Weather situation identification method and device based on high and low voltages, equipment and medium

Abstract

The invention provides a weather situation identification method and device based on high and low pressure, equipment and a medium. In the weather situation identification method based on high and low pressure, the zero isoline and the jump point are extracted from the air pressure difference matrix, the affiliation zero isoline of the jump point is determined through the distance from the jump point to the zero isoline, and the zero isoline, the jump point and the affiliation isoline of the jump point are used to determine whether the point location to be detected belongs to the high-pressure system or the low-pressure system. According to the invention, the weather situation automatic identification based on high and low voltages can be realized, and the accuracy and reliability of the weather situation identification based on high and low voltages are improved.

Description

Technical Field

[0001] This disclosure relates to a method, apparatus, device, and medium for identifying weather patterns based on high and low pressure. Background Technology

[0002] In the field of meteorological analysis and forecasting, objective and accurate analysis of the sea-level pressure field is crucial for diagnosing and predicting weather patterns. Identifying and locating high-pressure centers, low-pressure centers, and features such as high-pressure ridges and low-pressure troughs are important parts of weather pattern analysis. These features directly define the distribution of air masses, the activity of fronts, and dominate the development of future weather.

[0003] In related technologies, the identification of high and low pressure regions based on isolines suffers from ambiguity and vagueness. Because isolines are discretely distributed in space, it's ambiguous whether points scattered between them belong to high-pressure areas, low-pressure areas, or transition zones. This ambiguity is particularly pronounced in areas with sparse isolines. Currently, these ambiguities and vagueness primarily rely on subjective inferences based on human experience. This not only reduces the accuracy and reliability of the final weather pattern identification but also makes automation difficult due to the high dependence on human intervention. Summary of the Invention

[0004] In view of this, the present disclosure provides a method, apparatus, device and medium for identifying weather patterns based on high and low pressure.

[0005] According to a first aspect of this disclosure, a weather pattern identification method based on high and low pressure is provided, the method comprising: Obtain the air pressure data matrix of the target area. The air pressure data matrix is ​​gridded data with fixed grid point spacing. The rows of the air pressure data matrix represent latitude and the columns represent longitude. The values ​​of the elements in the air pressure data matrix represent air pressure values. The pressure data matrix is ​​obtained by row difference, where rows represent latitude and columns represent longitude. The values ​​of the elements in the pressure difference matrix are difference values, which indicate the magnitude and direction of the pressure gradient in the north-south direction of the target area. The pressure difference matrix is ​​used to extract all zero contour lines of the target area. The difference value of all latitude and longitude coordinate points on each zero contour line is zero, and the difference value of all points within the area enclosed by each zero contour line has the same sign. All transition points in the target area are extracted using the aforementioned pressure difference matrix; Determine the zero contour line to which each of the aforementioned transition points belongs in all zero contour lines; The system to which the test point belongs is determined based on the latitude and longitude of the test point, all zero contour lines, and the zero contour line to which each jump point belongs. The system to which the test point belongs is either a high-pressure system or a low-pressure system.

[0006] In some embodiments of the first aspect of this disclosure, the pressure data matrix is ​​differentially divided by row to obtain a pressure difference matrix, comprising: performing the following subtraction on each row of the pressure data matrix except the last row: subtracting the next row of the current row of the pressure data matrix from the current row of the pressure data matrix element by element to obtain the difference value of each element of the current row of the pressure difference matrix.

[0007] In some embodiments of the first aspect of this disclosure, the method further includes: before extracting all zero contour lines of the target area using the pressure difference matrix, performing the following edge processing on the pressure difference matrix: adding a row of zero values ​​before the first row of the pressure difference matrix, and setting the values ​​of the elements in the last row, the first column, and the last column of the pressure difference matrix to 0.

[0008] In some embodiments of the first aspect of this disclosure, the step of extracting all transition points of the target area using the pressure difference matrix includes: performing the following processing on each column of the pressure difference matrix: traversing each element of the current column to compare the sign of the difference value of each element with the element of the previous column; if an element has a different sign of the difference value with the element of the previous column, then the adjacent element pair formed by the element and the element of the previous column constitutes a transition point; determining the latitude and longitude of the transition point according to the latitude and longitude coordinates of the adjacent element pair; and determining the transition type of the transition point according to the sign of the difference value of the adjacent element pair.

[0009] In some embodiments of the first aspect of this disclosure, determining the attribution system of the point to be measured based on the latitude and longitude of the point to be measured, all zero contour lines, and the attribution zero contour line of each of the transition points includes: constructing a contour region containment tree using all zero contour lines of the target area, where each node in the contour region containment tree represents an area enclosed by one of the zero contour lines; determining the influence nodes of the point to be measured based on the latitude and longitude of the point to be measured and the contour region containment tree, and determining the zero contour line corresponding to the influence node as the attribution system of the transition point. The zero-isoline of the point to be measured is defined as follows: the influencing node is a node in the isoline region containing the point to be measured, but none of its child nodes contain the point to be measured; the relevant transition points of the point to be measured are determined based on the latitude and longitude of the point to be measured and the zero-isoline of the point to be measured; the distribution patterns of all relevant transition points located at the upper edge of the zero-isoline of the point to be measured and the distribution patterns of all relevant transition points located at the lower edge of the zero-isoline of the point to be measured are statistically analyzed to determine the attribution system of the point to be measured.

