Front line identification method based on Yunnan and Guizhou plateau ground

Abstract

The invention discloses a frontal line identification method based on the Yunnan and Guizhou plateau ground, and the objective discrimination method of the frontal line of the Yunnan and Guizhou plateau ground is suitable for various stations and grid point data, can be used for real-time data analysis, and can also be used for various numerical forecasting products. Compared with a traditional frontal surface analysis method, the method has the advantages that the ground frontal lines are determined through linear fitting, the characteristics of movement, cooling and heating and the like of the frontal surface can be objectively given on the basis that the trend and the position of each frontal line are objectively given, and on one hand, the dynamic evolution rule of a quasi-static peak is objectively expressed; and on the other hand, by comprehensively analyzing various factors such as the movement condition of the frontal line, the variable temperature and variable pressure near the frontal line and the like, a foundation is laid for synthetically analyzing a three-dimensional circulation structure and more comprehensively and systematically knowing the complete structure, category characteristics and associated refined weather evolution of the frontal surface.

Description

Technical Field

[0001] The invention relates to the technical field of forward line identification, and in particular to a forward line identification method based on the ground of the Yunnan-Guizhou Plateau. Background Art

[0002] The Yunnan-Guizhou Plateau is an important part of the Yangtze River Basin. It has complex terrain, changeable meteorological conditions, and frequent fronts, which have an important impact on regional climate and weather evolution. Accurately identifying ground fronts is of great significance for regional weather forecasting, agricultural production, and natural disaster prevention.

[0003] In weather forecasting services and weather case analysis, the position of the Yunnan-Guizhou quasi-stationary front is usually determined subjectively based on manual identification methods; during the manual identification process, meteorological observers will consider a variety of factors to infer the position of the front, including the advancement of cold air, the impact of terrain on airflow, the characteristics of cloud systems and precipitation distribution, etc. Based on this information, they will manually draw the position of the front on the map, or present it to other meteorological workers through oral reports and charts.

[0004] The existing artificial identification methods have certain limitations and subjectivity. Different observers may have different interpretations of the same set of data, resulting in differences in the judgment of the front position. It is impossible to monitor and verify the quasi-stationary front of Yunnan-Guizhou in real time. It is necessary to meet the needs of refined meteorological services and accurately control the changes in the front system of the Yunnan-Guizhou Plateau. It is necessary to deeply understand its dynamic evolution laws based on long-term statistical analysis to provide scientific support for its precise and accurate forecast. Based on the above reasons, the present invention proposes a front line identification method based on the ground of the Yunnan-Guizhou Plateau. Summary of the invention

[0005] 1. Technical issues to be solved

[0006] In view of the shortcomings of existing technologies, the objective identification method of the ground front line on the Yunnan-Guizhou Plateau proposed in this method is applicable to various types of stations and grid data, and can be used for real-time data analysis as well as various types of numerical forecast products. Compared with the traditional front analysis method, this method determines the ground front line through linear fitting, and can objectively give the movement, cold and warm characteristics of the front line on the basis of objectively giving the direction and position of each front line. On the one hand, it helps to objectively describe the "dynamic" evolution law of the "quasi-stationary" front; on the other hand, by comprehensively analyzing the movement of the front line, temperature and pressure changes near the front line and other factors, it lays the foundation for the synthetic analysis of the three-dimensional circulation structure and a more comprehensive and systematic understanding of the complete structure, category characteristics and related refined weather evolution of the front line.

[0007] (II) Technical solution

[0008] To achieve the above object, the present invention provides the following technical solution: a front line identification method based on the ground of Yunnan-Guizhou Plateau, the following steps:

[0009] S1: Identify stations in key areas of focus;

[0010] S2: stations that may be on the front line in the primary election;

[0011] S3: Fitting the primary forward line;

[0012] S4: Determine the effectiveness of the preliminary forward line and generate the final ground forward line product.

[0013] Preferably, in step S1, the observation results of each station are used to calculate the ten-day average of the daily maximum temperature, the standard deviation of the daily maximum temperature relative to the ten-day average, and the annual average frequency of the daily maximum temperature dropping by more than 5°C compared with the previous day, and key focus areas and stations are identified accordingly.

