CN112131958B - Method for automatically identifying southwest low vortex - Google Patents

Method for automatically identifying southwest low vortex Download PDF

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CN112131958B
CN112131958B CN202010882801.0A CN202010882801A CN112131958B CN 112131958 B CN112131958 B CN 112131958B CN 202010882801 A CN202010882801 A CN 202010882801A CN 112131958 B CN112131958 B CN 112131958B
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low vortex
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胡文东
舒红平
贾净翔
丁禹钦
肖天贵
邵建
张莹
罗飞
王亚强
赵卓宁
徐文嘉
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Chengdu University of Information Technology
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Abstract

The invention provides a method for automatically identifying southwest low vortex, belonging to the technical field of weather. According to the method, potential height field data is utilized, parameters are firstly set, then color gamut space projection processing is carried out on grid points, color gradations with different colors are given to data points of different levels, southwest low vortexes are identified, and finally element statistics is carried out on the southwest low vortexes, so that the position of the southwest low vortexes is obtained. Through the design, the southwest low vortex is automatically identified in the high-altitude isobaric surface, the key characteristics of the southwest low vortex are analyzed by using a digital image method, the defects and shortcomings of an isoline method are avoided, the analysis efficiency is improved, and the method contributes to disaster prevention and reduction work in areas with most developed economy and most dense population in southwest and eastern China.

Description

Method for automatically identifying southwest low vortex
Technical Field
The invention belongs to the technical field of weather, and particularly relates to a method for automatically identifying southwest low vortex.
Background
The southwest low vortex is generated under the special environment and certain circulation condition of the Qinghai-Tibet plateau on 700hPa or 850hPa pressure surface in southwest area of China with closed small low pressure of cyclone circulation. The diameter of the steel plate is generally 300-500 km. The southwest low vortex has one group or at least one contour line in a low-value area of a potential height field closed contour line, and the numerical value is higher than the numerical value and the numerical value is lower than the numerical value. In this region, the innermost contour is the core region, and the outermost contour tends to represent the range of the southwest low vortices. Potential height field analysis is commonly used in meteorological operations to determine low vortices in the air.
The southwest low vortex plays a very important role in the weather system influencing precipitation in China. In terms of the intensity, frequency and range of rainstorm weather caused by southwest low vortex, the intensity, frequency and range are second to typhoon, and many extraordinary flood disasters which are rare in history of China are closely related to southwest low vortex activities. Some rainy weather may be produced when the southwest low vortex is at the source. When the low vortex moves out of the source east in the southwest, the low vortex is often developed and combined with downstream weather systems such as the shear of the river and the Huai river, and the low vortex often brings strong precipitation weather to downstream economically developed areas (such as Chongqing, Hubei, Jiangsu, Zhejiang, Shanghai and the like), so that serious flood disasters and serious losses are caused. Therefore, the method can accurately identify the low vortexes in the southwest region, and has important significance for weather analysis, diagnosis and forecast in China.
Until now, the method for analyzing the low vortex in southwest of the weather business is still operated manually by forecasters according to self experiences in a man-machine interaction mode, and a series of related defects of strong subjectivity and low analysis efficiency from person to person exist.
Disclosure of Invention
Aiming at the defects in the prior art, the method for automatically identifying the southwest low vortex can automatically identify the southwest low vortex in the high-altitude isobaric surface, analyzes the key characteristics of the southwest low vortex by using a digital image method, avoids the defects and shortcomings of an isoline method, improves the analysis efficiency, and makes contribution to disaster prevention and reduction work in areas with most developed economy and most dense population in southwest and eastern China.
