CN110488392B - Cyclone center identification and radius estimation method based on sea level air pressure data - Google Patents
Cyclone center identification and radius estimation method based on sea level air pressure data Download PDFInfo
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Abstract
The invention relates to a cyclone center identification and cyclone radius estimation method based on sea level air pressure data. Reading MSLP data by using a program language, projecting sea level pressure (MSLP) data of global grids into equal-area polar orthographic projection with the resolution of 100km multiplied by 100km, calculating a Laplace value of each grid, and then performing loop iteration on all the grids to search for cyclone centers. Thereafter, adjacent cyclone centers are merged, and eight-direction gradient calculation is performed for each cyclone center to estimate the effective radius of the cyclone. And finally, establishing an image display window, and visualizing the MSLP data, the cyclone center obtained by identification and the radius. The method solves the problem of cyclone data shortage, is high in accuracy and scientificity, and enables a user to adjust parameters of the algorithm according to requirements, so that the algorithm is more flexible to use, and the extraction result is more targeted.
Description
Technical Field
The invention relates to a step of grid data processing, in particular to a cyclone center identification and radius estimation method flow based on sea level air pressure data.
Background
The cyclone is an extreme weather condition, and due to the characteristics of wide influence range, high moving speed, severe change of local weather and the like, the cyclone becomes a climate system which is very concerned and researched by human beings at the earliest. The cyclone plays an important role in the weather conditions in the area being traversed, and its attendant extreme weather can cause property damage and casualties. Furthermore, in the large context of global climate change, as an important mobile local weather pattern, cyclonic activity will also contribute to fluctuations in atmospheric conditions, leading to non-negligible climate effects. However, due to the complexity of the cyclone motion, the weather data related to the long-time sequence of the cyclones is relatively scarce, and the quantity and the quality of the re-analysis data of the MSLP are remarkably improved since 1979, so that a cyclone center identification and radius estimation algorithm based on sea level air pressure data is provided, the cyclone center and radius data related to the long-time sequence are expected to be obtained, basic data can be provided for the problems of later cyclone tracking, the distribution characteristics and the change rule of long-time scale cyclone activity, the influence of cyclone discussion on the weather change and the like, and the research result can also be applied to the forecast of partial weather conditions. Therefore, the algorithm has strong scientific research value and practical application value.
Disclosure of Invention
Aiming at the existing problems, the cyclone center identification and radius estimation algorithm is implemented by means of IDL programming language based on MSLP data, key parameters are set firstly, then the data is read for projection conversion, the data is subjected to iterative processing step by step, the cyclone center is extracted, the similar cyclones are combined, and the cyclone range is estimated. The user can modify parameters according to own requirements and different MSLP data, or carry out batch processing on data of different time nodes in a research period to obtain required cyclone data and carry out visual display. The algorithm has the advantages of high accuracy and scientificity, convenience in implementation and high flexibility, and can adjust various parameters according to different data and research requirements.
The technical scheme adopted for realizing the invention is as follows: a method for cyclone center identification and radius estimation based on sea level air pressure data, comprising:
1) reading sea level air pressure MSLP data under a global geographic grid;
2) projecting the data to equal-area polar orthographic projection under preset resolution;
3) calculating a Laplace operator value of the MSLP field under the equal-area polar orthographic projection;
4) for each MSLP grid, comparing the MSLP values of the peripheral outwardly extending grid cells using an iterative search to identify a cyclone center position;
5) after all cyclone centers are identified, merging adjacent or similar cyclone centers by utilizing a Laplace field;
6) the radius size is estimated for the cyclone center finally identified.
The equal-area polar orthographic projection of the data under the preset resolution is as follows:
firstly, establishing a target coordinate system, and setting parameters: projection type, ellipsoid, central meridian and unit; establishing a geographical lookup table file according to the initial coordinate system and the target coordinate system so as to determine the result position of the initial position in the original geographical grid in the target coordinate system;
and then, the MSLP data is transformed and interpolated according to the initial position and the result position, the resolution ratio of the target result is set, and the MSLP data under the equal-area polar orthographic projection is obtained.