[0014] Preferably, in step S2, the preliminary selection of stations that may be located on the front line includes the following steps:

[0015] S21: Calculate the potential temperature of stations in the identified key areas of concern;

[0016] S22: Calculate the potential temperature gradient and air temperature gradient of each station and its surrounding stations within 1 degree of longitude / latitude;

[0017] S23: Preliminary station determination: if the potential temperature gradient between a station and at least one adjacent station is greater than 12K / (longitude / latitude) and the air temperature gradient is greater than 6℃ / (longitude / latitude), and the warm station is located on the south or west side, then this station is determined to be a preliminary station that may be located on the front line.

[0018] Preferably, the potential temperature, potential temperature gradient and air temperature gradient are all calculated based on the air temperature at 14:00 at the station.

[0019] Preferably, the calculation formula of the potential temperature is: potential temperature = air temperature * (1000 / station air pressure) 0.286 .

[0020] Preferably, in step S3, fitting the preliminary forward line includes the following steps:

[0021] S31: Further screen the preliminary selected stations, perform cluster analysis on the latitude and longitude of the preliminary selected stations, divide the stations into N groups, and exclude the groups with less than 6 stations within 0.5 degrees;

[0022] S32: If the number of initially selected stations is not less than 6, perform iterative linear fitting on their longitudes and latitudes, and gradually eliminate stations that are farther from the fitting line, starting from those that are more than 2.5 longitudes / latitudes away from the fitting line;

[0023] S33: The threshold is gradually reduced with a step size of 0.1 longitude / latitude. After each elimination, the new fitting line is determined until the distance threshold is reduced to 0.5 longitude / latitude. The stations that are finally located within 0.5 longitude / latitude on both sides of the fitting line are identified as the stations on the preliminary front line;

[0024] S34: The fitted lines for the longitude and latitude of the above stations approximately represent the positions of the preliminary ground fronts.

[0025] Preferably, the cluster analysis adopts the dbscan method, and iterative linear fitting starts from the stations whose distance to the fitting line is greater than 2.5 longitude / latitude, and gradually eliminates the stations that are far away from the fitting line, and then gradually reduces the threshold with a step size of 0.1 longitude / latitude until it ends at 0.5 longitude / latitude.

[0026] Preferably, the determination of the effectiveness of the preliminary forward line in step S4 and the generation of the final ground forward line product include the following steps:

[0027] S41: Calculate the average potential temperature and the average 14:00 temperature in the range of 0.5-3 longitude / latitude on both sides of the primary front respectively;

[0028] S42: If the average potential temperature difference on both sides of the front exceeds 12K and the temperature difference at 14:00 exceeds 6°C, a rectangle is drawn according to the front, and the length of the front along the longitude or latitude exceeds 3 degrees of longitude / latitude, then the preliminary front is determined to be valid, that is, there is a ground front on that day

[0029] S43: Based on the determined front, calculate the temperature gradient at 14:00 between the adjacent stations on both sides of the front. If the gradient between the two stations is greater than 6°C / (longitude / latitude), and the warm station is located on the south or west side, record the longitude and latitude of the station;

[0030] S44: The front line and the station position are subjected to secondary filtering through a Gaussian function, and finally a front line that conforms to the actual position is formed.

[0031] Preferably, in step S44, the Gaussian function performs secondary filtering on the front line and the station position, including the following steps:

[0032] S441: Determine Gaussian filter kernel parameters, select a suitable kernel size and determine the standard deviation σ according to the required smoothing precision and data density;

[0033] S442: Generate a Gaussian filter kernel, and use a Gaussian function to calculate the weight for each position (x, y) in the kernel relative to the center point.

[0034] S443: filtering the striker position, converting the striker data into a form suitable for filtering, determining the influence area around each point on the striker, using a Gaussian filter to perform weighted averaging on the points in the influence area, calculating a new position or attribute, and updating the representation of the striker to reflect the filtered changes;

[0035] S444: Repeat and optimize, repeat the filtering process as needed, and adjust the kernel size and standard deviation σ value parameters to optimize the filtering effect.