In order to achieve the above purpose, the invention adopts the technical scheme that:
the scheme provides a method for automatically identifying the low vortex in southwest, which comprises the following steps:
s1, reading potential height field data;
s2, respectively setting a gradient interval, a southwest low vortex identification area and an auxiliary identification area according to the potential height field data, traversing the identification areas to respectively find a minimum potential height value and a maximum potential height value, and rounding the minimum potential height value and the maximum potential height value according to the gradient interval;
s3, traversing all data points in the identification area and the auxiliary identification area, generating n potential height levels according to different data points, and endowing the data points of the same level with the same color level;
s4, judging whether the potential height level n in the identification area is larger than 1, if so, determining that the potential height levels are multiple potential height levels and have southwest low vortexes, and entering the step S5, otherwise, determining that the potential height levels are 1 potential height level and have no southwest low vortexes, and completing automatic identification of the southwest low vortexes;
s5, the difference is smaller than the maximum value C of the color gradationmaxAs a recognition target Ctarget；
S6, distinguishing a plurality of southwest low vortexes and eliminating plateau vortexes;
s7, judging the identification target C for the color rank in the identification area according to the distinguishing resulttargetWhether the identification target exists on the boundary of the identification area or not is judged, if yes, the identification target is closed southwest low vortex, and the step S9 is carried out, and if not, the step S8 is carried out;
s8, counting the number N of data points in the southwest low vortex in the identification area and the auxiliary identification areainAnd NoutAnd determining NoutAnd NinIs less than the threshold, if so, the recognition target isClosing the southwest low vortex, and proceeding to step S9, otherwise, the identification target is non-southwest low vortex, and completing automatic identification of southwest low vortex, wherein N isinIndicating the number of data points located in the identified region, NoutRepresenting the number of data points located in the auxiliary identification area;
s9, calculating the area of the southwest low vortex by using the map magnification coefficient, and eliminating the southwest low vortex with the area smaller than the threshold value;
s10, according to the area of the removed southwest low vortexes, finding the lowest potential height point in each southwest low vortexes, using the lowest potential height point as the geometric center of the southwest low vortexes, and judging the source place of the southwest low vortexes according to the geometric center of the low vortexes to finish automatic identification of the southwest low vortexes.
Further, the expression for rounding the minimum and maximum potential height values in step S2 is as follows:
Figure BDA0002654576290000031
wherein h isminRepresents the minimum potential height value, Math. floor (. cndot.) represents rounding-down, Math. ceil (. cndot.) represents rounding-up, hmaxRepresenting the maximum potential height value and int erval the gradient interval.
Still further, the expression of the n potential height levels generated in the step S3 is as follows:
n＝(hmax-hmin)/int erval
where n denotes the number of potential height levels, hmaxRepresents the maximum potential height value, hminRepresenting the minimum potential height value and int erval the gradient interval.
Still further, the expression of the tone scale in step S3 is as follows:
Figure BDA0002654576290000032
wherein, C[i,j]Representing the tone scale, h, of each data point[i,j]Representing potential height field data, Math. floor (. cndot.) represents rounding down, hminRepresenting the minimum potential height value.
Still further, the step S6 includes the steps of:
s601, traversing data points in the identification area and the auxiliary identification area, recording num for recording the number of the low vortex in southwest, setting num to be 1, and recording T[i,j]Judging whether each data point has been analyzed for a judgment value used for judging whether each data point has been analyzed, identifying the number of the low vortex in southwest to which the data point belongs, and setting the initial judgment value T of the identification area and the auxiliary identification area[i,j]＝0；
S602, selecting a data point [ i ] of the west most side in the southwest low vortex data point setwest,jwest]And make an order
Figure BDA0002654576290000043
The southwest low vortex number num is propagated as a starting point, wherein,
Figure BDA0002654576290000044
a decision value representing the most west data point;
s603, spreading the number num of the southwest low vortex to each data point of the southwest low vortex, and calculating the number num of the southwest low vortex
Figure BDA0002654576290000045
The data point of (A) is taken as the center, and whether adjacent points have C or not is judged[i,j]＝Ctarget∧T[i,j]If 0, let T of the neighboring data point around[i,j]Num, and repeat step S603 up to T[i,j]Is no longer increased and proceeds to step S604, otherwise, the data point is skipped and proceeds to step S604, where C is[i,j]Representing the colour level, T[i,j]Represents a judgment value, CtargetRepresenting a recognition target;
s604, judging whether T exists or not[i,j]If yes, adding 1 to the total number of the southwest low vortex numbers num, and returning to step S602, otherwise, proceeding to step S605;
s605, judgmentJudging whether a data point C exists on the outer boundary of the auxiliary identification area[i,j]＝Ctarget∧T[i,j]Not equal to 0, the data points have the same low vortex number num, if yes, the data points are plateau vortexes, the plateau vortexes are eliminated, and the judgment value T of the data point set is made[i,j]And (5) when the low vortex number num is 0, subtracting 1 from the low vortex number num, reordering the low vortex number num, giving a southwest low vortex data point set, completing the distinguishing and identification of a plurality of southwest low vortexes, and entering the step S7, otherwise, indicating that no plateau vortex exists, and entering the step S7.