The cyclone center position is defined as a grid position where the minimum value of the MSLP is within a preset range, and the air pressure gradient between the cyclone center position and the grid within the preset range is greater than a preset threshold value.
The iterative search is as follows:
firstly, defining a gradient threshold value for identifying the center of the cyclone, a minimum search radius, a maximum search radius and a shell number between the minimum search radius and the maximum search radius, wherein the shell number is used for determining the step size of the search radius; identifying local minima of all grids in the MSLP field for determining cyclone candidate locations;
then, for each cyclone candidate location, using an iterative search to compare the MSLP values of the perimeter grid cells within a series of outwardly expanded hull ranges, if the difference between the minimum MSLP value in the adjacent hull and the MSLP value at the candidate location is greater than a preset gradient threshold, then the candidate location is the cyclone center; if the difference between the two is not satisfactory and the air pressure value in the adjacent shell is not reduced, the searching step length is increased, the air pressure values in the next shells are continuously compared outwards until the shells extend to the maximum searching radius, and the cyclone center is identified.
The merging of adjacent or near cyclone centers with laplace field is:
and searching whether other cyclone centers exist in a preset radius around each cyclone center, and when adjacent and close grids are identified as the cyclone centers, selecting the position of the cyclone center with the maximum laplacian operator as the final cyclone center in the range because the local laplacian operator value represents the strength of the cyclone.
The estimated radius of the finally identified cyclone center is specifically as follows:
since the cyclone can be in any shape, 8 radial directions are set in 45-degree angle increment in the circumferential direction by taking the current cyclone center as a center; for each radial direction, searching outwards for the position where the air pressure is not increased any more to estimate the cyclone size, and obtaining the radius in each direction; the radius of the effective circular area of the cyclone is taken as the average value of the radii in 8 directions.
For each radial direction, the position where the air pressure is not increased is searched outwards to estimate the cyclone size, and the following steps are carried out: finding a position in each search radius direction where the MSLP first radial derivative decreases to 0; if the air pressure continues to rise in this direction within the maximum preset cyclone radius, the maximum preset cyclone radius value is taken as the direction radius.
Further comprising: 7) and visualizing, superposing and displaying the identified and estimated cyclone center and radius results.
Finally, the original MSLP data, the cyclone center obtained by identification and the corresponding effective circle area can be drawn, and the specific implementation steps are as follows:
reading MSLP data by using IDL language, drawing an air pressure Contour map by using a Contour function, drawing an identified cyclone central point by using a PLOT function, drawing an effective circle area of each cyclone center by using an ELLIPSE function, and visually displaying original data and an algorithm result.
If steps 1) -7) are repeated over a period of time, cyclone center position and radius size data may be obtained for different time nodes over the period of time.
The invention has the advantages that:
1. the invention relates to a cyclone center identification and radius estimation method based on sea level air pressure data, which can realize a whole set of processes of data reading, data processing, iterative extraction and final mapping.
2. The algorithm has high scientificity and accuracy, and can quickly acquire the cyclone position and size data in the research area and the research period according to the research or practical application requirements.
3. The algorithm is realized by adopting the IDL program, can also be conveniently realized by utilizing other program languages, is convenient to operate and has higher flexibility.
Drawings
FIG. 1 is a flow chart of the present invention;
FIG. 2 is a graphical illustration of raw global-wide MSLP data;
FIG. 3 is a graphical representation of MSLP data projected as an equi-areal polar orthographic projection northern hemisphere region;
FIG. 4 is a one-dimensional schematic of cyclone center identification and search;
FIG. 5 is an exemplary plot of cyclone center location identified by the present method using MSLP data from ERA-Interim at a time;
FIG. 6 is an exemplary graph of cyclone center position and corresponding cyclone range identified by the present method using MSLP data from ERA-Interim at a time.
Detailed Description
The following detailed description of embodiments of the present invention is provided in connection with the accompanying drawings and examples. The following examples are intended to illustrate the invention, but are not intended to limit the scope of the invention.
