CN110488392A - A kind of cyclone center's identification and radius evaluation method based on sea-level pressure data - Google Patents
A kind of cyclone center's identification and radius evaluation method based on sea-level pressure data Download PDFInfo
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Abstract
The present invention relates to a kind of, and the cyclone center based on sea-level pressure data identifies and cyclone radius evaluation method.MSLP data are read using program language, by sea-level pressure (the Mean sea level pressure of Global Grid, MSLP) data projection resolution ratio is the homalographic polar region orthogonal projection of 100km × 100km, calculate the Laplacian values of each grid, then loop iteration is carried out to all grids, searches cyclone center.Hereafter adjacent cyclone center's merging is carried out, and each cyclone center calculate from all directions to gradient, estimates the effective radius of cyclone.Image display window is finally established, the cyclone center and radius obtain to MSLP data and identification visualizes.The present invention solves the problems, such as cyclone data deficiency, this method accuracy and scientific higher, and user can adjustment algorithm according to demand parameter so that algorithm is using more flexible, to extract result more targeted.
Description
Technical field
The step of the present invention relates to a kind of processing of grid data, specifically a kind of gas based on sea-level pressure data
Revolve center identification and radius evaluation method process.
Background technique
Cyclone is a kind of extreme weather situation, since its coverage is wide, movement speed is fast, can lead to localized weather
The features such as acute variation, becomes the weather system that the mankind are very concerned about He are studied earliest.Cyclone is to the weather by way of region
Situation plays a significant role, and adjoint extreme weather may cause property loss and casualties.In addition, becoming in global climate
Under the overall background of change, as it is a kind of it is important move local synoptic model, cyclonic activity will also do the fluctuation of atmospheric condition
It contributes out, and then leads to very important climatic effect.But the long-time due to the complexity of cyclonic motion, about cyclone
The meteorological data of sequence compares shortage, and analyze again data bulk and the quality of MSLP have all obtained significantly mentioning since 1979
Height, thus propose it is a kind of based on sea-level pressure data cyclone center identification and radius estimating algorithm, to obtain for a long time
The cyclone center of sequence and radius data can be tracked, the distribution characteristics of research long time scale cyclonic activity for the cyclone in later period
With changing rule, inquire into cyclone and the projects offer basic data such as influence caused by climate change, result of study can also be applied to
The forecast of part weather conditions.Therefore, this algorithm has stronger scientific research value and practical application value.
Summary of the invention
In view of the above problems, it is based on MSLP data herein, by IDL program language to cyclone center's identification and half
Diameter estimating algorithm is implemented, first setting key parameter, then reads data and carries out projection transform, changes step by step to data
Generation processing successively extracts cyclone center, merges close cyclone, estimation cyclone range.User can be according to their own needs and different
MSLP data modification parameter, or to research the period in different time nodes data carry out batch processing, needed
Cyclone data simultaneously carry out visualization display.The accuracy of algorithm and scientific stronger and easy to implement, flexibility ratio height, can basis
Different data and research need to adjust parameters.
Realize the technical scheme adopted by the invention is that: a kind of cyclone center's identification and half based on sea-level pressure data
Diameter evaluation method, comprising:
1) the sea-level pressure MSLP data under global geographic grid are read;
2) by the homalographic polar region orthogonal projection under data projection to default resolution ratio;
3) the Laplace operator value of the field MSLP under the orthogonal projection of homalographic polar region is calculated;
4) for each MSLP grid, compare periphery using iterative search and extend to the outside the MSLP value of grid cell to know
Other cyclone center position;
5) after the completion of all cyclone center's identifications, adjacent or similar cyclone center is closed using Laplce
And;
6) to finally identifying that obtained cyclone center estimates radius size.
The homalographic polar region orthogonal projection by under data projection to default resolution ratio are as follows:
Firstly, establishing target-based coordinate system, parameter: projection type, spheroid, central meridian and unit is set;According to initial
Coordinate system and target-based coordinate system establish geo-Iookup list file, with the initial position in the original geographic grid of determination in coordinates of targets
Result position in system;
Then, MSLP data are converted according to initial position and result position, interpolation, the resolution of objective result is set
Rate obtains the MSLP data under the orthogonal projection of homalographic polar region.
