CN106780245B - Method and system for determining and forecasting dust haze probability of coastal region caused by tropical cyclone - Google Patents
Method and system for determining and forecasting dust haze probability of coastal region caused by tropical cyclone Download PDFInfo
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Abstract
The invention provides a method and a system for determining and forecasting the probability of dust haze in coastal areas caused by tropical cyclones, wherein the determining method comprises the following steps: collecting tropical cyclone path point data which influences the visibility of the area to be measured and the visibility and relative humidity data of the area to be measured at corresponding time; classifying the tropical cyclone path point data according to the strength to obtain various tropical cyclone path point data; dividing the prediction range of the area to be detected into a plurality of sections, reserving a path point for each intensity tropical cyclone in the same tropical cyclone in each section, calculating the probability of causing the dust haze of the area to be detected by the tropical cyclone in each section according to the reserved path point data and the visibility data corresponding to the area to be detected, and performing interpolation operation according to the longitude and latitude of a preset position in each section and the probability of causing the dust haze of the area to be detected by each intensity tropical cyclone in each section to obtain the probability distribution of causing the dust haze of the area to be detected by each intensity tropical cyclone. The method can provide reliable basis for weather forecast early warning of influence of tropical cyclone on dust haze.
Description
Technical Field
The invention belongs to the technical field of analysis and measurement control, and particularly relates to a method and a system for determining the probability of dust haze in coastal areas caused by tropical cyclones, and a method and a system for forecasting the probability.
Background
The weather definition of dust haze is a weather phenomenon that a large amount of tiny dust particles, smoke particles or salt particles are suspended in the atmosphere, the relative humidity of the atmosphere is less than 80%, and the horizontal visibility is reduced to be below 10 kilometers. When the weather appears in dust-haze, outdoor visibility is low, pollution is continuous, traffic is blocked, and accidents occur frequently. The dust haze not only influences the normal life of people, but also brings great threat to the health of human bodies. Years of research show that peripheral downdraft of tropical cyclones during movement has a significant influence on surrounding meteorological conditions, including visibility, relative humidity, layer junctions, wind fields and the like, which are closely related to the dust-haze weather. In fact, it has been found in daily weather monitoring and forecasting that offshore tropical cyclones in south sea can produce haze in the pearl river delta. In the past, the influence of tropical cyclone on dust-haze weather is mainly qualitative analysis of atmospheric component factors (mass concentration of aerosol particles (PM10, PM2.5), black carbon concentration and the like), and the prediction of dust-haze in a region to be measured caused by the tropical cyclone depends on the experience of a predictor, so that the accuracy requirement cannot be met to a great extent. At present, no effective and objective forecasting method can be applied to business forecasting in China, particularly, probability distribution for analyzing dust haze caused by tropical cyclone in weather forecasting is blank, and quantitative research on correlation between the tropical cyclone and the dust haze in a long-time sequence is not available in the prior art.
Disclosure of Invention
The invention provides a method and a system for determining and forecasting the probability of coastal area dust haze caused by tropical cyclone, which are used for solving the problems that in the prior art, forecasting of coastal area dust haze caused by tropical cyclone depends on the experience of forecasters, mainly qualitative analysis is adopted, inaccurate analysis is easy to cause, and at present, no effective and objective forecasting method for business forecasting application exists in China.
In order to solve the technical problem, an aspect of the present invention is to provide a method for determining a probability of causing haze in a coastal area by a tropical cyclone, including:
collecting historical data of tropical cyclone path points which have influence on visibility of a region to be detected, and historical data of visibility and historical data of relative humidity of the region to be detected at corresponding time;
classifying the historical data of the tropical cyclone path points according to the strength to obtain various tropical cyclone path point data;
dividing the prediction range of the area to be detected into a plurality of sections, reserving a path point for each tropical cyclone with strength, calculating the probability of the tropical cyclone with strength in the section to cause the haze in the area to be detected according to the reserved path point data and the visibility data of the area to be detected corresponding to the reserved path point, and performing interpolation operation according to the longitude and latitude values of a preset position in the section and the probability value of the tropical cyclone with strength in the section to cause the haze in the area to be detected to obtain the probability distribution of the haze in the area to be detected caused by the tropical cyclones with strength.