As shown in fig. 1, the flow of the method relates to a cyclone center identification and cyclone radius estimation method based on sea level air pressure (MSLP) data: reading MSLP data of a global grid, carrying out projection conversion, then iteratively searching the cyclone center position, merging adjacent cyclones after the search is finished, calculating the cyclone range size for the finally obtained cyclone center, and visualizing the result. The specific implementation steps comprise:
reading sea level barometric pressure data of a global grid at a certain point in time, as shown in fig. 2, the global grid data having a horizontal resolution of 1.25 ° x 1.25 ° and a temporal resolution of 6 hours; selecting data of northern hemisphere, calculating target position of each grid of original data according to input projection and output projection, and performing interpolation projection to obtain MSLP data with equal-area polar orthographic projection in northern hemisphere range, as shown in FIG. 3, horizontal resolution is 100km × 100km, and time resolution is 6 hours.
Calculate the laplacian operator value for each grid location:
formula (II)1：
Wherein x represents the horizontal direction, y represents the vertical direction,
the final formula for calculating the laplacian can be derived from formula 2 and formula 3, see formula 4.
Equation 2:
equation 3:
equation 4:
after the laplacian operator value calculation is completed, the cyclone center is iteratively searched according to the search pattern shown in fig. 4. First, a gradient threshold value for cyclone center identification, a minimum search radius, a maximum search radius, and the number of shells therebetween are defined (0.15 hPa/km, 100km, 500km, 3, respectively, are used in the example). The cyclone center is defined as the minimum value within a certain range and the air pressure gradient of the peripheral grids is larger than a certain threshold value, the difference value of each grid and the adjacent grid is firstly compared, if the condition is met, the iteration is stopped, otherwise if the air pressure value of all the grids in the shell is not lower than the central grid, the iterative search is continued to compare a series of shell ranges which are expanded outwards, and the comparison is stopped until a point lower than the central air pressure value appears in the shell grids or the maximum search radius is reached.
After all cyclone centers are identified, adjacent or near cyclone centers are merged by using a laplace field, if a plurality of cyclone centers are present within a radius of 600km around the cyclone center, all cyclone center positions are recorded in an array, cyclone strength is compared, and the cyclone center with the highest strength is selected to represent the multi-center cyclone, and fig. 5 shows an example graph of the finally obtained cyclone centers.
Fig. 6 is an example diagram of the cyclone center and the cyclone range finally identified. Since the cyclone may be of any shape, the algorithm estimates the cyclone size by searching for locations along 8 radii (45 ° angular increments) where the calculated air pressure is not elevated. In each search radius direction, the position where the MSLP first radial derivative decreases to 0 is found, i.e. here:
equation 5:
if no location is found within 1000km in this direction that satisfies equation 5 and the barometric pressure continues to rise, then set this direction radius to 1000 km. The radius in each direction is obtained by circularly calculating 8 directions in this way, and the radius in each direction is averaged by using formula 6 to be used as the radius of the effective circle area of the cyclone.
Equation 6:
after acquiring the cyclone center and radius at a single time point, batch processing can be performed by using time cycle, cyclone data of all time nodes in the research period is acquired, and the result is output to serve subsequent applications.
While the foregoing is directed to the preferred embodiment of the present invention, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (10)
1. A method for cyclone center identification and radius estimation based on sea level air pressure data, comprising:
1) reading sea level air pressure MSLP data under a global geographic grid;
2) projecting the data to equal-area polar orthographic projection under preset resolution;
3) calculating a Laplace operator value of the MSLP field under the equal-area polar orthographic projection;
4) for each MSLP grid, comparing the MSLP values of the peripheral outwardly extending grid cells using an iterative search to identify a cyclone center position;
5) after all cyclone centers are identified, combining the close cyclone centers by utilizing a Laplace field;
6) the radius size is estimated for the cyclone center finally identified.