The cyclone center position is defined as the grid position where MSLP minimum, and cyclone within a preset range
The barometric gradient of grid should be greater than preset threshold in center and the preset range.
The iterative search are as follows:
Firstly, the Grads threshold of definition identification cyclone center, minimum search radius, maximum search radius and between the two
Outer hull number, the outer hull number are used to determine the step-length of search radius;Identify the local minimum of all grids in MSLP
For determining cyclone position candidate;
Then, for each cyclone position candidate, using within the scope of more a series of abducent shells of iterative search
The MSLP value of surrounding grid cell is preset if the difference of the minimum MSLP value in adjacent shells and the MSLP value at position candidate is greater than
Grads threshold, then this position candidate be cyclone center;If the two difference is undesirable, and the atmospheric pressure value in adjacent shells does not have
There is reduction, then increase step-size in search, continue the atmospheric pressure value in more next shell outward, is most wantonly searched for until shell extends to
Until rope radius, cyclone center is identified.
It is described that adjacent or similar cyclone center is merged using Laplce are as follows:
It searches for and whether there is other cyclone centers around each cyclone center in pre-set radius, when adjacent and similar grid
When being all identified as cyclone center, the intensity of cyclone is represented due to calculating its local Laplace operator value, selects Laplce
The maximum cyclone center position of operator is as cyclone center final within the scope of this.
It is described to finally identifying that obtained cyclone center estimates radius size, specifically:
Since cyclone may be arbitrary shape, by the way that using current cyclone center as the center of circle, circumferencial direction 45° angle increases
Amount 8 radial directions of setting;For each radial direction, searches for the no longer raised position of air pressure outward to estimate cyclone size, obtain each
Radius on direction;Using the radius average value in 8 directions as the radius of effective area of a circle of the cyclone.
It is described that the no longer raised position of air pressure is searched for outward to estimate cyclone size for each radial direction, are as follows: at each
The position that the first radial derivative of MSLP is reduced to 0 is found on search radius direction;If along this direction maximum preset cyclone radius
Air pressure persistently increases in range, then using maximum preset cyclone radius value as this direction radius.
Further include: 7) cyclone center and radius result of identification and estimation are visualized, Overlapping display.
Original MSLP data, the obtained cyclone center of identification and the corresponding effectively area of a circle can finally be drawn out
Come, implement step are as follows:
Using IDL language, MSLP data are read, air pressure isogram is drawn using Contour function, utilizes PLOT function
Cyclone center's point that identification obtains is drawn, effective area of a circle of each cyclone center is finally drawn out using ELLIPSE function, it is right
Initial data and arithmetic result carry out visualization display.
If repeating step 1) -7 whithin a period of time), the cyclone of the different time nodes in the available corresponding period
Center and radius size data.
Beneficial effects of the present invention and advantage:
1. the present invention be it is a kind of based on sea-level pressure data cyclone center identification and radius evaluation method, it can be achieved that from
Reading data, data processing, iterative extraction and finally at a whole set of process of figure.
2. algorithm scientific and accuracy with higher can need quick obtaining according to research or practical application
The data of survey region and cyclone position and size in the research period.
3. algorithm is realized using IDL program, also it is convenient to realize using other program languages, convenient for operation, also has
There is higher flexibility.
Detailed description of the invention
Fig. 1 is flow chart of the invention;
Fig. 2 is the MSLP schematic diagram data in original global range;
Fig. 3 is the MSLP schematic diagram data for being projected as homalographic polar region orthogonal projection Northern Hemisphere range;
Fig. 4 is the one-dimensional schematic diagram of cyclone center's identification and search;
Fig. 5 is that this method utilizes the cyclone center identified from the MSLP data of ERA-Interim sometime
Position exemplary diagram;
Fig. 6 is that this method utilizes the cyclone center identified from the MSLP data of ERA-Interim sometime
Position and corresponding cyclone examples of ranges figure.
Specific embodiment
With reference to the accompanying drawings and examples, specific embodiments of the present invention will be described in further detail.Implement below
Example for the purpose of illustrating the invention, but is not used to limit the scope of the invention.