The other technical scheme of the invention is to provide a forecasting method for the probability of dust haze in coastal areas caused by tropical cyclone, which comprises the following steps,
obtaining the distribution of the dust-haze probability of the area to be tested caused by the tropical cyclone at each intensity level by using a method for determining the dust-haze probability of the coastal area caused by the tropical cyclone;
according to the intensity of the tropical cyclone to be predicted, the probability distribution of the dust haze of the area to be predicted caused by the tropical cyclone under the corresponding intensity is obtained;
and determining the probability of the dust haze of the area to be predicted when the tropical cyclone to be predicted reaches the prediction place according to the path information of the tropical cyclone to be predicted.
The invention also provides a system for determining the probability of causing the dust haze of the area to be measured by the tropical cyclone, which comprises,
the collection module is used for collecting historical data of tropical cyclone path points which have influence on the visibility of a region to be detected, and historical data of the visibility and historical data of relative humidity of the region to be detected at corresponding time;
the classification module is used for classifying the historical data of the tropical cyclone path points according to the strength to obtain various data of the tropical cyclone path points;
the data processing module is used for dividing the prediction range of the area to be detected into a plurality of sections, reserving a path point for each tropical cyclone with strength in the same tropical cyclone in each section, calculating the probability of the tropical cyclone with the strength in each section to cause the haze in the area to be detected according to the reserved path point data and the visibility data of the area to be detected corresponding to the reserved path point, and performing interpolation operation according to the longitude and latitude values of the preset position in each section and the probability value of the tropical cyclone with the strength in each section to cause the haze in the area to be detected to obtain the probability distribution of the haze in the area to be detected caused by the tropical cyclone with each strength.
The invention also provides a forecasting system for the probability of causing the dust haze in the coastal area by the tropical cyclone, which comprises the following components:
the dust-haze probability distribution determining module is used for obtaining the probability distribution of dust haze in the area to be detected caused by the tropical cyclones at each intensity level by using the determining system for the dust-haze probability in the coastal area caused by the tropical cyclones;
the extraction module is used for calling the probability distribution of dust haze of the area to be detected caused by the tropical cyclone under the corresponding strength according to the strength of the tropical cyclone to be predicted;
and the prediction module is used for determining the probability of the dust haze of the area to be predicted when the tropical cyclone to be predicted reaches the prediction place according to the information of the tropical cyclone path to be predicted.
The method uses a mathematical statistical method to count historical data of the tropical cyclone and visibility and relative humidity data monitored by a weather station of an area to be detected when the tropical cyclone occurs in recent years, quantitatively analyzes the probability distribution of dust haze of the area to be detected caused by the tropical cyclone with different intensity levels, and provides a reliable basis for weather forecast early warning that the tropical cyclone influences the dust haze.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a flow chart of a method for determining a probability of causing haze in a coastal region by a tropical cyclone according to an embodiment of the present invention;
FIG. 2 is a flowchart of a method for forecasting the probability of causing haze in coastal areas by tropical cyclones according to an embodiment of the present invention;
FIG. 3 is a block diagram of a system for determining the probability of causing haze in a coastal region by a tropical cyclone according to an embodiment of the present invention;
FIG. 4 is a diagram of a system for forecasting the probability of dust haze in a coastal region caused by tropical cyclone according to an embodiment of the present invention;
fig. 5 is a typhoon level (TY) tropical cyclone induced Shenzhen gray haze probability distribution diagram according to an embodiment of the present invention.
Detailed Description
In order to make the technical features and effects of the invention more obvious, the technical solution of the invention is further described below with reference to the accompanying drawings, the invention can also be described or implemented by other different specific examples, and any equivalent changes made by those skilled in the art within the scope of the claims are within the scope of the invention.
The invention provides a statistical method for quantitatively analyzing and predicting the probability of dust haze in a coastal region caused by tropical cyclone aiming at the coastal region (a region influenced by the tropical cyclone, such as Shenzhen), and provides a reference for the early warning of dust haze forecast issued by the meteorological office in the coastal region.