Still further, the expression of the southwest low vortex area in step S9 is as follows:
Figure BDA0002654576290000041
N＝Nout+Nin
Figure BDA0002654576290000042
Figure BDA0002654576290000051
wherein S represents the area of the southwest low vortex, N represents the data point in the southwest low vortex, SiIndicates the area occupied by the ith grid point,
Figure BDA0002654576290000052
the dimensions of the standard are represented such that,
Figure BDA0002654576290000053
indicates latitude, rlonIndicating the weft distance, rlatDenotes the meridional distance, NinIndicating the number of data points located in the identified region, NoutRepresenting the number of data points located in the auxiliary identification area, m representing the lead-in map magnification factor, L representing the distance on the mapping plane, LsRepresenting the corresponding distance on the earth's surface.
Still further, the longitude and latitude expression of the geometric center in step S10 is as follows:
Figure BDA0002654576290000054
wherein (O)x,Oy) Representing latitude and longitude of the geometric center of the southwest low vortex, d representing the potential height minimum point, OxiLongitude, O, representing the lowest point of the potential altitudeyiThe latitude of the lowest point of the potential altitude is represented, and i represents the number of lattice points.
The invention has the beneficial effects that:
(1) according to the method, potential height field data is utilized, parameters are firstly set, then color gamut space projection processing is carried out on grid points, color gradations with different colors are given to data points of different levels, southwest low vortexes are identified, and finally element statistics is carried out on the southwest low vortexes, so that the position of the southwest low vortexes is obtained. Through the design, the southwest low vortex is automatically identified in the high-altitude isobaric surface, the key characteristics of the southwest low vortex are analyzed by using a digital image method, the defects and shortcomings of an isoline method are avoided, the analysis efficiency is improved, and the method contributes to disaster prevention and reduction work in areas with most developed economy and most dense population in southwest and eastern China.
(2) The contour line generation needs to be subjected to a large amount of processing such as calculation and judgment, and in order to perform southwest low vortex recognition quickly and efficiently, the color gamut space projection processing is performed on the data points, so that the analysis efficiency can be greatly improved.
(3) In the southwest low vortex system, weather in different areas of the southwest low vortex may have large differences, so that the analysis of the range and the geometric center of the southwest low vortex has important significance for the diagnosis and analysis of the weather system.
Drawings
FIG. 1 is a flow chart of the method of the present invention.
Fig. 2 is a contour map of the 700hPa potential height field in this example.
Fig. 3 is a projection diagram of 700hPa potential height field gamut space in this embodiment.
Fig. 4 is a schematic diagram of the recognition area and the auxiliary recognition area in this embodiment.
Fig. 5 is a schematic diagram of the color gamut space projection in the present embodiment.
Fig. 6 is a schematic diagram of the high primary vortex in this embodiment.
Fig. 7 is a schematic diagram illustrating different low vortices being analyzed and determined in the present embodiment.
Fig. 8 is a schematic diagram of quasi-closed and closed southwest low vortex in the present embodiment.
Fig. 9 shows the low vortex without the weather effect in this embodiment.
Fig. 10 is a schematic view of the positioning of the geometric center of the southwest low vortex in the present embodiment.
Fig. 11 is a diagram of an example of identification of the south-west low vortexes in this embodiment.
Detailed Description
The following description of the embodiments of the present invention is provided to facilitate the understanding of the present invention by those skilled in the art, but it should be understood that the present invention is not limited to the scope of the embodiments, and it will be apparent to those skilled in the art that various changes may be made without departing from the spirit and scope of the invention as defined and defined in the appended claims, and all matters produced by the invention using the inventive concept are protected.
Examples
As shown in fig. 1, the present invention provides a method for automatically identifying low vortexes in southwest, which is implemented as follows:
s1, reading potential height field data;
in this embodiment, the potential height data h is read[i,j]，[i,j]Representing the position of the data point in the data.