As shown in Figure 1, this method process be related to it is a kind of based on sea-level pressure (Mean sea level pressure,
MSLP) cyclone center's identification of data and cyclone radius evaluation method: the MSLP data of Global Grid are read, projection transform is carried out
Afterwards, iterative search cyclone center position carries out the merging of adjacent cyclone after the completion of search, calculate for finally obtained cyclone center
Cyclone range size, and result is visualized.Specifically implementation steps include:
The sea-level pressure data for sometime putting Global Grid are read, as shown in Fig. 2, Global Grid data have
1.25 ° × 1.25 ° of horizontal resolution and 6 hours temporal resolutions;The data for selecting the Northern Hemisphere, according to the projection of input and
Output projection calculate each grid of initial data target position, carry out interpolated projections, obtain in the Northern Hemisphere within the scope of with etc.
The MSLP data of area polar region orthogonal projection, as shown in figure 3, horizontal resolution is 100km × 100km, temporal resolution is 6 small
When.
Calculate the Laplace operator value of each grid position:
Formula 1:Wherein, x represents horizontal direction, and y represents vertical direction,For La Pula
This operator value, P is sea-level pressure value, and the final public affairs for calculating Laplace operator can be derived by formula 2 and formula 3
Formula is shown in formula 4.
Formula 2:
Formula 3:
Formula 4:
After the completion of Laplace operator value calculates, search pattern iterative search cyclone center according to Fig.4,.It is fixed first
Grads threshold, minimum search radius, maximum search radius and the outer hull number between the two of code of brotherhood rotation center identification (are adopted in example
It is respectively as follows: 0.15hPa/km, 100km, 500km, 3).Cyclone center be defined as in a certain range with periphery grid
Barometric gradient is greater than the minimum of a certain threshold value, the difference of more each first grid and adjacent mesh, if meeting condition stopping
Iteration, if otherwise the atmospheric pressure value of all grids is not less than central gridding in shell, continuation iterative search comes more a series of outside
Within the scope of the shell of extension, stop when occurring the point lower than central pressure value in shell grid or reaching maximum search radius
Only.
After the completion of all cyclone center's identifications, adjacent or similar cyclone center is closed using Laplce
And if occurring multiple cyclone centers in cyclone center's periphery 600km radius, all cyclone center positions are recorded in array
In, compare its cyclone intensity, selection intensity is maximum to represent this multicenter cyclone, and Fig. 5 illustrates the cyclone center finally obtained
Instance graph.
Fig. 6 is finally to identify obtained cyclone center and cyclone Example figure.Since cyclone may be arbitrary shape,
Therefore, algorithm calculates air pressure and does not estimate cyclone size in raised position by searching for along 8 radiuses (45° angle increment).In
On each search radius direction, find the position that the first radial derivative of MSLP is reduced to 0, i.e., herein:
Formula 5:
If not finding the position for meeting formula 5 within the scope of this side up 1000km and air pressure persistently increasing, by this
Direction radius is set as 1000km.Such 8 directions of cycle calculations, obtain radius size in each direction, will using formula 6
The radius in 8 directions carries out the average radius as the effective area of a circle of cyclone.
Formula 6:
After the cyclone center and radius for obtaining single time point, it can use time circulation and carry out batch processing, acquisition is ground
The cyclone data for studying carefully all timing nodes in the period, result is exported, subsequent applications are served.
The above is a preferred embodiment of the present invention, it is noted that for those skilled in the art
For, without departing from the principles of the present invention, several improvements and modifications can also be made, these improvements and modifications are answered
It is considered as protection scope of the present invention.
Claims (10)
1. a kind of cyclone center's identification and radius evaluation method based on sea-level pressure data characterized by comprising
1) the sea-level pressure MSLP data under global geographic grid are read;
2) by the homalographic polar region orthogonal projection under data projection to default resolution ratio;
3) the Laplace operator value of the field MSLP under the orthogonal projection of homalographic polar region is calculated;
4) for each MSLP grid, compare periphery using iterative search and extend to the outside the MSLP value of grid cell to identify gas
Revolve center;
5) after the completion of all cyclone center's identifications, adjacent or similar cyclone center is merged using Laplce;
6) to finally identifying that obtained cyclone center estimates radius size.