As shown in fig. 1, fig. 1 is a flowchart of a method for determining a probability of causing haze in a coastal area by a tropical cyclone according to an embodiment of the present invention. Specifically, the method for determining the probability of causing the dust haze in the coastal region by the tropical cyclone comprises the following steps:
step 101: collecting historical data of tropical cyclone path points which have influence on visibility of a region to be detected, and historical data of visibility and historical data of relative humidity of the region to be detected at corresponding time;
the region to be tested is a coastal region which is susceptible to tropical cyclone, such as Shenzhen, and the specific region to be tested is not limited by the method.
And the visibility historical data and the relative humidity historical data of the area to be detected are based on data measured by a national basic meteorological station of the area.
The tropical cyclone path point data is a point of each forecast time on the tropical cyclone path, and the path point data comprises the passing time of the tropical cyclone, path information and strength information of the tropical cyclone and the like. As the tropical cyclone approaches, the forecasted time interval will be shorter and shorter, and the waypoints will also become denser.
Step 102: classifying the historical data of the tropical cyclone path points according to the strength to obtain various tropical cyclone path point data;
step 103: dividing the prediction range of the area to be detected into a plurality of sections, reserving a path point for each tropical cyclone with strength, calculating the probability of the tropical cyclone with strength in the section to cause the haze in the area to be detected according to the reserved path point data and the visibility data of the area to be detected corresponding to the reserved path point, and performing interpolation operation according to the longitude and latitude values of a preset position in the section and the probability value of the tropical cyclone with strength in the section to cause the haze in the area to be detected to obtain the probability distribution of the haze in the area to be detected caused by the tropical cyclones with strength.
In specific implementation, in order to more intuitively know the probability distribution of the dust haze in the region to be detected caused by the tropical cyclone, the probability distribution of the dust haze in the region to be detected caused by the tropical cyclone is shown in a distribution diagram (as shown in fig. 5).
The prediction range of the area to be measured can be a range within a certain kilometer of a square circle with the national basic weather station of the area as the center of a circle. The interpolation operation includes, but is not limited to, a linear interpolation method, a moving average method and the like, and the probability of the dust haze in the area to be detected when the tropical cyclone passes through the non-path point can be obtained through the interpolation operation.
The preset position in the interval can be any point in the interval, and for the convenience of calculation, the central position of the interval is usually taken.
In an embodiment of the present invention, international convention is adopted to classify tropical cyclone strength, and different strength classification standards may be adopted according to actual needs, which is not limited in the present invention. The detailed process of classifying the historical data of the tropical cyclone path points according to the strength to obtain the path point data of various tropical cyclones comprises the following steps:
SuTY represents super typhoon, STY represents strong typhoon, TY represents typhoon, STS represents strong tropical storm, TS represents tropical storm, and TD represents tropical low voltage. The above six types of tropical cyclones are classified by the same strength classification method as the international convention. According to the classification standard, dividing all path points of the historical tropical cyclone 1 into a SUTY path point set 1, an STY path point set 1, a TY path point set 1, an STS path point set 1, a TS path point set 1 and a TD path point set 1 according to the current intensity level; dividing all path points of the tropical cyclone 2 into a Sun path point set 2, an STY path point set 2, a TY path point set 2, an STS path point set 2, a TS path point set 2 and a TD path point set 2 according to the current intensity level; …, respectively; and so on. Secondly, reclassifying the SUTY path point set 1, the SuTY path point set 2, the SuTY path point set 3 and … as a SuTY path point set, and reclassifying the STY path point set 1, the STY path point set 2 and the STY path point set 3 and … as an STY path point set; …, respectively; and so on. Thus, tropical cyclone classification data on an intensity basis is obtained.
In an embodiment of the present invention, dividing the prediction range of the area to be measured into a plurality of intervals further includes: the prediction range of the area to be measured is divided into a plurality of square longitude and latitude intervals of 1 degree multiplied by 1 degree, in other embodiments of the invention, the prediction range can also be divided into a plurality of square longitude and latitude intervals of 2 degrees multiplied by 2 degrees, and the size of the longitude and latitude intervals can be set according to the prediction precision. In other embodiments of the present invention, the prediction range may be divided into a plurality of intervals according to kilometer distance.