[0010] In some embodiments of the first aspect of this disclosure, the method further includes: calculating the distance from the point to be measured to its home zero contour line to determine the position of the point to be measured in its home system.

[0011] In some embodiments of the first aspect of this disclosure, determining the relevant transition points of the test point based on the latitude and longitude of the test point and its zero-homogeneity contour line includes: calculating the distances from the test point to each latitude and longitude coordinate point on its zero-homogeneity contour line to find the closest point of the test point, determining the orientation of the closest point relative to the test point, and selecting all transition points in the vicinity of the orientation portion of the zero-homogeneity contour line of the test point as the relevant transition points of the test point.

[0012] According to a second aspect of this disclosure, a weather pattern identification device based on high and low pressure is provided, comprising: The data acquisition unit is used to acquire the air pressure data matrix of the target area. The air pressure data matrix is ​​gridded data with fixed grid point spacing. The rows of the air pressure data matrix represent latitude and the columns represent longitude. The values ​​of the elements in the air pressure data matrix represent air pressure values. The differential operation unit is used to perform row-wise differential operations on the pressure data matrix to obtain a pressure differential matrix. The rows of the pressure differential matrix represent latitude and the columns represent longitude. The values ​​of the elements in the pressure differential matrix represent differential values, and the differential values ​​indicate the magnitude and direction of the pressure gradient in the north-south direction of the target area. The zero contour line extraction unit is used to extract all zero contour lines of the target area using the pressure difference matrix. The difference value of all latitude and longitude coordinate points on each zero contour line is zero, and the difference value of all points within the area enclosed by each zero contour line has the same sign. A transition point extraction unit is used to extract all transition points in the target area using the pressure difference matrix. A jump point assignment determination unit is used to determine the zero contour line to which each jump point is assigned in all zero contour lines; The unit for determining the attribution of a point to be measured is used to determine the attribution system of the point to be measured based on the latitude and longitude of the point to be measured, all zero contour lines, and the attribution zero contour line of each of the jump points. The attribution system is either a high-pressure system or a low-pressure system.

[0013] According to a third aspect of this disclosure, an electronic device is provided, comprising: one or more processors and a memory storing a program, the program including instructions that, when executed by the processor, cause the processor to perform the methods described above.

[0014] According to a third aspect of this disclosure, a computer-readable storage medium storing a program, the program including instructions that, when executed by one or more processors, cause the computing device to perform the method described above.

[0015] As can be seen from the above technical solution, the embodiments of this disclosure extract zero contour lines and transition points on the pressure difference matrix, determine the zero contour line to which the transition point belongs by the distance from the transition point to the zero contour line, and use these zero contour lines, transition points and their respective contour lines to determine whether the measured point belongs to a high-pressure system or a low-pressure system. This eliminates the ambiguity and vagueness of high and low pressure area identification based on contour lines, and enables automated identification of weather patterns based on high and low pressure, while improving the accuracy and reliability of weather pattern identification based on high and low pressure. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of this disclosure or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this disclosure. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 A schematic flowchart illustrating the weather pattern identification method based on high and low pressure provided in this embodiment of the disclosure; Figure 2 This is an exemplary implementation flowchart of the system for determining the attribution of a point to be measured according to an embodiment of this disclosure; Figure 3 A schematic diagram of the structure of a weather pattern identification device based on high and low pressure provided in an embodiment of this disclosure; Figure 4 A schematic structural block diagram of an electronic device provided in an embodiment of this disclosure. Detailed Implementation

[0018] The technical solutions of the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this disclosure, and not all embodiments. Based on the embodiments of this disclosure, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this disclosure.

[0019] The terminology used in the embodiments of this disclosure is for the purpose of describing particular embodiments only and is not intended to be limiting of this disclosure. The singular forms “a,” “the,” and “the” as used in the embodiments of this disclosure and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise.

[0020] Depending on the context, words such as "if," "when," etc., used here can be interpreted as "when," "when," "in response to determination," or "in response to detection." Similarly, depending on the context, the phrases "if determination" or "if detection (of the stated condition or event)" can be interpreted as "when determination," "in response to determination," "when detection (of the stated condition or event)," or "in response to detection (of the stated condition or event)."

[0021] As described in the background section, the identification of high and low pressure regions in a pressure field is mainly achieved through contour lines. However, contour lines are discrete, and it is ambiguous whether the points scattered between contour lines belong to high-pressure regions, low-pressure regions, or transitional zones between high and low pressure. At the same time, the determination of features such as high-pressure ridges and low-pressure troughs is also fuzzy and ambiguous.

[0022] In related technologies, whether the points scattered between contour lines belong to high-pressure areas, low-pressure areas, or transition zones between high and low pressure is mainly determined subjectively by staff based on their personal experience.

[0023] Despite some existing technological improvements, such as contour densification or simple curvature calculation, the ambiguity and susceptibility to data noise in analysis based on discrete lines have not been fundamentally resolved.

[0024] In view of this, the present disclosure provides the following methods, apparatus, devices and storage media for identifying weather patterns based on high and low pressure, which can eliminate the ambiguity and vagueness of identifying high and low pressure areas based on contour lines, realize automated identification of weather patterns based on high and low pressure, and improve the accuracy and reliability of weather pattern identification.