S2, respectively setting a gradient interval, a southwest low vortex identification area and an auxiliary identification area according to the potential height field data, traversing the identification areas to respectively find a minimum potential height value and a maximum potential height value, and rounding the minimum potential height value and the maximum potential height value according to the gradient interval;
in the embodiment, the low vortex has a group or at least one contour in a low-value area of the potential height field closed contour, and the value is higher than the value and lower than the value. Fig. 2 is a potential height contour map, in which a 700hPa potential height field contour map. The smooth curve is an isoline, the numerical value is the potential height, and the unit is gpm; the dotted line frame is the identification region of the southwest low vortex (26 ° N-34.5 ° N, 97 ° E-108.5 ° E), D is the geometric center of the southwest low vortex, the bottom map is the provincial map of southwest china, fig. 3 is a potential height color gamut space projection map, in which a potential height field color gamut space projection map of 700hPa is shown. The deeper the color, the lower the potential height, and D represents the geometric center of the southwest low vortex; the area within the dashed box is the identified region of southwest low vortices (26 ° N-34.5 ° N, 97 ° E-108.5 ° E). A contour is a line made up of points of equal value in a two-dimensional data field, which cannot appear inside the mean field, but can only be analyzed at its outer boundary. The contours do not intersect nor diverge. The contour line realization steps comprise: searching the starting point of the contour line, tracking the contour line, judging the open contour line and the closed contour line, smoothing the contour line and the like. The gamut space projection is generated from a set of grid data points, each of which is assigned a color rank to form a color map about the data point. There are no complicated steps such as connection judgment, smoothing and the like, thereby saving a large amount of time. Through multiple tests, the time consumed by the generation of the contour line is 0.011s more than that of the spatial projection of the color domain by using the same data, and about 87% of time is saved.
In this embodiment, the potential height field data is used to set parameters:
(1) a data interval is specified. In meteorological operations, the interval of the contour is 40gpm (potential height meter), i.e., the value of the potential height contour is a multiple of 40. The purpose is to standardize the hierarchy interval to ensure that the hierarchy interval accords with the meteorological service standard; if not processed, it may happen that the values between the inter levels are not integer multiples of the interval.
(2) An identification area and an auxiliary identification area are set. The southwest low vortex has two main source regions: firstly, in the nine-dragon, pond, kang ding, and ducheng zone (28 ° N-32 ° N,99 ° E-102 ° E), the nine-dragon vortex is abbreviated as nine-dragon vortex, in the nine-dragon vortex source region, an isolated high-frequency center of the beginning of the southwest low vortex, which is called a Xiaojin generation region, in order to prevent missing in the identification process: firstly, the identification region of the low vortex in the southwest is positioned in the whole Sichuan province (26-34.5 degrees N and 97-108.5 degrees E); secondly, in the identification process, southwest low vortexes which are not completely developed or partially move out of the identification area exist, the southwest low vortexes are expanded by 500km from four directions of the boundary of the identification area according to the scale of the southwest low vortexes, and the area between the boundary formed by the southwest low vortexes and the identification boundary is marked as an auxiliary identification area (as shown in fig. 4).
(3) And (6) rounding the extreme value. Traversing the lattice point data to find the minimum and maximum potential height values hminAnd hmax(ii) a Rounding it, and ordering:
Figure BDA0002654576290000081
wherein h isminRepresents the minimum potential height value, Math. floor (. cndot.) represents rounding-down, Math. ceil (. cndot.) represents rounding-up, hmaxRepresenting the maximum potential height value and int erval the gradient interval.
S3, traversing all data points in the identification area and the auxiliary identification area, generating n potential height levels according to different data points, and endowing the data points of the same level with the same color level;
in this embodiment, a large amount of processing such as calculation and judgment is required to generate the contour line, and in order to perform southwest low-vortex recognition quickly and efficiently, the analysis efficiency can be greatly improved by performing color gamut space projection processing on the data points. Firstly, traversing all data points in the identification area of the low vortex in southwest and the auxiliary identification area, giving different color levels to the data points according to the potential heights of the data points, and generating a color gamut space projection, as shown in fig. 5, fig. 5 is a color gamut space projection schematic diagram, which specifically comprises: in order to improve the analysis efficiency, the isoline is avoided being used for identification. According to the difference of the potential heights, giving a color level C to each potential height data point in the identification area; and according to:
n＝(hmax-hmin)/int erval
generating n levels, and assigning the same level to the same color level C, wherein:
Figure BDA0002654576290000091
wherein n represents the number of potential height levels, C represents the color level, and the lower the potential height, the smaller the color level C, the difference between levels. By projection relations, the gamut projection map composed of the color levels is equivalent to a contour map, the boundary lines between the color levels are equivalent to contour lines, and the areas contained in the contour lines are replaced by projections composed of the color levels.
S4, judging whether the potential height level n in the identification area is larger than 1, if so, determining that the potential height levels are multiple potential height levels and have southwest low vortexes, and entering the step S5, otherwise, determining that the potential height levels are 1 potential height level and have no southwest low vortexes, and completing automatic identification of the southwest low vortexes;
in this embodiment, in the identification area, it is determined whether or not the hierarchy n exists: if n >1 exists, the southwest low vortex possibly exists in the identification area, and further analysis is needed; and conversely, the southwest low vortex does not exist in the identification area.