[0036] Preferably, in step S442, all weights need to be added together to obtain a total, and then each weight is divided by the total to ensure that the sum of the weights of the core is 1. The calculation formula is:

[0037]

[0038] (III) Beneficial effects

[0039] Compared with the prior art, the present invention provides a front identification method based on the ground of the Yunnan-Guizhou Plateau, which has the following beneficial effects: the objective discrimination method of the ground front of the Yunnan-Guizhou Plateau proposed by the present method is applicable to various types of stations and grid data, and can be applied to real-time data analysis as well as various types of numerical forecast products. Compared with the traditional front analysis method, the present method determines the ground front through linear fitting, and can objectively give the movement, cold and warm characteristics of the front on the basis of objectively giving the direction and position of each front. On the one hand, it helps to objectively express the "dynamic" evolution law of the "quasi-stationary" front; on the other hand, by comprehensively analyzing the movement of the front, temperature and pressure changes near the front, and other factors, it lays the foundation for synthesizing and analyzing the three-dimensional circulation structure, and more comprehensively and systematically understanding the complete structure, category characteristics and related refined weather evolution of the front. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 This is a block diagram of forward line identification of the present invention;

[0041] Figure 2 This is a flow chart of the forward line identification method of the present invention. DETAILED DESCRIPTION

[0042] In order to better understand the purpose, structure and function of the present invention, and to realize the accurate identification of the front line on the ground of the Yunnan-Guizhou Plateau, the objective discrimination method of the ground front line on the Yunnan-Guizhou Plateau proposed by this method is applicable to various stations and grid data, and can be applied to real-time data analysis and various numerical forecast products. Compared with the traditional front analysis method, this method determines the ground front line through linear fitting, and can objectively give the movement, cold and warm characteristics of the front line on the basis of objectively giving the direction and position of each front line. On the one hand, it helps to objectively express the "dynamic" evolution law of the "quasi-stationary" front; on the other hand, by comprehensively analyzing the movement of the front line, temperature changes near the front line, pressure changes and other factors, it lays the foundation for synthesizing and analyzing the three-dimensional circulation structure, and more comprehensively and systematically understanding the complete structure, category characteristics and related refined weather evolution of the front. A front line identification method based on the ground of the Yunnan-Guizhou Plateau of the present invention is further described in detail.

[0043] refer to Figure 1-2 , the present invention: a front line identification method based on the ground of Yunnan-Guizhou Plateau, the following steps:

[0044] S1: Determine the stations in the key focus areas, and use the observation results of each station to calculate the ten-day average of the daily maximum temperature and the standard deviation of the daily maximum temperature relative to the ten-day average, as well as the annual average frequency of the daily maximum temperature dropping by more than 5°C compared with the previous day, and then frame the key focus areas and stations accordingly;

[0045] S2: stations that may be on the front line in the primary election;

[0046] Specifically, the primary election of stations that may be on the front line includes the following steps:

[0047] S21: Calculate the potential temperature of the stations in the identified key areas of concern. The calculation formula for potential temperature is: potential temperature = air temperature * (1000 / air pressure at this station) 0.286 ;

[0048] S22: Calculate the potential temperature gradient and air temperature gradient of each station and its surrounding stations within 1 degree of longitude / latitude. The potential temperature, potential temperature gradient and air temperature gradient are all calculated based on the temperature at 14:00.

[0049] S23: Preliminary station determination: if the potential temperature gradient between a station and at least one adjacent station is greater than 12K / (longitude / latitude) and the air temperature gradient is greater than 6℃ / (longitude / latitude), and the warm station is located on the south or west side, then this station is determined to be a preliminary station that may be located on the front line.

[0050] S3: Fitting the primary forward line;

[0051] Specifically, fitting the primary forward line includes the following steps:

[0052] S31: Further screen the preliminary selected stations, perform cluster analysis on the latitude and longitude of the preliminary selected stations, divide the stations into N groups, and exclude the groups with less than 6 stations within 0.5 degrees;

[0053] S32: If the number of initially selected stations is not less than 6, perform iterative linear fitting on their longitudes and latitudes, and gradually eliminate stations that are farther from the fitting line, starting from those that are more than 2.5 longitudes / latitudes away from the fitting line;

[0054] S33: The threshold is gradually reduced with a step size of 0.1 longitude / latitude. After each elimination, the new fitting line is determined until the distance threshold is reduced to 0.5 longitude / latitude. The stations that are finally located within 0.5 longitude / latitude on both sides of the fitting line are identified as the stations on the preliminary front line;

[0055] S34: The fitted lines for the longitude and latitude of the above stations approximately represent the positions of the preliminary ground fronts.