[0025] This improves the accuracy, stability, and rigor of weather pattern identification, while also enabling automated weather pattern identification.

[0026] The specific implementation methods of the embodiments disclosed herein will be described in detail below.

[0027] Figure 1 A flowchart illustrating a weather pattern identification method based on high and low pressure provided in this disclosure is shown. This method can be executed by an electronic device described below, which can automatically acquire raw air pressure data. See also... Figure 1 The weather pattern identification method based on high and low pressure in this embodiment may include the following steps: Step 101: Obtain the air pressure data matrix of the target area. The air pressure data matrix is ​​gridded data with fixed grid point spacing. The rows of the air pressure data matrix represent latitude and the columns represent longitude. The values ​​of the elements in the air pressure data matrix represent air pressure values. Step 102: Obtain the pressure difference matrix by dividing the row differential pressure data matrix. The rows of the pressure difference matrix represent latitude and the columns represent longitude. The values ​​of the elements in the pressure difference matrix represent the difference values. The difference values ​​indicate the magnitude and direction of the pressure gradient in the north-south direction of the target area. Step 103: Use the pressure difference matrix to extract all zero contour lines of the target area. The difference value of all latitude and longitude coordinate points on each zero contour line is zero, and the difference value of all points within the area enclosed by each zero contour line has the same sign. Step 104: Extract all transition points in the target area using the pressure difference matrix; Step 105: Determine the zero contour line to which each transition point belongs in all zero contour lines; Step 106: Determine the system to which the point to be measured belongs based on the latitude and longitude of the point to be measured, all zero contour lines, and the zero contour line to which each jump point belongs. The system to which the point belongs is either a high-pressure system or a low-pressure system.

[0028] This embodiment extracts zero-isolines and transition points from the pressure difference matrix. The distance from the transition point to the zero-isoline determines the zero-isoline to which the transition point belongs. Using these zero-isolines, transition points, and their respective isolines, it determines whether a point belongs to a high-pressure system or a low-pressure system. This completely eliminates the ambiguity and vagueness of high- and low-pressure area identification based on isolines, enabling automated identification of weather patterns based on high and low pressure, while improving the accuracy and reliability of weather pattern identification.

[0029] In step 101, the original air pressure data of the target area can be obtained based on the latitude and longitude of the target area, and the air pressure data matrix of the target area can be obtained using the original air pressure data of the target area.

[0030] If the obtained raw air pressure data is gridded data, it can be used directly as the air pressure data matrix, or the raw air pressure data can be interpolated to gridded data with a predetermined grid spacing to obtain the air pressure data matrix.

[0031] If the acquired raw air pressure data is not gridded, it can be interpolated to obtain a gridded data matrix with a predetermined grid spacing. Specifically, the unevenly distributed raw air pressure data is converted into gridded data with a predetermined grid spacing using interpolation algorithms such as bilinear interpolation or Kriging interpolation. This gridded data is the air pressure data matrix, a two-dimensional matrix where rows represent latitude and columns represent longitude. The elements of this two-dimensional matrix are the sea level air pressure values ​​at the corresponding grid points. In practical applications, the predetermined grid spacing can be preset, for example, to 1° × 1° or other values.

[0032] Raw atmospheric pressure data can be observational data reflecting the actual state of the atmosphere in the past and present, or computational data derived from computer simulations based on physical laws and initial observational data, reflecting the current and future state of the atmosphere. Raw atmospheric pressure data can be obtained directly from, for example, national meteorological observation stations and automatic weather stations, or from forecasting centers such as the European Centre for Medium-Range Weather Forecasts (ECMWF) and the China GRAPES.

[0033] Raw barometric pressure data can include spatial location, barometric pressure value, and time information.

[0034] Specifically, raw air pressure data can include metadata and feature data. Metadata can include station identifiers, grid identifiers, timestamps, etc. Station identifiers are the identifiers of observation points, and can include, but are not limited to, station numbers and station names. The latitude and longitude of the station can be obtained through the station identifier, which in turn allows us to obtain the latitude and longitude of the corresponding air pressure. If the raw air pressure data is gridded data with a fixed grid interval, the grid identifier can be the latitude and longitude coordinates of each grid point.

[0035] Raw air pressure data may include, but is not limited to, local station air pressure and sea level air pressure. Local station air pressure refers to the air pressure value at the sea level where the observation station is located, while sea level air pressure is the air pressure value after correcting the local station air pressure to the mean sea level. Because sea level air pressure makes stations at different altitudes comparable, it is usually used as the standard data for analyzing high and low pressure systems.

[0036] In addition, the raw air pressure data may also include the following elements: standard isobaric surface height, ancillary information, and quality control codes. The standard isobaric surface height may be, but is not limited to, the altitude values ​​of the 850hPa, 700hPa, and 500hPa isobaric surfaces. The ancillary information may include, but is not limited to, temperature, humidity, wind direction and wind speed recorded at the same time as the air pressure at this station. The quality control code can be used to identify whether the raw air pressure data has undergone quality control and whether it is reliable.

