaining evaluation results, and analyzing the southwest vortex and boundary layer structure based on the evaluation results and comparing them with the simulation results of the vertical layer, obtaining analysis results;

[0041] S300: According to the analysis results, the vertical mixing intensity algorithm of different boundary layer parameterization schemes is optimized to obtain the optimization results. According to the optimization results, the difference of different boundary layer parameterization schemes in simulating the southwest vortex is analyzed to obtain different low vortex center positions and precipitation intensity mechanisms;

[0042] It should be noted that by precisely simulating the interaction between the atmospheric boundary layer and the southwest vortex, the key factors affecting severe convective precipitation in Yunnan Province can be captured more accurately, thereby significantly improving the accuracy of precipitation forecasts and realizing the comparison and analysis of different boundary layer parameterization schemes. This will help determine the boundary layer parameterization scheme that best suits the actual situation in Yunnan Province and further improve the refinement of precipitation forecasts.

[0043] In the embodiment of the present application, the above step S100 includes the following sub-step A1:

[0044] In A1: different mainstream boundary layer parameterization schemes are set, while the cumulus convection parameterization scheme is turned off, and the severe convective precipitation parameterization scheme with the greatest adaptability is used for other physical processes.

[0045] Specifically, taking Yunnan Province as an example, we collected the real-time data set of severe convective precipitation in Yunnan Province, downloaded L-band second-level sounding data from the China Meteorological Administration, downloaded L-band high-altitude meteorological radar encrypted detection data set, and then downloaded FY-4A geostationary satellite China regional data to analyze the characteristics of precipitation cloud system such as cloud type, cloud phase, cloud top height, cloud top temperature, water vapor content, etc., collected Fengyun satellite precipitation fusion analysis data set, and finally downloaded NCEP 6h time interval, 0.25° horizontal resolution GDAS / FNL data as the initial field and lateral boundary field of the model;

[0046] The simulation kernel uses WRF-ARW 4.5 version to simulate the Yunnan Province area, using a three-layer nested grid method. The first layer of grids has 117×106 horizontal grid points and a horizontal pattern of 9km, including the Qinghai-Tibet Plateau and the southwest region; the second layer of grid points has 187×176 horizontal grid points and a horizontal pattern of 3km, including the entire southwest region; the third layer of grid points has 276×271 horizontal grid points and a horizontal pattern of 1km, including Yunnan Province, which is the area most directly affected by the generation and development of the southwest vortex. The NCEP 6h time interval and 0.25° horizontal resolution GDAS / FNL data are used as the model initial field and lateral boundary, the outermost integration step is 90 seconds, the model has 50 vertical layers, and the model layer top is 50hpa; Lambert projection is used, and the observation data assimilation module is turned on at the same time;

[0047] The WRF v4.5 model was used to design 7 groups of sensitivity experiments with different boundary layer parameterization schemes (YSU, MYJ, QNSE, MYNN2, ACM2, BL and SH). The severe convective precipitation in the historical typical southwest vortex and boundary layer interaction mechanism in Yunnan Province was numerically simulated. In addition to using different boundary layer parameterization schemes, the d03 nested cumulus convection parameterization scheme was closed, while the most suitable severe convective precipitation parameterization schemes, Thompson v3.1 microphysics scheme, Tiedtke cumulus convection scheme, unified-Noah land process scheme and rrtmg longwave radiation and shortwave radiation parameterization schemes were used for other physical processes.

[0048] It should be noted that in the numerical simulation process, the calculation and interpretation of turbulence in the boundary layer parameterization scheme mainly revolve around two centers: one is the order of turbulence closure, and the other is whether the scheme is local or non-local. The YSU scheme is a 1st-order non-local closure scheme, which takes into account the entrainment term and the description of the entrainment process. The SH scheme is essentially an upgraded convection scheme of YSU, which strengthens the performance of the scheme during unstable stratification. MYNN2 is an upgraded scheme of MYJ, which refers to some precipitation test characteristics of the non-local scheme and improves the parameter characteristics in the deep wet convective environment. The ACM2 scheme is an asymmetric convection mode of non-local upward mixing and local downward mixing. Its characteristic is that the non-local transport in the vertical direction is closed when the stratification is stable or neutral, and only turbulent transport between adjacent grids is allowed. The MYJ scheme is a 1.5-order local closure scheme. Compared with the previous MY scheme, the boundary layer calculation is simpler. The QNSE scheme is a 1.5-order local closure scheme, which corrects the description of the stable boundary layer through observational data and large eddy simulation data.