In an embodiment of the invention, for each occurred tropical cyclone in various tropical cyclones, only a path point with lowest visibility in a region to be detected in path points corresponding to the region to be detected with relative humidity less than 80% is selected when the tropical cyclone passes through a latitude and longitude interval, that is, the path point is kept as the path point with lowest visibility in the region to be detected in the path points corresponding to the region to be detected with relative humidity less than 80% under the same strength of the same tropical cyclone in the interval. In detail, in each section, for each type of tropical cyclone, the path point of the same tropical cyclone is to be screened for the path point corresponding to the area to be tested, where the relative humidity is less than 80%, and then the path points are compared with each other in the visibility corresponding to the screened path points, and the path point where the visibility of the area to be tested is lowest is retained, and the path points belonging to different tropical cyclones do not need to be removed by comparison.
In an embodiment of the present invention, calculating the probability of the intensity tropical cyclone causing the dust-haze of the area to be measured in the interval according to the reserved path point data and the visibility data of the area to be measured corresponding to the reserved path point further includes:
determining the number N of the tropical cyclones with the intensity in the interval according to the number of the reserved path points in the interval;
and determining the number M of times of the dust haze of the area to be detected when the intensity tropical cyclone passes through the interval according to the visibility data of the area to be detected corresponding to the reserved path point. In detail, the basis for judging whether the dust haze occurs according to the visibility and the relative humidity is as follows: and when the lowest visibility of the area to be detected is less than 10 kilometers and the relative humidity is less than 80%, determining that the area to be detected has dust haze.
And dividing the number M of dust haze in the area to be detected when the intensity tropical cyclone passes through the interval by the number N of the intensity tropical cyclones in the interval to obtain the probability of dust haze in the area to be detected when the intensity tropical cyclone passes through the interval.
As shown in fig. 2, in an embodiment of the present invention, after obtaining the probability distribution of dust haze in the area to be measured caused by tropical cyclone at each intensity by using the method of any of the foregoing embodiments, the method further includes:
step 104: according to the intensity of the tropical cyclone to be predicted, the probability distribution of the dust haze of the area to be predicted caused by the tropical cyclone under the corresponding intensity is obtained;
step 105: and determining the probability of the dust haze of the area to be predicted when the tropical cyclone to be predicted reaches the prediction place according to the path information of the tropical cyclone to be predicted.
The intensity and the path information of the tropical cyclone to be predicted can be predicted according to a numerical weather forecast model. Furthermore, the prediction can be assisted by the experience of weather forecasters.
The method uses a mathematical statistical method to count historical data of the tropical cyclone and visibility and relative humidity data monitored by a weather station of an area to be detected when the tropical cyclone occurs in recent years, quantitatively analyzes the probability distribution of dust haze of the area to be detected caused by the tropical cyclone with different intensity levels, and provides a reliable basis for weather forecast early warning that the tropical cyclone influences the dust haze.
As shown in fig. 3, fig. 3 is a structural diagram of a system for determining a probability of causing haze in a coastal area by a tropical cyclone according to an embodiment of the present invention. The system can be implemented by a logic circuit or a chip, or installed in an existing high-performance computing terminal, such as a mobile phone, a tablet computer, a computer, or the like, or the functions of the components are implemented by software in the form of functional modules.
Specifically, the system comprises: the collecting module 301 is configured to collect historical data of tropical cyclone path points affecting visibility of a region to be detected, historical data of visibility of the region to be detected at a corresponding time, and historical data of relative humidity;
the classification module 302 is used for classifying the tropical cyclone path point historical data according to the strength to obtain various tropical cyclone path point data;
the data processing module 303 is configured to divide the prediction range of the area to be detected into multiple intervals, reserve a path point for each intensity of tropical cyclone in the same tropical cyclone in each interval, calculate, according to the reserved path point data and visibility data of the area to be detected corresponding to the reserved path point, a probability that the intensity of the tropical cyclone in each interval causes the haze of the area to be detected, perform interpolation operation according to a longitude and latitude value of a predetermined position in each interval and a probability value that each intensity of the tropical cyclones in each interval causes the haze of the area to be detected, and obtain probability distribution that the tropical cyclones under each intensity cause the haze of the area to be detected.
In an embodiment of the present invention, the data processing module screens, as the reserved path point, a path point meeting the requirement of lowest visibility in the area to be measured among path points corresponding to the area to be measured with relative humidity less than 80% under the same intensity of the same tropical cyclone in the interval.