S5, the color level will be smaller than the maximum value C in the identification differencemaxAs a recognition target Ctarget。
In the present embodiment, in the recognition area, the data point set smaller than the maximum value Cmax is regarded as the recognition target and is denoted as Ctarget. The southwest low vortex appears as a single or multiple color regions in the gamut projection of the tone scale.
S6, distinguishing a plurality of southwest low vortexes and eliminating plateau vortexes, wherein the method comprises the following steps:
s601, traversing data points in the identification area and the auxiliary identification area, recording num for recording the number of the low vortex in southwest, setting num to be 1, and recording T[i,j]For judging value, judging whether each data point has been analyzed, identifying the number of the low vortex in southwest of the data point, and making the initial judgment value T of the identification region and the auxiliary identification region[i,j]＝0；
S602, selecting the southwest low vortexThe most west data point [ i ] in the data point setwest,jwest]And make an order
Figure BDA0002654576290000101
The southwest low vortex number num is propagated as a starting point, wherein,
Figure BDA0002654576290000102
a decision value representing the most west data point;
s603, spreading the number num of the southwest low vortex to each data point of the southwest low vortex, and calculating the number num of the southwest low vortex
Figure BDA0002654576290000103
The data point of (A) is taken as the center, and whether adjacent points have C or not is judged[i,j]＝Ctarget∧T[i,j]If 0, let T of the neighboring data point around[i,j]Num, and repeat step S603 up to T[i,j]Is no longer increased and proceeds to step S604, otherwise, the data point is skipped and proceeds to step S604, where C is[i,j]Representing the tone scale, T[i,j]Represents a judgment value, CtargetRepresenting a recognition target;
s604, judging whether T exists or not[i,j]If yes, adding 1 to the total number of the southwest low vortex numbers num, and returning to step S602, otherwise, proceeding to step S605;
s605, judging whether a data point C exists on the outer boundary of the auxiliary identification area[i,j]＝Ctarget∧T[i,j]Not equal to 0, the data points have the same low vortex number num, if yes, the data points are plateau vortexes, the plateau vortexes are eliminated, and the judgment value T of the data point set is made[i,j]And (4) when the number num of the low vortex is 0, subtracting 1 from the number num of the low vortex, reordering the number num of the low vortex, giving a southwest low vortex data point set, finishing distinguishing and identifying a plurality of southwest low vortices, and entering the step S7, otherwise, indicating that no plateau vortex exists, and entering the step S7.
In this embodiment, some plateau vortexes may enter the identification region or the auxiliary identification region when moving east, and in order to distinguish the plateau low vortexes from southwest low vortexes, the plateau low vortexes should just enter the auxiliary identification regionThe low vortices of (a) are rejected. If there is a data point C on the outer boundary of the auxiliary identification area[i,j]＝Ctarget∧T[i,j]Not equal to 0, and the data points have the same low vortex number num, let T of the point set[i,j](ii) 0, low vortex number num minus 1, reordering low vortex number num, assigning T to the southwest low vortex data point set[i,j]As shown in fig. 6, in the drawing, D1 is a southwest low vortex, D2 is a plateau vortex, a range of an inner ring dotted line is an identification region, and a range between an outer ring dotted line and an inner ring dotted line is an auxiliary identification region; and (5) assisting in removing plateau vortexes in the identification region.
In this embodiment, FIG. 7(a) shows the propagation initiation, black dots
Figure BDA0002654576290000104
The circle is T[i,j]Data point of 0, x point non-recognition target, data point
Figure BDA0002654576290000105
Propagating num to the surrounding data points, the T of the adjacent data points[i,j]Num is given. FIG. 7(b) is a propagation process, where data points are given num and then continue to propagate num to surrounding data points, where the circle is T[i,j]The data points are 0, the x points are not the recognition target, and num is obtained from the data points in four weeks at the same time of continuously spreading num outwards; when a southwest low vortex boundary is encountered, num stops propagating towards the direction, fig. 7(c) is a propagation process, and a black dot is T[i,j]Num data points, circle T[i,j]The data points are 0, the x points are not the identification target, no adjacent points can be spread around the black dots, the data points in the range belong to the same southwest low vortex (the number of the low vortex num is 1, the data points in the whole southwest low vortex range all acquire num, the southwest low vortex can not be spread, and T is the number of the data points in the southwest low vortex, and the number of the data points in the range is not larger than the number of the data points in the southwest low vortex, so that the data points in the southwest low vortex can not be spread[i,j]The data points for num belong to the same southwest low vortex, num 1, fig. 7(d) is the propagation process, num is increased by 1, and the gray dots are T[i,j]Data point of num (num 2) and circle T[i,j]A data point of 0, a black dot is a southwest low vortex of num 1, and x points are not recognition targets; starting from the gray dot and surrounding adjacent data pointsAnd spreading num, which is 2 at this time, starting from the gray circle point and spreading num to the adjacent data points at the periphery. Fig. 7e ends the propagation, the black dots are southwest low vortexes with num ═ 1, the gray dots are southwest low vortexes with num ═ 2, and x dots are not identified targets; when the propagation is finished, all recognition targets are distinguished, the propagation of another southwest low vortex is also finished, and at the moment, two low vortex data point sets existing in the region are distinguished by num and stored in T[i,j]In (1).