[0056] Furthermore, the cluster analysis adopts the dbscan method, and iterative linear fitting gradually eliminates stations that are farther away from the fitting line starting from the stations that are more than 2.5 longitudes / latitudes away from the fitting line, and then gradually reduces the threshold with a step size of 0.1 longitude / latitude until it ends at 0.5 longitude / latitude.

[0057] S4: Determine the effectiveness of the preliminary forward line and generate the final ground forward line product;

[0058] Specifically, the determination of the effectiveness of the preliminary forward line and the generation of the final ground forward line product include the following steps:

[0059] S41: Calculate the average potential temperature and the average 14:00 temperature in the range of 0.5-3 longitude / latitude on both sides of the primary front respectively;

[0060] S42: If the average potential temperature difference on both sides of the front exceeds 12K and the temperature difference at 14:00 exceeds 6°C, a rectangle is drawn according to the front, and the length of the front along the longitude or latitude exceeds 3 degrees of longitude / latitude, then the preliminary front is determined to be valid, that is, there is a ground front on that day

[0061] S43: Based on the determined front, calculate the temperature gradient at 14:00 between the adjacent stations on both sides of the front. If the gradient between the two stations is greater than 6°C / (longitude / latitude), and the warm station is located on the south or west side, record the longitude and latitude of the station;

[0062] S44: The front line and the station position are subjected to secondary filtering through a Gaussian function, and finally a front line that conforms to the actual position is formed.

[0063] Furthermore, the Gaussian function performs secondary filtering on the front line and the station position, including the following steps:

[0064] S441: Determine Gaussian filter kernel parameters, select a suitable kernel size and determine the standard deviation σ according to the required smoothing precision and data density;

[0065] S442: Generate a Gaussian filter kernel, and use a Gaussian function to calculate the weight for each position (x, y) in the kernel relative to the center point. All weights need to be added together to get the sum, and then each weight is divided by the sum to ensure that the weight sum of the kernel is 1. The calculation formula is:

[0066]

[0067] S443: filtering the striker position, converting the striker data into a form suitable for filtering, determining the influence area around each point on the striker, using a Gaussian filter to perform weighted averaging on the points in the influence area, calculating a new position or attribute, and updating the representation of the striker to reflect the filtered changes;

[0068] S444: Repeat and optimize, repeat the filtering process as needed, and adjust the kernel size and standard deviation σ value parameters to optimize the filtering effect.

[0069] Based on the observation data of ground meteorological stations in and around the Yunnan-Guizhou Plateau, a ground front determination method based on linear fitting is proposed. It can easily determine the existence of the main ground front in the Yunnan-Guizhou Plateau and approximately determine the stations located on the front. Then, by analyzing the basic characteristics of the front and its relationship with the changes of ground meteorological elements, the dynamic characteristics and laws of the front on the surface of the Yunnan-Guizhou Plateau are systematically studied.

[0070] It is to be understood that the present invention is described by some embodiments, and it is known to those skilled in the art that various changes or equivalent substitutions may be made to these features and embodiments without departing from the spirit and scope of the present invention. In addition, under the teachings of the present invention, these features and embodiments may be modified to adapt to specific circumstances and materials without departing from the spirit and scope of the present invention. Therefore, the present invention is not limited by the specific embodiments disclosed herein, and all embodiments falling within the scope of the claims of this application are within the scope of protection of the present invention.

Claims

1. A front line identification method based on the ground of Yunnan-Guizhou Plateau, characterized in that: The following steps are described: S1: Identify stations in key areas of focus; S2: stations that may be on the front line in the primary election; S3: Fitting the primary forward line; S4: Determine the effectiveness of the preliminary forward line and generate the final ground forward line product.

2. A front line identification method based on the ground of Yunnan-Guizhou Plateau according to claim 1, characterized in that: In step S1, the observation results of each station are used to calculate the ten-day average of the daily maximum temperature, the standard deviation of the daily maximum temperature relative to the ten-day average, and the annual average frequency of the daily maximum temperature dropping by more than 5°C compared with the previous day, and key focus areas and stations are identified accordingly.

3. The front line identification method based on the ground of Yunnan-Guizhou Plateau according to claim 1 is characterized in that: In step S2, the preliminary selection of stations that may be located on the front line includes the following steps: S21: Calculate the potential temperature of stations in the identified key areas of concern; S22: Calculate the potential temperature gradient and air temperature gradient of each station and its surrounding stations within 1 degree of longitude / latitude; S23: Preliminary station determination: if the potential temperature gradient between a station and at least one adjacent station is greater than 12K / (longitude / latitude) and the air temperature gradient is greater than 6℃ / (longitude / latitude), and the warm station is located on the south or west side, then this station is determined to be a preliminary station that may be located on the front line.