[0037] For example, assuming the target region has a longitude range of 70-140° and a latitude range of 0-55°, the obtained raw air pressure data is the raw air pressure dataset measured or calculated by all observation stations or model grid points within the geographical area of ​​70-140° longitude and 0-55° latitude during a specified time period. Interpolating this raw air pressure dataset into gridded data with a preset grid spacing yields the air pressure data matrix for the target region. Assuming the preset grid spacing is 1°×1°, a 551*601 air pressure data matrix can be obtained, with 551 rows and 601 columns. The first row has the highest latitude, and the 551st row has the lowest latitude. The latitude decreases as the row number increases, and the direction is from north to south. The first column has the lowest longitude, and the 601st column has the highest longitude, and the direction is from west to east. This air pressure data matrix is ​​denoted as M.

[0038] In step 102, the pressure data matrix is ​​differentially categorized by row, which means performing a difference operation on the pressure data matrix along the row direction. Specifically, for all rows in the pressure data matrix except the last row, the following subtraction is performed row by row: subtracting the next row of the current row from the current row of the pressure data matrix element by element to obtain the difference value of each element in the current row of the pressure difference matrix. That is, the difference calculation is performed along the direction where the columns of the pressure data matrix remain unchanged and the rows change. This difference operation is performed on every point in the pressure data matrix except the last row.

[0039] The number of rows in the pressure difference matrix is ​​equal to the number of rows in the pressure data matrix minus 1, and the number of columns is equal to the number of columns in the pressure data matrix. The element values ​​of the pressure difference matrix are the difference values. The difference values ​​can indicate the magnitude and direction of the pressure gradient in the north-south direction of the target area. The sign of a difference value indicates the direction of the pressure gradient at the corresponding latitude and longitude grid point, and the absolute value of a difference value indicates the magnitude of the pressure gradient at the corresponding latitude and longitude grid point.

[0040] Specifically, each difference value in the pressure difference matrix can be calculated using the following formula:

[0041] in, This is a column index representing longitude; For index, indicating latitude; Represents the first element in the pressure difference matrix. line, number The difference between the columns, Represents the first in the pressure data matrix line, number The air pressure values ​​of the column, Represents the first in the pressure data matrix line, number The air pressure value of the column.

[0042] Taking the pressure data matrix M mentioned earlier as an example, we can obtain a 550*601 pressure difference matrix M by calculating its row differences. G Pressure difference matrix M G The pressure difference matrix M has 550 rows and 601 columns. G The number of rows is less than that of the pressure data matrix M, and the number of columns is the same as that of the pressure data matrix M. The pressure difference matrix M... GThe value of each element in the graph represents the difference value for the corresponding latitude and longitude grid point, indicating the magnitude and direction of the pressure gradient from north to south at that grid point. A positive sign indicates that the air pressure is higher in the south than in the north, with pressure increasing southwards; a negative sign indicates that the air pressure is higher in the north than in the south, with pressure decreasing southwards. The absolute value of the difference represents the magnitude of the pressure gradient from north to south at the corresponding latitude and longitude grid point. A difference value of zero indicates that there is no pressure difference in the north-south direction at the corresponding latitude and longitude grid point.

[0043] Furthermore, to ensure that all zero contour lines extracted using the pressure difference matrix are closed curves, the method of this embodiment may further include: performing the following edge processing on the pressure difference matrix before step 103: adding a row of zero values ​​before the first row of the pressure difference matrix, and setting the values ​​of the elements in the last row, first column, and last column of the pressure difference matrix to 0. The pressure difference matrix M described above... G For example, in the pressure difference matrix M G Add a row of 0 elements before the first row to make the pressure difference matrix M G It becomes 551*601. Then, the pressure difference matrix M is... G All elements in the first column, last column, and last row are set to 0.

[0044] By performing the above edge processing on the pressure difference matrix, the integrity of the pressure difference matrix can be guaranteed, while avoiding interruptions at the boundaries when extracting zero contour lines, thus ensuring that all zero contour lines extracted using the pressure difference matrix are closed curves.

[0045] In step 103, all zero contour lines can be extracted from the pressure difference matrix using methods such as the marching squares algorithm, linear interpolation algorithm, or by finding grid points with zero difference values. The difference value of all latitude and longitude coordinate points on each zero contour line is zero.

[0046] Zero-isotropy lines represent continuous characteristic lines in the pressure field of a target area where the north-south gradient is zero. They are key geometric features for identifying the boundaries of weather systems such as high-pressure ridges and low-pressure troughs. Each zero-isotropy line can be represented as an ordered sequence of latitude and longitude coordinates. The latitude and longitude coordinates of each point in the sequence do not necessarily coincide with the grid points of the pressure difference matrix. These coordinates can be floating-point numbers or integers. After the aforementioned edge processing, all zero-isotropy lines extracted from the pressure difference matrix will be closed curves. At this point, the latitude and longitude coordinates in the sequence representing the zero-isotropy lines will form a closed loop when connected sequentially. The difference values ​​of all points within the area enclosed by each zero-isotropy line have the same sign. That is, the difference values ​​of all points within the area enclosed by each zero-isotropy line are either all positive or all negative. The zero-isotropy line is the boundary line of this area, which has a trend opposite to the external environment, and is also a reversal line of the pressure change trend.

[0047] In step 104, the following processing can be performed on each column of the pressure difference matrix to extract all transition points in the target area: Traverse each element in the current column and compare the sign of the difference value between each element and the element in the previous column. If the sign of the difference value between an element and the element in the previous column is different, then the adjacent element pair formed by the element and the element in the previous column constitutes a transition point. The latitude and longitude of the transition point are determined based on the latitude and longitude coordinates of the adjacent element pair, and the transition type of the transition point is determined based on the sign of the difference value of the adjacent element pair. Therefore, all transition points in the target area can be found through the pressure difference matrix, and the latitude, longitude, and transition type of each transition point can be determined.