S7, judging the identification target C for the color rank in the identification area according to the distinguishing resulttargetWhether the identification target exists on the boundary of the identification area or not is judged, if yes, the identification target is closed southwest low vortex, and the step S9 is carried out, and if not, the step S8 is carried out;
s8, counting the number N of data points in the southwest low vortex in the identification area and the auxiliary identification areainAnd NoutAnd determining NoutAnd NinIf the ratio P is smaller than the threshold value, the identification target is closed southwest low vortex, and the step S9 is carried out, otherwise, the identification target is non-southwest low vortex, and the automatic identification of the southwest low vortex is completed;
in the present embodiment, as shown in fig. 8, in the potential height field after the color gamut space projection, the southwest low vortex is classified into two types in the identification region: quasi-closed and closed. When the southwest low eddy is identified, if the low potential height color gamut space projection point of the same level is within the identification area range and is not on the identification boundary (D2 in FIG. 8), the color gamut space projection area is determined to be the southwest low eddy area; if the projection point of the low-potential height color gamut space at the same level is within the identification range and the data point is on the identification boundary (D1 in fig. 8), the projection area of the color gamut space is determined as the area to be determined. The judging step is as follows:
in this embodiment, the threshold is set to 5, and the numbers Nin and Nout of data points located in the identification region and the auxiliary identification region in the quasi-closed southwest low vortex are counted respectively. The ratio P of Nout to Nin is calculated. If P < 5: determining the quasi-closed southwest low vortex as a southwest low vortex region; on the contrary, the region is not the southwest low vortex region. The P value of D1 in fig. 6 is less than 5, so D1 is also a southwestern low vortex.
S9, calculating by using a map magnification coefficient to obtain the area of the southwest low vortex, and eliminating the southwest low vortex with the area smaller than a threshold value;
s10, according to the area of the removed southwest low vortexes, finding the lowest potential height point in each southwest low vortexes, using the lowest potential height point as the geometric center of the southwest low vortexes, and judging the source place of the southwest low vortexes according to the geometric center of the low vortexes to finish automatic identification of the southwest low vortexes.
In this embodiment, in the southwest low vortex system, there may be great differences in weather in different areas of the southwest low vortex, so analyzing the range and the geometric center of the southwest low vortex has important significance for the diagnostic analysis of the weather system.
In this embodiment, first, the data point N ═ N in the southwest low vortex is countedout+NinThe distances between the grid points are then looked up, due to the distance L on the image plane and the corresponding distance L on the earth's surfacesOftentimes not equal, to scale both, a map magnification factor m is introduced:
Figure BDA0002654576290000121
Figure BDA0002654576290000122
the converted latitudinal distance between data points is
Figure BDA0002654576290000131
A warp direction distance of
Figure BDA0002654576290000132
Area occupied by each lattice point
Figure BDA0002654576290000133
Finally calculating the area of the low vortex in the southwest
Figure BDA0002654576290000134
Sometimes, the pressure is increasedThe potential height of a single data point is lower than that of surrounding data points, a small low vortex is presented on the projection diagram, but the low vortex without obvious weather significance is eliminated because the horizontal scale of the low vortex in southwest is 300km-500 km. If: s is less than or equal to 2500km2The set of data points is culled from the southwest low vortex.
In this embodiment, the threshold is 2500km2As shown in FIG. 9, D1 is the southwest low vortex, D2 is the area less than 2500km2The area between the white dotted lines of the inner ring and the outer ring is an auxiliary identification area, and D2 is removed.