[0049] In the embodiment of the present application, the analysis of the southwest vortex and the boundary layer structure in the above step S200 includes the following sub-step B1;

[0050] In B1: different boundary layer parameterization schemes are evaluated using a scoring function, and precipitation classifications at different time points are tested to obtain the optimal combination of boundary layer parameterization schemes.

[0051] Specifically, the simulation results of seven boundary layer parameterization schemes are evaluated and analyzed using a precipitation real-time dataset, and the precipitation verification uses TS and BS scores;

[0052] The 24h and 48h precipitation classifications were tested separately, and the precipitation classification used the 24h precipitation classification standard of the National Meteorological Center;

[0053] In a preferred embodiment, four boundary layer parameterization scheme combinations are selected through inspection and evaluation: control experiment (YSU boundary layer scheme + MM5 near-surface layer scheme), comparative experiment 1 (MYJ boundary layer scheme + MO near-surface layer scheme), comparative experiment 2 (ACM2 boundary layer scheme + MM5 near-surface layer scheme), and comparative experiment 3 (BL boundary layer scheme + MM5 near-surface layer scheme).

[0054] It should be noted that the existing boundary layer parameterization combination schemes have quite different calculation results for the boundary layer mixing intensity in Yunnan Province. The reason may be that the default calibration parameters of these PBL schemes are obtained by foreign scholars through calculation and simulation calibration in the American continent, which is not suitable for the severe convective weather characteristics under the complex terrain of Yunnan Province.

[0055] In the embodiment of the present application, after completing step B1, the above step S200 may further include the following sub-steps B2-B3;

[0056] In B2: The simulation results of the vertical layer are compared with the L-band high-altitude meteorological radar second-level encrypted detection data for analysis, and the vertical structure of the vertical potential temperature stratification and humidity stratification of the boundary layer under the influence of the southwest vortex weather system is obtained by numerical simulation and observation.

[0057] In B3: The difference in the calculation of mixing intensity by different boundary layer parameterization schemes affects the boundary layer height. The higher the boundary layer height, the greater the mixing intensity of the boundary layer, and the heat and water vapor are transferred upward.

[0058] Specifically, based on the actual precipitation and forecast simulation test and evaluation results, the structural characteristics of the southwest vortex in the initial, mature and weakening stages are analyzed using meteorological principles, the influence of Yunnan Province's terrain on the movement and development of the southwest vortex structure is explored, the differences in boundary layer structure under different boundary layer parameterization schemes are simultaneously analyzed, the vertical mixing intensity, turbulent motion and water vapor conditions at different altitudes are studied, and a systematic analysis of the southwest vortex and boundary layer structure is conducted;

[0059] The analysis verifies the vertical structure of the vertical potential temperature stratification and humidity stratification of the boundary layer in Yunnan Province under the influence of the southwest vortex weather system by numerical simulation and observation, thereby verifying the accuracy of numerical simulation of the southwest vortex and boundary layer structure.

[0060] In the WRF model, the difference in the calculation of mixing intensity by the boundary layer parameterization schemes will directly affect the boundary layer height. The higher the boundary layer height, the greater the mixing intensity within the boundary layer, which is more conducive to the upward transfer of heat and water vapor. In addition, the development of the boundary layer has obvious daily variations, and its thickness reaches its highest in the afternoon, reaching more than 2 km or even higher, which ultimately affects the distribution of physical quantities and precipitation results when the southwest vortex precipitation occurs.

[0061] In the embodiment of the present application, the vertical mixing intensity algorithm of different boundary layer parameterization schemes is optimized in the above step S300, including the following sub-step C1;

[0062] In C1: Based on the analysis and verification of the meteorological mechanism of the southwest vortex and boundary layer structure, the optimal combination of boundary layer parameterization schemes for severe convective precipitation is selected to reduce the vertical mixing intensity and weaken the turbulent mixing in the daytime boundary layer and the entrainment flux at the top of the boundary layer.