In an embodiment of the present invention, the process of calculating the dust-haze probability by the data processing module includes:
determining the number N of the tropical cyclones with the intensity in the interval according to the number of the reserved path points in the interval;
determining the number M of times of dust haze generation of the area to be detected when the intensity tropical cyclone passes through an interval according to the visibility data of the area to be detected corresponding to the reserved path point;
and dividing the number M of dust haze in the area to be detected when the intensity tropical cyclone passes through the interval by the number N of the intensity tropical cyclones in the interval to obtain the probability of dust haze in the area to be detected when the intensity tropical cyclone passes through the interval.
Fig. 4 is a structural diagram of a system for forecasting the probability of causing haze in a coastal area by a tropical cyclone according to an embodiment of the present invention. Specifically, the system comprises a first control module,
an ash haze probability distribution determining module 401, configured to obtain probability distributions of the ash haze in the regions to be detected caused by the tropical cyclones at the respective intensity levels by using the determining system for the probability of the ash haze in the coastal regions caused by the tropical cyclones in the foregoing embodiment;
the extracting module 402 is used for calling the probability distribution of dust haze in the area to be predicted caused by the tropical cyclone under the corresponding strength according to the strength of the tropical cyclone to be predicted;
the forecasting module 403 is configured to determine, according to the information of the tropical cyclone path to be forecasted, a probability that the area to be forecasted has the dust haze when the tropical cyclone reaches the forecasting location.
The invention uses a mathematical statistical method to count the tropical cyclone data in recent years and the visibility and relative humidity data monitored by a weather station of an area to be detected when the tropical cyclone occurs, quantitatively analyzes the dust-haze probability distribution of the area to be detected caused by the tropical cyclones with different intensity levels, and provides a reliable basis for weather forecast early warning that the tropical cyclone influences the dust-haze.
In order to more clearly illustrate the technical scheme of the invention, Shenzhen is taken as an example below, and as a southeast coastal city, Shenzhen is susceptible to tropical cyclone in summer and autumn every year, and besides direct gale and rainfall, the coming of the tropical cyclone can also cause the Shenzhen to appear in dust-haze weather. The quantitative prediction method of the ash haze generation probability of Shenzhen caused by tropical cyclone is well verified during the period that No. 1506 'Hongxian' affects Shenzhen in 2015.
It should be noted that, in this embodiment, visibility and relative humidity data measured by the Shenzhen national basic meteorological station are used to represent visibility and temperature and humidity data of the entire Shenzhen, and the longitude and latitude of the Shenzhen national basic meteorological station are used to represent the longitude and latitude of the Shenzhen region; the prediction range described in this embodiment is a range with the Shenzhen national basic meteorological station as a center and a radius of 1500 km.
Specifically, the prediction method of the ash haze probability of Shenzhen caused by tropical cyclone comprises the following steps,
step 501: collecting historical data of tropical cyclone path points which have influence on the Shenzhen visibility and historical data of visibility and relative humidity recorded by a Shenzhen meteorological station corresponding to time;
the historical data of the invention is path point data (including strength and path information) of all tropical cyclones influencing Shenzhen visibility in 1985 to 2014, and visibility and relative humidity data of corresponding Shenzhen.
Step 502: classifying historical data of the tropical cyclone path points according to the intensity of the tropical cyclone to obtain various tropical cyclone path point data;
for a specific classification method, reference is made to the above embodiments, which are not described herein again.
Step 503: dividing the prediction range of Shenzhen into a plurality of latitude and longitude intervals of 1 degree multiplied by 1 degree, calculating the probability of various tropical cyclones in the interval for triggering Shenzhen haze (the visibility is less than 10 kilometers, and the relative humidity is less than 80%), and drawing the probability distribution diagram of various tropical cyclones for triggering Shenzhen haze;
1) dividing a Shenzhen 1500 kilometer prediction range into a plurality of 1-degree x 1-degree square longitude and latitude intervals, wherein the longitude range of the prediction range is 99.39-128.61-degree E, and the latitude range is 9.04-36.02-degree N. And defining (i, j) to represent the position of the current interval according to the latitude and longitude values of the prediction range, wherein i represents the sequence of the latitude of the current interval in the latitude sequence of the prediction range, and j represents the sequence of the longitude of the current interval in the longitude sequence of the prediction range.