In this embodiment, each data point in the southwest low vortex level is traversed to find a point having the lowest potential height, which is defined as the center O of the southwest low vortex. If d potential height minimum value points (d is more than or equal to 2) exist, the average value of the longitude and latitude of the points is calculated, the result is determined as the geometrical center O of the low vortex in the southwest, and the longitude and latitude are (O)x,Oy)。
Figure BDA0002654576290000135
And then judging the source of the southwest low vortex by using the position of the geometric center of the low vortex.
The main sources of the southwest low vortex are two, namely the nine-dragon vortex located in one area of Jiulong, Barbang, Kangding and Decheng (28 degrees N-32 degrees N,99 degrees E-102 degrees E), and the nine-dragon vortex located in the Sichuan basin area (30 degrees N-33 degrees N,103 degrees E-105.5 degrees E). Using longitude and latitude (O) of the geometric centre of low vortexx,Oy) Judging the source, if:
28°N≤Ox≤32°N∧99°E≤Oy≤102°E
the source of the southwest low vortex is determined to be the jiulong area.
If:
30°N≤Ox≤33°N∧103°E≤Oy≤105.5°E
the source of the southwest low vortex is determined to be the Sichuan basin.
If the southwest low vortex is not generated in the jiulong region or the sichuan basin, the source of the southwest low vortex is determined to be other regions of the Sichuan, in fig. 10, the black region is the southwest low vortex, the white lattice points are two data points with the lowest potential height, the white X-character is the center of the southwest low vortex, the numerical value is the average value of the longitude and latitude of the white lattice points, the black dotted line range of the inner ring is the low vortex identification region, and the region between the outer ring and the black dotted line of the inner ring is the auxiliary identification region.
In this embodiment, as shown in fig. 11, the black area in fig. 11 is a southwest low vortex, the white dot in the southwest low vortex is a geometric center O of the southwest low vortex, and is generated in a nine-dragon region, the black dotted line range of the inner ring is a low vortex identification area, and the area between the black dotted lines of the outer ring and the inner ring is an auxiliary identification area.
Through the design, the southwest low vortex is automatically identified in the high-altitude isobaric surface, the key characteristics of the southwest low vortex are analyzed by using a digital image method, the defects and shortcomings of an isoline method are avoided, the analysis efficiency is improved, and the method contributes to disaster prevention and reduction work in areas with most developed economy and most dense population in southwest and eastern China.

Claims (7)

1. A method for automatically identifying southwest low vortex is characterized by comprising the following steps:
s1, reading potential height field data;
s2, respectively setting a gradient interval, a southwest low vortex identification area and an auxiliary identification area according to the potential height field data, traversing the identification areas to respectively find a minimum potential height value and a maximum potential height value, and rounding the minimum potential height value and the maximum potential height value according to the gradient interval;
s3, traversing all data points in the identification area and the auxiliary identification area, generating n potential height levels according to different data points, and endowing the data points of the same level with the same color level;
s4, judging whether the potential height level n in the identification area is larger than 1, if so, determining that the potential height levels are multiple potential height levels and have southwest low vortexes, and entering the step S5, otherwise, determining that the potential height levels are 1 potential height level and have no southwest low vortexes, and completing automatic identification of the southwest low vortexes;
s5, the difference is smaller than the maximum value C of the color gradationmaxAs a recognition target Ctarget；
S6, distinguishing a plurality of southwest low vortexes and eliminating plateau vortexes;
s7, judging the identification target C for the color rank in the identification area according to the distinguishing resulttargetWhether the identification target exists on the boundary of the identification area or not is judged, if yes, the identification target is closed southwest low vortex, and the step S9 is carried out, and if not, the step S8 is carried out;
s8, counting the number N of data points in the southwest low vortex in the identification area and the auxiliary identification areainAnd NoutAnd determining NoutAnd NinIf the ratio P is smaller than the threshold value, the identification target is closed southwest low vortex, and the step S9 is performed, otherwise, the identification target is non-southwest low vortex, and the automatic identification of southwest low vortex is completed, wherein N isinIndicating the number of data points located in the identified region, NoutRepresenting the number of data points located in the auxiliary identification area;
s9, calculating the area of the southwest low vortex by using the map magnification coefficient, and eliminating the southwest low vortex with the area smaller than the threshold value;
s10, according to the area of the removed southwest low vortexes, finding the lowest potential height point in each southwest low vortexes, using the lowest potential height point as the geometric center of the southwest low vortexes, and judging the source place of the southwest low vortexes according to the geometric center of the low vortexes to finish automatic identification of the southwest low vortexes.