[0048] The latitude and longitude of the transition point can be the latitude and longitude coordinates of any element in an adjacent element pair, or it can be the average latitude and longitude coordinates of an adjacent element pair.

[0049] If the difference between the preceding row elements in an adjacent pair is negative and the difference between the current element is positive, then the transition type of this transition point is "from negative to positive". If the difference between the preceding row elements in an adjacent pair is positive and the difference between the current element is negative, then the transition type of this transition point is "from positive to negative".

[0050] In step 105, the following process can be performed for each transition point to determine the zero contour line to which the transition point belongs: calculate the distance from the transition point to each zero contour line, compare the distance from the transition point to all zero contour lines, and the zero contour line corresponding to the minimum distance is the zero contour line to which the transition point belongs.

[0051] Specifically, the distance from a jump point to a zero contour line can be obtained by traversing all segments of the zero contour line, calculating the shortest distance from the jump point to each segment, and taking the global minimum value. In practical applications, other methods can also be used to calculate the distance from a jump point to a zero contour line. This disclosure does not limit the method for calculating the distance from a jump point to a zero contour line.

[0052] Transition points are typically the most representative gradient points within high-low pressure transition zones. They are characteristic points of these zones and key features for identifying and locating them. By combining the transition type of each transition point with the sign of the difference values ​​of all points within the area enclosed by its corresponding zero-isotropy line, the edge characteristics of the weather system can be described more precisely.

[0053] Figure 2 A schematic diagram illustrating an exemplary implementation of the system for determining the attribution of the test point in step 106 is shown. See also... Figure 2 The exemplary implementation process of determining the system to which the test point belongs in step 106 may include the following steps 201 to 204: Step 201: Construct a contour region containment tree using all zero contour lines in the target area; Each node of the contour region tree represents a region enclosed by a zero contour line, signifying a continuous region bounded by the zero contour line and having a consistent difference value sign.

[0054] The attributes of contour line nodes can include the sign of the difference value within the region, the area of ​​the region, the location of the region, etc. The sign of the difference value within the region indicates the direction of the pressure gradient in that region.

[0055] The parent-child relationship between nodes in a contour line tree represents a spatial containment relationship, that is, the spatial containment relationship between regions contained by different zero contour lines. For example, if the region represented by node A completely contains the region represented by node B, then node B is a child node of node A. In other words, the zero contour line corresponding to the child node lies inside the closed zero contour line corresponding to the parent node.

[0056] Constructing a contour region containment tree can be achieved using, for example, a high-precision low-edge identification algorithm. This disclosure does not limit the specific method for constructing the contour region containment tree.

[0057] Step 202: Determine the influencing nodes of the point to be measured based on the latitude and longitude of the point and the contour area containment tree, and determine the zero contour line corresponding to the influencing node as the zero contour line to which the point belongs; In this context, an influential node is a node in the contour region containment tree that contains the node to be measured, but none of its child nodes contain the node to be measured. That is, if the node to be measured is contained by a node in the contour region containment tree but not by any of its child nodes, then that node is an influential node of the node to be measured. For example, suppose the contour region containment tree contains a root node and nodes A, B, C, and D. Node A is a child node of the root node, nodes B and D are children of node A, and node C is a child node of node B. If the point to be measured is contained by the root node, node A, and node B, but not by nodes C and node D, then by searching among the root node, node A, and node B for nodes whose child nodes do not contain the point to be measured, we can ultimately determine that node B is an influential node of the point to be measured.

[0058] Step 203: Determine the relevant transition points of the point to be measured based on the latitude and longitude of the point to be measured and the zero contour line to which the point to be measured belongs; Specifically, the distances from the point to be measured to each latitude and longitude coordinate point on its assigned zero-isotropic line are calculated to find the closest point to the point. The orientation of the closest point relative to the point is determined, and all transition points in the vicinity of that orientation portion of the assigned zero-isotropic line are selected as the relevant transition points of the point. For example, the orientation of the closest point relative to the point can be represented by up, down, left, and right, with up and down for latitude and left and right for longitude. Assuming the orientation of the closest point relative to the point is "up," the portion of the assigned isotropic line above the point (i.e., the northern section of the assigned zero-isotropic line) is selected, and all transition points in the vicinity outside this portion of the zero-isotropic line are found. These transition points are the relevant transition points of the point.

[0059] Step 204: Statistically analyze the distribution patterns of all relevant jump points located at the upper edge of the zero contour line of the test point and the lower edge of the zero contour line of the test point to determine the attribution system of the test point.

[0060] Specifically, when the differential value within the region enclosed by the zero-value contour line of the test point is negative, and all relevant transition points located at the upper edge of the zero-value contour line of the test point exhibit a statistical pattern of "more positive transitions at the upper edge and more positive transitions at the lower edge," it can be determined that the test point is located within a low-pressure system. Conversely, when the differential value within the region enclosed by the zero-value contour line of the test point is positive, and all relevant transition points located at the lower edge of the zero-value contour line of the test point exhibit a statistical pattern of "more positive transitions at the upper edge and more negative transitions at the lower edge," it can be determined that the test point is located within a high-pressure system.