[0063] Specifically, according to the analysis results of the southwest vortex and boundary layer structure, the southwest vortex is a deep, warm and humid low-pressure system, often accompanied by strong upward motion and abundant water vapor conditions. When the upward motion and positive vorticity area of ​​the southwest vortex are accompanied by strong turbulent motion and obvious vertical temperature and humidity structure in the boundary layer, the interaction mechanism relationship between the southwest vortex and the boundary layer structure is obtained.

[0064] In a preferred embodiment, based on the analysis and verification of the meteorological mechanism of the southwest vortex and the boundary layer structure, an optimal boundary layer parameterization scheme combination suitable for severe convective precipitation in Yunnan Province is selected;

[0065] By modifying the critical Richardson number, vortex diffusion term and mixing intensity index in the vertical mixing intensity calculation formula, the vertical mixing intensity algorithm of the boundary layer scheme during the southwest vortex precipitation process is analyzed and optimized for parameter sensitivity, and the forecast simulation improvement of the southwest vortex precipitation by the optimized boundary layer parameterization scheme is further explored, so as to analyze and verify the algorithm differences of different boundary layer schemes for vertical mixing intensity. The boundary layer scheme after reducing the vertical mixing intensity can improve both the boundary layer state and precipitation simulation to a certain extent. By adjusting the critical Richardson number, vortex diffusion term and mixing intensity index within the allowable range, the vertical mixing intensity is reduced, the turbulent mixing in the daytime boundary layer and the entrainment flux at the top of the boundary layer are weakened, and the boundary layer is colder and wetter.

[0066] In the embodiment of the present application, the above step S300 analyzes the difference between different boundary layer parameterization schemes in simulating the southwest vortex, including the following sub-steps D1-D3;

[0067] In D1: the local and non-local characteristics of the boundary scheme determine whether turbulent exchange can occur at altitudes where the modes are not adjacent;

[0068] In D2: for different boundary layer schemes, different vertical mixing intensity coefficients are used to affect the energy and water vapor distribution in the boundary layer;

[0069] In D3: Stronger mixing makes the boundary layer hotter, lower mixing intensity makes the lower boundary layer wetter.

[0070] Specifically, the difference in the simulation of the southwest vortex by different boundary layer parameterization schemes is mainly due to the different low vortex center locations and precipitation intensities. The location of the low vortex center affects the precipitation range, but ultimately it all stems from the local and non-local characteristics of the boundary layer scheme and the size of the mixing intensity. The local and non-local characteristics determine whether turbulent exchange can occur at altitude layers that are not adjacent to the model, which will restrict whether the underlying surface heat, water vapor and kinetic energy can directly affect the upper atmosphere in the boundary layer through larger-scale turbulence, making the entire boundary layer mix faster and more fully; while the mixing intensity represents the intensity of turbulent transmission. For different boundary layer schemes, the use of different vertical mixing intensity coefficients will affect the energy and water vapor distribution in the boundary layer. Stronger mixing will make the boundary layer hotter, which is conducive to the generation of large-scale precipitation; while reducing the mixing intensity, the lower layer of the boundary layer will be wetter, which is conducive to the generation of small-scale precipitation.

[0071] It should be noted that by optimizing the algorithm of vertical mixing intensity in the boundary layer scheme, the energy and water vapor distribution in the atmospheric boundary layer during the southwest vortex precipitation process is improved, a new idea and new method are proposed for the action mechanism of the atmospheric boundary layer and southwest vortex in Yunnan Province, and a boundary layer parameterization scheme that is more suitable for severe convective precipitation weather under the complex terrain of Yunnan Province is proposed.

[0072] The above is a schematic scheme of a numerical simulation method for severe convective precipitation in this embodiment. It should be noted that the technical scheme of the system for numerical simulation of severe convective precipitation and the technical scheme of the above-mentioned method for numerical simulation of severe convective precipitation belong to the same concept, and the details of the technical scheme of the system for numerical simulation of severe convective precipitation in this embodiment that are not described in detail can all be referred to the description of the technical scheme of the above-mentioned method for numerical simulation of severe convective precipitation.