2. a kind of cyclone center's identification and radius evaluation method based on sea-level pressure data according to claim 1,
It is characterized in that by the homalographic polar region orthogonal projection under data projection to default resolution ratio are as follows:
Firstly, establishing target-based coordinate system, parameter: projection type, spheroid, central meridian and unit is set;According to initial coordinate
System and target-based coordinate system establish geo-Iookup list file, with the initial position in the original geographic grid of determination in target-based coordinate system
Result position;
Then, MSLP data are converted according to initial position and result position, interpolation, the resolution ratio of objective result are set,
Obtain the MSLP data under the orthogonal projection of homalographic polar region.
3. a kind of cyclone center's identification and radius evaluation method based on sea-level pressure data according to claim 1,
It is characterized in that the cyclone center position is defined as the grid position where MSLP minimum, and gas within a preset range
The barometric gradient of grid should be greater than preset threshold in rotation center and the preset range.
4. a kind of cyclone center's identification and radius evaluation method based on sea-level pressure data according to claim 1,
It is characterized in that the iterative search are as follows:
Firstly, the Grads threshold of definition identification cyclone center, minimum search radius, maximum search radius and shell between the two
Number, the outer hull number are used to determine the step-length of search radius;Identify that the local minimum of all grids in MSLP is used for
Determine cyclone position candidate;
Then, for each cyclone position candidate, more a series of abducent shell range inner peripheries of iterative search are used
The MSLP value of grid cell, if the difference of the minimum MSLP value in adjacent shells and the MSLP value at position candidate is greater than preset ladder
Threshold value is spent, then this position candidate is cyclone center;If the two difference is undesirable, and the atmospheric pressure value in adjacent shells does not drop
It is low, then increase step-size in search, continue the atmospheric pressure value in more next shell outward, until shell extends to maximum search half
Until diameter, cyclone center is identified.
5. a kind of cyclone center's identification and radius evaluation method based on sea-level pressure data according to claim 1,
It is characterized in that described merge adjacent or similar cyclone center using Laplce are as follows:
Search for around each cyclone center in pre-set radius with the presence or absence of other cyclone centers, when adjacent and similar grid all by
When being identified as cyclone center, the intensity of cyclone is represented due to calculating its local Laplace operator value, selects Laplace operator
Maximum cyclone center position is as cyclone center final within the scope of this.
6. a kind of cyclone center's identification and radius evaluation method based on sea-level pressure data according to claim 1,
It is characterized in that it is described to finally identifying that obtained cyclone center estimates radius size, specifically:
Since cyclone may be arbitrary shape, by the way that using current cyclone center as the center of circle, circumferencial direction 45° angle increment is set
Set 8 radial directions;For each radial direction, searches for the no longer raised position of air pressure outward to estimate cyclone size, obtain each direction
On radius;Using the radius average value in 8 directions as the radius of effective area of a circle of the cyclone.
7. a kind of cyclone center's identification and radius evaluation method based on sea-level pressure data according to claim 6,
It is characterized in that described for each radial direction, the no longer raised position of air pressure is searched for outward to estimate cyclone size, are as follows: each
The position that the first radial derivative of MSLP is reduced to 0 is found on a search radius direction;If along this direction maximum preset cyclone half
Air pressure persistently increases within the scope of diameter, then using maximum preset cyclone radius value as this direction radius.
8. a kind of cyclone center's identification and radius evaluation method based on sea-level pressure data according to claim 1,
Characterized by further comprising: 7) cyclone center and radius result of identification and estimation is visualized, Overlapping display.
9. a kind of cyclone center's identification and radius evaluation method based on sea-level pressure data according to claim 8,
It is characterized in that finally original MSLP data, the obtained cyclone center of identification and the corresponding effectively area of a circle can be drawn out
Come, implement step are as follows:
Using IDL language, MSLP data are read, air pressure isogram is drawn using Contour function, is drawn using PLOT function
It identifies obtained cyclone center's point, effective area of a circle of each cyclone center is finally drawn out using ELLIPSE function, to original
Data and arithmetic result carry out visualization display.
10. a kind of cyclone center's identification and radius evaluation method based on sea-level pressure data according to claim 8,
It is characterized in that if repeating step 1) -7 whithin a period of time), the gas of the different time nodes in the available corresponding period
Revolve center and radius size data.