[0061] Among them, "upper edge" refers to the part of the zero contour line located north of the point to be measured, "lower edge" refers to the part of the zero contour line located south of the point to be measured, "positive to negative" and "negative to positive" refer to the jump type of the relevant jump point, "more from negative to positive" means that the number of relevant jump points with the jump type "negative to positive" is greater than the number of relevant jump points with the jump type "positive to negative", and "more from positive to negative" means that the number of relevant jump points with the jump type "positive to negative" is greater than the number of relevant jump points with the jump type "negative to positive".

[0062] It should be noted that the specific implementation methods for determining the attribution of a measurement point in practical applications are not limited to those described above. Figure 2 The process shown can also be implemented in any other applicable manner, and this disclosure does not limit the embodiments thereto.

[0063] In practical applications, the measurement points are located within the target area and can be specified in advance. For example, the measurement points could be pre-selected cities within the target area.

[0064] Further, see Figure 2 The method of this disclosure embodiment may further include: step 205, calculating the distance from the point to be measured to its corresponding zero contour line to determine the position of the point to be measured in its corresponding system, thereby further improving the accuracy of weather situation identification at the point to be measured.

[0065] Specifically, the distance from the point to be measured to its corresponding zero contour line is calculated. If the distance from the point to be measured to its corresponding zero contour line is close, the point to be measured is determined to be located at the front of the corresponding system; if the distance from the point to be measured to its corresponding zero contour line is far, the point to be measured is determined to be located at the rear of the corresponding system.

[0066] The pressure distribution inside a high-pressure system typically exhibits a pattern of high pressure at the center and decreasing outwards. If the distance between the measured point and its corresponding zero contour line is close, it is near the boundary, and the measured point is located at the front of the high-pressure system; if the distance between the measured point and its corresponding zero contour line is far, it is far from the boundary, and the measured point is located at the rear of the high-pressure system.

[0067] Low-pressure systems typically have a low central pressure and an increasing external pressure. If the distance between the measured point and its corresponding zero contour line is close, it is near the boundary and located at the front of the low-pressure system; if the distance between the measured point and its corresponding zero contour line is far, it is far from the boundary and located at the rear of the low-pressure system.

[0068] The distance from a measured point to its assigned zero contour line can be determined by comparing the relative distance with a preset relative distance threshold. The relative distance is the ratio of the distance from the measured point to its assigned zero contour line to the system characteristic scale. A relative distance greater than the preset relative distance threshold indicates a closer distance to the assigned zero contour line, while a relative distance less than or equal to the threshold indicates a greater distance. The distance from the measured point to its assigned zero contour line can be calculated using a point-to-curve distance algorithm, and the system characteristic scale refers to the system characteristic scale of the system to which the measured point belongs.

[0069] It should be noted that the specific implementation method for determining the location of the point to be measured in its own system in a specific application is not limited to the implementation method of step 205, and any other applicable method can be used. This disclosure embodiment does not limit this.

[0070] Figure 3 A schematic diagram of the structure of a weather pattern identification device based on high and low pressure provided in an embodiment of this disclosure is shown. See also Figure 3 The weather pattern identification device 300 based on high and low pressure in this embodiment may include: The data acquisition unit 301 is used to acquire the air pressure data matrix of the target area. The air pressure data matrix is ​​gridded data with fixed grid point spacing. The rows of the air pressure data matrix represent latitude and the columns represent longitude. The values ​​of the elements in the air pressure data matrix represent air pressure values. The differential operation unit 302 is used to differentially analyze the pressure data matrix by row to obtain a pressure difference matrix. The rows of the pressure difference matrix represent latitude and the columns represent longitude. The values ​​of the elements in the pressure difference matrix represent the difference values. The difference values ​​indicate the magnitude and direction of the pressure gradient in the north-south direction of the target area. The zero contour line extraction unit 303 is used to extract all zero contour lines of the target area using the pressure difference matrix. The difference value of all latitude and longitude coordinate points on each zero contour line is zero, and the difference value of all points within the area enclosed by each zero contour line has the same sign. The transition point extraction unit 304 is used to extract all transition points in the target area using the pressure difference matrix; Jump point assignment determination unit 305 is used to determine the zero contour line to which each jump point is assigned in all zero contour lines; The unit 306 for determining the attribution of a point to be measured is used to determine the attribution system of the point to be measured based on the latitude and longitude of the point to be measured, all zero contour lines, and the attribution zero contour line of each jump point. The attribution system is either a high-pressure system or a low-pressure system.

[0071] Furthermore, the difference operation unit 302 can be specifically used to perform the following subtraction on each row of all rows except the last row in the pressure data matrix: subtract the next row of the current row in the pressure data matrix from the current row element by element to obtain the difference value of each element in the current row of the pressure difference matrix.

[0072] Furthermore, the weather pattern identification device 300 based on high and low pressure in this embodiment may further include: an edge processing unit 307, which can be used to perform the following edge processing on the pressure difference matrix: add a row of zero values ​​before the first row of the pressure difference matrix, and set the values ​​of the elements in the last row, the first column and the last column of the pressure difference matrix to 0.