2. The cyclone center identification and radius estimation method based on sea level air pressure data as claimed in claim 1, wherein the equal area polar orthographic projection of the data to the preset resolution is:
firstly, establishing a target coordinate system, and setting parameters: projection type, ellipsoid, central meridian and unit; establishing a geographical lookup table file according to the initial coordinate system and the target coordinate system so as to determine the result position of the initial position in the original geographical grid in the target coordinate system;
and then, the MSLP data is transformed and interpolated according to the initial position and the result position, the resolution ratio of the target result is set, and the MSLP data under the equal-area polar orthographic projection is obtained.
3. The method of claim 1, wherein the cyclone center position is defined as a grid position where the MSLP minimum value is located within a preset range, and the air pressure gradient between the cyclone center position and the grid within the preset range is greater than a preset threshold.
4. The method of claim 1 wherein the iterative search is performed by:
firstly, defining a gradient threshold value for identifying the center of the cyclone, a minimum search radius, a maximum search radius and a shell number between the maximum search radius and the minimum search radius, wherein the shell number is used for determining the step size of the search radius; identifying local minima of all grids in the MSLP field for determining cyclone candidate locations;
then, for each cyclone candidate location, using an iterative search to compare the MSLP values of the perimeter grid cells within a series of outwardly expanded hull ranges, if the difference between the minimum MSLP value in the adjacent hull and the MSLP value at the candidate location is greater than a preset gradient threshold, then the candidate location is the cyclone center; if the difference between the two is not satisfactory and the air pressure value in the adjacent shell is not reduced, the searching step length is increased, the air pressure values in the next shells are continuously compared outwards until the shells extend to the maximum searching radius, and the cyclone center is identified.
5. The method of claim 1, wherein the utilizing laplace field to combine the approximate cyclone centers is as follows:
and searching whether other cyclone centers exist in a preset radius around each cyclone center, and when adjacent and close grids are identified as the cyclone centers, selecting the position of the cyclone center with the maximum laplacian operator as the final cyclone center in the range because the local laplacian operator value represents the strength of the cyclone.
6. The method of claim 1, wherein the step of estimating the radius of the cyclone center based on the sea level air pressure data comprises:
since the cyclone can be in any shape, 8 radial directions are set in 45-degree angle increment in the circumferential direction by taking the current cyclone center as a center; for each radial direction, searching outwards for the position where the air pressure is not increased any more to estimate the cyclone size, and obtaining the radius in each direction; the radius of the effective circular area of the cyclone is taken as the average value of the radii in 8 directions.
7. The method of claim 6 wherein for each radial direction, searching outwardly for a location where the air pressure is no longer elevated to estimate the cyclone size comprises: finding a position in each search radius direction where the MSLP first radial derivative decreases to 0; if the air pressure continues to rise in this direction within the maximum preset cyclone radius, the maximum preset cyclone radius value is taken as the direction radius.
8. The method of claim 1, further comprising the step of identifying the cyclone center and estimating the radius based on the sea level air pressure data, wherein the method further comprises the steps of: 7) and visualizing, superposing and displaying the identified and estimated cyclone center and radius results.
9. The method of claim 8, wherein the original MSLP data, the identified cyclone center and the corresponding effective circle area are finally plotted, and the method comprises:
reading MSLP data by using IDL language, drawing an air pressure Contour map by using a Contour function, drawing an identified cyclone central point by using a PLOT function, drawing an effective circle area of each cyclone center by using an ELLIPSE function, and visually displaying original data and an algorithm result.
10. The method of claim 8, wherein the steps 1) -7) are repeated for a period of time, and cyclone center location and radius size data for different time nodes of the period of time are obtained.
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| CN113344136B (en) * | 2021-07-06 | 2022-03-15 | 南京信息工程大学 | Novel anticyclone objective identification method based on Mask R-CNN |
| CN113724280B (en) * | 2021-09-15 | 2023-12-01 | 南京信息工程大学 | Automatic identification method for ground weather map high-voltage system |
| CN115082788B (en) * | 2022-06-21 | 2023-03-21 | 中科三清科技有限公司 | Air pressure center identification method and device, electronic equipment and storage medium |
| CN116010812B (en) * | 2022-12-13 | 2023-11-21 | 南京信息工程大学 | North cyclone identification method, storage medium and device based on traditional method and deep learning |
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