2. The method for automatically identifying southwest low vortex as claimed in claim 1, wherein the expression of the rounding process for the minimum and maximum potential height values in step S2 is as follows:
Figure FDA0002654576280000021
wherein h isminMath. floor (. cndot.) table showing the minimum potential height valueTail (-) means round up, hmaxRepresents the maximum potential height value and interval represents the gradient interval.
3. The method for automatically identifying southwest low vortex as claimed in claim 1, wherein the expression of n potential height levels generated in step S3 is as follows:
n＝(hmax-hmin)/interval
where n denotes the number of potential height levels, hmaxRepresents the maximum potential height value, hminThe minimum potential height value is indicated and interval indicates the gradient interval.
4. The method for automatically identifying southwest low vortex as claimed in claim 1, wherein the expression of the tone scale in step S3 is as follows:
Figure FDA0002654576280000022
wherein, C[i,j]Representing the tone scale, h, of each data point[i,j]Representing potential height field data, Math. floor (. cndot.) represents rounding down, hminRepresenting the minimum potential height value.
5. The method for automatically identifying southwest low vortex as claimed in claim 1, wherein the step S6 comprises the steps of:
s601, traversing data points in the identification area and the auxiliary identification area, recording num for recording the number of the low vortex in southwest, setting num to be 1, and recording T[i,j]Judging whether each data point has been analyzed for a judgment value used for judging whether each data point has been analyzed, identifying the number of the low vortex in southwest to which the data point belongs, and setting the initial judgment value T of the identification area and the auxiliary identification area[i,j]＝0；
S602, selecting a data point [ i ] of the west most side in the southwest low vortex data point setwest,jwest]And make an order
Figure FDA0002654576280000031
The southwest low vortex number num is propagated as a starting point, wherein,
Figure FDA0002654576280000032
a decision value representing the west-most data point;
s603, spreading the number num of the southwest low vortex to each data point of the southwest low vortex, and calculating the number num of the southwest low vortex
Figure FDA0002654576280000033
The data point of (A) is taken as the center, and whether adjacent points have C or not is judged[i,j]＝Ctarget∧T[i,j]If 0, let T of the neighboring data point around[i,j]Num, and repeat step S603 until T[i,j]Is no longer increased and proceeds to step S604, otherwise, the data point is skipped and proceeds to step S604, where C is[i,j]Representing the colour level, T[i,j]Represents a judgment value, CtargetRepresenting a recognition target;
s604, judging whether T exists or not[i,j]If yes, adding 1 to the total number of the southwest low vortex numbers num, and returning to step S602, otherwise, proceeding to step S605;
s605, judging whether a data point C exists on the outer boundary of the auxiliary identification area[i,j]＝Ctarget∧T[i,j]Not equal to 0, the data points have the same low vortex number num, if yes, the data points are plateau vortexes, the plateau vortexes are eliminated, and the judgment value T of the data point set is made[i,j]And (4) reordering the low vortex number num when the low vortex number num is minus 1, giving a southwest low vortex data point set, completing the distinguishing and identifying of a plurality of southwest low vortices, and entering the step S7, otherwise, indicating that no plateau vortex exists, and entering the step S7.
6. The method for automatically identifying southwest low vortex, according to claim 1, wherein the expression of southwest low vortex area in step S9 is as follows:
Figure FDA0002654576280000034
N＝Nout+Nin
Figure FDA0002654576280000035
Figure FDA0002654576280000041
wherein S represents the area of the southwest low vortex, N represents the data point in the southwest low vortex, SiIndicates the area occupied by the ith grid point,
Figure FDA0002654576280000042
the dimensions of the standard are represented such that,
Figure FDA0002654576280000043
indicates latitude, rlonIndicating the weft distance, rlatDenotes the meridional distance, NinIndicating the number of data points located in the identified region, NoutRepresenting the number of data points located in the auxiliary identification area, m representing the lead-in map magnification factor, L representing the distance on the mapping plane, LsRepresenting the corresponding distance on the earth's surface.
7. The method for automatically identifying southwest low vortex as claimed in claim 1, wherein the longitude and latitude expression of the geometric center in step S10 is as follows:
Figure FDA0002654576280000044
wherein (O)x,Oy) Represents the latitude and longitude of the geometric center of the southwest low vortex, d represents the potential height minimum point,
Figure FDA0002654576280000045
representing the longitude of the lowest point of the potential altitude,
Figure FDA0002654576280000046
the latitude of the lowest point of the potential height is represented, and i represents the number of grid points.
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