2) For each type (each intensity) of tropical cyclone, one path point is reserved for the same tropical cyclone in each zone; the reserved path point is the path point with the lowest Shenzhen visibility in the path point which meets the condition that the relative humidity of the Shenzhen region corresponding to the time is less than 80% in the tropical cyclone path point.
3) Counting the number of tropical cyclones passing through various tropical cyclones in the latitude and longitude interval, summarizing according to the intensity (level) of the tropical cyclones, and recording the result as NSuTY(i,j)、NSTY(i,j)、NTY(i,j)、NSTS(i,j)、NTS(i,j)、NTD(i,j)In which N isSuTY(i,j)Represents the number of susty-type tropical cyclones passing through location (i, j), and so on;
counting the times of occurrence of haze (the lowest visibility is less than 10 kilometers and the relative humidity is less than 80%) of Shenzhen in the process that various tropical cyclones pass through latitude and longitude intervals, corresponding to corresponding levels, and recording as MSuTY(i,j)、MSTY(i,j)、MTY(i,j)、MSTS(i,j)、MTS(i，j)、MTD(i,j)Wherein M isSuTY(i,j)Representing the times of causing Shenzhen dust haze when the Sun type tropical cyclone passes through the position (i, j) interval, and the like.
And calculating the probability of various types of heat band cyclones for inducing Shenzhen dust haze at various interval positions by using the following formula:
SuTY：PSuTY(i,j)＝MSuTY(i,j)/NSuTY(i,j)；
STY：PSTY(i,j)＝MSTY(i,j)/NSTY(i,j)；
TY：PTY(i,j)＝MTY(i,j)/NTY(i,j)(ii) a …, respectively; and so on.
4) And performing interpolation operation according to the longitude and latitude value of the central position in the interval and the probability value of the dust haze generation of Shenzhen when each level of tropical cyclone passes through the interval, drawing a probability distribution diagram of the dust haze generation of the Shenzhen due to the influence of each strength level of tropical cyclone in the 1500 km range, and referring to fig. 5, which is a typhoon level (TY) tropical cyclone induced Shenzhen dust haze probability distribution diagram, wherein the pentagon position is Shenzhen, and different grays in the diagram indicate that the dust haze generation probability of the Shenzhen region is different.
Step 504: predicting the probability of causing dust haze to occur in Shenzhen according to the strength and path information of future tropical cyclone and the dust haze probability distribution map;
specifically, for the forthcoming tropical cyclone, under the condition that the possible intensity of the tropical cyclone is known, the gray haze probability distribution map corresponding to the intensity is selected, after the predicted path information is known, the probability that Shenzhen appears in the gray haze when the tropical cyclone reaches the prediction place can be predicted by combining the gray haze probability distribution map.
The method uses a mathematical statistical method, combines tropical cyclone data in recent years and visibility and relative humidity data monitored by a weather station of an area to be detected when the tropical cyclone occurs, quantitatively analyzes the probability distribution of dust haze in the area caused by the tropical cyclones with different intensity levels, and provides a reliable basis for weather forecast early warning of the influence of the tropical cyclones on the dust haze.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above description is only for the purpose of illustrating the present invention, and any person skilled in the art can modify and change the above embodiments without departing from the spirit and scope of the present invention. Therefore, the scope of the claims should be accorded the full scope of the claims.
Claims (6)
1. A method for determining the probability of causing dust-haze in coastal areas by tropical cyclones is characterized by comprising the following steps,
collecting historical data of tropical cyclone path points which have influence on visibility of a region to be detected, and historical data of visibility and historical data of relative humidity of the region to be detected at corresponding time;
classifying the historical data of the tropical cyclone path points according to the intensity of the historical data of the tropical cyclone path points to obtain various types of tropical cyclone path point data;
dividing the prediction range of the area to be detected into a plurality of intervals, reserving a path point for each intensity tropical cyclone in the interval, calculating the probability of the intensity tropical cyclone in the interval to cause the haze of the area to be detected according to the reserved path point data and the visibility data of the area to be detected corresponding to the reserved path point, and performing interpolation operation according to the longitude and latitude values of a preset position in the interval and the probability values of the intensity tropical cyclones in the interval to cause the haze of the area to be detected to obtain the probability distribution of the haze of the area to be detected caused by the tropical cyclones under each intensity;
wherein, the calculating the probability of the intensity tropical cyclone causing the dust-haze of the area to be measured according to the reserved path point data and the visibility data of the area to be measured corresponding to the reserved path point further comprises,
determining the number N of the tropical cyclones with the intensity in the interval according to the number of the reserved path points in the interval;
determining the number M of times of dust haze generation of the area to be detected when the intensity tropical cyclone passes through an interval according to the visibility data of the area to be detected corresponding to the reserved path point;
and dividing the number M of dust haze in the area to be detected when the intensity tropical cyclone passes through the interval by the number N of the intensity tropical cyclones in the interval to obtain the probability of dust haze in the area to be detected when the intensity tropical cyclone passes through the interval.