4. The front line identification method based on the ground of the Yunnan-Guizhou Plateau according to claim 3 is characterized in that: The potential temperature, potential temperature gradient and air temperature gradient are all calculated by the station based on the temperature at 14:

00.

5. The front line identification method based on the ground of the Yunnan-Guizhou Plateau according to claim 4 is characterized in that: The calculation formula of the potential temperature is: potential temperature = air temperature * (1000 / station air pressure) 0.286 .

6. The front line identification method based on the ground of Yunnan-Guizhou Plateau according to claim 1 is characterized in that: In step S3, fitting the preliminary forward line includes the following steps: S31: Further screen the preliminary selected stations, perform cluster analysis on the latitude and longitude of the preliminary selected stations, divide the stations into N groups, and exclude the groups with less than 6 stations within 0.5 degrees; S32: If the number of initially selected stations is not less than 6, perform iterative linear fitting on their longitudes and latitudes, and gradually eliminate stations that are farther from the fitting line, starting from those that are more than 2.5 longitudes / latitudes away from the fitting line; S33: The threshold is gradually reduced with a step size of 0.1 longitude / latitude. After each elimination, the new fitting line is determined until the distance threshold is reduced to 0.5 longitude / latitude. The stations that are finally located within 0.5 longitude / latitude on both sides of the fitting line are identified as the stations on the preliminary front line; S34: The fitted lines for the longitude and latitude of the above stations approximately represent the positions of the preliminary ground fronts.

7. A front line identification method based on the ground of the Yunnan-Guizhou Plateau according to claim 6, characterized in that: The cluster analysis adopts the dbscan method, and iterative linear fitting starts from the stations with a distance greater than 2.5 longitudes / latitudes from the fitting line and gradually eliminates the stations that are far from the fitting line, and then gradually reduces the threshold with a step size of 0.1 longitude / latitude until it ends at 0.5 longitude / latitude.

8. The front line identification method based on the ground of Yunnan-Guizhou Plateau according to claim 1 is characterized in that: The determination of the effectiveness of the preliminary forward line in step S4 and the generation of the final ground forward line product include the following steps: S41: Calculate the average potential temperature and the average 14:00 temperature in the range of 0.5-3 longitude / latitude on both sides of the primary front respectively; S42: If the average potential temperature difference on both sides of the front exceeds 12K and the temperature difference at 14:00 exceeds 6°C, a rectangle is drawn according to the front, and the length of the front along the longitude or latitude exceeds 3 degrees of longitude / latitude, then the preliminary front is determined to be valid, that is, there is a ground front on that day S43: Based on the determined front, calculate the temperature gradient at 14:00 between the adjacent stations on both sides of the front. If the gradient between the two stations is greater than 6°C / (longitude / latitude), and the warm station is located on the south or west side, record the longitude and latitude of the station; S44: The front line and the station position are subjected to secondary filtering through a Gaussian function, and finally a front line that conforms to the actual position is formed.

9. A front line identification method based on the ground of the Yunnan-Guizhou Plateau according to claim 8, characterized in that: In step S44, the Gaussian function performs secondary filtering on the front line and the station position, including the following steps: S441: Determine Gaussian filter kernel parameters, select a suitable kernel size and determine the standard deviation σ according to the required smoothing precision and data density; S442: Generate a Gaussian filter kernel, and use a Gaussian function to calculate the weight for each position (x, y) in the kernel relative to the center point. S443: filtering the striker position, converting the striker data into a form suitable for filtering, determining the influence area around each point on the striker, using a Gaussian filter to perform weighted averaging on the points in the influence area, calculating a new position or attribute, and updating the representation of the striker to reflect the filtered changes; S444: Repeat and optimize, repeat the filtering process as needed, and adjust the kernel size and standard deviation σ value parameters to optimize the filtering effect.

10. A front line identification method based on the ground of the Yunnan-Guizhou Plateau according to claim 9, characterized in that: In step S442, all weights need to be added together to obtain a total, and then each weight is divided by the total to ensure that the sum of the weights of the core is 1. The calculation formula is:

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