[0073] The numerical simulation system for severe convective precipitation in this embodiment includes:

[0074] Numerical simulation module, used to obtain the actual data set of severe convective precipitation and design different boundary layer parameterization schemes to perform numerical simulation of severe convective precipitation;

[0075] An evaluation and analysis module, used to evaluate the simulation results of different boundary layer parameterization schemes using the severe convection real-time data set to obtain evaluation results, and to analyze the southwest vortex and boundary layer structure based on the evaluation results and in comparison with the simulation results of the vertical layer to obtain analysis results;

[0076] The optimization module is used to optimize the parameters of the vertical mixing intensity algorithm of different boundary layer parameterization schemes according to the analysis results to obtain optimization results, analyze the differences in the simulation of the southwest vortex by different boundary layer parameterization schemes according to the optimization results, and obtain different low vortex center positions and precipitation intensity mechanisms.

[0077] This embodiment further provides a computing device, which is applicable to the numerical simulation of severe convective precipitation, and includes:

[0078] Memory and processor; the memory is used to store computer executable instructions, and the processor is used to execute computer executable instructions to implement the numerical simulation method for severe convective precipitation proposed in the above embodiment.

[0079] This embodiment further provides a storage medium on which a computer program is stored. When the program is executed by a processor, the numerical simulation method for severe convective precipitation proposed in the above embodiment is implemented.

[0080] The storage medium proposed in this embodiment and the numerical simulation method for realizing severe convective precipitation proposed in the above embodiment belong to the same inventive concept. The technical details not fully described in this embodiment can be referred to the above embodiment, and this embodiment has the same beneficial effects as the above embodiment.

[0081] Through the above description of the implementation methods, the technicians in the relevant field can clearly understand that the present invention can be implemented by means of software and necessary general hardware, and of course can also be implemented by hardware. Based on such an understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ReadOnly, Memory, ROM), random access memory (Random Access Memory, RAM), flash memory (FLASH), hard disk or optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform the methods of various embodiments of the present invention.

[0082] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

[0083] Example 2

[0084] Referring to Table 1, based on the previous embodiment, this embodiment provides an application case of a numerical simulation method for severe convective precipitation to illustrate the feasibility and beneficial effects of our solution.

[0085] Take a severe convective precipitation process brought about by the passage of a southwest vortex as an example;

[0086] The assessment area is Yunnan Province (20.9°N~30.10°N, 96.90°E~107.08°E), 10 cities;

[0087] A heavy rainfall case in Yunnan Province was selected, and the process of a heavy rainfall case in Yunnan Province was comprehensively evaluated. According to the statistical index results analysis in Table 1, the optimization of parameterized scheme has significantly improved the forecast of heavy convective rainfall in Yunnan Province.

[0088] Table 1 Comparison of precipitation forecast results before and after parameterization scheme optimization

[0089]

[0090] According to Table 1, for most regions, the mean absolute error (MAE) and root mean square error (RMSE) of the optimized parameterization scheme in multiple regions have been reduced, which indicates that the forecast accuracy has been improved. Smaller MAE and RMSE values ​​mean that the difference between the predicted precipitation and the actual observed value is reduced.

[0091] In many regions, the optimized scheme has improved the correlation coefficient (R), which indicates a stronger linear relationship between the predicted precipitation and the actual precipitation. A higher R value means that the forecast is more consistent with the actual observation data.

[0092] Although the RMSE and MAE increased after optimization in some areas (e.g., Red River), improvements were observed in most areas. This indicates that the optimization scheme provides more stable forecast results in most cases.

[0093] In the overall evaluation of Yunnan Province, although the improvement of MAE and RMSE is not obvious, the correlation coefficient R is improved, which indicates that the performance of the overall forecast has been improved.

[0094] The optimized scheme can better adapt to the specific climate characteristics of different regions, which is reflected in the improvements of MAE and RMSE in different regions.