2. The method for determining the probability of causing the dust-haze in the coastal region by the tropical cyclone as claimed in claim 1, wherein the reserved path point is a path point which satisfies the condition that the visibility of the region to be measured is lowest among the path points corresponding to the region to be measured with the relative humidity of less than 80% in the same intensity of the same tropical cyclone in the zone.
3. A forecasting method for the probability of causing the dust-haze of the coastal area by the tropical cyclone is characterized in that the probability distribution of causing the dust-haze of the coastal area to be tested by the tropical cyclone at each intensity level is obtained by the method for determining the probability of causing the dust-haze of the coastal area by the tropical cyclone according to any one of claims 1 to 2;
according to the intensity of the tropical cyclone to be predicted, the probability distribution of the dust haze of the area to be predicted caused by the tropical cyclone under the corresponding intensity is obtained;
and determining the probability of the dust haze of the area to be predicted when the tropical cyclone to be predicted reaches the prediction place according to the path information of the tropical cyclone to be predicted.
4. A system for determining the probability of causing dust-haze in coastal areas by tropical cyclones is characterized by comprising,
the collection module is used for collecting historical data of tropical cyclone path points which have influence on the visibility of a region to be detected, and historical data of the visibility and historical data of relative humidity of the region to be detected at corresponding time;
the sorting module is used for sorting the historical data of the tropical cyclone path points according to the intensity of the historical data of the tropical cyclone path points to obtain various data of the tropical cyclone path points;
the data processing module is used for dividing the prediction range of the area to be detected into a plurality of intervals, reserving a path point for each tropical cyclone with strength in the interval, calculating the probability of the tropical cyclone with the strength in the interval causing the haze of the area to be detected according to the reserved path point data and the visibility data of the area to be detected corresponding to the reserved path point, and performing interpolation operation according to the longitude and latitude values of preset positions in the interval and the probability values of the tropical cyclones with the strength in the interval causing the haze of the area to be detected to obtain the probability distribution of the haze of the area to be detected caused by the tropical cyclones with the strengths;
wherein the data processing module is further configured to,
determining the number N of the tropical cyclones with the intensity in the interval according to the number of the reserved path points in the interval;
determining the number M of times of dust haze generation of the area to be detected when the intensity tropical cyclone passes through an interval according to the visibility data of the area to be detected corresponding to the reserved path point;
and dividing the number M of dust haze in the area to be detected when the intensity tropical cyclone passes through the interval by the number N of the intensity tropical cyclones in the interval to obtain the probability of dust haze in the area to be detected when the intensity tropical cyclone passes through the interval.
5. The system for determining the probability of causing the dust-haze in the coastal region by the tropical cyclone as claimed in claim 4, wherein the data processing module is configured to screen, as the reserved path point, a path point meeting the requirement of lowest visibility in the region to be measured among the path points corresponding to the region to be measured with relative humidity less than 80% at the same intensity in the zone.
6. A forecasting system for the probability of dust haze in coastal areas caused by tropical cyclones is characterized by comprising,
an ash-haze probability distribution determining module, configured to obtain probability distributions of the tropical cyclone at each intensity level for inducing ash-haze in the region to be tested, by using the system for determining the probability of inducing ash-haze in the coastal region by the tropical cyclone according to any one of claims 4 to 5;
the extraction module is used for calling the probability distribution of dust haze of the area to be detected caused by the tropical cyclone under the corresponding strength according to the strength of the tropical cyclone to be predicted;
and the prediction module is used for determining the probability of the dust haze of the area to be predicted when the tropical cyclone to be predicted reaches the prediction place according to the information of the tropical cyclone path to be predicted.
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