[0073] Furthermore, the jump point extraction unit 304 can be specifically used to perform the following processing for each column of the pressure difference matrix: traverse each element of the current column to compare the sign of the difference value of each element with the element of the previous column. If the sign of the difference value of an element is different from that of the element of the previous column, the adjacent element pair formed by the element and the element of the previous column constitutes a jump point. Determine the latitude and longitude of the jump point according to the latitude and longitude coordinates of the adjacent element pair, and determine the jump type of the jump point according to the sign of the difference value of the adjacent element pair.

[0074] Furthermore, the unit 306 for determining the attribution of the point to be measured can be specifically used for: constructing a contour area containment tree using all zero contour lines of the target area, where each node in the contour area containment tree represents an area enclosed by a zero contour line; determining the influencing nodes of the point to be measured based on the latitude and longitude of the point to be measured and the contour area containment tree, and determining the zero contour line corresponding to the influencing node as the attribution zero contour line of the point to be measured. An influencing node is a node in the contour area containment tree that contains the point to be measured but none of its child nodes contain the point to be measured; determining the relevant jump points of the point to be measured based on the latitude and longitude of the point to be measured and the attribution zero contour line of the point to be measured; and statistically analyzing the distribution patterns of all relevant jump points located at the upper edge of the attribution zero contour line of the point to be measured and the distribution patterns of all relevant jump points located at the lower edge of the attribution zero contour line of the point to be measured to determine the attribution system of the point to be measured.

[0075] Furthermore, the unit 306 for determining the attribution of a point to be measured can also be used to: calculate the distance from the point to be measured to its attribution zero contour line to determine the position of the point to be measured in its attribution system.

[0076] Furthermore, the unit 306 for determining the location of the test point can be used to: calculate the distance from the test point to each latitude and longitude coordinate point on its zero contour line to find the closest point to the test point, determine the orientation of the closest point relative to the test point, and select all the jump points in the adjacent area of ​​the orientation part of the zero contour line of the test point as the relevant jump points of the test point.

[0077] In practical applications, the high and low pressure-based weather pattern identification device 300 can be implemented through software, hardware, or a combination of both. For example, the high and low pressure-based weather pattern identification device 300 can be implemented as software running in the electronic device 400 described below.

[0078] In addition, this disclosure also provides a computer-readable storage medium storing a computer program thereon, the program including instructions that, when executed by one or more processors, implement the steps of the aforementioned weather pattern identification method based on high and low pressure.

[0079] Figure 4 A schematic diagram of the structure of an electronic device provided in an embodiment of this disclosure is shown. See also... Figure 4 The electronic device 400 may include one or more processors 401, and a memory 402 storing one or more programs, wherein the programs in the memory are executed by the one or more processors 401 to implement the method flow and / or program units corresponding to each unit in the apparatus shown in the above embodiments of this disclosure.

[0080] Processor 401 may include one or more single-core or multi-core processors. Processor 401 may include any combination of general-purpose processors or special-purpose processors.

[0081] Memory 402 is the computer-readable storage medium provided in this disclosure, which can be used to store non-transitory software programs, non-transitory computer-executable programs, and units, such as those in the embodiments of this disclosure. Figure 1 The program instructions / units corresponding to the weather pattern identification method based on high and low pressure are shown. The processor 501 executes non-transient software programs, instructions, and units stored in the memory 502, thereby performing operations such as those described in the above method embodiments. Figure 1 The program, instructions, and units corresponding to the weather pattern identification method based on high and low pressure are shown.

[0082] See Figure 4 The electronic device 400 may further include a communication component 403, which can be used to communicate with external devices. For example, the aforementioned raw air pressure data can be acquired by the communication component 403. The processor 401, memory 402, and communication component 403 can be connected via a bus or other means. Figure 4 Taking the example of a connection between China and Israel via a bus.

[0083] Furthermore, the electronic device 400 may include any other suitable components, which are not limited by the embodiments disclosed herein.

[0084] The aforementioned programs (also known as software, software applications, or code) include the machine instructions of a programmable processor and can be implemented using object-oriented programming languages, assembly language, or machine language.

[0085] With the development of time and technology, the meaning of "medium" has become increasingly broad. The dissemination of computer programs is no longer limited to tangible media; they can also be downloaded directly from the network. Any combination of one or more computer-readable storage media can be used. Computer-readable storage media can be, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or any combination thereof. More specific examples of computer-readable storage media (a non-exhaustive list) include: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this document, a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, device, or apparatus.

[0086] In a specific implementation, the electronic device 400 can be implemented as a computer, a server, or a cluster thereof. This disclosure does not limit the specific implementation of the electronic device 400.

[0087] The technical solutions provided in this disclosure have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of this disclosure. The descriptions of the embodiments above are only for the purpose of helping to understand the methods and core ideas of this disclosure. Furthermore, those skilled in the art will recognize that, based on the ideas of this disclosure, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this disclosure.

[0088] The above description is merely a preferred embodiment of this disclosure and is not intended to limit this disclosure. Any modifications or equivalent substitutions made within the spirit and principles of this disclosure should be included within the scope of protection of this disclosure.