[0095] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A numerical simulation method for severe convective precipitation, characterized in that: include: Obtain a real-time severe convective precipitation data set and design different boundary layer parameterization schemes to perform numerical simulations of severe convective precipitation; Using the severe convection real-time data set to evaluate simulation results of different boundary layer parameterization schemes, obtaining evaluation results, and analyzing the southwest vortex and boundary layer structure based on the evaluation results and in comparison with the simulation results of the vertical layer, obtaining analysis results; According to the analysis results, the vertical mixing intensity algorithm of different boundary layer parameterization schemes is optimized to obtain optimization results. According to the optimization results, the differences in the simulation of the southwest vortex by different boundary layer parameterization schemes are analyzed to obtain different low vortex center positions and precipitation intensity mechanisms.

2. The numerical simulation method for severe convective precipitation according to claim 1, characterized in that: The evaluation of different boundary layer parameterization schemes includes: The scoring function is used to evaluate different boundary layer parameterization schemes, and the precipitation classification at different time points is tested to obtain the optimal combination of boundary layer parameterization schemes.

3. The numerical simulation method for severe convective precipitation according to claim 2, characterized in that: Analysis of the southwest vortex and boundary layer structure includes: The simulation results of the vertical layer were compared with the L-band high-altitude meteorological radar's second-level encrypted detection data for analysis, and the vertical structures of the vertical potential temperature stratification and humidity stratification of the boundary layer under the influence of the southwest vortex weather system were obtained by numerical simulation and observation.

4. The numerical simulation method for severe convective precipitation according to claim 2 or 3, characterized in that: Also includes: The difference in the calculation of mixing intensity by different boundary layer parameterization schemes affects the boundary layer height. The higher the boundary layer height, the greater the mixing intensity of the boundary layer, and the heat and water vapor are transferred upward.

5. The numerical simulation method for severe convective precipitation according to claim 4, characterized in that: Designing different boundary layer parameterization schemes to simulate severe convective precipitation includes: Different mainstream boundary layer parameterization schemes are set, and the cumulus convection parameterization scheme is turned off. The severe convective precipitation parameterization scheme with the greatest adaptability is adopted for other physical processes.

6. The numerical simulation method for severe convective precipitation according to claim 5, characterized in that: Parameter optimization of the vertical mixing intensity algorithm for different boundary layer parameterization schemes includes: Based on the analysis and verification of the meteorological mechanism of the southwest vortex and boundary layer structure, the optimal boundary layer parameterization scheme combination for severe convective precipitation is selected to reduce the vertical mixing intensity and weaken the turbulent mixing in the daytime boundary layer and the entrainment flux at the top of the boundary layer.

7. The numerical simulation method for severe convective precipitation according to claim 6, characterized in that: The differences in the simulation of the southwest vortex due to different boundary layer parameterization schemes are analyzed as follows: The local and nonlocal characteristics of the boundary scheme determine whether turbulent exchange can occur at altitudes where the modes are not adjacent; For different boundary layer schemes, different vertical mixing intensity coefficients are used to affect the energy and water vapor distribution in the boundary layer; Stronger mixing makes the boundary layer hotter, reduces the mixing intensity, and makes the lower boundary layer wetter.

8. A system using the numerical simulation method for severe convective precipitation according to any one of claims 1 to 7, characterized in that: include: Numerical simulation module, used to obtain the actual data set of severe convective precipitation and design different boundary layer parameterization schemes to perform numerical simulation of severe convective precipitation; An evaluation and analysis module, used to evaluate the simulation results of different boundary layer parameterization schemes using the severe convection real-time data set to obtain evaluation results, and to analyze the southwest vortex and boundary layer structure based on the evaluation results and in comparison with the simulation results of the vertical layer to obtain analysis results; The optimization module is used to optimize the parameters of the vertical mixing intensity algorithm of different boundary layer parameterization schemes according to the analysis results to obtain optimization results, analyze the differences in the simulation of the southwest vortex by different boundary layer parameterization schemes according to the optimization results, and obtain different low vortex center positions and precipitation intensity mechanisms.

9. An electronic device, comprising: Memory and processor; The memory is used to store computer executable instructions, and the processor is used to execute the computer executable instructions. When the computer executable instructions are executed by the processor, the steps of the numerical simulation method of severe convective precipitation described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the steps of the method for numerical simulation of severe convective precipitation according to any one of claims 1 to 7.

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