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Cited By (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
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Citations (9)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20070158452A1 (en) * | 2006-01-06 | 2007-07-12 | Hofffmann Eugene J | Tropical hurricane storm control system |
US20120168361A1 (en) * | 2010-06-25 | 2012-07-05 | Abbas Motakef | Cyclone induced sweeping flow separator |
CN102831626A (en) * | 2012-06-18 | 2012-12-19 | 清华大学 | Visualization method for multivariable spatio-temporal data under polar region projection mode |
CN103955009A (en) * | 2014-04-25 | 2014-07-30 | 宁波市气象台 | Method for extracting typhoon objective forecast information from numerical forecasting product |
US20140344209A1 (en) * | 2010-08-23 | 2014-11-20 | Institute Of Nuclear Energy Research, Atomic Energy Council, Executive Yuan | Wind energy forecasting method with extreme wind speed prediction function |
CN104200082A (en) * | 2014-08-22 | 2014-12-10 | 清华大学 | Typhoon landing prediction method |
CN106919792A (en) * | 2017-02-24 | 2017-07-04 | 天津大学 | Vortex center automatic identifying method based on high accuracy numerical value Wind Data |
US20180081080A1 (en) * | 2016-09-16 | 2018-03-22 | The Government Of The United States Of America, As Represented By The Secretary Of The Navy | Automated Tropical Storm Wind Radii Analysis and Forecasting |
CN107945242A (en) * | 2017-11-16 | 2018-04-20 | 中国科学院海洋研究所 | It is a kind of towards IDL projection transform algorithms |
-
2019
- 2019-08-13 CN CN201910743427.3A patent/CN110488392B/en active Active
Patent Citations (9)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20070158452A1 (en) * | 2006-01-06 | 2007-07-12 | Hofffmann Eugene J | Tropical hurricane storm control system |
US20120168361A1 (en) * | 2010-06-25 | 2012-07-05 | Abbas Motakef | Cyclone induced sweeping flow separator |
US20140344209A1 (en) * | 2010-08-23 | 2014-11-20 | Institute Of Nuclear Energy Research, Atomic Energy Council, Executive Yuan | Wind energy forecasting method with extreme wind speed prediction function |
CN102831626A (en) * | 2012-06-18 | 2012-12-19 | 清华大学 | Visualization method for multivariable spatio-temporal data under polar region projection mode |
CN103955009A (en) * | 2014-04-25 | 2014-07-30 | 宁波市气象台 | Method for extracting typhoon objective forecast information from numerical forecasting product |
CN104200082A (en) * | 2014-08-22 | 2014-12-10 | 清华大学 | Typhoon landing prediction method |
US20180081080A1 (en) * | 2016-09-16 | 2018-03-22 | The Government Of The United States Of America, As Represented By The Secretary Of The Navy | Automated Tropical Storm Wind Radii Analysis and Forecasting |
CN106919792A (en) * | 2017-02-24 | 2017-07-04 | 天津大学 | Vortex center automatic identifying method based on high accuracy numerical value Wind Data |
CN107945242A (en) * | 2017-11-16 | 2018-04-20 | 中国科学院海洋研究所 | It is a kind of towards IDL projection transform algorithms |
Non-Patent Citations (1)
Title |
---|
涂小萍 等: "基于ECMWF海平面气压场的热带气旋路径预报效果检验", 《气象》 * |
Cited By (12)
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---|---|---|---|---|
CN111650673A (en) * | 2020-06-05 | 2020-09-11 | 成都信息工程大学 | Method for correcting central position of low vortex by using wind field data |
CN111650673B (en) * | 2020-06-05 | 2022-01-11 | 成都信息工程大学 | Method for correcting central position of low vortex by using wind field data |
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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 |
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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 |
CN115082788A (en) * | 2022-06-21 | 2022-09-20 | 中科三清科技有限公司 | Air pressure center identification method and device, electronic equipment and storage medium |
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 |
CN116010812A (en) * | 2022-12-13 | 2023-04-25 | 南京信息工程大学 | North cyclone identification method, storage medium and device based on traditional method and deep learning |
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 |
CN117036983A (en) * | 2023-10-08 | 2023-11-10 | 中国海洋大学 | Typhoon center positioning method based on physical reinforcement deep learning |
CN117036983B (en) * | 2023-10-08 | 2024-01-30 | 中国海洋大学 | Typhoon center positioning method based on physical reinforcement deep learning |
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