Claims

1. A weather pattern identification method based on high and low pressure, characterized in that, The method includes: Obtain the air pressure data matrix of the target area. The air pressure data matrix is ​​gridded data with fixed grid point spacing. The rows of the air pressure data matrix represent latitude and the columns represent longitude. The values ​​of the elements in the air pressure data matrix represent air pressure values. The pressure data matrix is ​​obtained by row difference, where rows represent latitude and columns represent longitude. The values ​​of the elements in the pressure difference matrix are difference values, which indicate the magnitude and direction of the pressure gradient in the north-south direction of the target area. The pressure difference matrix is ​​used to extract all zero contour lines of the target area. The difference value of all latitude and longitude coordinate points on each zero contour line is zero, and the difference value of all points within the area enclosed by each zero contour line has the same sign. All transition points in the target area are extracted using the aforementioned pressure difference matrix; Determine the zero contour line to which each of the aforementioned transition points belongs in all zero contour lines; The system to which the test point belongs is determined based on the latitude and longitude of the test point, all zero contour lines, and the zero contour line to which each jump point belongs. The system to which the test point belongs is either a high-pressure system or a low-pressure system.

2. The method according to claim 1, characterized in that, The pressure data matrix is ​​differentially analyzed by row to obtain a pressure difference matrix, including: For all rows in the pressure data matrix except the last row, perform the following subtraction: subtract the next row of the current row from the current row of the pressure data matrix element by element to obtain the difference value of each element in the current row of the pressure difference matrix.

3. The method according to claim 1, characterized in that, The method further includes: Before extracting all zero contour lines of the target area using the pressure difference matrix, the pressure difference matrix is ​​subjected to the following edge processing: a zero value is added before the first row of the pressure difference matrix, and the elements of the last row, first column, and last column of the pressure difference matrix are set to 0.

4. The method according to claim 1, characterized in that, The step of extracting all transition points in the target region using the pressure difference matrix includes: For each column of the pressure difference matrix, the following processing is performed: traverse each element of the current column and compare the sign of the difference value of each element with the element of the previous column. If the sign of the difference value of an element is different from that of the element of the previous column, the adjacent element pair formed by the element and the element of the previous column constitutes a jump point. Determine the latitude and longitude of the jump point according to the latitude and longitude coordinates of the adjacent element pair, and determine the jump type of the jump point according to the sign of the difference value of the adjacent element pair.

5. The method according to claim 1, characterized in that, The system for determining the attribution of a point to be measured based on its latitude and longitude, all zero contour lines, and the attribution zero contour line for each transition point includes: A contour region containment tree is constructed using all zero contour lines of the target region, where each node in the contour region containment tree represents a region enclosed by one of the zero contour lines; Based on the latitude and longitude of the point to be measured and the contour area containment tree, the influence nodes of the point to be measured are determined, and the zero contour line corresponding to the influence node is determined as the zero contour line to which the point to be measured belongs. The influence node is a node in the contour area containment tree that contains the point to be measured but none of its child nodes contain the point to be measured. The relevant transition points of the test point are determined based on the latitude and longitude of the test point and the zero contour line of the test point. The distribution patterns of all relevant transition points located at the upper edge of the zero contour line of the test point and the distribution patterns of all relevant transition points located at the lower edge of the zero contour line of the test point are statistically analyzed to determine the attribution system of the test point.

6. The method according to claim 5, characterized in that, The method further includes: calculating the distance from the point to be measured to its corresponding zero contour line to determine the position of the point to be measured in its system of reference.

7. The method according to claim 5, characterized in that, The step of determining the relevant transition points of the test point based on the latitude and longitude of the test point and its zero-homogeneity contour line includes: calculating the distance from the test point to each latitude and longitude coordinate point on its zero-homogeneity contour line to find the closest point of the test point, determining the orientation of the closest point relative to the test point, and selecting all transition points in the adjacent area of ​​the orientation portion of the zero-homogeneity contour line of the test point as the relevant transition points of the test point.

8. A weather pattern identification device based on high and low pressure, characterized in that, The weather pattern identification device based on high and low pressure includes: The data acquisition unit is used to acquire the air pressure data matrix of the target area. The air pressure data matrix is ​​gridded data with fixed grid point spacing. The rows of the air pressure data matrix represent latitude and the columns represent longitude. The values ​​of the elements in the air pressure data matrix represent air pressure values. The differential operation unit is used to perform row-wise differential operations on the pressure data matrix to obtain a pressure differential matrix. The rows of the pressure differential matrix represent latitude and the columns represent longitude. The values ​​of the elements in the pressure differential matrix represent differential values, and the differential values ​​indicate the magnitude and direction of the pressure gradient in the north-south direction of the target area. The zero contour line extraction unit is used to extract all zero contour lines of the target area using the pressure difference matrix. The difference value of all latitude and longitude coordinate points on each zero contour line is zero, and the difference value of all points within the area enclosed by each zero contour line has the same sign. A transition point extraction unit is used to extract all transition points in the target area using the pressure difference matrix. A jump point assignment determination unit is used to determine the zero contour line to which each jump point is assigned in all zero contour lines; The unit for determining the attribution of a point to be measured is used to determine the attribution system of the point to be measured based on the latitude and longitude of the point to be measured, all zero contour lines, and the attribution zero contour line of each of the jump points. The attribution system is either a high-pressure system or a low-pressure system.

9. An electronic device, characterized in that, include: A memory for storing one or more processors and programs, the programs comprising instructions that, when executed by the processor, cause the processor to perform the method as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a program, the program comprising instructions that, when executed by one or more processors, cause the processors to perform the method as described in any one of claims 1 to 7.

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